From a4dbbf1bdbcb93f1e053f45319381e7bb490e94b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andreas=20S=C3=B8gaard?= Date: Wed, 11 Dec 2024 02:30:07 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20Aske-Ros?= =?UTF-8?q?ted/graphnet@92b150aa5fbe149cdd7d473932d05375df176417=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- _modules/graphnet/data/constants.html | 2 + .../extractors/icecube/i3truthextractor.html | 125 ++++- .../icecube/utilities/i3_filters.html | 27 + .../i3modules/deprecated_methods.html | 434 +++++++++++++++ .../deployment/icecube/i3deployer.html | 507 ++++++++++++++++++ .../graphnet/models/detector/detector.html | 21 +- .../graphnet/models/graphs/nodes/nodes.html | 34 +- _modules/graphnet/models/graphs/utils.html | 338 +++++++++++- .../graphnet/models/task/reconstruction.html | 19 + .../graphnet/training/loss_functions.html | 11 + _modules/index.html | 2 + api/graphnet.data.constants.html | 6 +- ...a.extractors.icecube.i3truthextractor.html | 46 +- ...net.data.extractors.icecube.utilities.html | 1 + ...tractors.icecube.utilities.i3_filters.html | 23 + ...ployment.i3modules.deprecated_methods.html | 48 +- api/graphnet.deployment.i3modules.html | 13 +- api/graphnet.deployment.icecube.html | 10 +- ...raphnet.deployment.icecube.i3deployer.html | 48 +- api/graphnet.models.detector.detector.html | 3 + api/graphnet.models.detector.icecube.html | 12 + api/graphnet.models.detector.liquido.html | 3 + api/graphnet.models.detector.prometheus.html | 39 ++ api/graphnet.models.graphs.html | 1 + api/graphnet.models.graphs.nodes.nodes.html | 5 + api/graphnet.models.graphs.utils.html | 254 +++++++++ api/graphnet.models.task.html | 1 + api/graphnet.models.task.reconstruction.html | 82 +++ api/graphnet.training.html | 1 + api/graphnet.training.loss_functions.html | 29 + ...graphnet.utilities.config.base_config.html | 34 -- ...phnet.utilities.config.dataset_config.html | 34 -- ...raphnet.utilities.config.model_config.html | 34 -- ...hnet.utilities.config.training_config.html | 34 -- genindex.html | 98 +++- objects.inv | Bin 9280 -> 9395 bytes py-modindex.html | 20 + searchindex.js | 2 +- sitemap.xml | 2 +- 39 files changed, 2194 insertions(+), 209 deletions(-) create mode 100644 _modules/graphnet/deployment/i3modules/deprecated_methods.html create mode 100644 _modules/graphnet/deployment/icecube/i3deployer.html diff --git a/_modules/graphnet/data/constants.html b/_modules/graphnet/data/constants.html index 6faca659d..db2ecaf6c 100644 --- a/_modules/graphnet/data/constants.html +++ b/_modules/graphnet/data/constants.html @@ -406,6 +406,8 @@

Source code for graphnet.dat "interaction_type", "interaction_time", # Added for vertex reconstruction "inelasticity", + "visible_inelasticity", + "visible_energy", "stopped_muon", ] DEEPCORE = ICECUBE86 diff --git a/_modules/graphnet/data/extractors/icecube/i3truthextractor.html b/_modules/graphnet/data/extractors/icecube/i3truthextractor.html index a09f20a2b..ff185ed4d 100644 --- a/_modules/graphnet/data/extractors/icecube/i3truthextractor.html +++ b/_modules/graphnet/data/extractors/icecube/i3truthextractor.html @@ -353,6 +353,7 @@

So import numpy as np import matplotlib.path as mpath +from scipy.spatial import ConvexHull, Delaunay from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple from .i3extractor import I3Extractor @@ -363,10 +364,12 @@

So from graphnet.utilities.imports import has_icecube_package if has_icecube_package() or TYPE_CHECKING: - from icecube import ( + from icecube import ( # noqa: F401 dataclasses, icetray, phys_services, + dataio, + LeptonInjector, ) # pyright: reportMissingImports=false @@ -380,6 +383,7 @@

So name: str = "truth", borders: Optional[List[np.ndarray]] = None, mctree: Optional[str] = "I3MCTree", + extend_boundary: Optional[float] = 0.0, ): """Construct I3TruthExtractor. @@ -390,6 +394,8 @@

So stopping within the detector. Defaults to hard-coded boundary coordinates. mctree: Str of which MCTree to use for truth values. + extend_boundary: Distance to extend the convex hull of the detector + for defining starting events. """ # Base class constructor super().__init__(name) @@ -431,15 +437,56 @@

So self._borders = [border_xy, border_z] else: self._borders = borders + + self._extend_boundary = extend_boundary self._mctree = mctree +
+[docs] + def set_gcd(self, i3_file: str, gcd_file: Optional[str] = None) -> None: + """Extract GFrame and CFrame from i3/gcd-file pair. + + Information from these frames will be set as member variables of + `I3Extractor.` + + Args: + i3_file: Path to i3 file that is being converted. + gcd_file: Path to GCD file. Defaults to None. If no GCD file is + given, the method will attempt to find C and G frames in + the i3 file instead. If either one of those are not + present, `RuntimeErrors` will be raised. + """ + super().set_gcd(i3_file=i3_file, gcd_file=gcd_file) + + # Modifications specific to I3TruthExtractor + # These modifications are needed to identify starting events + coordinates = [] + for _, g in self._gcd_dict.items(): + if g.position.z > 1200: + continue # We want to exclude icetop + coordinates.append([g.position.x, g.position.y, g.position.z]) + coordinates = np.array(coordinates) + + if self._extend_boundary != 0.0: + center = np.mean(coordinates, axis=0) + d = coordinates - center + norms = np.linalg.norm(d, axis=1, keepdims=True) + dn = d / norms + coordinates = coordinates + dn * self._extend_boundary + + hull = ConvexHull(coordinates) + + self.hull = hull + self.delaunay = Delaunay(coordinates[self.hull.vertices])
+ + def __call__( self, frame: "icetray.I3Frame", padding_value: Any = -1 ) -> Dict[str, Any]: """Extract truth-level information.""" is_mc = frame_is_montecarlo(frame, self._mctree) is_noise = frame_is_noise(frame, self._mctree) - sim_type = self._find_data_type(is_mc, self._i3_file) + sim_type = self._find_data_type(is_mc, self._i3_file, frame) output = { "energy": padding_value, @@ -472,6 +519,7 @@

So "L5_oscNext_bool": padding_value, "L6_oscNext_bool": padding_value, "L7_oscNext_bool": padding_value, + "is_starting": padding_value, } # Only InIceSplit P frames contain ML appropriate @@ -583,6 +631,13 @@

So } ) + is_starting = self._contained_vertex(output) + output.update( + { + "is_starting": is_starting, + } + ) + return output def _extract_dbang_decay_length( @@ -727,15 +782,34 @@

So # all variables and has no nans (always muon) else: MCInIcePrimary = None - try: - interaction_type = frame["I3MCWeightDict"]["InteractionType"] - except KeyError: - interaction_type = padding_value - try: - elasticity = frame["I3GENIEResultDict"]["y"] - except KeyError: - elasticity = padding_value + if sim_type == "LeptonInjector": + event_properties = frame["EventProperties"] + final_state_1 = event_properties.finalType1 + if final_state_1 in [ + dataclasses.I3Particle.NuE, + dataclasses.I3Particle.NuMu, + dataclasses.I3Particle.NuTau, + dataclasses.I3Particle.NuEBar, + dataclasses.I3Particle.NuMuBar, + dataclasses.I3Particle.NuTauBar, + ]: + interaction_type = 2 # NC + else: + interaction_type = 1 # CC + + elasticity = 1 - event_properties.finalStateY + + else: + try: + interaction_type = frame["I3MCWeightDict"]["InteractionType"] + except KeyError: + interaction_type = int(padding_value) + + try: + elasticity = 1 - frame["I3MCWeightDict"]["BjorkenY"] + except KeyError: + elasticity = padding_value return MCInIcePrimary, interaction_type, elasticity @@ -771,12 +845,15 @@

So return energy_track, energy_cascade, inelasticity # Utility methods - def _find_data_type(self, mc: bool, input_file: str) -> str: + def _find_data_type( + self, mc: bool, input_file: str, frame: "icetray.I3Frame" + ) -> str: """Determine the data type. Args: mc: Whether `input_file` is Monte Carlo simulation. input_file: Path to I3-file. + frame: Physics frame containing MC record Returns: The simulation/data type. @@ -792,11 +869,29 @@

So sim_type = "genie" elif "noise" in input_file: sim_type = "noise" - elif "L2" in input_file: # not robust - sim_type = "dbang" - else: + elif frame.Has("EventProprties") or frame.Has( + "LeptonInjectorProperties" + ): + sim_type = "LeptonInjector" + elif frame.Has("I3MCWeightDict"): sim_type = "NuGen" - return sim_type + else: + raise NotImplementedError("Could not determine data type.") + return sim_type + + def _contained_vertex(self, truth: Dict[str, Any]) -> bool: + """Determine if an event is starting based on vertex position. + + Args: + truth: Dictionary of already extracted truth-level information. + + Returns: + True/False if vertex is inside detector. + """ + vertex = np.array( + [truth["position_x"], truth["position_y"], truth["position_z"]] + ) + return self.delaunay.find_simplex(vertex) >= 0 diff --git a/_modules/graphnet/data/extractors/icecube/utilities/i3_filters.html b/_modules/graphnet/data/extractors/icecube/utilities/i3_filters.html index a33d1908a..629f9c625 100644 --- a/_modules/graphnet/data/extractors/icecube/utilities/i3_filters.html +++ b/_modules/graphnet/data/extractors/icecube/utilities/i3_filters.html @@ -421,6 +421,33 @@

+[docs] +class SubEventStreamI3Filter(I3Filter): + """A filter that only keeps frames from select splits.""" + + def __init__(self, selection: List[str]): + """Initialize SubEventStreamI3Filter. + + Args: + selection: List of subevent streams to keep. + """ + self._selection = selection + + def _keep_frame(self, frame: "icetray.I3Frame") -> bool: + """Check if current frame should be kept. + + Args: + frame: I3-frame + The I3-frame to check. + """ + if frame.Has("I3EventHeader"): + if frame["I3EventHeader"].sub_event_stream not in self._selection: + return False + return True + + +
[docs] class I3FilterMask(I3Filter): diff --git a/_modules/graphnet/deployment/i3modules/deprecated_methods.html b/_modules/graphnet/deployment/i3modules/deprecated_methods.html new file mode 100644 index 000000000..e50aaf171 --- /dev/null +++ b/_modules/graphnet/deployment/i3modules/deprecated_methods.html @@ -0,0 +1,434 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + graphnet.deployment.i3modules.deprecated_methods — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
+ +
+ + +
+ + + + +
+
+ +
+
+
+ +
+
+
+
+
+
+ + +
+
+
+ +
+
+ +

Source code for graphnet.deployment.i3modules.deprecated_methods

+"""Contains deprecated methods."""
+
+from typing import Union, Sequence
+
+# from graphnet.deployment.icecube import I3Deployer, I3InferenceModule
+from ..icecube.i3deployer import I3Deployer
+from ..icecube.inference_module import I3InferenceModule
+
+
+

+[docs]
+class GraphNeTI3Deployer(I3Deployer):
+    """Class has been renamed to `I3Deployer`.
+
+    Please use `I3Deployer` instead.
+    """
+
+    def __init__(
+        self,
+        graphnet_modules: Union[
+            I3InferenceModule, Sequence[I3InferenceModule]
+        ],
+        gcd_file: str,
+        n_workers: int = 1,
+    ) -> None:
+        """Initialize `GraphNeTI3Deployer`.
+
+        Will apply `DeploymentModules` to files in the order in which they
+        appear in `modules`. Each module is run independently.
+
+        Args:
+            graphnet_modules: List of `DeploymentModules`.
+                              Order of appearence in the list determines order
+                              of deployment.
+            gcd_file: path to gcd file.
+            n_workers: Number of workers. The deployer will divide the number
+                       of input files across workers. Defaults to 1.
+        """
+        super().__init__(
+            modules=graphnet_modules, n_workers=n_workers, gcd_file=gcd_file
+        )
+        self.warning(
+            f"{self.__class__} will be deprecated in GraphNeT 2.0"
+            " Please use `I3Deployer` instead. "
+            " E.g.: `from graphnet.deployment.icecube import I3Deployer`"
+        )

+
+
+ +
+
+
+
+
+
+
+ +
+
+
+
+
+ © Copyright 2021-2024, GraphNeT team. + +
+ Created using + Sphinx 8.1.3. + and + Material for + Sphinx +
+
+
+
+ + + + \ No newline at end of file diff --git a/_modules/graphnet/deployment/icecube/i3deployer.html b/_modules/graphnet/deployment/icecube/i3deployer.html new file mode 100644 index 000000000..2ce130b5c --- /dev/null +++ b/_modules/graphnet/deployment/icecube/i3deployer.html @@ -0,0 +1,507 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + graphnet.deployment.icecube.i3deployer — graphnet documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + Skip to content +
+ +
+ + +
+ + + + +
+
+ +
+
+
+ +
+
+
+
+
+
+ + +
+
+
+ +
+
+ +

Source code for graphnet.deployment.icecube.i3deployer

+"""Contains an IceCube-specific implementation of Deployer."""
+
+from typing import TYPE_CHECKING, List, Union, Sequence
+import os
+import numpy as np
+
+from graphnet.utilities.imports import has_icecube_package
+from graphnet.deployment.icecube import I3InferenceModule
+from graphnet.data.dataclasses import Settings
+from graphnet.deployment import Deployer
+
+if has_icecube_package() or TYPE_CHECKING:
+    from icecube import icetray, dataio  # pyright: reportMissingImports=false
+    from icecube.icetray import I3Tray
+
+
+

+[docs]
+class I3Deployer(Deployer):
+    """A generic baseclass for applying `DeploymentModules` to analysis files.
+
+    Modules are applied in the order that they appear in `modules`.
+    """
+
+    def __init__(
+        self,
+        modules: Union[I3InferenceModule, Sequence[I3InferenceModule]],
+        gcd_file: str,
+        n_workers: int = 1,
+    ) -> None:
+        """Initialize `Deployer`.
+
+        Will apply `DeploymentModules` to files in the order in which they
+        appear in `modules`. Each module is run independently.
+
+        Args:
+            modules: List of `DeploymentModules`.
+                              Order of appearence in the list determines order
+                              of deployment.
+            gcd_file: path to gcd file.
+            n_workers: Number of workers. The deployer will divide the number
+                       of input files across workers. Defaults to 1.
+        """
+        super().__init__(modules=modules, n_workers=n_workers)
+
+        # Member variables
+        self._gcd_file = gcd_file
+
+    def _process_files(
+        self,
+        settings: Settings,
+    ) -> None:
+        """Will start an IceTray read/write chain with graphnet modules.
+
+        If n_workers > 1, this function is run in parallel n_worker times. Each
+        worker will loop over an allocated set of i3 files. The new i3 files
+        will appear as copies of the original i3 files but with reconstructions
+        added. Original i3 files are left untouched.
+        """
+        for i3_file in settings.i3_files:
+            tray = I3Tray()
+            tray.context["I3FileStager"] = dataio.get_stagers()
+            tray.AddModule(
+                "I3Reader",
+                "reader",
+                FilenameList=[settings.gcd_file, i3_file],
+            )
+            for i3_module in settings.modules:
+                tray.AddModule(i3_module)
+            tray.Add(
+                "I3Writer",
+                Streams=[
+                    icetray.I3Frame.DAQ,
+                    icetray.I3Frame.Physics,
+                    icetray.I3Frame.TrayInfo,
+                    icetray.I3Frame.Simulation,
+                ],
+                filename=settings.output_folder + "/" + i3_file.split("/")[-1],
+            )
+            tray.Execute()
+            tray.Finish()
+        return
+
+    def _prepare_settings(
+        self, input_files: List[str], output_folder: str
+    ) -> List[Settings]:
+        """Will prepare the settings for each worker."""
+        try:
+            os.makedirs(output_folder)
+        except FileExistsError as e:
+            self.error(
+                f"{output_folder} already exists. To avoid overwriting "
+                "existing files, the process has been stopped."
+            )
+            raise e
+        if self._n_workers > len(input_files):
+            self._n_workers = len(input_files)
+        if self._n_workers > 1:
+            file_batches = np.array_split(input_files, self._n_workers)
+            settings: List[Settings] = []
+            for i in range(self._n_workers):
+                settings.append(
+                    Settings(
+                        file_batches[i],
+                        self._gcd_file,
+                        output_folder,
+                        self._modules,
+                    )
+                )
+        else:
+            settings = [
+                Settings(
+                    input_files,
+                    self._gcd_file,
+                    output_folder,
+                    self._modules,
+                )
+            ]
+        return settings

+
+
+ +
+
+
+
+
+
+
+ +
+
+
+
+
+ © Copyright 2021-2024, GraphNeT team. + +
+ Created using + Sphinx 8.1.3. + and + Material for + Sphinx +
+
+
+
+ + + + \ No newline at end of file diff --git a/_modules/graphnet/models/detector/detector.html b/_modules/graphnet/models/detector/detector.html index 82b7e729a..afc15fde8 100644 --- a/_modules/graphnet/models/detector/detector.html +++ b/_modules/graphnet/models/detector/detector.html @@ -352,7 +352,7 @@

Source code for gr """Base detector-specific `Model` class(es).""" from abc import abstractmethod -from typing import Dict, Callable, List +from typing import Dict, Callable, List, Optional from torch_geometric.data import Data import torch @@ -367,10 +367,19 @@

Source code for gr class Detector(Model): """Base class for all detector-specific read-ins in graphnet.""" - def __init__(self) -> None: - """Construct `Detector`.""" + def __init__( + self, replace_with_identity: Optional[List[str]] = None + ) -> None: + """Construct `Detector`. + + Args: + replace_with_identity: A list of feature names from the + feature_map that should be replaced with the identity + function. + """ # Base class constructor super().__init__(name=__name__, class_name=self.__class__.__name__) + self._replace_with_identity = replace_with_identity
[docs] @@ -423,9 +432,13 @@

Source code for gr def _standardize( self, input_features: torch.tensor, input_feature_names: List[str] ) -> Data: + feature_map = self.feature_map() + if self._replace_with_identity is not None: + for feature in self._replace_with_identity: + feature_map[feature] = self._identity for idx, feature in enumerate(input_feature_names): try: - input_features[:, idx] = self.feature_map()[ + input_features[:, idx] = feature_map[ feature ]( # noqa: E501 # type: ignore input_features[:, idx] diff --git a/_modules/graphnet/models/graphs/nodes/nodes.html b/_modules/graphnet/models/graphs/nodes/nodes.html index 74c515c1f..a3882b41f 100644 --- a/_modules/graphnet/models/graphs/nodes/nodes.html +++ b/_modules/graphnet/models/graphs/nodes/nodes.html @@ -360,7 +360,7 @@

Source code for g from graphnet.utilities.decorators import final from graphnet.models import Model from graphnet.models.graphs.utils import ( - cluster_summarize_with_percentiles, + cluster_and_pad, identify_indices, lex_sort, ice_transparency, @@ -537,9 +537,7 @@

Source code for g cluster_idx, summ_idx, new_feature_names, - ) = self._get_indices_and_feature_names( - input_feature_names, self._add_counts - ) + ) = self._get_indices_and_feature_names(input_feature_names) self._cluster_indices = cluster_idx self._summarization_indices = summ_idx return new_feature_names @@ -547,7 +545,6 @@

Source code for g def _get_indices_and_feature_names( self, feature_names: List[str], - add_counts: bool, ) -> Tuple[List[int], List[int], List[str]]: cluster_idx, summ_idx, summ_names = identify_indices( feature_names, self._cluster_on @@ -556,7 +553,7 @@

Source code for g for feature in summ_names: for pct in self._percentiles: new_feature_names.append(f"{feature}_pct{pct}") - if add_counts: + if self._add_counts: # add "counts" as the last feature new_feature_names.append("counts") return cluster_idx, summ_idx, new_feature_names @@ -566,13 +563,16 @@

Source code for g x = x.numpy() # Construct clusters with percentile-summarized features if hasattr(self, "_summarization_indices"): - array = cluster_summarize_with_percentiles( - x=x, + cluster_class = cluster_and_pad( + x=x, cluster_columns=self._cluster_indices + ) + cluster_class.add_percentile_summary( summarization_indices=self._summarization_indices, - cluster_indices=self._cluster_indices, percentiles=self._percentiles, - add_counts=self._add_counts, ) + if self._add_counts: + cluster_class.add_counts() + array = cluster_class.clustered_x else: self.error( f"""{self.__class__.__name__} was not instatiated with @@ -700,6 +700,7 @@

Source code for g "z_offset": None, "z_scaling": None, }, + sample_pulses: bool = True, ) -> None: """Construct `IceMixNodes`. @@ -713,6 +714,9 @@

Source code for g ice in IceCube are added to the feature set based on z coordinate. ice_args: Offset and scaling of the z coordinate in the Detector, to be able to make similar conversion in the ice data. + sample_pulses: Enable sampling random pulses. If True and the + event is longer than the max_length, they will be sampled. If + False, then only the first max_length pulses will be selected. """ if input_feature_names is None: input_feature_names = [ @@ -758,6 +762,7 @@

Source code for g self.z_name = z_name self.hlc_name = hlc_name self.add_ice_properties = add_ice_properties + self.sampling_enabled = sample_pulses def _define_output_feature_names( self, input_feature_names: List[str] @@ -811,7 +816,14 @@

Source code for g x[:, self.feature_indexes[self.hlc_name]] = torch.logical_not( x[:, self.feature_indexes[self.hlc_name]] ) # hlc in kaggle was flipped - ids = self._pulse_sampler(x, event_length) + if self.sampling_enabled: + ids = self._pulse_sampler(x, event_length) + else: + if event_length < self.max_length: + ids = torch.arange(event_length) + else: + ids = torch.arange(self.max_length) + event_length = min(self.max_length, event_length) graph = torch.zeros([event_length, self.n_features]) diff --git a/_modules/graphnet/models/graphs/utils.html b/_modules/graphnet/models/graphs/utils.html index a55b26707..bff78be4e 100644 --- a/_modules/graphnet/models/graphs/utils.html +++ b/_modules/graphnet/models/graphs/utils.html @@ -351,7 +351,7 @@

Source code for graphnet.models.graphs.utils

 """Utility functions for construction of graphs."""
 
-from typing import List, Tuple, Optional
+from typing import List, Tuple, Optional, Union
 import os
 import numpy as np
 import pandas as pd
@@ -473,6 +473,8 @@ 
Source code for graphne
 
 
 
+# TODO Remove this function as it is superseded by
+# cluster_and_pad wich has the same functionality
 

 [docs]
 def cluster_summarize_with_percentiles(
@@ -535,6 +537,340 @@ 
Source code for graphne
 
 
 
+

+[docs]
+class cluster_and_pad:
+    """Cluster and pad the data for further summarization.
+
+    Clusters the inptut data according to the specified columns
+    and computes aggregate statistics on the clusters.
+    The clustering will happen only ones creating a cluster matrix
+    which will hold all the aggregated statistics and a padded matrix which
+    will hold the padded data for quick calculation of aggregate statistics.
+
+    Example:
+    cluster_and_pad(x = single_event_as_array,
+                                 cluster_columns = [0,1,2])
+    # Creates a cluster matrix and a padded matrix,
+    # the cluster matrix will contain the unique values of the cluster columns,
+    # no additional aggregate statistics are added yet.
+
+    cluster_class.add_percentile_summary(summarization_indices = [3,4,5],
+                                         percentiles = [10,50,90])
+    # Adds the 10th, 50th and 90th percentile of columns 3,4
+    # and 5 in the input data to the cluster matrix.
+
+    cluster_class.add_std(column = 4)
+    # Adds the standard deviation of column 4 in the input data
+    # to the cluster matrix.
+    x = cluster_class.clustered_x
+    # Gets the clustered matrix with all the aggregate statistics.
+    """
+
+    def __init__(
+        self,
+        x: np.ndarray,
+        cluster_columns: List[int],
+        input_names: Optional[List[str]] = None,
+    ) -> None:
+        """Initialize the class with the data and cluster columns.
+
+        Args:
+            x: Array to be clustered
+            cluster_columns: List of column indices on which the clusters
+                            are constructed.
+            input_names: Names of the columns in the input data for automatic
+                        generation of names.
+            Adds:
+                clustered_x: Added to the class
+                _counts: Added to the class
+                _padded_x: Added to the class
+        """
+        x = lex_sort(x=x, cluster_columns=cluster_columns)
+
+        unique_sensors, self._counts = np.unique(
+            x[:, cluster_columns], axis=0, return_counts=True
+        )
+
+        contingency_table = np.concatenate(
+            [unique_sensors, self._counts.reshape(-1, 1)], axis=1
+        )
+
+        contingency_table = lex_sort(
+            x=contingency_table, cluster_columns=cluster_columns
+        )
+
+        self.clustered_x = contingency_table[:, 0 : unique_sensors.shape[1]]
+        self._counts = (
+            contingency_table[:, self.clustered_x.shape[1] :]
+            .flatten()
+            .astype(int)
+        )
+
+        self._padded_x = np.empty(
+            (len(self._counts), max(self._counts), x.shape[1])
+        )
+        self._padded_x.fill(np.nan)
+
+        for i in range(len(self._counts)):
+            self._padded_x[i, : self._counts[i]] = x[: self._counts[i]]
+            x = x[self._counts[i] :]
+
+        self._input_names = input_names
+        if self._input_names is not None:
+            assert (
+                len(self._input_names) == x.shape[1]
+            ), "The input names must have the same length as the input data"
+
+            self._cluster_names = np.array(input_names)[cluster_columns]
+
+    def _add_column(
+        self, column: np.ndarray, location: Optional[int] = None
+    ) -> None:
+        """Add a column to the clustered tensor.
+
+        Args:
+            column: Column to be added to the tensor
+            location: Location to insert the column in the clustered tensor.
+        Altered:
+            clustered_x: The column is added at the end of the tenor or
+                            inserted at the specified location
+        """
+        if location is None:
+            self.clustered_x = np.column_stack([self.clustered_x, column])
+        else:
+            self.clustered_x = np.insert(
+                self.clustered_x, location, column, axis=1
+            )
+
+    def _add_column_names(
+        self, names: List[str], location: Optional[int] = None
+    ) -> None:
+        """Add names to the columns of the clustered tensor.
+
+        Args:
+            names: Names to be added to the columns of the tensor
+            location: Location to insert the names in the clustered tensor
+        Altered:
+            _cluster_names: The names are added at the end of the tensor
+                            or inserted at the specified location
+        """
+        if location is None:
+            self._cluster_names = np.append(self._cluster_names, names)
+        else:
+            self._cluster_names = np.insert(
+                self._cluster_names, location, names
+            )
+
+    def _calculate_charge_sum(self, charge_index: int) -> np.ndarray:
+        """Calculate the sum of the charge."""
+        assert not hasattr(
+            self, "_charge_sum"
+        ), "Charge sum has already been calculated, \
+            re-calculation is not allowed"
+        self._charge_sum = self._padded_x[:, :, charge_index].sum(axis=1)
+
+    def _calculate_charge_weights(self, charge_index: int) -> np.ndarray:
+        """Calculate the weights of the charge."""
+        assert not hasattr(
+            self, "_charge_weights"
+        ), "Charge weights have already been calculated, \
+            re-calculation is not allowed"
+        assert hasattr(
+            self, "_charge_sum"
+        ), "Charge sum has not been calculated, \
+            please run calculate_charge_sum"
+        self._charge_weights = (
+            self._padded_x[:, :, charge_index]
+            / self._charge_sum[:, np.newaxis]
+        )
+
+

+[docs]
+    def add_charge_threshold_summary(
+        self,
+        summarization_indices: List[int],
+        percentiles: List[int],
+        charge_index: int,
+        location: Optional[int] = None,
+    ) -> np.ndarray:
+        """Summarize features through percentiles on charge of sensor.
+
+        Args:
+            summarization_indices: List of column indices that defines features
+                                   that will be summarized with percentiles.
+            percentiles: percentiles used to summarize `x`. E.g. [10,50,90].
+            charge_index: index of the charge column in the padded tensor
+            location: Location to insert the summarization indices in the
+                      clustered tensor defaults to adding at the end
+        Adds:
+            _charge_sum: Added to the class
+            _charge_weights: Added to the class
+        Altered:
+            _padded_x: Charge is altered to be the cumulative sum
+                       of the charge divided by the total charge
+            clustered_x: The summarization indices are added at the end
+                         of the tensor or inserted at the specified location.
+            _cluster_names: The names are added at the end of the tensor
+                            or inserted at the specified location
+        """
+        # convert the charge to the cumulative sum of the charge divided
+        # by the total charge
+        self._calculate_charge_sum(charge_index)
+        self._calculate_charge_weights(charge_index)
+
+        self._padded_x[:, :, charge_index] = (
+            self._padded_x[:, :, charge_index]
+            / self._charge_sum[:, np.newaxis]
+        )
+
+        # Summarize the charge at different percentiles
+        selections = np.argmax(
+            self._padded_x[:, :, charge_index][:, :, np.newaxis]
+            >= (np.array(percentiles) / 100),
+            axis=1,
+        )
+
+        selections += (np.arange(len(self._counts)) * self._padded_x.shape[1])[
+            :, np.newaxis
+        ]
+
+        selections = self._padded_x[:, :, summarization_indices].reshape(
+            -1, len(summarization_indices)
+        )[selections]
+        selections = selections.transpose(0, 2, 1).reshape(
+            len(self.clustered_x), -1
+        )
+        self._add_column(selections, location)
+
+        # update the cluster names
+        if self._input_names is not None:
+            new_names = [
+                self._input_names[i] + "_charge_threshold_" + str(p)
+                for i in summarization_indices
+                for p in percentiles
+            ]
+            self._add_column_names(new_names, location)

+
+
+

+[docs]
+    def add_percentile_summary(
+        self,
+        summarization_indices: List[int],
+        percentiles: List[int],
+        method: str = "linear",
+        location: Optional[int] = None,
+    ) -> np.ndarray:
+        """Summarize the features of the sensors using percentiles.
+
+        Args:
+            summarization_indices: List of column indices that defines features
+                                    that will be summarized with percentiles.
+            percentiles: percentiles used to summarize `x`. E.g. [10,50,90].
+            method: Method to summarize the features. E.g. "linear"
+            location: Location to insert the summarization indices in the
+                       clustered tensor defaults to adding at the end
+        Altered:
+            clustered_x: The summarization indices are added at the end of
+                         the tensor or inserted at the specified location
+            _cluster_names: The names are added at the end of the tensor
+                            or inserted at the specified location
+        """
+        percentiles_x = np.nanpercentile(
+            self._padded_x[:, :, summarization_indices],
+            percentiles,
+            axis=1,
+            method=method,
+        )
+
+        percentiles_x = percentiles_x.transpose(1, 2, 0).reshape(
+            len(self.clustered_x), -1
+        )
+        self._add_column(percentiles_x, location)
+
+        # update the cluster names
+        if self._input_names is not None:
+            new_names = [
+                self._input_names[i] + "_percentile_" + str(p)
+                for i in summarization_indices
+                for p in percentiles
+            ]
+            self._add_column_names(new_names, location)

+
+
+

+[docs]
+    def add_counts(self, location: Optional[int] = None) -> np.ndarray:
+        """Add the counts of the sensor to the summarization features."""
+        self._add_column(np.log10(self._counts), location)
+        if self._input_names is not None:
+            new_name = ["counts"]
+            self._add_column_names(new_name, location)

+
+
+

+[docs]
+    def add_sum_charge(
+        self, charge_index: int, location: Optional[int] = None
+    ) -> np.ndarray:
+        """Add the sum of the charge to the summarization features."""
+        if not hasattr(self, "_charge_sum"):
+            self._calculate_charge_sum(charge_index)
+        self._add_column(self._charge_sum, location)
+        # update the cluster names
+        if self._input_names is not None:
+            new_name = [self._input_names[charge_index] + "_sum"]
+            self._add_column_names(new_name, location)

+
+
+

+[docs]
+    def add_std(
+        self,
+        columns: List[int],
+        location: Optional[int] = None,
+        weights: Union[np.ndarray, int] = 1,
+    ) -> np.ndarray:
+        """Add the standard deviation of the column.
+
+        Args:
+            columns: Index of the columns from which to calculate the standard
+                    deviation.
+            location: Location to insert the standard deviation in the
+                      clustered tensor defaults to adding at the end
+            weights: Optional weights to be applied to the standard deviation
+        """
+        self._add_column(
+            np.nanstd(self._padded_x[:, :, columns] * weights, axis=1),
+            location,
+        )
+        if self._input_names is not None:
+            new_names = [self._input_names[i] + "_std" for i in columns]
+            self._add_column_names(new_names, location)

+
+
+

+[docs]
+    def add_mean(
+        self,
+        columns: List[int],
+        location: Optional[int] = None,
+        weights: Union[np.ndarray, int] = 1,
+    ) -> np.ndarray:
+        """Add the mean of the column."""
+        self._add_column(
+            np.nanmean(self._padded_x[:, :, columns] * weights, axis=1),
+            location,
+        )
+        # update the cluster names
+        if self._input_names is not None:
+            new_names = [self._input_names[i] + "_mean" for i in columns]
+            self._add_column_names(new_names, location)

+

+
+
+
 

 [docs]
 def ice_transparency(
diff --git a/_modules/graphnet/models/task/reconstruction.html b/_modules/graphnet/models/task/reconstruction.html
index 2489a49fc..d72c056bc 100644
--- a/_modules/graphnet/models/task/reconstruction.html
+++ b/_modules/graphnet/models/task/reconstruction.html
@@ -622,6 +622,25 @@ 
Source code for
         # Transform output to unit range
         return torch.sigmoid(x)

 
+
+
+

+[docs]
+class VisibleInelasticityReconstruction(StandardLearnedTask):
+    """Reconstructs interaction visible inelasticity.
+
+    That is, 1-(visible track energy / visible hadronic energy).
+    """
+
+    # Requires one features: inelasticity itself
+    default_target_labels = ["visible_inelasticity"]
+    default_prediction_labels = ["visible_inelasticity_pred"]
+    nb_inputs = 1
+
+    def _forward(self, x: Tensor) -> Tensor:
+        # Transform output to unit range
+        return 0.5 * (torch.tanh(2.0 * x) + 1.0)

+
diff --git a/_modules/graphnet/training/loss_functions.html b/_modules/graphnet/training/loss_functions.html index ad790443c..6af0330d4 100644 --- a/_modules/graphnet/training/loss_functions.html +++ b/_modules/graphnet/training/loss_functions.html @@ -420,6 +420,17 @@

Source code for gra +
+[docs] +class MAELoss(LossFunction): + """Mean absolute error loss.""" + + def _forward(self, prediction: Tensor, target: Tensor) -> Tensor: + """Implement loss calculation.""" + return torch.mean(torch.abs(prediction - target), dim=-1)
+ + +
[docs] class MSELoss(LossFunction): diff --git a/_modules/index.html b/_modules/index.html index 0586ff87f..9827ecddb 100644 --- a/_modules/index.html +++ b/_modules/index.html @@ -397,7 +397,9 @@

All modules for which code is available

  • graphnet.datasets.test_dataset
  • graphnet.deployment.deployer
  • graphnet.deployment.deployment_module
    • +
  • graphnet.deployment.i3modules.deprecated_methods
  • graphnet.deployment.icecube.cleaning_module
    • +
  • graphnet.deployment.icecube.i3deployer
  • graphnet.deployment.icecube.inference_module
  • graphnet.exceptions.exceptions
  • graphnet.models.coarsening
    • diff --git a/api/graphnet.data.constants.html b/api/graphnet.data.constants.html index 625dbf0df..34c4d3f7d 100644 --- a/api/graphnet.data.constants.html +++ b/api/graphnet.data.constants.html @@ -727,15 +727,15 @@

    Namespace for standard names working with I3TruthExtractor.

    -ICECUBE86 = ['energy', 'energy_track', 'energy_cascade', 'position_x', 'position_y', 'position_z', 'azimuth', 'zenith', 'pid', 'elasticity', 'interaction_type', 'interaction_time', 'inelasticity', 'stopped_muon']
    +ICECUBE86 = ['energy', 'energy_track', 'energy_cascade', 'position_x', 'position_y', 'position_z', 'azimuth', 'zenith', 'pid', 'elasticity', 'interaction_type', 'interaction_time', 'inelasticity', 'visible_inelasticity', 'visible_energy', 'stopped_muon']
    -DEEPCORE = ['energy', 'energy_track', 'energy_cascade', 'position_x', 'position_y', 'position_z', 'azimuth', 'zenith', 'pid', 'elasticity', 'interaction_type', 'interaction_time', 'inelasticity', 'stopped_muon']
    +DEEPCORE = ['energy', 'energy_track', 'energy_cascade', 'position_x', 'position_y', 'position_z', 'azimuth', 'zenith', 'pid', 'elasticity', 'interaction_type', 'interaction_time', 'inelasticity', 'visible_inelasticity', 'visible_energy', 'stopped_muon']
    -UPGRADE = ['energy', 'energy_track', 'energy_cascade', 'position_x', 'position_y', 'position_z', 'azimuth', 'zenith', 'pid', 'elasticity', 'interaction_type', 'interaction_time', 'inelasticity', 'stopped_muon']
    +UPGRADE = ['energy', 'energy_track', 'energy_cascade', 'position_x', 'position_y', 'position_z', 'azimuth', 'zenith', 'pid', 'elasticity', 'interaction_type', 'interaction_time', 'inelasticity', 'visible_inelasticity', 'visible_energy', 'stopped_muon']
    diff --git a/api/graphnet.data.extractors.icecube.i3truthextractor.html b/api/graphnet.data.extractors.icecube.i3truthextractor.html index 2ff521bed..6dedd02b6 100644 --- a/api/graphnet.data.extractors.icecube.i3truthextractor.html +++ b/api/graphnet.data.extractors.icecube.i3truthextractor.html @@ -443,7 +443,11 @@ @@ -658,7 +669,11 @@
    • i3truthextractor
      • @@ -676,7 +691,7 @@

      I3Extractor class(es) for extracting truth-level information.

      -class graphnet.data.extractors.icecube.i3truthextractor.I3TruthExtractor(name, borders, mctree)[source]
      +class graphnet.data.extractors.icecube.i3truthextractor.I3TruthExtractor(name, borders, mctree, extend_boundary)[source]

    Bases: I3Extractor

    Class for extracting truth-level information.

    Construct I3TruthExtractor.

    @@ -689,10 +704,35 @@ stopping within the detector. Defaults to hard-coded boundary coordinates.

  • mctree (Optional[str], default: 'I3MCTree') – Str of which MCTree to use for truth values.

    • +

  • extend_boundary (Optional[float], default: 0.0) – Distance to extend the convex hull of the detector +for defining starting events.

    • + +
    +
    +
    +
    +set_gcd(i3_file, gcd_file)[source]
    +

    Extract GFrame and CFrame from i3/gcd-file pair.

    +
    +

    Information from these frames will be set as member variables of +I3Extractor.

    +
    +
    +
    Parameters:
    +
      +

    • i3_file (str) – Path to i3 file that is being converted.

      • +

    • gcd_file (Optional[str], default: None) – Path to GCD file. Defaults to None. If no GCD file is +given, the method will attempt to find C and G frames in +the i3 file instead. If either one of those are not +present, RuntimeErrors will be raised.

    +
    Return type:
    +

    None

    +
    + diff --git a/api/graphnet.data.extractors.icecube.utilities.html b/api/graphnet.data.extractors.icecube.utilities.html index 1e73af226..7ccde11e9 100644 --- a/api/graphnet.data.extractors.icecube.utilities.html +++ b/api/graphnet.data.extractors.icecube.utilities.html @@ -699,6 +699,7 @@
  • i3_filters
    • diff --git a/api/graphnet.data.extractors.icecube.utilities.i3_filters.html b/api/graphnet.data.extractors.icecube.utilities.i3_filters.html index 0ba0f72f7..d0e06cdff 100644 --- a/api/graphnet.data.extractors.icecube.utilities.i3_filters.html +++ b/api/graphnet.data.extractors.icecube.utilities.i3_filters.html @@ -390,6 +390,8 @@
  • NullSplitI3Filter
    • +
  • SubEventStreamI3Filter +
  • I3FilterMask
    • @@ -410,6 +412,13 @@ NullSplitI3Filter + +
  • + + + SubEventStreamI3Filter + +
  • @@ -709,6 +718,8 @@
  • NullSplitI3Filter
    • +
  • SubEventStreamI3Filter +
  • I3FilterMask
    • @@ -762,6 +773,18 @@
    +
    +class graphnet.data.extractors.icecube.utilities.i3_filters.SubEventStreamI3Filter(selection)[source]
    +

    Bases: I3Filter

    +

    A filter that only keeps frames from select splits.

    +

    Initialize SubEventStreamI3Filter.

    +
    +
    Parameters:
    +

    selection (List[str]) – List of subevent streams to keep.

    +
    +
    +
    +
    class graphnet.data.extractors.icecube.utilities.i3_filters.I3FilterMask(filter_names, filter_any)[source]

    Bases: I3Filter

    diff --git a/api/graphnet.deployment.i3modules.deprecated_methods.html b/api/graphnet.deployment.i3modules.deprecated_methods.html index 6698f987c..dda05e0fe 100644 --- a/api/graphnet.deployment.i3modules.deprecated_methods.html +++ b/api/graphnet.deployment.i3modules.deprecated_methods.html @@ -363,11 +363,25 @@ + + @@ -443,7 +457,14 @@
    @@ -453,8 +474,31 @@
    -
    -

    deprecated_methods

    +
    +

    deprecated_methods

    +

    Contains deprecated methods.

    +
    +
    +class graphnet.deployment.i3modules.deprecated_methods.GraphNeTI3Deployer(graphnet_modules, gcd_file, n_workers)[source]
    +

    Bases: I3Deployer

    +

    Class has been renamed to I3Deployer.

    +

    Please use I3Deployer instead.

    +

    Initialize GraphNeTI3Deployer.

    +

    Will apply DeploymentModules to files in the order in which they +appear in modules. Each module is run independently.

    +
    +
    Parameters:
    +
      +

    • graphnet_modules (Union[I3InferenceModule, Sequence[I3InferenceModule]]) – List of DeploymentModules. +Order of appearence in the list determines order +of deployment.

      • +

    • gcd_file (str) – path to gcd file.

      • +

    • n_workers (int, default: 1) – Number of workers. The deployer will divide the number +of input files across workers. Defaults to 1.

      • +
    +
    +
    +
    diff --git a/api/graphnet.deployment.i3modules.html b/api/graphnet.deployment.i3modules.html index 97570b150..8b1c2ea9b 100644 --- a/api/graphnet.deployment.i3modules.html +++ b/api/graphnet.deployment.i3modules.html @@ -452,12 +452,19 @@
    -
    -

    i3modules

    +
    +

    i3modules

    +

    Collection of I3Modules.

    +

    This module contains various I3Modules which allow for running GNN model +inference as part of an icetray reconstruction chain, for different IceCube +detector configurations.

    Submodules

    diff --git a/api/graphnet.deployment.icecube.html b/api/graphnet.deployment.icecube.html index b3e97d1d3..98e81bdf0 100644 --- a/api/graphnet.deployment.icecube.html +++ b/api/graphnet.deployment.icecube.html @@ -466,8 +466,9 @@
    -
    -

    icecube

    +
    +

    icecube

    +

    Deployment modules specific to IceCube.

    Submodules

    -
  • i3deployer
    • +
  • i3deployer +
  • inference_module diff --git a/api/graphnet.deployment.icecube.i3deployer.html b/api/graphnet.deployment.icecube.i3deployer.html index a87442295..6184a2bb8 100644 --- a/api/graphnet.deployment.icecube.i3deployer.html +++ b/api/graphnet.deployment.icecube.i3deployer.html @@ -377,11 +377,25 @@ + +
  • @@ -457,7 +471,14 @@
    @@ -467,8 +488,31 @@
    -
    -

    i3deployer

    +
    +

    i3deployer

    +

    Contains an IceCube-specific implementation of Deployer.

    +
    +
    +class graphnet.deployment.icecube.i3deployer.I3Deployer(modules, gcd_file, n_workers)[source]
    +

    Bases: Deployer

    +

    A generic baseclass for applying DeploymentModules to analysis files.

    +

    Modules are applied in the order that they appear in modules.

    +

    Initialize Deployer.

    +

    Will apply DeploymentModules to files in the order in which they +appear in modules. Each module is run independently.

    +
    +
    Parameters:
    +
      +

    • modules (Union[I3InferenceModule, Sequence[I3InferenceModule]]) – List of DeploymentModules. +Order of appearence in the list determines order +of deployment.

      • +

    • gcd_file (str) – path to gcd file.

      • +

    • n_workers (int, default: 1) – Number of workers. The deployer will divide the number +of input files across workers. Defaults to 1.

      • +
    +
    +
    +
    diff --git a/api/graphnet.models.detector.detector.html b/api/graphnet.models.detector.detector.html index f46a6c6a0..f0caf02cf 100644 --- a/api/graphnet.models.detector.detector.html +++ b/api/graphnet.models.detector.detector.html @@ -647,6 +647,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    diff --git a/api/graphnet.models.detector.icecube.html b/api/graphnet.models.detector.icecube.html index 576844a04..29c049d0b 100644 --- a/api/graphnet.models.detector.icecube.html +++ b/api/graphnet.models.detector.icecube.html @@ -802,6 +802,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -846,6 +849,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -890,6 +896,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -918,6 +927,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    diff --git a/api/graphnet.models.detector.liquido.html b/api/graphnet.models.detector.liquido.html index 62992983c..0c10ddecc 100644 --- a/api/graphnet.models.detector.liquido.html +++ b/api/graphnet.models.detector.liquido.html @@ -636,6 +636,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    diff --git a/api/graphnet.models.detector.prometheus.html b/api/graphnet.models.detector.prometheus.html index cfdcebb5e..f0c889bab 100644 --- a/api/graphnet.models.detector.prometheus.html +++ b/api/graphnet.models.detector.prometheus.html @@ -1417,6 +1417,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1461,6 +1464,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1505,6 +1511,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1549,6 +1558,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1593,6 +1605,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1637,6 +1652,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1681,6 +1699,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1725,6 +1746,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1769,6 +1793,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1813,6 +1840,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1857,6 +1887,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1901,6 +1934,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    @@ -1945,6 +1981,9 @@
    Parameters:
      +

    • replace_with_identity (Optional[List[str]], default: None) – A list of feature names from the

      • +

    • identity (feature_map that should be replaced with the)

      • +

    • function.

    • args (Any)

    • kwargs (Any)

    diff --git a/api/graphnet.models.graphs.html b/api/graphnet.models.graphs.html index b4bbe2d36..82fc54397 100644 --- a/api/graphnet.models.graphs.html +++ b/api/graphnet.models.graphs.html @@ -587,6 +587,7 @@
  • gather_cluster_sequence()
  • identify_indices()
  • cluster_summarize_with_percentiles()
    • +
  • cluster_and_pad
  • ice_transparency()
    • diff --git a/api/graphnet.models.graphs.nodes.nodes.html b/api/graphnet.models.graphs.nodes.nodes.html index 13ee94a3d..1be0bd7f4 100644 --- a/api/graphnet.models.graphs.nodes.nodes.html +++ b/api/graphnet.models.graphs.nodes.nodes.html @@ -838,6 +838,11 @@

  • coordinate. (ice in IceCube are added to the feature set based on z)

  • ice_args (Dict[str, Optional[float]], default: {'z_offset': None, 'z_scaling': None}) – Offset and scaling of the z coordinate in the Detector,

  • data. (to be able to make similar conversion in the ice)

    • +

  • sample_pulses (bool, default: True) – Enable sampling random pulses. If True and the

    • +

  • max_length (event is longer than the)

    • +

  • If (they will be sampled.)

    • +

  • False

    • +

  • selected. (then only the first max_length pulses will be)

  • args (Any)

  • kwargs (Any)

    • diff --git a/api/graphnet.models.graphs.utils.html b/api/graphnet.models.graphs.utils.html index e20e2262f..55911184e 100644 --- a/api/graphnet.models.graphs.utils.html +++ b/api/graphnet.models.graphs.utils.html @@ -438,6 +438,22 @@
  • cluster_summarize_with_percentiles()
    • +
  • cluster_and_pad +
  • ice_transparency()
    • @@ -472,6 +488,55 @@ cluster_summarize_with_percentiles() + +
  • + + + cluster_and_pad + +
  • @@ -603,6 +668,22 @@
  • cluster_summarize_with_percentiles()
    • +
  • cluster_and_pad +
  • ice_transparency()
    • @@ -728,6 +809,179 @@
    +
    +
    +class graphnet.models.graphs.utils.cluster_and_pad(x, cluster_columns, input_names)[source]
    +

    Bases: object

    +

    Cluster and pad the data for further summarization.

    +

    Clusters the inptut data according to the specified columns +and computes aggregate statistics on the clusters. +The clustering will happen only ones creating a cluster matrix +which will hold all the aggregated statistics and a padded matrix which +will hold the padded data for quick calculation of aggregate statistics.

    +

    Example: +cluster_and_pad(x = single_event_as_array,

    +
    +

    cluster_columns = [0,1,2])

    +
    +

    # Creates a cluster matrix and a padded matrix, +# the cluster matrix will contain the unique values of the cluster columns, +# no additional aggregate statistics are added yet.

    +
    +
    cluster_class.add_percentile_summary(summarization_indices = [3,4,5],

    percentiles = [10,50,90])

    +
    +
    +

    # Adds the 10th, 50th and 90th percentile of columns 3,4 +# and 5 in the input data to the cluster matrix.

    +

    cluster_class.add_std(column = 4) +# Adds the standard deviation of column 4 in the input data +# to the cluster matrix. +x = cluster_class.clustered_x +# Gets the clustered matrix with all the aggregate statistics.

    +

    Initialize the class with the data and cluster columns.

    +
    +
    Parameters:
    +
      +

    • x (ndarray) – Array to be clustered

      • +

    • cluster_columns (List[int]) – List of column indices on which the clusters +are constructed.

      • +

    • input_names (Optional[List[str]], default: None) – Names of the columns in the input data for automatic +generation of names.

      • +

    • Adds – clustered_x: Added to the class +_counts: Added to the class +_padded_x: Added to the class

      • +
    +
    +
    +
    +
    +add_charge_threshold_summary(summarization_indices, percentiles, charge_index, location)[source]
    +

    Summarize features through percentiles on charge of sensor.

    +
    +
    Parameters:
    +
      +

    • summarization_indices (List[int]) – List of column indices that defines features +that will be summarized with percentiles.

      • +

    • percentiles (List[int]) – percentiles used to summarize x. E.g. [10,50,90].

      • +

    • charge_index (int) – index of the charge column in the padded tensor

      • +

    • location (Optional[int], default: None) – Location to insert the summarization indices in the +clustered tensor defaults to adding at the end

      • +
    +
    +
    Return type:
    +

    ndarray

    +
    +
    +
    +
    Adds:

    _charge_sum: Added to the class +_charge_weights: Added to the class

    +
    +
    Altered:
    +
    _padded_x: Charge is altered to be the cumulative sum

    of the charge divided by the total charge

    +
    +
    clustered_x: The summarization indices are added at the end

    of the tensor or inserted at the specified location.

    +
    +
    _cluster_names: The names are added at the end of the tensor

    or inserted at the specified location

    +
    +
    +
    +
    +
    +
    +
    +add_percentile_summary(summarization_indices, percentiles, method, location)[source]
    +

    Summarize the features of the sensors using percentiles.

    +
    +
    Parameters:
    +
      +

    • summarization_indices (List[int]) – List of column indices that defines features +that will be summarized with percentiles.

      • +

    • percentiles (List[int]) – percentiles used to summarize x. E.g. [10,50,90].

      • +

    • method (str, default: 'linear') – Method to summarize the features. E.g. “linear”

      • +

    • location (Optional[int], default: None) – Location to insert the summarization indices in the +clustered tensor defaults to adding at the end

      • +
    +
    +
    Return type:
    +

    ndarray

    +
    +
    +
    +
    Altered:
    +
    clustered_x: The summarization indices are added at the end of

    the tensor or inserted at the specified location

    +
    +
    _cluster_names: The names are added at the end of the tensor

    or inserted at the specified location

    +
    +
    +
    +
    +
    +
    +
    +add_counts(location)[source]
    +

    Add the counts of the sensor to the summarization features.

    +
    +
    Return type:
    +

    ndarray

    +
    +
    Parameters:
    +

    location (int | None)

    +
    +
    +
    +
    +
    +add_sum_charge(charge_index, location)[source]
    +

    Add the sum of the charge to the summarization features.

    +
    +
    Return type:
    +

    ndarray

    +
    +
    Parameters:
    +
      +

    • charge_index (int)

      • +

    • location (int | None)

      • +
    +
    +
    +
    +
    +
    +add_std(columns, location, weights)[source]
    +

    Add the standard deviation of the column.

    +
    +
    Parameters:
    +
      +

    • columns (List[int]) – Index of the columns from which to calculate the standard +deviation.

      • +

    • location (Optional[int], default: None) – Location to insert the standard deviation in the +clustered tensor defaults to adding at the end

      • +

    • weights (Union[ndarray, int], default: 1) – Optional weights to be applied to the standard deviation

      • +
    +
    +
    Return type:
    +

    ndarray

    +
    +
    +
    +
    +
    +add_mean(columns, location, weights)[source]
    +

    Add the mean of the column.

    +
    +
    Return type:
    +

    ndarray

    +
    +
    Parameters:
    +
      +

    • columns (List[int])

      • +

    • location (int | None)

      • +

    • weights (ndarray | int)

      • +
    +
    +
    +
    +
    graphnet.models.graphs.utils.ice_transparency(z_offset, z_scaling)[source]
    diff --git a/api/graphnet.models.task.html b/api/graphnet.models.task.html index 9fb706e68..8b5e96515 100644 --- a/api/graphnet.models.task.html +++ b/api/graphnet.models.task.html @@ -562,6 +562,7 @@
  • PositionReconstruction
  • TimeReconstruction
  • InelasticityReconstruction
    • +
  • VisibleInelasticityReconstruction
  • task
      diff --git a/api/graphnet.models.task.reconstruction.html b/api/graphnet.models.task.reconstruction.html index 17b3a4811..4d98f06ee 100644 --- a/api/graphnet.models.task.reconstruction.html +++ b/api/graphnet.models.task.reconstruction.html @@ -550,6 +550,16 @@
    • default_prediction_labels
    • nb_inputs +
    + +
    • +
  • VisibleInelasticityReconstruction
    • @@ -919,6 +929,34 @@ nb_inputs + + + +
  • + + + VisibleInelasticityReconstruction +
    • @@ -1157,6 +1195,16 @@
  • default_prediction_labels
  • nb_inputs +
    • + + +
  • VisibleInelasticityReconstruction
    • @@ -1604,6 +1652,40 @@ nb_inputs = 1
    +
    +
    +class graphnet.models.task.reconstruction.VisibleInelasticityReconstruction(*args, **kwargs)[source]
    +

    Bases: StandardLearnedTask

    +

    Reconstructs interaction visible inelasticity.

    +

    That is, 1-(visible track energy / visible hadronic energy).

    +

    Construct StandardLearnedTask.

    +
    +
    Parameters:
    +
      +

    • hidden_size (int) – The number of columns in the output of +the last latent layer of Model using this Task. +Available through Model.nb_outputs

      • +

    • args (Any)

      • +

    • kwargs (Any)

      • +
    +
    +
    Return type:
    +

    object

    +
    +
    +
    +
    +default_target_labels = ['visible_inelasticity']
    +
    +
    +
    +default_prediction_labels = ['visible_inelasticity_pred']
    +
    +
    +
    +nb_inputs = 1
    +
    +
    diff --git a/api/graphnet.training.html b/api/graphnet.training.html index bfca3a9b8..46b6c14b2 100644 --- a/api/graphnet.training.html +++ b/api/graphnet.training.html @@ -472,6 +472,7 @@
  • loss_functions
    • LossFunction
      • +
    • MAELoss
    • MSELoss
    • RMSELoss
    • LogCoshLoss
      • diff --git a/api/graphnet.training.loss_functions.html b/api/graphnet.training.loss_functions.html index 01a3b5356..36998888a 100644 --- a/api/graphnet.training.loss_functions.html +++ b/api/graphnet.training.loss_functions.html @@ -402,6 +402,8 @@
    • +
  • MAELoss +
  • MSELoss
  • RMSELoss @@ -458,6 +460,13 @@
    • + +
  • + + + MAELoss + +
  • @@ -634,6 +643,8 @@
    • +
  • MAELoss +
  • MSELoss
  • RMSELoss @@ -730,6 +741,24 @@
    +
    +class graphnet.training.loss_functions.MAELoss(*args, **kwargs)[source]
    +

    Bases: LossFunction

    +

    Mean absolute error loss.

    +

    Construct LossFunction, saving model config.

    +
    +
    Parameters:
    +
      +

    • args (Any)

      • +

    • kwargs (Any)

      • +
    +
    +
    Return type:
    +

    object

    +
    +
    +
    +
    class graphnet.training.loss_functions.MSELoss(*args, **kwargs)[source]

    Bases: LossFunction

    diff --git a/api/graphnet.utilities.config.base_config.html b/api/graphnet.utilities.config.base_config.html index b1f19da85..d5561f803 100644 --- a/api/graphnet.utilities.config.base_config.html +++ b/api/graphnet.utilities.config.base_config.html @@ -403,11 +403,7 @@
  • as_dict()
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -443,13 +439,6 @@ as_dict() - -
  • - - - model_computed_fields - -
  • @@ -457,13 +446,6 @@ model_config -
    • -
  • - - - model_fields - -
    • @@ -597,11 +579,7 @@
  • as_dict()
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -670,22 +648,10 @@
    -
    -model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}
    -

    A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

    -
    -
    model_config: ClassVar[ConfigDict] = {}

    Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

    -
    -
    -model_fields: ClassVar[Dict[str, FieldInfo]] = {}
    -

    Metadata about the fields defined on the model, -mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

    -

    This replaces Model.__fields__ from Pydantic V1.

    -
    diff --git a/api/graphnet.utilities.config.dataset_config.html b/api/graphnet.utilities.config.dataset_config.html index 95673d876..d51c5e478 100644 --- a/api/graphnet.utilities.config.dataset_config.html +++ b/api/graphnet.utilities.config.dataset_config.html @@ -445,11 +445,7 @@
  • as_dict()
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -587,13 +583,6 @@ as_dict() - -
  • - - - model_computed_fields - -
  • @@ -601,13 +590,6 @@ model_config -
    • -
  • - - - model_fields - -
    • @@ -769,11 +751,7 @@
  • as_dict()
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -974,22 +952,10 @@
    -
    -model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}
    -

    A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

    -
    -
    model_config: ClassVar[ConfigDict] = {}

    Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

    -
    -
    -model_fields: ClassVar[Dict[str, FieldInfo]] = {'features': FieldInfo(annotation=List[str], required=True), 'graph_definition': FieldInfo(annotation=Any, required=False, default=None), 'index_column': FieldInfo(annotation=str, required=False, default='event_no'), 'labels': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'loss_weight_column': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'loss_weight_default_value': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'loss_weight_table': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'node_truth': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'node_truth_table': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'path': FieldInfo(annotation=Union[str, List[str]], required=True), 'pulsemaps': FieldInfo(annotation=Union[str, List[str]], required=True), 'seed': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'selection': FieldInfo(annotation=Union[str, List[str], List[Union[int, List[int]]], Dict[str, Union[str, List[str]]], NoneType], required=False, default=None), 'string_selection': FieldInfo(annotation=Union[List[int], NoneType], required=False, default=None), 'truth': FieldInfo(annotation=List[str], required=True), 'truth_table': FieldInfo(annotation=str, required=False, default='truth')}
    -

    Metadata about the fields defined on the model, -mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

    -

    This replaces Model.__fields__ from Pydantic V1.

    -
    diff --git a/api/graphnet.utilities.config.model_config.html b/api/graphnet.utilities.config.model_config.html index 59d76b2e3..eb59948ea 100644 --- a/api/graphnet.utilities.config.model_config.html +++ b/api/graphnet.utilities.config.model_config.html @@ -424,11 +424,7 @@
  • as_dict()
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -468,13 +464,6 @@ as_dict() - -
  • - - - model_computed_fields - -
  • @@ -482,13 +471,6 @@ model_config -
    • -
  • - - - model_fields - -
    • @@ -615,11 +597,7 @@
  • as_dict()
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -697,22 +675,10 @@
    -
    -model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}
    -

    A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

    -
    -
    model_config: ClassVar[ConfigDict] = {}

    Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

    -
    -
    -model_fields: ClassVar[Dict[str, FieldInfo]] = {'arguments': FieldInfo(annotation=Dict[str, Any], required=True), 'class_name': FieldInfo(annotation=str, required=True)}
    -

    Metadata about the fields defined on the model, -mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

    -

    This replaces Model.__fields__ from Pydantic V1.

    -
    diff --git a/api/graphnet.utilities.config.training_config.html b/api/graphnet.utilities.config.training_config.html index 0757132b4..6982933f0 100644 --- a/api/graphnet.utilities.config.training_config.html +++ b/api/graphnet.utilities.config.training_config.html @@ -440,11 +440,7 @@
  • dataloader
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -485,13 +481,6 @@ dataloader - -
  • - - - model_computed_fields - -
  • @@ -499,13 +488,6 @@ model_config -
    • -
  • - - - model_fields - -
    • @@ -599,11 +581,7 @@
  • dataloader
    • -
  • model_computed_fields -
  • model_config -
    • -
  • model_fields
    • @@ -657,22 +635,10 @@ dataloader: Dict[str, Any]
    -
    -model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}
    -

    A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

    -
    -
    model_config: ClassVar[ConfigDict] = {}

    Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

    -
    -
    -model_fields: ClassVar[Dict[str, FieldInfo]] = {'dataloader': FieldInfo(annotation=Dict[str, Any], required=True), 'early_stopping_patience': FieldInfo(annotation=int, required=True), 'fit': FieldInfo(annotation=Dict[str, Any], required=True), 'target': FieldInfo(annotation=Union[str, List[str]], required=True)}
    -

    Metadata about the fields defined on the model, -mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

    -

    This replaces Model.__fields__ from Pydantic V1.

    -
    diff --git a/genindex.html b/genindex.html index 0572876f5..32417e483 100644 --- a/genindex.html +++ b/genindex.html @@ -383,13 +383,27 @@

    A

  • accepted_extractors (graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader property)
  • accepted_file_extensions (graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader property) +
    • +
  • add_charge_threshold_summary() (graphnet.models.graphs.utils.cluster_and_pad method) +
    • +
  • add_counts() (graphnet.models.graphs.utils.cluster_and_pad method)
  • add_label() (graphnet.data.dataset.dataset.Dataset method) +
    • +
  • add_mean() (graphnet.models.graphs.utils.cluster_and_pad method) +
    • +
  • add_percentile_summary() (graphnet.models.graphs.utils.cluster_and_pad method) +
    • +
  • add_std() (graphnet.models.graphs.utils.cluster_and_pad method) +
    • +
  • add_sum_charge() (graphnet.models.graphs.utils.cluster_and_pad method)
  • ARCA115 (class in graphnet.models.detector.prometheus)
  • ArgumentParser (class in graphnet.utilities.argparse)
    • + + - - - -
    • graphnet.data.writers.parquet_writer @@ -1432,6 +1448,8 @@

      G

    • module
    + +
    • graphnet.datasets @@ -1472,6 +1490,27 @@

      G

      • +
    • + graphnet.deployment.i3modules + +
      • +
    • + graphnet.deployment.i3modules.deprecated_methods + +
      • +
    • + graphnet.deployment.icecube + +
    • @@ -1479,6 +1518,13 @@

      G

      • +
    • + graphnet.deployment.icecube.i3deployer + +
    • @@ -1955,6 +2001,8 @@

      G

    • GraphnetEarlyStopping (class in graphnet.training.callbacks)
    • GraphNeTFileReader (class in graphnet.data.readers.graphnet_file_reader) +
      • +
    • GraphNeTI3Deployer (class in graphnet.deployment.i3modules.deprecated_methods)
    • GraphNeTWriter (class in graphnet.data.writers.graphnet_writer)
      • @@ -1997,6 +2045,8 @@

      I

    • i3_file (graphnet.data.dataclasses.I3FileSet attribute)
    • i3_files (graphnet.data.dataclasses.Settings attribute) +
      • +
    • I3Deployer (class in graphnet.deployment.icecube.i3deployer)
    • I3Extractor (class in graphnet.data.extractors.icecube.i3extractor)
      • @@ -2214,6 +2264,8 @@

      L

      M

      + + + + + + + + + + + +
        +
      • MAELoss (class in graphnet.training.loss_functions) +
      • make_dataloader() (in module graphnet.training.utils)
      • make_train_validation_dataloader() (in module graphnet.training.utils) @@ -2240,16 +2292,6 @@

        M

      • Model (class in graphnet.models.model)
        • -
      • model_computed_fields (graphnet.utilities.config.base_config.BaseConfig attribute) - -
      • model_config (graphnet.utilities.config.base_config.BaseConfig attribute)
        • -
      • model_fields (graphnet.utilities.config.base_config.BaseConfig attribute) - -
      • ModelConfig (class in graphnet.utilities.config.model_config) @@ -2419,8 +2451,16 @@

        M

      • graphnet.deployment.deployer
      • graphnet.deployment.deployment_module +
        • +
      • graphnet.deployment.i3modules +
        • +
      • graphnet.deployment.i3modules.deprecated_methods +
        • +
      • graphnet.deployment.icecube
      • graphnet.deployment.icecube.cleaning_module +
        • +
      • graphnet.deployment.icecube.i3deployer
      • graphnet.deployment.icecube.inference_module
        • @@ -2601,6 +2641,8 @@

        N

      • (graphnet.models.task.reconstruction.TimeReconstruction attribute)
      • (graphnet.models.task.reconstruction.VertexReconstruction attribute) +
        • +
      • (graphnet.models.task.reconstruction.VisibleInelasticityReconstruction attribute)
      • (graphnet.models.task.reconstruction.ZenithReconstruction attribute)
        • @@ -2886,7 +2928,11 @@

        S

      • set_extractors() (graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader method)
      • set_gcd() (graphnet.data.extractors.icecube.i3extractor.I3Extractor method) + +
      • set_number_of_inputs() (graphnet.models.graphs.nodes.nodes.NodeDefinition method)
      • set_output_feature_names() (graphnet.models.graphs.nodes.nodes.NodeDefinition method) @@ -2978,6 +3024,8 @@

        S

      • string_selection (graphnet.utilities.config.dataset_config.DatasetConfig attribute)
      • StringSelectionResolver (class in graphnet.data.utilities.string_selection_resolver) +
        • +
      • SubEventStreamI3Filter (class in graphnet.data.extractors.icecube.utilities.i3_filters)
      • sum_pool() (in module graphnet.models.components.pool)
        • @@ -3090,6 +3138,8 @@

        V

      • verbose_print (graphnet.models.model.Model attribute)
      • VertexReconstruction (class in graphnet.models.task.reconstruction) +
        • +
      • VisibleInelasticityReconstruction (class in graphnet.models.task.reconstruction)
      • VonMisesFisher2DLoss (class in graphnet.training.loss_functions)
        • diff --git a/objects.inv b/objects.inv index 16ef418471f0064d902b9a91845291c61265591a..a9ef51305c96736ad3d3a5048eef19b4cf4d1133 100644 GIT binary patch delta 9214 zcmVbtXsDb=|%}qhPna7ul>3ZGk>abP`vHO+pCu^Pq)tk z*bfn7o1g5s5Wwxt?d{|B=cikNjIxZ9U7q2|(C@BqufKe_{o8-e1OMCAFTZ@6$@EWm z|NL@y^LZZd$EVNtw=cimetDh;|I6bqPggh7dgkTn%ge8m1)xNmC;AlhJfWwsXNWrm zJV($e!7QcSbc?DRg#P)3q?S<)nmuzo}?M@liu61pg7p#FLRS(q0ypOVxR zY=pC863otuzwtu#GMZ<{MRO~8mklQT#(9Vc;zeoqJb#39ikHo6N^y!P_KL3YGSQUg zA;T*~ljMz1x~!9BKD|sl2Ka`0#FF?=<^bCUT_s6N51}l1clnWo z_}S*F1~?FPd+-BqPgKG8cbx`Pkjr@(ICe(j1Dn({26R5h6b#xgY(54RVKWjWd6wpx zw@<l6 z2YimKX{ks|GVc&3I}~~(4)B|xC~`K6Bur2MDsm+VC~qw&-1Dgb?=R^xHV|~Xr%B|Q z-Zszbo*V#<2Q&Fe81jdaw~s--2IB^a$By}auYa1j32;HfW$-Y$B>0Q?;Q_x0pWhcG z{RL@%YIlOWbQH!?@sP>WnK?3yXpnr5XQyGASFOmsJ;~906p?sI!f(9Io1BjIy>BQ> z0jf)B)DOfQguMlI-dica*jp3?UWj%$1Vrr!8s1#{ym5{Bzj=w|LjwG87(tXGz?gL; z$A8xx)6;ptIA3O5My3O)Zeu>;=J<04wP-QC^W)L_tQ|nXA6N`~QpOALUi8y+UvoY- zSwGp-92}d+7qkV_(!dtXNbA3zTWi^&J&t?(sP3KOuh){XCT#s<9>02w{0W%sTgD>y z24|o>3`J>(DFa4?5eJ4qA^r)+_bBs^AAiJu&ngvG@>NCv)f0+?B)S$wx-^jrBzO!> zK`CTBmgLmOi}J>K6q18YNLo0z2 zR(~8@;8xu+yxZr0e&V-Ijc<<;qu2+ua!#h;H$G(Yv&7oEodqqfEeZNbv?DS0hJTPW zb;s~-uT@fTYm)kl6<|oO1-MKD%W!cC&*xdiJzF(8SDtN*B70*xkdOG-&vzK^JFNis zoKYZ`14^nzc@*>Z?$W*dI*k~^E~cKmgCAI0nhDL&FOWx-LLFmBVKgxAEon|`S_X(tL0?x)3zIo)9Zxd_kU~Qmz2W=@4>)F@uvSFAq>BWIgXDZI;?Bs0mqo~ z+cCAXjxnTmHZblke^E(eYG=D;K$DKA9VG$9elp5CEigkI)CR+SghGBv{KpW*_*W_N z#6`yVtkYhgp>Y=FNvtM`Mmeq(Xo&0Df$lCJUhaANCy_qJVLf&N4NMW`Wq%lsdqy@u zhPbK;!rLsJHpWLC#zCzj42|f#!fbkH|8F(*LPviLmq~rKbXBMH$CUOTd~9IIinaw>zkIH(s3=L z1Q-+03Sh_G@#^^}KYt{?N4X4TkmW{D(+1h(Bk=^={lOnSUY78dh+;22@&4(1uuJVI zQw`(0vQBPKz|jso#4&p8x3(GL zVj&}V7m&s%bZCFIhC_pEG|a-aA!FW7j4A9eYx4$-el2$O8h;d$uQ>@4xEHhnJj;c` z&qJKvrag{(`|Ho{KJGSS2>-7nTib+z6JZ05NNFOPHJm$ivd%j2@-FF|FNcJk1!yvh zwvR=kdtrc#oXEPtOF5P_a$ryoG!eF<9=4L+NCi0M-F~@AUiAYQ5WcB6n6bP{9Jrg; zWf7gP%kzU^sAe+CvgBe>|hCFSbup;^BxTPhC&j^!vkjakXWbS z(83sTV5?Gyi}e)n_M^(;0Ph}EU@AQX_RJ92&28=4P%n09>j#~aXZs8pX~6*J53@!O z5#5TQss!|WP3e=o{p{lKHrio)?(TKtE)7ha9NW+X`nIWe9%i|CxPyNTvAe6mMu4{G zfwtvoA%ExbT&LbpzS3qmU|-u}LX#W1dIq{w<}7Dgo-FY|Mbo1R=A?2LDws%#JEC** z2>njPt1IAHLG6TnOnUdCd*Rd-!Fg*aqKpsIj=&SGYz8#yVO+(0!0!chcbWDw52chRRr{G(DL@bUG~M&s&fck`dF-jq zsei3x1pIu?f&8XN=@fERC1AwWl=Lv(CEnU-hw%;Ys~fp)`<=X6(E&QOs-p%)E-r21 z96~n0pAcq-ZC@u668)}{5~ZQC18$4fFs|(fL|#$&%fD`(BNT?cMbpm=r+obUaJwK| zz6*(ep3{Jwkuw$d%hTP>?ZeAFnJo?~wSS&F)DQ>6N=5vI-+=wrB&sstG)zwBvkx6c z7cxDTo@LZ!Z)?^Rc0%6XlqlM>-^Boi7Ndxs7HSy2xb&55VI<|6m zk&?^Ox$xGE71E##ou!>76k!0PEhxHTcb6`4X}77<80+aq4Ov(wwX7dv6pK-gLw}@p z=#Jqv=b2oKWK7|a+iQ!>2y*Gvel^vcvRqPgjGhi&D`C9H6vsXuQn+zllW;{hLb9GTnJ8$v8p|M&Dj1VIIZzgfSk!w*5(iM|R}GfgaH=cPG%h-!J>t*g-Nq>@MvSb|iLb7DmY?X$# zxPvv+v(3`xU63rnVf0i(ESY^4&egXQ#`9=ZoRsx`PZqRhJ2Me zs>v6tr?&6eOii?KARE@zBH0+QPAC`btHiQlpD&oL$If*qz8GE;m7`AQ$TO^dj3pggMaJ@vswJbz$5fQDAuown zj&^Cont`qiSTV+>0Skw>o_+eSr9#~BtrF%1`O2YQ*s*4~pN&{CeQ zfnQ->E9NUktP<{33)YDAiUo@W`Epb1`UtL{{`%8TOL8q+o65v%Ri?5HtJI~60c%vH zvH?rgq~B2{o=}U7W=mYlhIfCNc&+d*+ptP_R}5Gqyvqj65#AWFlP9mOYjMt^)+IP4 z(OZ7`e2O#lW~(Z7d@!)w1I7K}g$c87HyuNxKg}jj;fctfkln4r>GmX>6CJqCXgEW0 zcGrv?Da8Ttv-uf3#Lh=h&rc_ICWUCHPw=vA5E{AU_#J zB%U)T0$&~sKd;A%Pp@T&y|Vd{$fA1ciUmW~Y=5r?+;y4$^SGnT} z-UzkmIk~c|r}GJIojR!pat?AWm>l|;fIce3zh536AdV^^Em%$t0E5OmkHmbu0_h65 z0w;MkB{K1GMBYHfq(ng_rA5WcvO6EtqL#s7s7^&U06tE<@0foaj+qx=ADt$nNfFJ6 zA7bdUy(ACveOdldUq4__bKRhFNB7>LqNY>ovLl}(YQ;W@<#orztmY{h;0YTxsOc9A+lke=6xP@Y& z<`#};wR>|l$d`XLdIw%JM_8oD!<>*jS{^}84jX8P{KFp-4ux*SW_J8gWuch85WpAAx_~kG1Fw;n{v5F`}pIO5%&oSzn}g@{c9n z26&J1F!Ng1fZMwJ^PAOJ#=V|Nl_gZGneiz(kc_PsFN*%1MorDQ_Y*tXuw^6Yp8J5v zv?babiv1*J8O?oogId*rHK;Y6t3OGUXUC@oyES)hzZ$+IJB{6T{%)LMlByD9R@8MA!5_R!qL&BTsbm&3|c-aT8vpX zBL2nuKlp9om}nziIVyThT0SmX%~?1y2qU`?uhPm1CyYq~*h;)tvPsW4Y=7UiNnwEAL_Azu&HzqX)iD3BFiK{&y!g>|`hK>-#f4 z9JoKCEL&yAv$`JIIGoYtJR~QUPZ-e{2a}gl3D<4O;$Rl&GR46Jvz38akSI1MOkNOm z@a3vZgL#$`YOqv_X?mWyDolS1{)`o;jcvC0p4?Z<#_@7ZzGQ+Q3GI$OYY}ht_KR;Q zoWyjor(^Br~~FiL}%ws+51eq7L6AvzhIso)K-6DRCI z3D`*zN(xbmPF|L{>{z#Kz}6e_QRwHP+NpFt(2A;K8>c0BJN=n?$0UDB(jy5^Q{js? zXHRe#u&EGV40p(XWdO87)&*Ccxy66GMKnA; zXGxlB+god67ug^du}5uBvi==vlQZgOIZgcI!px<;UJDX4oaO2CWRC><_&aYFKarUC znm#>E9y1LFS?xnQLtcMqa-f*84~R~mi!-*gUwjmY_-xipY{h9&rYGoSUxR1?x(u`B zxMUq(h^$m?=Vx4^f$HJoy#bm{#dsbSSe{%;5b)U2g2mckdu=U4_hNn$f2PLUzT#8g z*uow5g>tV?VkRF%d!~y6Dx``6q_C)9di1l$MJubthDfg2p6QfjTw%1 zA)cGY99(>(yX`aceM%13_rJ|fuoW#y|A=fdD(l#98m5FDXD=JZKAI8AGBis#@BZp` zX2;z>&&}|(48^~a_@4KU*+;^Tm|ot@Oj)J->#}qU=WcN_E^+Yu=ylGj)y?Xml=o2H zRwBo5$j>I_woHG;RpkIZ89k|$gmOx2ANS1;wSn7Flk>5Z-Y)lFL!5!8VSprJ;CX&A zz^1f6La$h!W+l!)QghRjLaWh9X$&?Gmpt!}4~p_IW0T`D9G=H3VDpSs z1wg>p6h8csU>bkwIe)L03dHdxCSt06Muy+z?MHrx=|X=r{U2n7bBT~38R`~lxd%KIp4Zd_JmQL?q9W)WEJiNG_y1l%I@_tT> zR(nz}YFzQLM6pY4KFhahl6v};@nj^W<8CbxtRx}vt0i}cVb2-Aq&19d`+;9y7qphL z?qVH6w-tY%D(*eBa3ca^ z18+dHGKyL@DRqZ~8x&V+G1J`p8m&vip%F0}WM%vG_`k^Mkgg=}=ATnlJj^^@-bR z!5Hdob4 zg(&wn@#PL+-sJkP=m0dm!UZ7t14YqEepi#tOT=3P|2Q87#b0wmapAS;7{cUm0QT3l zD5Ri`=qLUcv|y=%4FcWzlqdUr#{qwgf)DU6Kg@)UDNX21*rIlON8X_gF=eo~=L1+~ zCm``YnaM*8XP@vlJXhebjA9hcUj*L~EjGqap9_udCB0{b45N6$DMr~x5@wUP4P|Ii z6*R+K){8SwsJv%l=$d>7zfyrPMkqUi9>G!&(k?4OoH8#YufV5B30$C}U6OxiKg$0% zEDQb~B>v_Hu6$0GvYRiAKM60&m=*Cdmz2MHysJoWT_5~c-Y8-qxRlk<^4bcl|G0UsRkcjp z<2F9zrO1~PAH7^>IR$*a?*$cS%t z$K{T(ss+Uu*76h7wm6IOBvwls$5_{jW9)1F5o#fC@x}LgM+I2}!&uh%0c;gvXp}`| z{lc1ZBGeN8IAo&&s|tT$Y^kO~jiETBql~En7-OobP-9pc^2bAzjtZS7h%u`93)C>V zvTBS`RRCj9H5F`39*r`kq+S?ON`skk-iPUGL3MlPrnq(FmD|O!-o-uKh7yYDqZA3Q z7VRmDMma2g4}EjV?fdOZOe`2$D%M$Eh* z#(}41SQ!kysi)^J8tHB1)a;DoBZa_1SdlgUDyLZqs`FROiLa{KGWXS%KZ?Z!mW4=(tDiv2o(59(a+kWXWLGjp_Qi#j5X=*q;YlNTKVSZme^YbRHxr zH+Djx^3sI0gOnRdIB<(nqiwbD$^)PwF9I6UdaP4QsZroGOip6!OOwGK7Joc(!}bEN zN2#6@ul1$g8Gu}xRpCp$%2R;K!V77M`4bi^W7ENJ4#7M3tffrwg zs-9n|CR+K)rAu@+wM?N}BehU9pV=9Z#B!s$dQ{VcDI2qDPE`YKioh8lWoVo7+j?yH?eJeg1lEs^oZyyzZ>g%R- zDd-W1ytYxKNfJ5`2yy*1S7t$Sj2#Kvl?U3(jR_hwJ8M_Yo zo*BEk24KRhTcv-(OzUC9PHJnSjo~b*!@sz11wO>F4UvoJu5uiAVQils9=wcX2?Wf@ zDpYgV2`%P;`WD4CMT@0n;-(XSH#o&OIA92_7S(aBZfv;TA0%d(1G-YEaHu3J(e&b-XL&FvZ(z0x)apAy9S0%NxT@QnS^!@ac`~gN~$!} zWIbS8;e9Bil+|@yTv~Alpu2NKBz{f4vsdE8Q)ubljJfUOYn;LbBdn``m5Qd6Y9(ea zbl~zAr~g2arK|#$msZ>X=q?=U@N*dY`KW0*OW2MJdfb(sblnfRIH3^=$)92%B(^x& zKQsc8~vN0TT7b(6@Csav3nkDhLS#8oGZIsk<1iQ3!=LanNpadV$^9Icqsb-ws$g(|lv@E_#my0Kk^c3fQRY3-EEyaQONe(3?`i1^k3xIAP;l z;7vK@!sSRYIBCmKWSeT*1^nnCIBny=qD?vF0(7DaoUMEW%tqf_I2}v@=W09AVpB`J zu%1}~;Hw>Qu{qy=UqDZa0I{^4F0pAOU-Tbi0AMN~c(Bno7yWzY0jTBO^&5S2(ZAah zfLh)cy3scmeLFJ&nCBgw8+j@5I$my7USl!pUx?3HsLiZDo-fN#5>Y|AKPBvHhw(gNzuC!kQg2L zNAX2h0U)~!Z98B8?cX=Q@~7qxq1xO9SM^t|Jc-D(a0UmOlTF)3!x#jcR2~Ax|r7w@tb~Cqw~XvNc_tt zJ)Rix*$)XNm>Uz6UXhg8ijHN3VkG8r)F`S*7JT?E#gxc**1A&sL#FRZ%&k2AWz+U{ zyJWwzOG0upw6Wrc;=P)PnYwdp;}%}{gm>sJ4&v>9QGnm7abQwa1l@^CE-5=s>O;Ud z__20hjzo*7LN$T1$#UKt6BJ&Y4beCy8;Zyk)2&E+7)?|leN)wG{%*2y{^ddh6!){1 zDz2+Yts(|YC-9ucz;=QlvrT&Zdz1uuh&TVSK`Ht1pnupt zXHocX>Zc$6ee=Uv@q?elEJJa|x^)YYZj=CJs2f21+OG>Sqkk#~#oK<0F-F+M4y75C-fBd3~{G` z=LkB5JX6Fe@P7%zEvG2MfhTTs3uqq2rq!gnpp^I_`>aQ1&g?TaaDM?Mi zMmT#;g4tQ|D=$KA=-HnlHli zfKQP%EftAL<{iRhheD6U0e%-0Mb1W%gb4~jMXm$^<*fyUdu|Hw{*o?Z13|ZYnna%I zZS$<|$pPSaFq5BzA%7To`xxYFFm8}|>^a}>ReuvV0WN5`3?3$z1b-1f+~FtT^V@=? zzaZ^T?M`r)j>1?f9x{14Ge?FI4U)Hbb{dv>)r#EPlN`-Q5s8;1eC2K4dqY_Y zP+dx+ejw%`>@BGC-bw++-l8DzLbSsnAZka@@aEd*jcd&R%}XR765xl!2%;1L#;hYb zzJKSK9!~?t`7+}&G95^D74s1{$DcE(MT_B`9*@>%?Enh?z+%{wGG2i9qMxSwn)9*A z`pKr|;MhFApe>k|2DV^ETL1OjTFVaYaopQ`b?+2^y_SqMVe3EV@r%dEpMaNr%UI;z z;0&~fp(qV8Wx$9q;=m9n#BXqXi!%TDvw!&SQKiC4zRC!odO&fIL>Hn+mnKqy1dpL9 zD20s2lAQW@QQkO@JoWpG`91JwJEmTUV=oesg9C4u`!6_yH^N}f?;*)Bv>HfZXeCg> z>W^a!+^RcTO1e4bR?vsI&W<=Mt4vNxs!`G}AGe23w_(+Y6U z83l4aprl%qM=@`&&)v(f(}*$b;?RrGocy!1M;X+sACK%j0VQ_`4^QmrfAwN zo6e+bA75}`HJ$8Z+IER?dXZ54aepoRmU6h@BN%uuzVzQEgyARgj^j&+4(r-@z%i!$ zc1-Q8V+^UC4UFsaUsTeV+SzUy(4^<%j*@_4KN;nn7MLLpYJ=fELLt8-{(XpI{Hqjs z;38vu)@d)$&^U|oBvvnpMmeq(Xo&0Dfv(T*o^E;ijYuEkupT>s2BwJeGJg!mJtG?+ zLtNDa;cb>q8{?x6&H){{LwTBXbB%JvT+Sk6=8@sY6#co z|NM6K_;rjw+H3+ELvcpOIi!j(#340=>+=VZFvcNmHUW)cX~;*jQ97qX2dkqZiLV`XTW>%4H~n z%$|XoHpnI)iO0n54}adids)J(JH=jl%$`4lU21`pYJEPGb#k^nj&_)OuZVX7cH!9O zajZrB`LRn9?lV=zK87tg&ZE^$(La3<$LNn>Ynvf17BYhOvuKP$hxS)%I5fCM!_31P zGO+B#n8FS-)oj2J(_&YzK_U5`lOTb6K`X$sTqyiJ#OZC?-tZ1R<{dBbqg-2Cj%Vb5^ma(dE zW!)!pBdY3-;eQpcj}z@zs88*-3^77Y^<2*e?Sv%^;e+YGUglcLQo2UUq{@ZOo=OE0 zw5g6@EtUp~{S6+leOvLcKdLMa@a|Cs zrqV-T&kTXx+}5rQ^(X9xoNBV^Ng;Q4q z=dGcLGCoXu25!(~Gr);iZgh%IYZ%vImh&SRdc`^nm$gLvzC%n5cL)Q_@R^5PIbsbH z#3$I4k_geGoUO7fyIMqR+^{S+&0`U6o}UB@Gk-4@>=`BT!DCoYJLAuFmV~d?ZV>}O)806plR)-^r^L9iUUII%-hl;?fq*A!Gym31Mc~cG!-P=y#QrC=Hbz za9gy7acw^%@`A!&{&o2np)l+%ntooz(KaX_q8#Gm*L*l$guDg#c#~STeGIH6Y}=5MA4r8 zE(S2P7)A87P{Z)WrDxrsw@1stO=YdiBE`0Gua&!t)J%Z%LyTh4MRv$$hb}0yUAlU2 zhYOL6DLmV~w%Cjy@g7qg`*=w1>&i~qZzx}%Uz;TN%(t6Tu>rq}Ps;u4;!ZN%d4DO% zI6@9a-(DnP9>uqWF=)SWn@G>LKVX`KyGKus$|#VVK}fYs!t z(jcbomn5eI)2mp#0;Tq%=;9qn=uj_5Ge43zX9)>Vc%QJVXtzLS>y(RTH$^_qcwJtu zZ0nTsXE#L0-dCnw8ZMPZYkU%G==F=-(7~By!U0S}eCSU3IZXVQSu-UW7Jtml?4?w& zER(5AnxyyosDRn>WJuIZOP;xuE|aT;e0Yqnc&|WA@0iz(C!WPJ_9V8em^)XJWSJ}( z2R@N3nKfHwqUE!;jWA>AfEQ$>Sj-bnk@yl;d~lqN`Zi2wEk2GvbE&0C61wy-guF}t zLdqX#lBeG82pX%jP{BFWHh&~y?tz}YwG>?%WpmO+B=$^E&CTJx&&k5FVD_9Cj+t|k zNAu@IbI3Vl0b%By%Mz56Ixpa@asT4mnxM6jDFof2hjVN%OJse`eg~Hui8Zm4Pte)BqznGe6;XpR5t3|RgV4YAd z*jI^V!#-ayTQ~LUP=A2;!i<7m1M9v11g8GE523L+cog>e%`Z1PtY!w;HKdP3DCLdE##*(|%m7#pa zto*;t9?2)FWrMlIyH-4xOjsqP%lvCZb%}qez%E_^+*h6rvwuc-3+J+--e$mBG2dp( zD#71s$Qrev&5(twgL!xKx25VrLAXjqII*u>3r>ctSp`Z~tQh|%D;5s^UvT`_rQ%+2 ztrGH*c;#r9Hmn)w%77JPTpF-&cdFWX4ieKx{qpL6nAeK=iV>@Xd)0z9BE4e4VnM##t98A>(SJ{W{pqJAxt6U>W#Y9eQ`v@9 z>QcpkHL6nCfTe2E?CjM&kW*Vef> zCsFGZoRa7jzkEE#8G5%>l{!8cSgwKM{_w(t*_WG+q0t9l$z6CN@+V|<>u|a~$>u}{ zE;Aa=P=D;*H6uq#aX|cReg+S*(+0ou(}|TyA=>F3yetcZhO@C}#Q8jy;dI74Wr&JB z;1|eGMiGhU%!$C4+iuV6vEpE>46zqBKamKx$+C2aW9zeo%UB;GLgwM_&dc-`4OT!S z?1U^Yp01z1+8$3$1~4?Zv4wMpQy1gD4PKkFAb+eyz@xR z$A2r3u8=Eml4nyQ6CX$99aKz86jV}LRLm^9_CYOb861Y{RCEL2Kd;20HC1!Vz5)-W$7*h&6ArHYH z$|5)By2N`vW-Ok@zKf zV=u%l6bm)Ca6GBqnyW#+tkFC0ns%0p#E;? z$@7_<8-aHE5xlPL!7u}ulY5zyQ&kHWV#Z|FTpY=O){6#a2Jo2QfjuLIp^j0)1Ap*` zvWRJZx8(iKFan&^AOtcAj!*3J>#f+a{t;8M2%~dNorcV{dQQaZHe{KUTI^C9=g|&R zFWHwyWDDkAn4q%nnNPdLc4Tv#!9Fp0F3sFAeUGUxwi^%eMVK?QA?(D2;#f>@10;o^ zO^*`xmFXVKqX<#*C-&Y*_Uxra-hUXp15u*4@*Yt3%xMdH{5>}x)TSrn!&5I4J23OH z7iT%n#1aUP?T=y)JkB_i<3jxIv4m!mp~F6r!@iCysau2CR~IawT1rSRd#VpY<^TCP zW#ko4iNB{w(b`)D$Nq17>jUY^QXFkZ6z0|VNY zF@(@ChH;2jJpqUFcEoP!0tZkdw8n@|3GaKVNb!fObjy2V>f>!hBRv(>mP~~u&v^ohRv_+kS%%w{( z387PZI!mF*jKfhUxIjifLRGBZbni)6Afn;p8cv18pG-_(beVo|QhAkUGx7-IrrY+Il zQ0yl$%V_Sy8`P=}tU;~meEO3_dG`F!V7KP3jeHdA1eIbwn}*ee>Fsf^0+ZYDJIS7Z zLurcE36p~UBgRY9xPK24I48rFji5`y6U5b8F=R7fqmx&();AiexCch>>n^znznt6pgGy~F{0;N>|>fC5@*NNVyI-p z2aTjQ3qMXgm91MNs-7-Zd0y3NKSb3B&MEr~Q zfAIUlG0{f4a#Zx1w0vB&nzL+V{2z|V;xGQ&NLP-GUXzxOj8=2jkBsGB*!Hr2z*zYR zuWI}4nmKylGk;6q(@W%k*K&zPb_9QLJ>kQF`yz-o68C|yPaALW^h{iaW zyp&3~Zj;Ogvp^@74JMea49pZVF`az!f~bQpS7jQ^vy@PSrBY1O^UPIYTJUGAIBjgR z#rNdCS~iZCYw{%%e8*CE>{*L=t0&CAqHq$^#VSzVWPe2JGhlxQ4Px3}KVo_Im9;{2GCEVi8(t?)*m`H!LT4p~C`CsvOI+3%Tb9h~rPC<%^H8lV zIqkPX)vjXG61*S(%)I9$O44T%9;d<=ZO)$HFkn+5zQnPowl~?K%zqvMYZiobhk}vl z4ue91JAX3VA^(K|&T(u<(|LqFV@c5V|X{v2+t&Lq|gIL6>qCLs_*Az|8sGH?9 z@t+rFF0Ia4keJ~tPp2olC)metyji>ywzt2hpDC;(!XNq5vtZs)Ak* zLwV{|oN(HzMJH5ar@is1Y6OP^pD6U zqkpoF{ib0`*z@dV!`K%yLRp4p3FqBDUd`;dhh-@KmBhEa@5;Uq_KfNI<;;{-y1y<< zw{Y$jC*u+a&yQZ_4E%0Z52d{S@V*i`en);bDYxZCSyc|u&(N=&l2E>I+Q)tGZrZ@@ zsL5%YKW~@&FCorAFG+wTVpw>3ZO^8(KYv0mSndua_LEU>jwgjyV~5fRX&x@Qe;OaM zmvyEB+FoL0jmmtfUhZh{v*LOzUkS|td|PJ@hv9eMfi*izsuV% z{0`HFX!=j{gL8?HAQ|b~Zn+TYF5Z&}qK6bwh9Pi9)&+O_i5~I@$JxEO>-KgRi+>w@ zX_FzH-amI|B38K>Y&&&(c@O3Nnij40q+Zmx;-oFH>SsR7w`r1k`h)IdB&F>`EfK6F zA@QpvcZgxn8NZ}8jBERuUtbioma^_*9YVJi=Unz~0yh(HkVom_r2X5(&O|D|>3MpB zNl^N>2xz8eF~o$~I{XXgUvz*`7=IS6wCGUg{o7EFr8nmWi?g#GT9LAvLo-rQyQopa zT9PL7K+00n-1S;|Msm>J(lheQ9{=q8ViY7cW_Er`RTUi~tfqLWZe1T&ZS=!=2RyeX zHb9@?;MkH)Y((2>L#r7>;sC$%pTay^*AT#pg4s019(Jk{GHJ}d;TD1e1N!3(aPRP#koQeO4khyhHsi5h#g5@0!kG1I>IbQ$k75(_PoFPtafa6FGD{m4Hb4%Enj;qQ$lKk3`ZE(aI4Y|- z42>#ka$j=SVNsKK7~|IU4S)FL{LTZi$*85L$einLe-3n5(Lui# z$3h=L+0&wsOc~KV;eXFCa_;R3_`z9WvA{p`(HnlxaLg=o6^Fr#?uH*o<7WZaj+qXd zL}@}ZP+@9ONMRPD+}p&LYySB&$$voypy?GZ0LdRHijMN^Q#LOVZw>tC`6wvzap)+BN+U-5_ z9)E}_gH1#kz%n}liTBA&9%4AV!LN9(z+oB1D4M?r-ViOe!k9i68r@5JcLy3q@qkl| zvM(geCT|{lfgD^%Ydj>s%r68nTR)RQXUPxYmPmvP1 zKt;PG&wiBuZ+}=8{5?qg%@17plq_X8-xz-qo|Q2x;$ zPzc3s6-SK5J0Zl6N?Tkt6#-UM#jK`m{hSXT_>fcF=z{HsZpdqnMtTdG_|Lq<>t!hk zp8TN`x^R>DRcud80mw$Qgl&>K(De%xE3}e3;i~%%P=AQO>wdQSm-U2pS?C1EZ@RJE zFdeZ|M8D@yY%Q#?^^G0d{Pmpj(V<-7_U!p%C`#p17es2L6^ps+ga6JOMGOR&vKm@m zTY>c-H_x@ImT7z3#)rHV`SQg_FV{&<0iW)BLB+0;I}&4W08dlZG_CdYeiMpIFmrKP z%WFT68Go5US+u<3&^I84Ejf43Q;V)N6-_0#~4wEFt*gwp(Y)0j48hzVNxB! zm{d=Pn)H0!Q4)v^vd37}f?^D7`3Y)UoJDyOt69QhtZT(F_O<>9wUD>?;!NdHLDs-9 zmNk9=TSXWeWl>qbu%?^{wS+$o*{Hy(0vKDWsee#oD9-38W2ykgm})B27?y_o@erk> zLZ=C0jB5S@HB8RL8)H-zz!+3b1sjt`qf9BO7lxG5U}l`wcDq_oUGlvtZXJ2$78F?T z3^Ck>5{l`g6bY^t?J0^zIYa>{JJhwS3F>1)hUpkHP9P>e%)P5Q*)bjE5UH<>ke3$z zn3J|08-IIFf&@&jGPNN*#jW|1i$DFhb6imdThIn7E?eSgKA z_^PTc@4njdN3nQ;Wg*f+3R2&6V{MDMZu0ApN`HkBv}r2VwqJTo5dAqgt&u+U1#R%U zJ@ib&=fu{oTy4^8Kla$7TPr6MsydZ+)lOJy0$ey7YK;b^lNs_N4DmDS3FLpwp^3jB~gOnRdIB<(n zqiwbD$}Qg^9|9WEdaP4QsZroGOpaoyR5xxRQnaV~z6(lU_LXQ;whZ1V#k#oMyvFtc zuScn#6R-87-U)!5n`!z0wnEr+SoEzO-RaQ>(+55SOJKHd7Y)(A&lXK#Kg3ARCV>}U zhpK+RQcbjf@{@Cy=xl14LbXO}p=u7+8j$0!N6cOR$yudz-d=ChW$?}Bnf zg%YSEemW8L2|yA;UAL)k{X}e&CnrEzkWP~3<(#?i0FKfm#(gtB8j{7ANquht-r{J7 zg8*cEQ%8H(+}gN8bnNSfpLm}xzX*io(Bv@x6{b@&(et-yykwjpv6-Bpg` zE{yHN-JO?_EP;R-S%qruI-$iopuS0QP0?a%nYii14URDm4j6)~MRi=O8yl|o2Z>qc zfUXoO94g6w%JhN`hY*AP-=bD!E&b5R4GbJm@bGFJk#`83k}N7ezwQJz->!k7QxY$R zX(pkaL)=>{ypk#nHCYeXR(Kx@DP?sX7nfGt0qE`=5s6=tH}*oDcnU4un=!Y2e2oq5 zV1#wGQqh!Bt;EcQ4qX0Xw38KLh`2=2#F<5Hqg4f@jx}Tm5SP%MQWNv+R-Em0l9A&5X{J)3d-w(K5a$*iYYpX z5ii8c9ct!XVC#?l{BE>uY~3W{2xA*`am?{XTy?^z4P(fjsKuQi)T)XZhnLg3>BJ;8 z{=}z$xeunRs+jLw<+QWj!=6DT5OL!wy(ECt+jm&U&{50Kk^^3fQRYGw{yn zaQOOm>YGx+8GN&BIALRp?M*r5%w-EYIBCn)b(?D18GLUhIBjD`r%gHK47BA9oUOb^ z&PLyyIc-b<=W5&0VpB^zv+h{|;HzzLu{qtJL3fG(v9#?jv1ufq^>1SUU@C8Tu+cYv zXZ>sD0jTBG^&5S2*1y^lfLdM`y3sdheJe8on5Pw-8+j@5IzDbyK4UTJpNS)K)MC~j zPnTt_Rsp4dVeUoVpOTF{MEwpwor!k9Q?sDNh8sWD?#u8NQAH&7`4ntMpTt!z@s0Gy zw$HbXA5VBv^tuEjMo0d$IKx>0$Sy;F+sfB}`}fVS{HggvDA$-L+@x26-!{p9gTw?> zxn;pyLSN*NEtk!Wq4@izx@r~2qJ3r?Jzq?S21&##{0}U}zUX+%3~aK5=QzlD*ZBB@ z8A<#_ORc|Y7|u@3qJgwVoKyU zYh5Y+A=CFH=2jm6vT6IeU9w-J@m)>COx?M)aSJbe!aHsBNVTND*Y z-&A#)zng5FemN5X#r>?Mit8#;tB3*93A`xoc$K&+3Y7`Pq-=0TlON^(HFT3)%b_aK zADiD6D?ccuTP0Mk+WhC15>1akm>&vF@iAAGZRuBw+Wj$m=5DHJGmNMy|6Em6X-el& k{eCYN(X)KVGQx|zKK`iup!EJbPBuI##Q$^l|LR#fmoyCRV*mgE diff --git a/py-modindex.html b/py-modindex.html index bd011d5c9..bc64fe3eb 100644 --- a/py-modindex.html +++ b/py-modindex.html @@ -712,11 +712,31 @@

        Python Module Index

      		    graphnet.deployment.deployment_module
          + graphnet.deployment.i3modules +
          + graphnet.deployment.i3modules.deprecated_methods +
          + graphnet.deployment.icecube +
          graphnet.deployment.icecube.cleaning_module
          + graphnet.deployment.icecube.i3deployer +
          diff --git a/searchindex.js b/searchindex.js index e7b8ba7df..9c5320058 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"1) Adding Support for Your Data": [[150, "adding-support-for-your-data"]], "2) Implementing a Detector Class": [[150, "implementing-a-detector-class"]], "API": [[1, null]], "Acknowledgements": [[0, "acknowledgements"]], "Adding Your Own Model": [[152, "adding-your-own-model"]], "Adding custom Labels": [[146, "adding-custom-labels"]], "Adding custom truth labels": [[147, "adding-custom-truth-labels"]], "Advanced Functionality in SQLiteDataset": [[147, "advanced-functionality-in-sqlitedataset"]], "Appendix": [[147, "appendix"]], "Choosing a subset of events using selection": [[146, "choosing-a-subset-of-events-using-selection"]], "Code quality": [[144, "code-quality"]], "Combining Multiple Datasets": [[146, "combining-multiple-datasets"], [147, "combining-multiple-datasets"]], "Contents": [[147, "contents"]], "Contributing To GraphNeTgraphnet": [[144, null]], "Conventions": [[144, "conventions"]], "Creating reproducible Datasets using DatasetConfig": [[147, "creating-reproducible-datasets-using-datasetconfig"]], "Creating reproducible Models using ModelConfig": [[147, "creating-reproducible-models-using-modelconfig"]], "Data Conversion in GraphNeTgraphnet": [[145, null]], "DataConverter": [[145, "dataconverter"]], "Dataset": [[146, "dataset"]], "Datasets In GraphNeTgraphnet": [[146, null]], "Example DataConfig": [[147, "example-dataconfig"]], "Example ModelConfig": [[147, "example-modelconfig"]], "Example of geometry table before applying multi-index": [[150, "id1"]], "Example: Energy Reconstruction using ModelConfig": [[152, "example-energy-reconstruction-using-modelconfig"]], "Experiment Tracking": [[152, "experiment-tracking"]], "Extractors": [[145, "extractors"]], "GitHub issues": [[144, "github-issues"]], "GraphDefinition, backbone & Task": [[152, "graphdefinition-backbone-task"]], "GraphNeT tutorial": [[147, null]], "GraphNeTgraphnet": [[148, null], [151, null]], "Implementing a new Dataset": [[146, "implementing-a-new-dataset"]], "Installation": [[149, null]], "Installation in CVMFS (IceCube)": [[149, "installation-in-cvmfs-icecube"]], "Instantiating a StandardModel": [[152, "instantiating-a-standardmodel"]], "Integrating New Experiments into GraphNeTgraphnet": [[150, null]], "Introduction": [[147, "introduction"]], "Model.save": [[152, "model-save"]], "ModelConfig and state_dict": [[152, "modelconfig-and-state-dict"]], "Models In GraphNeTgraphnet": [[152, null]], "Overview of GraphNeT": [[147, "overview-of-graphnet"]], "Pull requests": [[144, "pull-requests"]], "Quick Start": [[149, "quick-start"]], "RNN_tito": [[92, null]], "Readers": [[145, "readers"]], "SQLiteDataset & ParquetDataset": [[146, "sqlitedataset-parquetdataset"]], "SQLiteDataset vs. ParquetDataset": [[146, "sqlitedataset-vs-parquetdataset"]], "Saving, loading, and checkpointing Models": [[152, "saving-loading-and-checkpointing-models"]], "The Model class": [[147, "the-model-class"], [152, "the-model-class"]], "The StandardModel class": [[147, "the-standardmodel-class"], [152, "the-standardmodel-class"]], "Training Syntax for StandardModel": [[152, "training-syntax-for-standardmodel"]], "Usage": [[0, null]], "Using checkpoints": [[152, "using-checkpoints"]], "Writers": [[145, "writers"]], "Writing your own Extractor and GraphNeTFileReader": [[150, "writing-your-own-extractor-and-graphnetfilereader"]], "argparse": [[129, null]], "base_config": [[131, null]], "callbacks": [[123, null]], "classification": [[116, null]], "cleaning_module": [[74, null]], "coarsening": [[80, null]], "collections": [[34, null]], "combine_extractors": [[18, null]], "components": [[81, null]], "config": [[130, null]], "configurable": [[132, null]], "constants": [[2, null], [4, null]], "convnet": [[93, null]], "curated_datamodule": [[5, null]], "data": [[3, null]], "dataclasses": [[6, null]], "dataconverter": [[7, null]], "dataconverters": [[47, null]], "dataloader": [[8, null]], "datamodule": [[9, null]], "dataset": [[10, null], [11, null]], "dataset_config": [[133, null]], "datasets": [[65, null]], "decorators": [[137, null]], "deployer": [[69, null]], "deployment": [[68, null]], "deployment_module": [[70, null]], "deprecated_methods": [[45, null], [55, null], [72, null]], "deprecation_tools": [[138, null]], "detector": [[85, null], [86, null]], "dynedge": [[94, null]], "dynedge_jinst": [[95, null]], "dynedge_kaggle_tito": [[96, null]], "easy_model": [[90, null]], "edges": [[101, null], [102, null]], "embedding": [[82, null]], "exceptions": [[77, null], [78, null]], "extractor": [[19, null]], "extractors": [[17, null]], "filesys": [[139, null]], "frames": [[35, null]], "gnn": [[91, null], [97, null]], "graph_definition": [[104, null]], "graphnet_file_reader": [[49, null]], "graphnet_writer": [[62, null]], "graphs": [[100, null], [105, null]], "h5_extractor": [[41, null]], "i3_filters": [[36, null]], "i3deployer": [[75, null]], "i3extractor": [[21, null]], "i3featureextractor": [[22, null]], "i3genericextractor": [[23, null]], "i3hybridrecoextractor": [[24, null]], "i3modules": [[71, null]], "i3ntmuonlabelsextractor": [[25, null]], "i3particleextractor": [[26, null]], "i3pisaextractor": [[27, null]], "i3quesoextractor": [[28, null]], "i3reader": [[50, null]], "i3retroextractor": [[29, null]], "i3splinempeextractor": [[30, null]], "i3truthextractor": [[31, null]], "i3tumextractor": [[32, null]], "icecube": [[20, null], [73, null], [87, null]], "icemix": [[98, null]], "imports": [[140, null]], "inference_module": [[76, null]], "internal": [[38, null]], "internal_parquet_reader": [[51, null]], "iseecube": [[120, null]], "labels": [[124, null]], "layers": [[83, null]], "liquido": [[40, null], [88, null]], "liquido_reader": [[52, null]], "logging": [[141, null]], "loss_functions": [[125, null]], "maths": [[142, null]], "minkowski": [[103, null]], "model": [[109, null]], "model_config": [[134, null]], "models": [[79, null]], "node_rnn": [[112, null]], "nodes": [[106, null], [107, null]], "normalizing_flow": [[110, null]], "parquet": [[12, null], [44, null]], "parquet_dataset": [[13, null]], "parquet_extractor": [[39, null]], "parquet_to_sqlite": [[57, null]], "parquet_writer": [[63, null]], "parsing": [[135, null]], "particlenet": [[99, null]], "pool": [[84, null]], "pre_configured": [[46, null]], "prometheus": [[42, null], [89, null]], "prometheus_datasets": [[66, null]], "prometheus_extractor": [[43, null]], "prometheus_reader": [[53, null]], "random": [[58, null]], "readers": [[48, null]], "reconstruction": [[117, null]], "rnn": [[111, null]], "samplers": [[14, null]], "sqlite": [[15, null], [54, null]], "sqlite_dataset": [[16, null]], "sqlite_utilities": [[59, null]], "sqlite_writer": [[64, null]], "src": [[143, null]], "standard_averaged_model": [[113, null]], "standard_model": [[114, null]], "string_selection_resolver": [[60, null]], "task": [[115, null], [118, null]], "test_dataset": [[67, null]], "training": [[122, null]], "training_config": [[136, null]], "transformer": [[119, null]], "types": [[37, null]], "utilities": [[33, null], [56, null], [128, null]], "utils": [[108, null], [121, null], [126, null]], "weight_fitting": [[127, null]], "writers": [[61, null]]}, "docnames": ["about/about", "api/graphnet", "api/graphnet.constants", "api/graphnet.data", "api/graphnet.data.constants", "api/graphnet.data.curated_datamodule", "api/graphnet.data.dataclasses", "api/graphnet.data.dataconverter", "api/graphnet.data.dataloader", "api/graphnet.data.datamodule", "api/graphnet.data.dataset", "api/graphnet.data.dataset.dataset", "api/graphnet.data.dataset.parquet", "api/graphnet.data.dataset.parquet.parquet_dataset", "api/graphnet.data.dataset.samplers", "api/graphnet.data.dataset.sqlite", "api/graphnet.data.dataset.sqlite.sqlite_dataset", "api/graphnet.data.extractors", "api/graphnet.data.extractors.combine_extractors", "api/graphnet.data.extractors.extractor", "api/graphnet.data.extractors.icecube", "api/graphnet.data.extractors.icecube.i3extractor", "api/graphnet.data.extractors.icecube.i3featureextractor", "api/graphnet.data.extractors.icecube.i3genericextractor", "api/graphnet.data.extractors.icecube.i3hybridrecoextractor", "api/graphnet.data.extractors.icecube.i3ntmuonlabelsextractor", "api/graphnet.data.extractors.icecube.i3particleextractor", "api/graphnet.data.extractors.icecube.i3pisaextractor", "api/graphnet.data.extractors.icecube.i3quesoextractor", "api/graphnet.data.extractors.icecube.i3retroextractor", "api/graphnet.data.extractors.icecube.i3splinempeextractor", "api/graphnet.data.extractors.icecube.i3truthextractor", "api/graphnet.data.extractors.icecube.i3tumextractor", "api/graphnet.data.extractors.icecube.utilities", "api/graphnet.data.extractors.icecube.utilities.collections", "api/graphnet.data.extractors.icecube.utilities.frames", "api/graphnet.data.extractors.icecube.utilities.i3_filters", "api/graphnet.data.extractors.icecube.utilities.types", "api/graphnet.data.extractors.internal", "api/graphnet.data.extractors.internal.parquet_extractor", "api/graphnet.data.extractors.liquido", "api/graphnet.data.extractors.liquido.h5_extractor", "api/graphnet.data.extractors.prometheus", "api/graphnet.data.extractors.prometheus.prometheus_extractor", "api/graphnet.data.parquet", "api/graphnet.data.parquet.deprecated_methods", "api/graphnet.data.pre_configured", "api/graphnet.data.pre_configured.dataconverters", "api/graphnet.data.readers", "api/graphnet.data.readers.graphnet_file_reader", "api/graphnet.data.readers.i3reader", "api/graphnet.data.readers.internal_parquet_reader", "api/graphnet.data.readers.liquido_reader", "api/graphnet.data.readers.prometheus_reader", "api/graphnet.data.sqlite", "api/graphnet.data.sqlite.deprecated_methods", "api/graphnet.data.utilities", "api/graphnet.data.utilities.parquet_to_sqlite", "api/graphnet.data.utilities.random", "api/graphnet.data.utilities.sqlite_utilities", "api/graphnet.data.utilities.string_selection_resolver", "api/graphnet.data.writers", "api/graphnet.data.writers.graphnet_writer", "api/graphnet.data.writers.parquet_writer", "api/graphnet.data.writers.sqlite_writer", "api/graphnet.datasets", "api/graphnet.datasets.prometheus_datasets", "api/graphnet.datasets.test_dataset", "api/graphnet.deployment", "api/graphnet.deployment.deployer", "api/graphnet.deployment.deployment_module", "api/graphnet.deployment.i3modules", "api/graphnet.deployment.i3modules.deprecated_methods", "api/graphnet.deployment.icecube", "api/graphnet.deployment.icecube.cleaning_module", "api/graphnet.deployment.icecube.i3deployer", "api/graphnet.deployment.icecube.inference_module", "api/graphnet.exceptions", "api/graphnet.exceptions.exceptions", "api/graphnet.models", "api/graphnet.models.coarsening", "api/graphnet.models.components", "api/graphnet.models.components.embedding", "api/graphnet.models.components.layers", "api/graphnet.models.components.pool", "api/graphnet.models.detector", "api/graphnet.models.detector.detector", "api/graphnet.models.detector.icecube", "api/graphnet.models.detector.liquido", "api/graphnet.models.detector.prometheus", "api/graphnet.models.easy_model", "api/graphnet.models.gnn", "api/graphnet.models.gnn.RNN_tito", "api/graphnet.models.gnn.convnet", "api/graphnet.models.gnn.dynedge", "api/graphnet.models.gnn.dynedge_jinst", "api/graphnet.models.gnn.dynedge_kaggle_tito", "api/graphnet.models.gnn.gnn", "api/graphnet.models.gnn.icemix", "api/graphnet.models.gnn.particlenet", "api/graphnet.models.graphs", "api/graphnet.models.graphs.edges", "api/graphnet.models.graphs.edges.edges", "api/graphnet.models.graphs.edges.minkowski", "api/graphnet.models.graphs.graph_definition", "api/graphnet.models.graphs.graphs", "api/graphnet.models.graphs.nodes", "api/graphnet.models.graphs.nodes.nodes", "api/graphnet.models.graphs.utils", "api/graphnet.models.model", "api/graphnet.models.normalizing_flow", "api/graphnet.models.rnn", "api/graphnet.models.rnn.node_rnn", "api/graphnet.models.standard_averaged_model", "api/graphnet.models.standard_model", "api/graphnet.models.task", "api/graphnet.models.task.classification", "api/graphnet.models.task.reconstruction", "api/graphnet.models.task.task", "api/graphnet.models.transformer", "api/graphnet.models.transformer.iseecube", "api/graphnet.models.utils", "api/graphnet.training", "api/graphnet.training.callbacks", "api/graphnet.training.labels", "api/graphnet.training.loss_functions", "api/graphnet.training.utils", "api/graphnet.training.weight_fitting", "api/graphnet.utilities", "api/graphnet.utilities.argparse", "api/graphnet.utilities.config", "api/graphnet.utilities.config.base_config", "api/graphnet.utilities.config.configurable", "api/graphnet.utilities.config.dataset_config", "api/graphnet.utilities.config.model_config", "api/graphnet.utilities.config.parsing", "api/graphnet.utilities.config.training_config", "api/graphnet.utilities.decorators", "api/graphnet.utilities.deprecation_tools", "api/graphnet.utilities.filesys", "api/graphnet.utilities.imports", "api/graphnet.utilities.logging", "api/graphnet.utilities.maths", "api/modules", "contribute/contribute", "data_conversion/data_conversion", "datasets/datasets", "getting_started/getting_started", "index", "installation/install", "integration/integration", "intro/intro", "models/models", "substitutions"], "envversion": {"sphinx": 64, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinx.ext.todo": 2, "sphinx.ext.viewcode": 1}, "filenames": ["about/about.rst", "api/graphnet.rst", "api/graphnet.constants.rst", "api/graphnet.data.rst", "api/graphnet.data.constants.rst", "api/graphnet.data.curated_datamodule.rst", "api/graphnet.data.dataclasses.rst", "api/graphnet.data.dataconverter.rst", "api/graphnet.data.dataloader.rst", "api/graphnet.data.datamodule.rst", "api/graphnet.data.dataset.rst", "api/graphnet.data.dataset.dataset.rst", "api/graphnet.data.dataset.parquet.rst", "api/graphnet.data.dataset.parquet.parquet_dataset.rst", "api/graphnet.data.dataset.samplers.rst", "api/graphnet.data.dataset.sqlite.rst", "api/graphnet.data.dataset.sqlite.sqlite_dataset.rst", "api/graphnet.data.extractors.rst", "api/graphnet.data.extractors.combine_extractors.rst", "api/graphnet.data.extractors.extractor.rst", "api/graphnet.data.extractors.icecube.rst", "api/graphnet.data.extractors.icecube.i3extractor.rst", "api/graphnet.data.extractors.icecube.i3featureextractor.rst", "api/graphnet.data.extractors.icecube.i3genericextractor.rst", "api/graphnet.data.extractors.icecube.i3hybridrecoextractor.rst", "api/graphnet.data.extractors.icecube.i3ntmuonlabelsextractor.rst", "api/graphnet.data.extractors.icecube.i3particleextractor.rst", "api/graphnet.data.extractors.icecube.i3pisaextractor.rst", "api/graphnet.data.extractors.icecube.i3quesoextractor.rst", "api/graphnet.data.extractors.icecube.i3retroextractor.rst", "api/graphnet.data.extractors.icecube.i3splinempeextractor.rst", "api/graphnet.data.extractors.icecube.i3truthextractor.rst", "api/graphnet.data.extractors.icecube.i3tumextractor.rst", "api/graphnet.data.extractors.icecube.utilities.rst", "api/graphnet.data.extractors.icecube.utilities.collections.rst", "api/graphnet.data.extractors.icecube.utilities.frames.rst", "api/graphnet.data.extractors.icecube.utilities.i3_filters.rst", "api/graphnet.data.extractors.icecube.utilities.types.rst", "api/graphnet.data.extractors.internal.rst", "api/graphnet.data.extractors.internal.parquet_extractor.rst", "api/graphnet.data.extractors.liquido.rst", "api/graphnet.data.extractors.liquido.h5_extractor.rst", "api/graphnet.data.extractors.prometheus.rst", "api/graphnet.data.extractors.prometheus.prometheus_extractor.rst", "api/graphnet.data.parquet.rst", "api/graphnet.data.parquet.deprecated_methods.rst", "api/graphnet.data.pre_configured.rst", "api/graphnet.data.pre_configured.dataconverters.rst", "api/graphnet.data.readers.rst", "api/graphnet.data.readers.graphnet_file_reader.rst", "api/graphnet.data.readers.i3reader.rst", "api/graphnet.data.readers.internal_parquet_reader.rst", "api/graphnet.data.readers.liquido_reader.rst", "api/graphnet.data.readers.prometheus_reader.rst", "api/graphnet.data.sqlite.rst", "api/graphnet.data.sqlite.deprecated_methods.rst", "api/graphnet.data.utilities.rst", "api/graphnet.data.utilities.parquet_to_sqlite.rst", "api/graphnet.data.utilities.random.rst", "api/graphnet.data.utilities.sqlite_utilities.rst", "api/graphnet.data.utilities.string_selection_resolver.rst", "api/graphnet.data.writers.rst", "api/graphnet.data.writers.graphnet_writer.rst", "api/graphnet.data.writers.parquet_writer.rst", "api/graphnet.data.writers.sqlite_writer.rst", "api/graphnet.datasets.rst", "api/graphnet.datasets.prometheus_datasets.rst", "api/graphnet.datasets.test_dataset.rst", "api/graphnet.deployment.rst", "api/graphnet.deployment.deployer.rst", "api/graphnet.deployment.deployment_module.rst", "api/graphnet.deployment.i3modules.rst", "api/graphnet.deployment.i3modules.deprecated_methods.rst", "api/graphnet.deployment.icecube.rst", "api/graphnet.deployment.icecube.cleaning_module.rst", "api/graphnet.deployment.icecube.i3deployer.rst", "api/graphnet.deployment.icecube.inference_module.rst", "api/graphnet.exceptions.rst", "api/graphnet.exceptions.exceptions.rst", "api/graphnet.models.rst", "api/graphnet.models.coarsening.rst", "api/graphnet.models.components.rst", "api/graphnet.models.components.embedding.rst", "api/graphnet.models.components.layers.rst", "api/graphnet.models.components.pool.rst", "api/graphnet.models.detector.rst", "api/graphnet.models.detector.detector.rst", "api/graphnet.models.detector.icecube.rst", "api/graphnet.models.detector.liquido.rst", "api/graphnet.models.detector.prometheus.rst", "api/graphnet.models.easy_model.rst", "api/graphnet.models.gnn.rst", "api/graphnet.models.gnn.RNN_tito.rst", "api/graphnet.models.gnn.convnet.rst", "api/graphnet.models.gnn.dynedge.rst", "api/graphnet.models.gnn.dynedge_jinst.rst", "api/graphnet.models.gnn.dynedge_kaggle_tito.rst", "api/graphnet.models.gnn.gnn.rst", "api/graphnet.models.gnn.icemix.rst", "api/graphnet.models.gnn.particlenet.rst", "api/graphnet.models.graphs.rst", "api/graphnet.models.graphs.edges.rst", "api/graphnet.models.graphs.edges.edges.rst", "api/graphnet.models.graphs.edges.minkowski.rst", "api/graphnet.models.graphs.graph_definition.rst", "api/graphnet.models.graphs.graphs.rst", "api/graphnet.models.graphs.nodes.rst", "api/graphnet.models.graphs.nodes.nodes.rst", "api/graphnet.models.graphs.utils.rst", "api/graphnet.models.model.rst", "api/graphnet.models.normalizing_flow.rst", "api/graphnet.models.rnn.rst", "api/graphnet.models.rnn.node_rnn.rst", "api/graphnet.models.standard_averaged_model.rst", "api/graphnet.models.standard_model.rst", "api/graphnet.models.task.rst", "api/graphnet.models.task.classification.rst", "api/graphnet.models.task.reconstruction.rst", "api/graphnet.models.task.task.rst", "api/graphnet.models.transformer.rst", "api/graphnet.models.transformer.iseecube.rst", "api/graphnet.models.utils.rst", "api/graphnet.training.rst", "api/graphnet.training.callbacks.rst", "api/graphnet.training.labels.rst", "api/graphnet.training.loss_functions.rst", "api/graphnet.training.utils.rst", "api/graphnet.training.weight_fitting.rst", "api/graphnet.utilities.rst", "api/graphnet.utilities.argparse.rst", "api/graphnet.utilities.config.rst", "api/graphnet.utilities.config.base_config.rst", "api/graphnet.utilities.config.configurable.rst", "api/graphnet.utilities.config.dataset_config.rst", "api/graphnet.utilities.config.model_config.rst", "api/graphnet.utilities.config.parsing.rst", "api/graphnet.utilities.config.training_config.rst", "api/graphnet.utilities.decorators.rst", "api/graphnet.utilities.deprecation_tools.rst", "api/graphnet.utilities.filesys.rst", "api/graphnet.utilities.imports.rst", "api/graphnet.utilities.logging.rst", "api/graphnet.utilities.maths.rst", "api/modules.rst", "contribute/contribute.rst", "data_conversion/data_conversion.rst", "datasets/datasets.rst", "getting_started/getting_started.md", "index.rst", "installation/install.rst", "integration/integration.rst", "intro/intro.rst", "models/models.rst", "substitutions.rst"], "indexentries": {"accepted_extractors (graphnet.data.readers.graphnet_file_reader.graphnetfilereader property)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.accepted_extractors", false]], "accepted_file_extensions (graphnet.data.readers.graphnet_file_reader.graphnetfilereader property)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.accepted_file_extensions", false]], "add_label() (graphnet.data.dataset.dataset.dataset method)": [[11, "graphnet.data.dataset.dataset.Dataset.add_label", false]], "arca115 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.ARCA115", false]], "argumentparser (class in graphnet.utilities.argparse)": [[129, "graphnet.utilities.argparse.ArgumentParser", false]], "arguments (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.arguments", false]], "array_to_sequence() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.array_to_sequence", false]], "as_dict() (graphnet.utilities.config.base_config.baseconfig method)": [[131, "graphnet.utilities.config.base_config.BaseConfig.as_dict", false]], "as_dict() (graphnet.utilities.config.dataset_config.datasetconfig method)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.as_dict", false]], "as_dict() (graphnet.utilities.config.model_config.modelconfig method)": [[134, "graphnet.utilities.config.model_config.ModelConfig.as_dict", false]], "attach_index() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.attach_index", false]], "attention_rel (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Attention_rel", false]], "attributecoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.AttributeCoarsening", false]], "available_backends (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.available_backends", false]], "azimuthreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction", false]], "azimuthreconstructionwithkappa (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa", false]], "backward() (graphnet.training.loss_functions.logcmk static method)": [[125, "graphnet.training.loss_functions.LogCMK.backward", false]], "baikalgvd8 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8", false]], "baikalgvdsmall (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.BaikalGVDSmall", false]], "baseconfig (class in graphnet.utilities.config.base_config)": [[131, "graphnet.utilities.config.base_config.BaseConfig", false]], "binaryclassificationtask (class in graphnet.models.task.classification)": [[116, "graphnet.models.task.classification.BinaryClassificationTask", false]], "binaryclassificationtasklogits (class in graphnet.models.task.classification)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits", false]], "binarycrossentropyloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.BinaryCrossEntropyLoss", false]], "bjoernlow (class in graphnet.training.weight_fitting)": [[127, "graphnet.training.weight_fitting.BjoernLow", false]], "block (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Block", false]], "block_rel (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Block_rel", false]], "break_cyclic_recursion() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.break_cyclic_recursion", false]], "calculate_distance_matrix() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.calculate_distance_matrix", false]], "calculate_xyzt_homophily() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.calculate_xyzt_homophily", false]], "cast_object_to_pure_python() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.cast_object_to_pure_python", false]], "cast_pulse_series_to_pure_python() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.cast_pulse_series_to_pure_python", false]], "chunk_sizes (graphnet.data.dataset.parquet.parquet_dataset.parquetdataset property)": [[13, "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset.chunk_sizes", false]], "chunks (graphnet.data.dataset.samplers.randomchunksampler property)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler.chunks", false]], "citation (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.citation", false]], "class_name (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.class_name", false]], "clean_up_data_object() (graphnet.models.rnn.node_rnn.node_rnn method)": [[112, "graphnet.models.rnn.node_rnn.Node_RNN.clean_up_data_object", false]], "cluster_summarize_with_percentiles() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.cluster_summarize_with_percentiles", false]], "coarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.Coarsening", false]], "collate_fn() (in module graphnet.data.dataloader)": [[8, "graphnet.data.dataloader.collate_fn", false]], "collate_fn() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.collate_fn", false]], "collator_sequence_buckleting (class in graphnet.training.utils)": [[126, "graphnet.training.utils.collator_sequence_buckleting", false]], "columnmissingexception": [[78, "graphnet.exceptions.exceptions.ColumnMissingException", false]], "combinedextractor (class in graphnet.data.extractors.combine_extractors)": [[18, "graphnet.data.extractors.combine_extractors.CombinedExtractor", false]], "comments (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.comments", false]], "compute_loss() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.compute_loss", false]], "compute_loss() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.compute_loss", false]], "compute_loss() (graphnet.models.task.task.learnedtask method)": [[118, "graphnet.models.task.task.LearnedTask.compute_loss", false]], "compute_loss() (graphnet.models.task.task.standardlearnedtask method)": [[118, "graphnet.models.task.task.StandardLearnedTask.compute_loss", false]], "compute_minkowski_distance_mat() (in module graphnet.models.graphs.edges.minkowski)": [[103, "graphnet.models.graphs.edges.minkowski.compute_minkowski_distance_mat", false]], "concatenate() (graphnet.data.dataset.dataset.dataset class method)": [[11, "graphnet.data.dataset.dataset.Dataset.concatenate", false]], "config (graphnet.utilities.config.configurable.configurable property)": [[132, "graphnet.utilities.config.configurable.Configurable.config", false]], "configurable (class in graphnet.utilities.config.configurable)": [[132, "graphnet.utilities.config.configurable.Configurable", false]], "configure_optimizers() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.configure_optimizers", false]], "contains() (graphnet.utilities.argparse.options method)": [[129, "graphnet.utilities.argparse.Options.contains", false]], "convnet (class in graphnet.models.gnn.convnet)": [[93, "graphnet.models.gnn.convnet.ConvNet", false]], "create_table() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.create_table", false]], "create_table_and_save_to_sql() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.create_table_and_save_to_sql", false]], "creator (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.creator", false]], "critical() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.critical", false]], "crossentropyloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.CrossEntropyLoss", false]], "curateddataset (class in graphnet.data.curated_datamodule)": [[5, "graphnet.data.curated_datamodule.CuratedDataset", false]], "customdomcoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.CustomDOMCoarsening", false]], "data_source (graphnet.data.dataset.samplers.randomchunksampler property)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler.data_source", false]], "database_exists() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.database_exists", false]], "database_table_exists() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.database_table_exists", false]], "dataconverter (class in graphnet.data.dataconverter)": [[7, "graphnet.data.dataconverter.DataConverter", false]], "dataloader (class in graphnet.data.dataloader)": [[8, "graphnet.data.dataloader.DataLoader", false]], "dataloader (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.dataloader", false]], "dataset (class in graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.Dataset", false]], "dataset_dir (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.dataset_dir", false]], "datasetconfig (class in graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig", false]], "datasetconfigsaverabcmeta (class in graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfigSaverABCMeta", false]], "datasetconfigsavermeta (class in graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfigSaverMeta", false]], "debug() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.debug", false]], "deepcore (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.DEEPCORE", false]], "deepcore (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.DEEPCORE", false]], "deepice (class in graphnet.models.gnn.icemix)": [[98, "graphnet.models.gnn.icemix.DeepIce", false]], "default_prediction_labels (graphnet.models.task.classification.binaryclassificationtask attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTask.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.classification.binaryclassificationtasklogits attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.azimuthreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.azimuthreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.directionreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energyreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energyreconstructionwithpower attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energyreconstructionwithuncertainty attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energytcreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.inelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.positionreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.timereconstruction attribute)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.vertexreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.zenithreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.zenithreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.task.identitytask property)": [[118, "graphnet.models.task.task.IdentityTask.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.task.standardflowtask property)": [[118, "graphnet.models.task.task.StandardFlowTask.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.task.task property)": [[118, "graphnet.models.task.task.Task.default_prediction_labels", false]], "default_target_labels (graphnet.models.task.classification.binaryclassificationtask attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTask.default_target_labels", false]], "default_target_labels (graphnet.models.task.classification.binaryclassificationtasklogits attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.azimuthreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.azimuthreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.directionreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energyreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energyreconstructionwithpower attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energyreconstructionwithuncertainty attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energytcreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.inelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.positionreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.timereconstruction attribute)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.vertexreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.zenithreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.zenithreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa.default_target_labels", false]], "default_target_labels (graphnet.models.task.task.identitytask property)": [[118, "graphnet.models.task.task.IdentityTask.default_target_labels", false]], "default_target_labels (graphnet.models.task.task.task property)": [[118, "graphnet.models.task.task.Task.default_target_labels", false]], "deployer (class in graphnet.deployment.deployer)": [[69, "graphnet.deployment.deployer.Deployer", false]], "deploymentmodule (class in graphnet.deployment.deployment_module)": [[70, "graphnet.deployment.deployment_module.DeploymentModule", false]], "description() (graphnet.data.curated_datamodule.curateddataset method)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.description", false]], "detector (class in graphnet.models.detector.detector)": [[86, "graphnet.models.detector.detector.Detector", false]], "direction (class in graphnet.training.labels)": [[124, "graphnet.training.labels.Direction", false]], "directionreconstructionwithkappa (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa", false]], "do_shuffle() (in module graphnet.data.dataloader)": [[8, "graphnet.data.dataloader.do_shuffle", false]], "domandtimewindowcoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.DOMAndTimeWindowCoarsening", false]], "domcoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.DOMCoarsening", false]], "droppath (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.DropPath", false]], "dump() (graphnet.utilities.config.base_config.baseconfig method)": [[131, "graphnet.utilities.config.base_config.BaseConfig.dump", false]], "dynedge (class in graphnet.models.gnn.dynedge)": [[94, "graphnet.models.gnn.dynedge.DynEdge", false]], "dynedgeconv (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.DynEdgeConv", false]], "dynedgejinst (class in graphnet.models.gnn.dynedge_jinst)": [[95, "graphnet.models.gnn.dynedge_jinst.DynEdgeJINST", false]], "dynedgetito (class in graphnet.models.gnn.dynedge_kaggle_tito)": [[96, "graphnet.models.gnn.dynedge_kaggle_tito.DynEdgeTITO", false]], "dyntrans (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.DynTrans", false]], "early_stopping_patience (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.early_stopping_patience", false]], "easysyntax (class in graphnet.models.easy_model)": [[90, "graphnet.models.easy_model.EasySyntax", false]], "edgeconvtito (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.EdgeConvTito", false]], "edgedefinition (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.EdgeDefinition", false]], "edgelessgraph (class in graphnet.models.graphs.graphs)": [[105, "graphnet.models.graphs.graphs.EdgelessGraph", false]], "energyreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction", false]], "energyreconstructionwithpower (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower", false]], "energyreconstructionwithuncertainty (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty", false]], "energytcreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction", false]], "ensembledataset (class in graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.EnsembleDataset", false]], "ensembleloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.EnsembleLoss", false]], "eps_like() (in module graphnet.utilities.maths)": [[142, "graphnet.utilities.maths.eps_like", false]], "erdahosteddataset (class in graphnet.data.curated_datamodule)": [[5, "graphnet.data.curated_datamodule.ERDAHostedDataset", false]], "error() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.error", false]], "euclideandistanceloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.EuclideanDistanceLoss", false]], "euclideanedges (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.EuclideanEdges", false]], "event_truth (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.event_truth", false]], "events (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.events", false]], "expects_merged_dataframes (graphnet.data.writers.graphnet_writer.graphnetwriter property)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter.expects_merged_dataframes", false]], "experiment (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.experiment", false]], "extra_repr() (graphnet.models.components.layers.droppath method)": [[83, "graphnet.models.components.layers.DropPath.extra_repr", false]], "extra_repr() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.extra_repr", false]], "extra_repr_recursive() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.extra_repr_recursive", false]], "extracor_names (graphnet.data.readers.graphnet_file_reader.graphnetfilereader property)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.extracor_names", false]], "extractor (class in graphnet.data.extractors.extractor)": [[19, "graphnet.data.extractors.extractor.Extractor", false]], "feature_map() (graphnet.models.detector.detector.detector method)": [[86, "graphnet.models.detector.detector.Detector.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecube86 method)": [[87, "graphnet.models.detector.icecube.IceCube86.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecubedeepcore method)": [[87, "graphnet.models.detector.icecube.IceCubeDeepCore.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecubekaggle method)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecubeupgrade method)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.feature_map", false]], "feature_map() (graphnet.models.detector.liquido.liquido_v1 method)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.arca115 method)": [[89, "graphnet.models.detector.prometheus.ARCA115.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.baikalgvd8 method)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecube86prometheus method)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecubedeepcore8 method)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecubegen2 method)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecubeupgrade7 method)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icedemo81 method)": [[89, "graphnet.models.detector.prometheus.IceDemo81.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.orca150 method)": [[89, "graphnet.models.detector.prometheus.ORCA150.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.orca150superdense method)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.ponetriangle method)": [[89, "graphnet.models.detector.prometheus.PONETriangle.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.trident1211 method)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.waterdemo81 method)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.feature_map", false]], "features (class in graphnet.data.constants)": [[4, "graphnet.data.constants.FEATURES", false]], "features (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.features", false]], "features (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.features", false]], "file_extension (graphnet.data.writers.graphnet_writer.graphnetwriter property)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter.file_extension", false]], "file_handlers (graphnet.utilities.logging.logger property)": [[141, "graphnet.utilities.logging.Logger.file_handlers", false]], "filter() (graphnet.utilities.logging.repeatfilter method)": [[141, "graphnet.utilities.logging.RepeatFilter.filter", false]], "find_files() (graphnet.data.readers.graphnet_file_reader.graphnetfilereader method)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.find_files", false]], "find_files() (graphnet.data.readers.i3reader.i3reader method)": [[50, "graphnet.data.readers.i3reader.I3Reader.find_files", false]], "find_files() (graphnet.data.readers.internal_parquet_reader.parquetreader method)": [[51, "graphnet.data.readers.internal_parquet_reader.ParquetReader.find_files", false]], "find_files() (graphnet.data.readers.liquido_reader.liquidoreader method)": [[52, "graphnet.data.readers.liquido_reader.LiquidOReader.find_files", false]], "find_files() (graphnet.data.readers.prometheus_reader.prometheusreader method)": [[53, "graphnet.data.readers.prometheus_reader.PrometheusReader.find_files", false]], "find_i3_files() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.find_i3_files", false]], "fit (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.fit", false]], "fit() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.fit", false]], "fit() (graphnet.training.weight_fitting.weightfitter method)": [[127, "graphnet.training.weight_fitting.WeightFitter.fit", false]], "flatten_nested_dictionary() (in module graphnet.data.extractors.icecube.utilities.collections)": [[34, "graphnet.data.extractors.icecube.utilities.collections.flatten_nested_dictionary", false]], "forward() (graphnet.models.coarsening.coarsening method)": [[80, "graphnet.models.coarsening.Coarsening.forward", false]], "forward() (graphnet.models.components.embedding.fourierencoder method)": [[82, "graphnet.models.components.embedding.FourierEncoder.forward", false]], "forward() (graphnet.models.components.embedding.sinusoidalposemb method)": [[82, "graphnet.models.components.embedding.SinusoidalPosEmb.forward", false]], "forward() (graphnet.models.components.embedding.spacetimeencoder method)": [[82, "graphnet.models.components.embedding.SpacetimeEncoder.forward", false]], "forward() (graphnet.models.components.layers.attention_rel method)": [[83, "graphnet.models.components.layers.Attention_rel.forward", false]], "forward() (graphnet.models.components.layers.block method)": [[83, "graphnet.models.components.layers.Block.forward", false]], "forward() (graphnet.models.components.layers.block_rel method)": [[83, "graphnet.models.components.layers.Block_rel.forward", false]], "forward() (graphnet.models.components.layers.droppath method)": [[83, "graphnet.models.components.layers.DropPath.forward", false]], "forward() (graphnet.models.components.layers.dynedgeconv method)": [[83, "graphnet.models.components.layers.DynEdgeConv.forward", false]], "forward() (graphnet.models.components.layers.dyntrans method)": [[83, "graphnet.models.components.layers.DynTrans.forward", false]], "forward() (graphnet.models.components.layers.edgeconvtito method)": [[83, "graphnet.models.components.layers.EdgeConvTito.forward", false]], "forward() (graphnet.models.components.layers.mlp method)": [[83, "graphnet.models.components.layers.Mlp.forward", false]], "forward() (graphnet.models.detector.detector.detector method)": [[86, "graphnet.models.detector.detector.Detector.forward", false]], "forward() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.forward", false]], "forward() (graphnet.models.gnn.convnet.convnet method)": [[93, "graphnet.models.gnn.convnet.ConvNet.forward", false]], "forward() (graphnet.models.gnn.dynedge.dynedge method)": [[94, "graphnet.models.gnn.dynedge.DynEdge.forward", false]], "forward() (graphnet.models.gnn.dynedge_jinst.dynedgejinst method)": [[95, "graphnet.models.gnn.dynedge_jinst.DynEdgeJINST.forward", false]], "forward() (graphnet.models.gnn.dynedge_kaggle_tito.dynedgetito method)": [[96, "graphnet.models.gnn.dynedge_kaggle_tito.DynEdgeTITO.forward", false]], "forward() (graphnet.models.gnn.gnn.gnn method)": [[97, "graphnet.models.gnn.gnn.GNN.forward", false]], "forward() (graphnet.models.gnn.icemix.deepice method)": [[98, "graphnet.models.gnn.icemix.DeepIce.forward", false]], "forward() (graphnet.models.gnn.particlenet.particlenet method)": [[99, "graphnet.models.gnn.particlenet.ParticleNeT.forward", false]], "forward() (graphnet.models.gnn.rnn_tito.rnn_tito method)": [[92, "graphnet.models.gnn.RNN_tito.RNN_TITO.forward", false]], "forward() (graphnet.models.graphs.edges.edges.edgedefinition method)": [[102, "graphnet.models.graphs.edges.edges.EdgeDefinition.forward", false]], "forward() (graphnet.models.graphs.graph_definition.graphdefinition method)": [[104, "graphnet.models.graphs.graph_definition.GraphDefinition.forward", false]], "forward() (graphnet.models.graphs.nodes.nodes.nodedefinition method)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.forward", false]], "forward() (graphnet.models.normalizing_flow.normalizingflow method)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow.forward", false]], "forward() (graphnet.models.rnn.node_rnn.node_rnn method)": [[112, "graphnet.models.rnn.node_rnn.Node_RNN.forward", false]], "forward() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.forward", false]], "forward() (graphnet.models.task.task.learnedtask method)": [[118, "graphnet.models.task.task.LearnedTask.forward", false]], "forward() (graphnet.models.task.task.standardflowtask method)": [[118, "graphnet.models.task.task.StandardFlowTask.forward", false]], "forward() (graphnet.models.transformer.iseecube.iseecube method)": [[120, "graphnet.models.transformer.iseecube.ISeeCube.forward", false]], "forward() (graphnet.training.loss_functions.logcmk static method)": [[125, "graphnet.training.loss_functions.LogCMK.forward", false]], "forward() (graphnet.training.loss_functions.lossfunction method)": [[125, "graphnet.training.loss_functions.LossFunction.forward", false]], "fourierencoder (class in graphnet.models.components.embedding)": [[82, "graphnet.models.components.embedding.FourierEncoder", false]], "frame_is_montecarlo() (in module graphnet.data.extractors.icecube.utilities.frames)": [[35, "graphnet.data.extractors.icecube.utilities.frames.frame_is_montecarlo", false]], "frame_is_noise() (in module graphnet.data.extractors.icecube.utilities.frames)": [[35, "graphnet.data.extractors.icecube.utilities.frames.frame_is_noise", false]], "from_config() (graphnet.data.dataset.dataset.dataset class method)": [[11, "graphnet.data.dataset.dataset.Dataset.from_config", false]], "from_config() (graphnet.models.model.model class method)": [[109, "graphnet.models.model.Model.from_config", false]], "from_config() (graphnet.utilities.config.configurable.configurable method)": [[132, "graphnet.utilities.config.configurable.Configurable.from_config", false]], "from_dataset_config() (graphnet.data.dataloader.dataloader class method)": [[8, "graphnet.data.dataloader.DataLoader.from_dataset_config", false]], "gather_cluster_sequence() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.gather_cluster_sequence", false]], "gather_len_matched_buckets() (in module graphnet.data.dataset.samplers)": [[14, "graphnet.data.dataset.samplers.gather_len_matched_buckets", false]], "gcd_file (graphnet.data.dataclasses.i3fileset attribute)": [[6, "graphnet.data.dataclasses.I3FileSet.gcd_file", false]], "gcd_file (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.gcd_file", false]], "geometry_table (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.geometry_table", false]], "geometry_table_path (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.geometry_table_path", false]], "get_all_argument_values() (in module graphnet.utilities.config.base_config)": [[131, "graphnet.utilities.config.base_config.get_all_argument_values", false]], "get_all_grapnet_classes() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.get_all_grapnet_classes", false]], "get_fields() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.get_fields", false]], "get_graphnet_classes() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.get_graphnet_classes", false]], "get_lr() (graphnet.training.callbacks.piecewiselinearlr method)": [[123, "graphnet.training.callbacks.PiecewiseLinearLR.get_lr", false]], "get_map_function() (graphnet.data.dataconverter.dataconverter method)": [[7, "graphnet.data.dataconverter.DataConverter.get_map_function", false]], "get_member_variables() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.get_member_variables", false]], "get_metrics() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.get_metrics", false]], "get_om_keys_and_pulseseries() (in module graphnet.data.extractors.icecube.utilities.frames)": [[35, "graphnet.data.extractors.icecube.utilities.frames.get_om_keys_and_pulseseries", false]], "get_predictions() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.get_predictions", false]], "get_primary_keys() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.get_primary_keys", false]], "gnn (class in graphnet.models.gnn.gnn)": [[97, "graphnet.models.gnn.gnn.GNN", false]], "graph_definition (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.graph_definition", false]], "graphdefinition (class in graphnet.models.graphs.graph_definition)": [[104, "graphnet.models.graphs.graph_definition.GraphDefinition", false]], "graphnet": [[1, "module-graphnet", false]], "graphnet.constants": [[2, "module-graphnet.constants", false]], "graphnet.data": [[3, "module-graphnet.data", false]], "graphnet.data.constants": [[4, "module-graphnet.data.constants", false]], "graphnet.data.curated_datamodule": [[5, "module-graphnet.data.curated_datamodule", false]], "graphnet.data.dataclasses": [[6, "module-graphnet.data.dataclasses", false]], "graphnet.data.dataconverter": [[7, "module-graphnet.data.dataconverter", false]], "graphnet.data.dataloader": [[8, "module-graphnet.data.dataloader", false]], "graphnet.data.datamodule": [[9, "module-graphnet.data.datamodule", false]], "graphnet.data.dataset": [[10, "module-graphnet.data.dataset", false]], "graphnet.data.dataset.dataset": [[11, "module-graphnet.data.dataset.dataset", false]], "graphnet.data.dataset.parquet": [[12, "module-graphnet.data.dataset.parquet", false]], "graphnet.data.dataset.parquet.parquet_dataset": [[13, "module-graphnet.data.dataset.parquet.parquet_dataset", false]], "graphnet.data.dataset.samplers": [[14, "module-graphnet.data.dataset.samplers", false]], "graphnet.data.dataset.sqlite": [[15, "module-graphnet.data.dataset.sqlite", false]], "graphnet.data.dataset.sqlite.sqlite_dataset": [[16, "module-graphnet.data.dataset.sqlite.sqlite_dataset", false]], "graphnet.data.extractors": [[17, "module-graphnet.data.extractors", false]], "graphnet.data.extractors.combine_extractors": [[18, "module-graphnet.data.extractors.combine_extractors", false]], "graphnet.data.extractors.extractor": [[19, "module-graphnet.data.extractors.extractor", false]], "graphnet.data.extractors.icecube": [[20, "module-graphnet.data.extractors.icecube", false]], "graphnet.data.extractors.icecube.i3extractor": [[21, "module-graphnet.data.extractors.icecube.i3extractor", false]], "graphnet.data.extractors.icecube.i3featureextractor": [[22, "module-graphnet.data.extractors.icecube.i3featureextractor", false]], "graphnet.data.extractors.icecube.i3genericextractor": [[23, "module-graphnet.data.extractors.icecube.i3genericextractor", false]], "graphnet.data.extractors.icecube.i3hybridrecoextractor": [[24, "module-graphnet.data.extractors.icecube.i3hybridrecoextractor", false]], "graphnet.data.extractors.icecube.i3ntmuonlabelsextractor": [[25, "module-graphnet.data.extractors.icecube.i3ntmuonlabelsextractor", false]], "graphnet.data.extractors.icecube.i3particleextractor": [[26, "module-graphnet.data.extractors.icecube.i3particleextractor", false]], "graphnet.data.extractors.icecube.i3pisaextractor": [[27, "module-graphnet.data.extractors.icecube.i3pisaextractor", false]], "graphnet.data.extractors.icecube.i3quesoextractor": [[28, "module-graphnet.data.extractors.icecube.i3quesoextractor", false]], "graphnet.data.extractors.icecube.i3retroextractor": [[29, "module-graphnet.data.extractors.icecube.i3retroextractor", false]], "graphnet.data.extractors.icecube.i3splinempeextractor": [[30, "module-graphnet.data.extractors.icecube.i3splinempeextractor", false]], "graphnet.data.extractors.icecube.i3truthextractor": [[31, "module-graphnet.data.extractors.icecube.i3truthextractor", false]], "graphnet.data.extractors.icecube.i3tumextractor": [[32, "module-graphnet.data.extractors.icecube.i3tumextractor", false]], "graphnet.data.extractors.icecube.utilities": [[33, "module-graphnet.data.extractors.icecube.utilities", false]], "graphnet.data.extractors.icecube.utilities.collections": [[34, "module-graphnet.data.extractors.icecube.utilities.collections", false]], "graphnet.data.extractors.icecube.utilities.frames": [[35, "module-graphnet.data.extractors.icecube.utilities.frames", false]], "graphnet.data.extractors.icecube.utilities.i3_filters": [[36, "module-graphnet.data.extractors.icecube.utilities.i3_filters", false]], "graphnet.data.extractors.icecube.utilities.types": [[37, "module-graphnet.data.extractors.icecube.utilities.types", false]], "graphnet.data.extractors.internal": [[38, "module-graphnet.data.extractors.internal", false]], "graphnet.data.extractors.internal.parquet_extractor": [[39, "module-graphnet.data.extractors.internal.parquet_extractor", false]], "graphnet.data.extractors.liquido": [[40, "module-graphnet.data.extractors.liquido", false]], "graphnet.data.extractors.liquido.h5_extractor": [[41, "module-graphnet.data.extractors.liquido.h5_extractor", false]], "graphnet.data.extractors.prometheus": [[42, "module-graphnet.data.extractors.prometheus", false]], "graphnet.data.extractors.prometheus.prometheus_extractor": [[43, "module-graphnet.data.extractors.prometheus.prometheus_extractor", false]], "graphnet.data.parquet": [[44, "module-graphnet.data.parquet", false]], "graphnet.data.parquet.deprecated_methods": [[45, "module-graphnet.data.parquet.deprecated_methods", false]], "graphnet.data.pre_configured": [[46, "module-graphnet.data.pre_configured", false]], "graphnet.data.pre_configured.dataconverters": [[47, "module-graphnet.data.pre_configured.dataconverters", false]], "graphnet.data.readers": [[48, "module-graphnet.data.readers", false]], "graphnet.data.readers.graphnet_file_reader": [[49, "module-graphnet.data.readers.graphnet_file_reader", false]], "graphnet.data.readers.i3reader": [[50, "module-graphnet.data.readers.i3reader", false]], "graphnet.data.readers.internal_parquet_reader": [[51, "module-graphnet.data.readers.internal_parquet_reader", false]], "graphnet.data.readers.liquido_reader": [[52, "module-graphnet.data.readers.liquido_reader", false]], "graphnet.data.readers.prometheus_reader": [[53, "module-graphnet.data.readers.prometheus_reader", false]], "graphnet.data.sqlite": [[54, "module-graphnet.data.sqlite", false]], "graphnet.data.sqlite.deprecated_methods": [[55, "module-graphnet.data.sqlite.deprecated_methods", false]], "graphnet.data.utilities": [[56, "module-graphnet.data.utilities", false]], "graphnet.data.utilities.parquet_to_sqlite": [[57, "module-graphnet.data.utilities.parquet_to_sqlite", false]], "graphnet.data.utilities.random": [[58, "module-graphnet.data.utilities.random", false]], "graphnet.data.utilities.sqlite_utilities": [[59, "module-graphnet.data.utilities.sqlite_utilities", false]], "graphnet.data.utilities.string_selection_resolver": [[60, "module-graphnet.data.utilities.string_selection_resolver", false]], "graphnet.data.writers": [[61, "module-graphnet.data.writers", false]], "graphnet.data.writers.graphnet_writer": [[62, "module-graphnet.data.writers.graphnet_writer", false]], "graphnet.data.writers.parquet_writer": [[63, "module-graphnet.data.writers.parquet_writer", false]], "graphnet.data.writers.sqlite_writer": [[64, "module-graphnet.data.writers.sqlite_writer", false]], "graphnet.datasets": [[65, "module-graphnet.datasets", false]], "graphnet.datasets.prometheus_datasets": [[66, "module-graphnet.datasets.prometheus_datasets", false]], "graphnet.datasets.test_dataset": [[67, "module-graphnet.datasets.test_dataset", false]], "graphnet.deployment": [[68, "module-graphnet.deployment", false]], "graphnet.deployment.deployer": [[69, "module-graphnet.deployment.deployer", false]], "graphnet.deployment.deployment_module": [[70, "module-graphnet.deployment.deployment_module", false]], "graphnet.deployment.icecube.cleaning_module": [[74, "module-graphnet.deployment.icecube.cleaning_module", false]], "graphnet.deployment.icecube.inference_module": [[76, "module-graphnet.deployment.icecube.inference_module", false]], "graphnet.exceptions": [[77, "module-graphnet.exceptions", false]], "graphnet.exceptions.exceptions": [[78, "module-graphnet.exceptions.exceptions", false]], "graphnet.models": [[79, "module-graphnet.models", false]], "graphnet.models.coarsening": [[80, "module-graphnet.models.coarsening", false]], "graphnet.models.components": [[81, "module-graphnet.models.components", false]], "graphnet.models.components.embedding": [[82, "module-graphnet.models.components.embedding", false]], "graphnet.models.components.layers": [[83, "module-graphnet.models.components.layers", false]], "graphnet.models.components.pool": [[84, "module-graphnet.models.components.pool", false]], "graphnet.models.detector": [[85, "module-graphnet.models.detector", false]], "graphnet.models.detector.detector": [[86, "module-graphnet.models.detector.detector", false]], "graphnet.models.detector.icecube": [[87, "module-graphnet.models.detector.icecube", false]], "graphnet.models.detector.liquido": [[88, "module-graphnet.models.detector.liquido", false]], "graphnet.models.detector.prometheus": [[89, "module-graphnet.models.detector.prometheus", false]], "graphnet.models.easy_model": [[90, "module-graphnet.models.easy_model", false]], "graphnet.models.gnn": [[91, "module-graphnet.models.gnn", false]], "graphnet.models.gnn.convnet": [[93, "module-graphnet.models.gnn.convnet", false]], "graphnet.models.gnn.dynedge": [[94, "module-graphnet.models.gnn.dynedge", false]], "graphnet.models.gnn.dynedge_jinst": [[95, "module-graphnet.models.gnn.dynedge_jinst", false]], "graphnet.models.gnn.dynedge_kaggle_tito": [[96, "module-graphnet.models.gnn.dynedge_kaggle_tito", false]], "graphnet.models.gnn.gnn": [[97, "module-graphnet.models.gnn.gnn", false]], "graphnet.models.gnn.icemix": [[98, "module-graphnet.models.gnn.icemix", false]], "graphnet.models.gnn.particlenet": [[99, "module-graphnet.models.gnn.particlenet", false]], "graphnet.models.gnn.rnn_tito": [[92, "module-graphnet.models.gnn.RNN_tito", false]], "graphnet.models.graphs": [[100, "module-graphnet.models.graphs", false]], "graphnet.models.graphs.edges": [[101, "module-graphnet.models.graphs.edges", false]], "graphnet.models.graphs.edges.edges": [[102, "module-graphnet.models.graphs.edges.edges", false]], "graphnet.models.graphs.edges.minkowski": [[103, "module-graphnet.models.graphs.edges.minkowski", false]], "graphnet.models.graphs.graph_definition": [[104, "module-graphnet.models.graphs.graph_definition", false]], "graphnet.models.graphs.graphs": [[105, "module-graphnet.models.graphs.graphs", false]], "graphnet.models.graphs.nodes": [[106, "module-graphnet.models.graphs.nodes", false]], "graphnet.models.graphs.nodes.nodes": [[107, "module-graphnet.models.graphs.nodes.nodes", false]], "graphnet.models.graphs.utils": [[108, "module-graphnet.models.graphs.utils", false]], "graphnet.models.model": [[109, "module-graphnet.models.model", false]], "graphnet.models.normalizing_flow": [[110, "module-graphnet.models.normalizing_flow", false]], "graphnet.models.rnn": [[111, "module-graphnet.models.rnn", false]], "graphnet.models.rnn.node_rnn": [[112, "module-graphnet.models.rnn.node_rnn", false]], "graphnet.models.standard_averaged_model": [[113, "module-graphnet.models.standard_averaged_model", false]], "graphnet.models.standard_model": [[114, "module-graphnet.models.standard_model", false]], "graphnet.models.task": [[115, "module-graphnet.models.task", false]], "graphnet.models.task.classification": [[116, "module-graphnet.models.task.classification", false]], "graphnet.models.task.reconstruction": [[117, "module-graphnet.models.task.reconstruction", false]], "graphnet.models.task.task": [[118, "module-graphnet.models.task.task", false]], "graphnet.models.transformer": [[119, "module-graphnet.models.transformer", false]], "graphnet.models.transformer.iseecube": [[120, "module-graphnet.models.transformer.iseecube", false]], "graphnet.models.utils": [[121, "module-graphnet.models.utils", false]], "graphnet.training": [[122, "module-graphnet.training", false]], "graphnet.training.callbacks": [[123, "module-graphnet.training.callbacks", false]], "graphnet.training.labels": [[124, "module-graphnet.training.labels", false]], "graphnet.training.loss_functions": [[125, "module-graphnet.training.loss_functions", false]], "graphnet.training.utils": [[126, "module-graphnet.training.utils", false]], "graphnet.training.weight_fitting": [[127, "module-graphnet.training.weight_fitting", false]], "graphnet.utilities": [[128, "module-graphnet.utilities", false]], "graphnet.utilities.argparse": [[129, "module-graphnet.utilities.argparse", false]], "graphnet.utilities.config": [[130, "module-graphnet.utilities.config", false]], "graphnet.utilities.config.base_config": [[131, "module-graphnet.utilities.config.base_config", false]], "graphnet.utilities.config.configurable": [[132, "module-graphnet.utilities.config.configurable", false]], "graphnet.utilities.config.dataset_config": [[133, "module-graphnet.utilities.config.dataset_config", false]], "graphnet.utilities.config.model_config": [[134, "module-graphnet.utilities.config.model_config", false]], "graphnet.utilities.config.parsing": [[135, "module-graphnet.utilities.config.parsing", false]], "graphnet.utilities.config.training_config": [[136, "module-graphnet.utilities.config.training_config", false]], "graphnet.utilities.decorators": [[137, "module-graphnet.utilities.decorators", false]], "graphnet.utilities.deprecation_tools": [[138, "module-graphnet.utilities.deprecation_tools", false]], "graphnet.utilities.filesys": [[139, "module-graphnet.utilities.filesys", false]], "graphnet.utilities.imports": [[140, "module-graphnet.utilities.imports", false]], "graphnet.utilities.logging": [[141, "module-graphnet.utilities.logging", false]], "graphnet.utilities.maths": [[142, "module-graphnet.utilities.maths", false]], "graphnetdatamodule (class in graphnet.data.datamodule)": [[9, "graphnet.data.datamodule.GraphNeTDataModule", false]], "graphnetearlystopping (class in graphnet.training.callbacks)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping", false]], "graphnetfilereader (class in graphnet.data.readers.graphnet_file_reader)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader", false]], "graphnetwriter (class in graphnet.data.writers.graphnet_writer)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter", false]], "group_by() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.group_by", false]], "group_pulses_to_dom() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.group_pulses_to_dom", false]], "group_pulses_to_pmt() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.group_pulses_to_pmt", false]], "h5extractor (class in graphnet.data.extractors.liquido.h5_extractor)": [[41, "graphnet.data.extractors.liquido.h5_extractor.H5Extractor", false]], "h5hitextractor (class in graphnet.data.extractors.liquido.h5_extractor)": [[41, "graphnet.data.extractors.liquido.h5_extractor.H5HitExtractor", false]], "h5truthextractor (class in graphnet.data.extractors.liquido.h5_extractor)": [[41, "graphnet.data.extractors.liquido.h5_extractor.H5TruthExtractor", false]], "handlers (graphnet.utilities.logging.logger property)": [[141, "graphnet.utilities.logging.Logger.handlers", false]], "has_extension() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.has_extension", false]], "has_icecube_package() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.has_icecube_package", false]], "has_jammy_flows_package() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.has_jammy_flows_package", false]], "has_torch_package() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.has_torch_package", false]], "i3_file (graphnet.data.dataclasses.i3fileset attribute)": [[6, "graphnet.data.dataclasses.I3FileSet.i3_file", false]], "i3_files (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.i3_files", false]], "i3extractor (class in graphnet.data.extractors.icecube.i3extractor)": [[21, "graphnet.data.extractors.icecube.i3extractor.I3Extractor", false]], "i3featureextractor (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractor", false]], "i3featureextractoricecube86 (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractorIceCube86", false]], "i3featureextractoricecubedeepcore (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractorIceCubeDeepCore", false]], "i3featureextractoricecubeupgrade (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractorIceCubeUpgrade", false]], "i3fileset (class in graphnet.data.dataclasses)": [[6, "graphnet.data.dataclasses.I3FileSet", false]], "i3filter (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.I3Filter", false]], "i3filtermask (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.I3FilterMask", false]], "i3galacticplanehybridrecoextractor (class in graphnet.data.extractors.icecube.i3hybridrecoextractor)": [[24, "graphnet.data.extractors.icecube.i3hybridrecoextractor.I3GalacticPlaneHybridRecoExtractor", false]], "i3genericextractor (class in graphnet.data.extractors.icecube.i3genericextractor)": [[23, "graphnet.data.extractors.icecube.i3genericextractor.I3GenericExtractor", false]], "i3inferencemodule (class in graphnet.deployment.icecube.inference_module)": [[76, "graphnet.deployment.icecube.inference_module.I3InferenceModule", false]], "i3ntmuonlabelextractor (class in graphnet.data.extractors.icecube.i3ntmuonlabelsextractor)": [[25, "graphnet.data.extractors.icecube.i3ntmuonlabelsextractor.I3NTMuonLabelExtractor", false]], "i3particleextractor (class in graphnet.data.extractors.icecube.i3particleextractor)": [[26, "graphnet.data.extractors.icecube.i3particleextractor.I3ParticleExtractor", false]], "i3pisaextractor (class in graphnet.data.extractors.icecube.i3pisaextractor)": [[27, "graphnet.data.extractors.icecube.i3pisaextractor.I3PISAExtractor", false]], "i3pulsecleanermodule (class in graphnet.deployment.icecube.cleaning_module)": [[74, "graphnet.deployment.icecube.cleaning_module.I3PulseCleanerModule", false]], "i3pulsenoisetruthflagicecubeupgrade (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3PulseNoiseTruthFlagIceCubeUpgrade", false]], "i3quesoextractor (class in graphnet.data.extractors.icecube.i3quesoextractor)": [[28, "graphnet.data.extractors.icecube.i3quesoextractor.I3QUESOExtractor", false]], "i3reader (class in graphnet.data.readers.i3reader)": [[50, "graphnet.data.readers.i3reader.I3Reader", false]], "i3retroextractor (class in graphnet.data.extractors.icecube.i3retroextractor)": [[29, "graphnet.data.extractors.icecube.i3retroextractor.I3RetroExtractor", false]], "i3splinempeicextractor (class in graphnet.data.extractors.icecube.i3splinempeextractor)": [[30, "graphnet.data.extractors.icecube.i3splinempeextractor.I3SplineMPEICExtractor", false]], "i3toparquetconverter (class in graphnet.data.pre_configured.dataconverters)": [[47, "graphnet.data.pre_configured.dataconverters.I3ToParquetConverter", false]], "i3tosqliteconverter (class in graphnet.data.pre_configured.dataconverters)": [[47, "graphnet.data.pre_configured.dataconverters.I3ToSQLiteConverter", false]], "i3truthextractor (class in graphnet.data.extractors.icecube.i3truthextractor)": [[31, "graphnet.data.extractors.icecube.i3truthextractor.I3TruthExtractor", false]], "i3tumextractor (class in graphnet.data.extractors.icecube.i3tumextractor)": [[32, "graphnet.data.extractors.icecube.i3tumextractor.I3TUMExtractor", false]], "ice_transparency() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.ice_transparency", false]], "icecube86 (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCube86", false]], "icecube86 (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.ICECUBE86", false]], "icecube86 (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.ICECUBE86", false]], "icecube86prometheus (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus", false]], "icecubedeepcore (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCubeDeepCore", false]], "icecubedeepcore8 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8", false]], "icecubegen2 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2", false]], "icecubekaggle (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle", false]], "icecubeupgrade (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade", false]], "icecubeupgrade7 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7", false]], "icedemo81 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceDemo81", false]], "icemixnodes (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.IceMixNodes", false]], "identify_indices() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.identify_indices", false]], "identitytask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.IdentityTask", false]], "index_column (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.index_column", false]], "inelasticityreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction", false]], "inference() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.inference", false]], "inference() (graphnet.models.task.task.task method)": [[118, "graphnet.models.task.task.Task.inference", false]], "info() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.info", false]], "init_global_index() (in module graphnet.data.dataconverter)": [[7, "graphnet.data.dataconverter.init_global_index", false]], "init_predict_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_predict_tqdm", false]], "init_test_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_test_tqdm", false]], "init_train_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_train_tqdm", false]], "init_validation_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_validation_tqdm", false]], "is_boost_class() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_boost_class", false]], "is_boost_enum() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_boost_enum", false]], "is_gcd_file() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.is_gcd_file", false]], "is_graphnet_class() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.is_graphnet_class", false]], "is_graphnet_module() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.is_graphnet_module", false]], "is_i3_file() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.is_i3_file", false]], "is_icecube_class() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_icecube_class", false]], "is_method() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_method", false]], "is_type() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_type", false]], "iseecube (class in graphnet.models.transformer.iseecube)": [[120, "graphnet.models.transformer.iseecube.ISeeCube", false]], "kaggle (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.KAGGLE", false]], "kaggle (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.KAGGLE", false]], "key (graphnet.training.labels.label property)": [[124, "graphnet.training.labels.Label.key", false]], "knn_graph_batch() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.knn_graph_batch", false]], "knnedges (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.KNNEdges", false]], "knngraph (class in graphnet.models.graphs.graphs)": [[105, "graphnet.models.graphs.graphs.KNNGraph", false]], "label (class in graphnet.training.labels)": [[124, "graphnet.training.labels.Label", false]], "labels (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.labels", false]], "learnedtask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.LearnedTask", false]], "lenmatchbatchsampler (class in graphnet.data.dataset.samplers)": [[14, "graphnet.data.dataset.samplers.LenMatchBatchSampler", false]], "lex_sort() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.lex_sort", false]], "liquido (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.LIQUIDO", false]], "liquido (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.LIQUIDO", false]], "liquido_v1 (class in graphnet.models.detector.liquido)": [[88, "graphnet.models.detector.liquido.LiquidO_v1", false]], "liquidoreader (class in graphnet.data.readers.liquido_reader)": [[52, "graphnet.data.readers.liquido_reader.LiquidOReader", false]], "list_all_submodules() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.list_all_submodules", false]], "load() (graphnet.models.model.model class method)": [[109, "graphnet.models.model.Model.load", false]], "load() (graphnet.utilities.config.base_config.baseconfig class method)": [[131, "graphnet.utilities.config.base_config.BaseConfig.load", false]], "load_module() (in module graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.load_module", false]], "load_state_dict() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.load_state_dict", false]], "load_state_dict() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.load_state_dict", false]], "log_cmk() (graphnet.training.loss_functions.vonmisesfisherloss class method)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss.log_cmk", false]], "log_cmk_approx() (graphnet.training.loss_functions.vonmisesfisherloss class method)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss.log_cmk_approx", false]], "log_cmk_exact() (graphnet.training.loss_functions.vonmisesfisherloss class method)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss.log_cmk_exact", false]], "logcmk (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.LogCMK", false]], "logcoshloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.LogCoshLoss", false]], "logger (class in graphnet.utilities.logging)": [[141, "graphnet.utilities.logging.Logger", false]], "loss_weight_column (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.loss_weight_column", false]], "loss_weight_default_value (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.loss_weight_default_value", false]], "loss_weight_table (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.loss_weight_table", false]], "lossfunction (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.LossFunction", false]], "make_dataloader() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.make_dataloader", false]], "make_train_validation_dataloader() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.make_train_validation_dataloader", false]], "merge_files() (graphnet.data.dataconverter.dataconverter method)": [[7, "graphnet.data.dataconverter.DataConverter.merge_files", false]], "merge_files() (graphnet.data.writers.graphnet_writer.graphnetwriter method)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter.merge_files", false]], "merge_files() (graphnet.data.writers.parquet_writer.parquetwriter method)": [[63, "graphnet.data.writers.parquet_writer.ParquetWriter.merge_files", false]], "merge_files() (graphnet.data.writers.sqlite_writer.sqlitewriter method)": [[64, "graphnet.data.writers.sqlite_writer.SQLiteWriter.merge_files", false]], "message() (graphnet.models.components.layers.edgeconvtito method)": [[83, "graphnet.models.components.layers.EdgeConvTito.message", false]], "min_pool() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.min_pool", false]], "min_pool_x() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.min_pool_x", false]], "minkowskiknnedges (class in graphnet.models.graphs.edges.minkowski)": [[103, "graphnet.models.graphs.edges.minkowski.MinkowskiKNNEdges", false]], "mlp (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Mlp", false]], "model (class in graphnet.models.model)": [[109, "graphnet.models.model.Model", false]], "model_computed_fields (graphnet.utilities.config.base_config.baseconfig attribute)": [[131, "graphnet.utilities.config.base_config.BaseConfig.model_computed_fields", false]], "model_computed_fields (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.model_computed_fields", false]], "model_computed_fields (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.model_computed_fields", false]], "model_computed_fields (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.model_computed_fields", false]], "model_config (graphnet.utilities.config.base_config.baseconfig attribute)": [[131, "graphnet.utilities.config.base_config.BaseConfig.model_config", false]], "model_config (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.model_config", false]], "model_config (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.model_config", false]], "model_config (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.model_config", false]], "model_fields (graphnet.utilities.config.base_config.baseconfig attribute)": [[131, "graphnet.utilities.config.base_config.BaseConfig.model_fields", false]], "model_fields (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.model_fields", false]], "model_fields (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.model_fields", false]], "model_fields (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.model_fields", false]], "modelconfig (class in graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.ModelConfig", false]], "modelconfigsaverabc (class in graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.ModelConfigSaverABC", false]], "modelconfigsavermeta (class in graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.ModelConfigSaverMeta", false]], "module": [[1, "module-graphnet", false], [2, "module-graphnet.constants", false], [3, "module-graphnet.data", false], [4, "module-graphnet.data.constants", false], [5, "module-graphnet.data.curated_datamodule", false], [6, "module-graphnet.data.dataclasses", false], [7, "module-graphnet.data.dataconverter", false], [8, "module-graphnet.data.dataloader", false], [9, "module-graphnet.data.datamodule", false], [10, "module-graphnet.data.dataset", false], [11, "module-graphnet.data.dataset.dataset", false], [12, "module-graphnet.data.dataset.parquet", false], [13, "module-graphnet.data.dataset.parquet.parquet_dataset", false], [14, "module-graphnet.data.dataset.samplers", false], [15, "module-graphnet.data.dataset.sqlite", false], [16, "module-graphnet.data.dataset.sqlite.sqlite_dataset", false], [17, "module-graphnet.data.extractors", false], [18, "module-graphnet.data.extractors.combine_extractors", false], [19, "module-graphnet.data.extractors.extractor", false], [20, "module-graphnet.data.extractors.icecube", false], [21, "module-graphnet.data.extractors.icecube.i3extractor", false], [22, "module-graphnet.data.extractors.icecube.i3featureextractor", false], [23, "module-graphnet.data.extractors.icecube.i3genericextractor", false], [24, "module-graphnet.data.extractors.icecube.i3hybridrecoextractor", false], [25, "module-graphnet.data.extractors.icecube.i3ntmuonlabelsextractor", false], [26, "module-graphnet.data.extractors.icecube.i3particleextractor", false], [27, "module-graphnet.data.extractors.icecube.i3pisaextractor", false], [28, "module-graphnet.data.extractors.icecube.i3quesoextractor", false], [29, "module-graphnet.data.extractors.icecube.i3retroextractor", false], [30, "module-graphnet.data.extractors.icecube.i3splinempeextractor", false], [31, "module-graphnet.data.extractors.icecube.i3truthextractor", false], [32, "module-graphnet.data.extractors.icecube.i3tumextractor", false], [33, "module-graphnet.data.extractors.icecube.utilities", false], [34, "module-graphnet.data.extractors.icecube.utilities.collections", false], [35, "module-graphnet.data.extractors.icecube.utilities.frames", false], [36, "module-graphnet.data.extractors.icecube.utilities.i3_filters", false], [37, "module-graphnet.data.extractors.icecube.utilities.types", false], [38, "module-graphnet.data.extractors.internal", false], [39, "module-graphnet.data.extractors.internal.parquet_extractor", false], [40, "module-graphnet.data.extractors.liquido", false], [41, "module-graphnet.data.extractors.liquido.h5_extractor", false], [42, "module-graphnet.data.extractors.prometheus", false], [43, "module-graphnet.data.extractors.prometheus.prometheus_extractor", false], [44, "module-graphnet.data.parquet", false], [45, "module-graphnet.data.parquet.deprecated_methods", false], [46, "module-graphnet.data.pre_configured", false], [47, "module-graphnet.data.pre_configured.dataconverters", false], [48, "module-graphnet.data.readers", false], [49, "module-graphnet.data.readers.graphnet_file_reader", false], [50, "module-graphnet.data.readers.i3reader", false], [51, "module-graphnet.data.readers.internal_parquet_reader", false], [52, "module-graphnet.data.readers.liquido_reader", false], [53, "module-graphnet.data.readers.prometheus_reader", false], [54, "module-graphnet.data.sqlite", false], [55, "module-graphnet.data.sqlite.deprecated_methods", false], [56, "module-graphnet.data.utilities", false], [57, "module-graphnet.data.utilities.parquet_to_sqlite", false], [58, "module-graphnet.data.utilities.random", false], [59, "module-graphnet.data.utilities.sqlite_utilities", false], [60, "module-graphnet.data.utilities.string_selection_resolver", false], [61, "module-graphnet.data.writers", false], [62, "module-graphnet.data.writers.graphnet_writer", false], [63, "module-graphnet.data.writers.parquet_writer", false], [64, "module-graphnet.data.writers.sqlite_writer", false], [65, "module-graphnet.datasets", false], [66, "module-graphnet.datasets.prometheus_datasets", false], [67, "module-graphnet.datasets.test_dataset", false], [68, "module-graphnet.deployment", false], [69, "module-graphnet.deployment.deployer", false], [70, "module-graphnet.deployment.deployment_module", false], [74, "module-graphnet.deployment.icecube.cleaning_module", false], [76, "module-graphnet.deployment.icecube.inference_module", false], [77, "module-graphnet.exceptions", false], [78, "module-graphnet.exceptions.exceptions", false], [79, "module-graphnet.models", false], [80, "module-graphnet.models.coarsening", false], [81, "module-graphnet.models.components", false], [82, "module-graphnet.models.components.embedding", false], [83, "module-graphnet.models.components.layers", false], [84, "module-graphnet.models.components.pool", false], [85, "module-graphnet.models.detector", false], [86, "module-graphnet.models.detector.detector", false], [87, "module-graphnet.models.detector.icecube", false], [88, "module-graphnet.models.detector.liquido", false], [89, "module-graphnet.models.detector.prometheus", false], [90, "module-graphnet.models.easy_model", false], [91, "module-graphnet.models.gnn", false], [92, "module-graphnet.models.gnn.RNN_tito", false], [93, "module-graphnet.models.gnn.convnet", false], [94, "module-graphnet.models.gnn.dynedge", false], [95, "module-graphnet.models.gnn.dynedge_jinst", false], [96, "module-graphnet.models.gnn.dynedge_kaggle_tito", false], [97, "module-graphnet.models.gnn.gnn", false], [98, "module-graphnet.models.gnn.icemix", false], [99, "module-graphnet.models.gnn.particlenet", false], [100, "module-graphnet.models.graphs", false], [101, "module-graphnet.models.graphs.edges", false], [102, "module-graphnet.models.graphs.edges.edges", false], [103, "module-graphnet.models.graphs.edges.minkowski", false], [104, "module-graphnet.models.graphs.graph_definition", false], [105, "module-graphnet.models.graphs.graphs", false], [106, "module-graphnet.models.graphs.nodes", false], [107, "module-graphnet.models.graphs.nodes.nodes", false], [108, "module-graphnet.models.graphs.utils", false], [109, "module-graphnet.models.model", false], [110, "module-graphnet.models.normalizing_flow", false], [111, "module-graphnet.models.rnn", false], [112, "module-graphnet.models.rnn.node_rnn", false], [113, "module-graphnet.models.standard_averaged_model", false], [114, "module-graphnet.models.standard_model", false], [115, "module-graphnet.models.task", false], [116, "module-graphnet.models.task.classification", false], [117, "module-graphnet.models.task.reconstruction", false], [118, "module-graphnet.models.task.task", false], [119, "module-graphnet.models.transformer", false], [120, "module-graphnet.models.transformer.iseecube", false], [121, "module-graphnet.models.utils", false], [122, "module-graphnet.training", false], [123, "module-graphnet.training.callbacks", false], [124, "module-graphnet.training.labels", false], [125, "module-graphnet.training.loss_functions", false], [126, "module-graphnet.training.utils", false], [127, "module-graphnet.training.weight_fitting", false], [128, "module-graphnet.utilities", false], [129, "module-graphnet.utilities.argparse", false], [130, "module-graphnet.utilities.config", false], [131, "module-graphnet.utilities.config.base_config", false], [132, "module-graphnet.utilities.config.configurable", false], [133, "module-graphnet.utilities.config.dataset_config", false], [134, "module-graphnet.utilities.config.model_config", false], [135, "module-graphnet.utilities.config.parsing", false], [136, "module-graphnet.utilities.config.training_config", false], [137, "module-graphnet.utilities.decorators", false], [138, "module-graphnet.utilities.deprecation_tools", false], [139, "module-graphnet.utilities.filesys", false], [140, "module-graphnet.utilities.imports", false], [141, "module-graphnet.utilities.logging", false], [142, "module-graphnet.utilities.maths", false]], "modules (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.modules", false]], "mseloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.MSELoss", false]], "multiclassclassificationtask (class in graphnet.models.task.classification)": [[116, "graphnet.models.task.classification.MulticlassClassificationTask", false]], "name (graphnet.data.extractors.extractor.extractor property)": [[19, "graphnet.data.extractors.extractor.Extractor.name", false]], "nb_inputs (graphnet.models.gnn.gnn.gnn property)": [[97, "graphnet.models.gnn.gnn.GNN.nb_inputs", false]], "nb_inputs (graphnet.models.task.classification.binaryclassificationtask attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.classification.binaryclassificationtasklogits attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.azimuthreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.azimuthreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.directionreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energyreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energyreconstructionwithpower attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energyreconstructionwithuncertainty attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energytcreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.inelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.positionreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.timereconstruction attribute)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.vertexreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.zenithreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.zenithreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.identitytask property)": [[118, "graphnet.models.task.task.IdentityTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.learnedtask property)": [[118, "graphnet.models.task.task.LearnedTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.standardlearnedtask property)": [[118, "graphnet.models.task.task.StandardLearnedTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.task property)": [[118, "graphnet.models.task.task.Task.nb_inputs", false]], "nb_inputs() (graphnet.models.task.task.standardflowtask method)": [[118, "graphnet.models.task.task.StandardFlowTask.nb_inputs", false]], "nb_outputs (graphnet.models.gnn.gnn.gnn property)": [[97, "graphnet.models.gnn.gnn.GNN.nb_outputs", false]], "nb_outputs (graphnet.models.graphs.nodes.nodes.nodedefinition property)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.nb_outputs", false]], "nb_repeats_allowed (graphnet.utilities.logging.repeatfilter attribute)": [[141, "graphnet.utilities.logging.RepeatFilter.nb_repeats_allowed", false]], "no_weight_decay() (graphnet.models.gnn.icemix.deepice method)": [[98, "graphnet.models.gnn.icemix.DeepIce.no_weight_decay", false]], "node_rnn (class in graphnet.models.rnn.node_rnn)": [[112, "graphnet.models.rnn.node_rnn.Node_RNN", false]], "node_truth (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.node_truth", false]], "node_truth_table (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.node_truth_table", false]], "nodeasdomtimeseries (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.NodeAsDOMTimeSeries", false]], "nodedefinition (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition", false]], "nodesaspulses (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.NodesAsPulses", false]], "normalizingflow (class in graphnet.models.normalizing_flow)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow", false]], "nullspliti3filter (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.NullSplitI3Filter", false]], "num_samples (graphnet.data.dataset.samplers.randomchunksampler property)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler.num_samples", false]], "on_fit_end() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.on_fit_end", false]], "on_train_end() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.on_train_end", false]], "on_train_epoch_end() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.on_train_epoch_end", false]], "on_train_epoch_end() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.on_train_epoch_end", false]], "on_train_epoch_start() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.on_train_epoch_start", false]], "on_validation_end() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.on_validation_end", false]], "optimizer_step() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.optimizer_step", false]], "options (class in graphnet.utilities.argparse)": [[129, "graphnet.utilities.argparse.Options", false]], "orca150 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.ORCA150", false]], "orca150superdense (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense", false]], "output_folder (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.output_folder", false]], "pairwise_shuffle() (in module graphnet.data.utilities.random)": [[58, "graphnet.data.utilities.random.pairwise_shuffle", false]], "parquetdataconverter (class in graphnet.data.parquet.deprecated_methods)": [[45, "graphnet.data.parquet.deprecated_methods.ParquetDataConverter", false]], "parquetdataset (class in graphnet.data.dataset.parquet.parquet_dataset)": [[13, "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset", false]], "parquetextractor (class in graphnet.data.extractors.internal.parquet_extractor)": [[39, "graphnet.data.extractors.internal.parquet_extractor.ParquetExtractor", false]], "parquetreader (class in graphnet.data.readers.internal_parquet_reader)": [[51, "graphnet.data.readers.internal_parquet_reader.ParquetReader", false]], "parquettosqliteconverter (class in graphnet.data.pre_configured.dataconverters)": [[47, "graphnet.data.pre_configured.dataconverters.ParquetToSQLiteConverter", false]], "parquetwriter (class in graphnet.data.writers.parquet_writer)": [[63, "graphnet.data.writers.parquet_writer.ParquetWriter", false]], "parse_graph_definition() (in module graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.parse_graph_definition", false]], "parse_labels() (in module graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.parse_labels", false]], "particlenet (class in graphnet.models.gnn.particlenet)": [[99, "graphnet.models.gnn.particlenet.ParticleNeT", false]], "path (graphnet.data.dataset.dataset.dataset property)": [[11, "graphnet.data.dataset.dataset.Dataset.path", false]], "path (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.path", false]], "percentileclusters (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.PercentileClusters", false]], "piecewiselinearlr (class in graphnet.training.callbacks)": [[123, "graphnet.training.callbacks.PiecewiseLinearLR", false]], "ponesmall (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.PONESmall", false]], "ponetriangle (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.PONETriangle", false]], "pop_default() (graphnet.utilities.argparse.options method)": [[129, "graphnet.utilities.argparse.Options.pop_default", false]], "positionreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction", false]], "predict() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.predict", false]], "predict_as_dataframe() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.predict_as_dataframe", false]], "prediction_labels (graphnet.models.easy_model.easysyntax property)": [[90, "graphnet.models.easy_model.EasySyntax.prediction_labels", false]], "prepare_data() (graphnet.data.curated_datamodule.curateddataset method)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.prepare_data", false]], "prepare_data() (graphnet.data.curated_datamodule.erdahosteddataset method)": [[5, "graphnet.data.curated_datamodule.ERDAHostedDataset.prepare_data", false]], "prepare_data() (graphnet.data.datamodule.graphnetdatamodule method)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.prepare_data", false]], "progressbar (class in graphnet.training.callbacks)": [[123, "graphnet.training.callbacks.ProgressBar", false]], "prometheus (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.Prometheus", false]], "prometheus (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.PROMETHEUS", false]], "prometheus (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.PROMETHEUS", false]], "prometheusextractor (class in graphnet.data.extractors.prometheus.prometheus_extractor)": [[43, "graphnet.data.extractors.prometheus.prometheus_extractor.PrometheusExtractor", false]], "prometheusfeatureextractor (class in graphnet.data.extractors.prometheus.prometheus_extractor)": [[43, "graphnet.data.extractors.prometheus.prometheus_extractor.PrometheusFeatureExtractor", false]], "prometheusreader (class in graphnet.data.readers.prometheus_reader)": [[53, "graphnet.data.readers.prometheus_reader.PrometheusReader", false]], "prometheustruthextractor (class in graphnet.data.extractors.prometheus.prometheus_extractor)": [[43, "graphnet.data.extractors.prometheus.prometheus_extractor.PrometheusTruthExtractor", false]], "publicprometheusdataset (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.PublicPrometheusDataset", false]], "pulse_truth (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.pulse_truth", false]], "pulsemaps (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.pulsemaps", false]], "pulsemaps (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.pulsemaps", false]], "query_database() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.query_database", false]], "query_table() (graphnet.data.dataset.dataset.dataset method)": [[11, "graphnet.data.dataset.dataset.Dataset.query_table", false]], "query_table() (graphnet.data.dataset.parquet.parquet_dataset.parquetdataset method)": [[13, "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset.query_table", false]], "query_table() (graphnet.data.dataset.sqlite.sqlite_dataset.sqlitedataset method)": [[16, "graphnet.data.dataset.sqlite.sqlite_dataset.SQLiteDataset.query_table", false]], "radialedges (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.RadialEdges", false]], "randomchunksampler (class in graphnet.data.dataset.samplers)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler", false]], "reduce_options (graphnet.models.coarsening.coarsening attribute)": [[80, "graphnet.models.coarsening.Coarsening.reduce_options", false]], "rename_state_dict_entries() (in module graphnet.utilities.deprecation_tools)": [[138, "graphnet.utilities.deprecation_tools.rename_state_dict_entries", false]], "repeatfilter (class in graphnet.utilities.logging)": [[141, "graphnet.utilities.logging.RepeatFilter", false]], "requires_icecube() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.requires_icecube", false]], "reset_parameters() (graphnet.models.components.layers.edgeconvtito method)": [[83, "graphnet.models.components.layers.EdgeConvTito.reset_parameters", false]], "resolve() (graphnet.data.utilities.string_selection_resolver.stringselectionresolver method)": [[60, "graphnet.data.utilities.string_selection_resolver.StringSelectionResolver.resolve", false]], "rmseloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.RMSELoss", false]], "rmsevonmisesfisher3dloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.RMSEVonMisesFisher3DLoss", false]], "rnn_tito (class in graphnet.models.gnn.rnn_tito)": [[92, "graphnet.models.gnn.RNN_tito.RNN_TITO", false]], "run() (graphnet.deployment.deployer.deployer method)": [[69, "graphnet.deployment.deployer.Deployer.run", false]], "run_sql_code() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.run_sql_code", false]], "save() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.save", false]], "save_config() (graphnet.utilities.config.configurable.configurable method)": [[132, "graphnet.utilities.config.configurable.Configurable.save_config", false]], "save_dataset_config() (in module graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.save_dataset_config", false]], "save_model_config() (in module graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.save_model_config", false]], "save_results() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.save_results", false]], "save_selection() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.save_selection", false]], "save_state_dict() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.save_state_dict", false]], "save_to_sql() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.save_to_sql", false]], "seed (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.seed", false]], "selection (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.selection", false]], "sensor_id_column (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.sensor_id_column", false]], "sensor_index_name (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.sensor_index_name", false]], "sensor_position_names (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.sensor_position_names", false]], "serialise() (in module graphnet.data.extractors.icecube.utilities.collections)": [[34, "graphnet.data.extractors.icecube.utilities.collections.serialise", false]], "set_extractors() (graphnet.data.readers.graphnet_file_reader.graphnetfilereader method)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.set_extractors", false]], "set_gcd() (graphnet.data.extractors.icecube.i3extractor.i3extractor method)": [[21, "graphnet.data.extractors.icecube.i3extractor.I3Extractor.set_gcd", false]], "set_number_of_inputs() (graphnet.models.graphs.nodes.nodes.nodedefinition method)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.set_number_of_inputs", false]], "set_output_feature_names() (graphnet.models.graphs.nodes.nodes.nodedefinition method)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.set_output_feature_names", false]], "set_verbose_print_recursively() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.set_verbose_print_recursively", false]], "setlevel() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.setLevel", false]], "settings (class in graphnet.data.dataclasses)": [[6, "graphnet.data.dataclasses.Settings", false]], "setup() (graphnet.data.datamodule.graphnetdatamodule method)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.setup", false]], "setup() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.setup", false]], "shared_step() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.shared_step", false]], "shared_step() (graphnet.models.normalizing_flow.normalizingflow method)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow.shared_step", false]], "shared_step() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.shared_step", false]], "sinusoidalposemb (class in graphnet.models.components.embedding)": [[82, "graphnet.models.components.embedding.SinusoidalPosEmb", false]], "spacetimeencoder (class in graphnet.models.components.embedding)": [[82, "graphnet.models.components.embedding.SpacetimeEncoder", false]], "sqlitedataconverter (class in graphnet.data.sqlite.deprecated_methods)": [[55, "graphnet.data.sqlite.deprecated_methods.SQLiteDataConverter", false]], "sqlitedataset (class in graphnet.data.dataset.sqlite.sqlite_dataset)": [[16, "graphnet.data.dataset.sqlite.sqlite_dataset.SQLiteDataset", false]], "sqlitewriter (class in graphnet.data.writers.sqlite_writer)": [[64, "graphnet.data.writers.sqlite_writer.SQLiteWriter", false]], "standard_arguments (graphnet.utilities.argparse.argumentparser attribute)": [[129, "graphnet.utilities.argparse.ArgumentParser.standard_arguments", false]], "standardaveragedmodel (class in graphnet.models.standard_averaged_model)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel", false]], "standardflowtask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.StandardFlowTask", false]], "standardlearnedtask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.StandardLearnedTask", false]], "standardmodel (class in graphnet.models.standard_model)": [[114, "graphnet.models.standard_model.StandardModel", false]], "std_pool() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.std_pool", false]], "std_pool_x() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.std_pool_x", false]], "stream_handlers (graphnet.utilities.logging.logger property)": [[141, "graphnet.utilities.logging.Logger.stream_handlers", false]], "string_id_column (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.string_id_column", false]], "string_id_column (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.string_id_column", false]], "string_id_column (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.string_id_column", false]], "string_id_column (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.string_id_column", false]], "string_index_name (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.string_index_name", false]], "string_selection (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.string_selection", false]], "stringselectionresolver (class in graphnet.data.utilities.string_selection_resolver)": [[60, "graphnet.data.utilities.string_selection_resolver.StringSelectionResolver", false]], "sum_pool() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.sum_pool", false]], "sum_pool_and_distribute() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.sum_pool_and_distribute", false]], "sum_pool_x() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.sum_pool_x", false]], "target (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.target", false]], "target_labels (graphnet.models.easy_model.easysyntax property)": [[90, "graphnet.models.easy_model.EasySyntax.target_labels", false]], "task (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.Task", false]], "teardown() (graphnet.data.datamodule.graphnetdatamodule method)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.teardown", false]], "test_dataloader (graphnet.data.datamodule.graphnetdatamodule property)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.test_dataloader", false]], "testdataset (class in graphnet.datasets.test_dataset)": [[67, "graphnet.datasets.test_dataset.TestDataset", false]], "timereconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction", false]], "track (class in graphnet.training.labels)": [[124, "graphnet.training.labels.Track", false]], "train() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.train", false]], "train_dataloader (graphnet.data.datamodule.graphnetdatamodule property)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.train_dataloader", false]], "train_eval() (graphnet.models.task.task.task method)": [[118, "graphnet.models.task.task.Task.train_eval", false]], "training_step() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.training_step", false]], "training_step() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.training_step", false]], "trainingconfig (class in graphnet.utilities.config.training_config)": [[136, "graphnet.utilities.config.training_config.TrainingConfig", false]], "transpose_list_of_dicts() (in module graphnet.data.extractors.icecube.utilities.collections)": [[34, "graphnet.data.extractors.icecube.utilities.collections.transpose_list_of_dicts", false]], "traverse_and_apply() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.traverse_and_apply", false]], "trident1211 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211", false]], "tridentsmall (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.TRIDENTSmall", false]], "truth (class in graphnet.data.constants)": [[4, "graphnet.data.constants.TRUTH", false]], "truth (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.truth", false]], "truth_table (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.truth_table", false]], "truth_table (graphnet.data.dataset.dataset.dataset property)": [[11, "graphnet.data.dataset.dataset.Dataset.truth_table", false]], "truth_table (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.truth_table", false]], "unbatch_edge_index() (in module graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.unbatch_edge_index", false]], "uniform (class in graphnet.training.weight_fitting)": [[127, "graphnet.training.weight_fitting.Uniform", false]], "upgrade (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.UPGRADE", false]], "upgrade (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.UPGRADE", false]], "val_dataloader (graphnet.data.datamodule.graphnetdatamodule property)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.val_dataloader", false]], "validate_files() (graphnet.data.readers.graphnet_file_reader.graphnetfilereader method)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.validate_files", false]], "validate_tasks() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.validate_tasks", false]], "validate_tasks() (graphnet.models.normalizing_flow.normalizingflow method)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow.validate_tasks", false]], "validate_tasks() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.validate_tasks", false]], "validation_step() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.validation_step", false]], "validation_step() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.validation_step", false]], "verbose_print (graphnet.models.model.model attribute)": [[109, "graphnet.models.model.Model.verbose_print", false]], "vertexreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction", false]], "vonmisesfisher2dloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.VonMisesFisher2DLoss", false]], "vonmisesfisher3dloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.VonMisesFisher3DLoss", false]], "vonmisesfisherloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss", false]], "warning() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.warning", false]], "warning_once() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.warning_once", false]], "waterdemo81 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.WaterDemo81", false]], "weightfitter (class in graphnet.training.weight_fitting)": [[127, "graphnet.training.weight_fitting.WeightFitter", false]], "with_standard_arguments() (graphnet.utilities.argparse.argumentparser method)": [[129, "graphnet.utilities.argparse.ArgumentParser.with_standard_arguments", false]], "xyz (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.xyz", false]], "xyz (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.xyz", false]], "xyz (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.xyz", false]], "xyz (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.xyz", false]], "xyz (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.xyz", false]], "xyz (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.xyz", false]], "xyz (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.xyz", false]], "xyz (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.xyz", false]], "xyz (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.xyz", false]], "xyz (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.xyz", false]], "xyz (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.xyz", false]], "xyz (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.xyz", false]], "zenithreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction", false]], "zenithreconstructionwithkappa (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa", false]]}, "objects": {"": [[1, 0, 0, "-", "graphnet"]], "graphnet": [[2, 0, 0, "-", "constants"], [3, 0, 0, "-", "data"], [65, 0, 0, "-", "datasets"], [68, 0, 0, "-", "deployment"], [77, 0, 0, "-", "exceptions"], [79, 0, 0, "-", "models"], [122, 0, 0, "-", "training"], [128, 0, 0, "-", "utilities"]], "graphnet.data": [[4, 0, 0, "-", "constants"], [5, 0, 0, "-", "curated_datamodule"], [6, 0, 0, "-", "dataclasses"], [7, 0, 0, "-", "dataconverter"], [8, 0, 0, "-", "dataloader"], [9, 0, 0, "-", "datamodule"], [10, 0, 0, "-", "dataset"], [17, 0, 0, "-", "extractors"], [44, 0, 0, "-", "parquet"], [46, 0, 0, "-", "pre_configured"], [48, 0, 0, "-", "readers"], [54, 0, 0, "-", "sqlite"], [56, 0, 0, "-", "utilities"], [61, 0, 0, "-", "writers"]], "graphnet.data.constants": [[4, 1, 1, "", "FEATURES"], [4, 1, 1, "", "TRUTH"]], "graphnet.data.constants.FEATURES": [[4, 2, 1, "", "DEEPCORE"], [4, 2, 1, "", "ICECUBE86"], [4, 2, 1, "", "KAGGLE"], [4, 2, 1, "", "LIQUIDO"], [4, 2, 1, "", "PROMETHEUS"], [4, 2, 1, "", "UPGRADE"]], "graphnet.data.constants.TRUTH": [[4, 2, 1, "", "DEEPCORE"], [4, 2, 1, "", "ICECUBE86"], [4, 2, 1, "", "KAGGLE"], [4, 2, 1, "", "LIQUIDO"], [4, 2, 1, "", "PROMETHEUS"], [4, 2, 1, "", "UPGRADE"]], "graphnet.data.curated_datamodule": [[5, 1, 1, "", "CuratedDataset"], [5, 1, 1, "", "ERDAHostedDataset"]], "graphnet.data.curated_datamodule.CuratedDataset": [[5, 3, 1, "", "available_backends"], [5, 3, 1, "", "citation"], [5, 3, 1, "", "comments"], [5, 3, 1, "", "creator"], [5, 3, 1, "", "dataset_dir"], [5, 4, 1, "", "description"], [5, 3, 1, "", "event_truth"], [5, 3, 1, "", "events"], [5, 3, 1, "", "experiment"], [5, 3, 1, "", "features"], [5, 4, 1, "", "prepare_data"], [5, 3, 1, "", "pulse_truth"], [5, 3, 1, "", "pulsemaps"], [5, 3, 1, "", "truth_table"]], "graphnet.data.curated_datamodule.ERDAHostedDataset": [[5, 4, 1, "", "prepare_data"]], "graphnet.data.dataclasses": [[6, 1, 1, "", "I3FileSet"], [6, 1, 1, "", "Settings"]], "graphnet.data.dataclasses.I3FileSet": [[6, 2, 1, "", "gcd_file"], [6, 2, 1, "", "i3_file"]], "graphnet.data.dataclasses.Settings": [[6, 2, 1, "", "gcd_file"], [6, 2, 1, "", "i3_files"], [6, 2, 1, "", "modules"], [6, 2, 1, "", "output_folder"]], "graphnet.data.dataconverter": [[7, 1, 1, "", "DataConverter"], [7, 5, 1, "", "init_global_index"]], "graphnet.data.dataconverter.DataConverter": [[7, 4, 1, "", "get_map_function"], [7, 4, 1, "", "merge_files"]], "graphnet.data.dataloader": [[8, 1, 1, "", "DataLoader"], [8, 5, 1, "", "collate_fn"], [8, 5, 1, "", "do_shuffle"]], "graphnet.data.dataloader.DataLoader": [[8, 4, 1, "", "from_dataset_config"]], "graphnet.data.datamodule": [[9, 1, 1, "", "GraphNeTDataModule"]], "graphnet.data.datamodule.GraphNeTDataModule": [[9, 4, 1, "", "prepare_data"], [9, 4, 1, "", "setup"], [9, 4, 1, "", "teardown"], [9, 3, 1, "", "test_dataloader"], [9, 3, 1, "", "train_dataloader"], [9, 3, 1, "", "val_dataloader"]], "graphnet.data.dataset": [[11, 0, 0, "-", "dataset"], [12, 0, 0, "-", "parquet"], [14, 0, 0, "-", "samplers"], [15, 0, 0, "-", "sqlite"]], "graphnet.data.dataset.dataset": [[11, 1, 1, "", "Dataset"], [11, 1, 1, "", "EnsembleDataset"], [11, 5, 1, "", "load_module"], [11, 5, 1, "", "parse_graph_definition"], [11, 5, 1, "", "parse_labels"]], "graphnet.data.dataset.dataset.Dataset": [[11, 4, 1, "", "add_label"], [11, 4, 1, "", "concatenate"], [11, 4, 1, "", "from_config"], [11, 3, 1, "", "path"], [11, 4, 1, "", "query_table"], [11, 3, 1, "", "truth_table"]], "graphnet.data.dataset.parquet": [[13, 0, 0, "-", "parquet_dataset"]], "graphnet.data.dataset.parquet.parquet_dataset": [[13, 1, 1, "", "ParquetDataset"]], "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset": [[13, 3, 1, "", "chunk_sizes"], [13, 4, 1, "", "query_table"]], "graphnet.data.dataset.samplers": [[14, 1, 1, "", "LenMatchBatchSampler"], [14, 1, 1, "", "RandomChunkSampler"], [14, 5, 1, "", "gather_len_matched_buckets"]], "graphnet.data.dataset.samplers.RandomChunkSampler": [[14, 3, 1, "", "chunks"], [14, 3, 1, "", "data_source"], [14, 3, 1, "", "num_samples"]], "graphnet.data.dataset.sqlite": [[16, 0, 0, "-", "sqlite_dataset"]], "graphnet.data.dataset.sqlite.sqlite_dataset": [[16, 1, 1, "", "SQLiteDataset"]], "graphnet.data.dataset.sqlite.sqlite_dataset.SQLiteDataset": [[16, 4, 1, "", "query_table"]], "graphnet.data.extractors": [[18, 0, 0, "-", "combine_extractors"], [19, 0, 0, "-", "extractor"], [20, 0, 0, "-", "icecube"], [38, 0, 0, "-", "internal"], [40, 0, 0, "-", "liquido"], [42, 0, 0, "-", "prometheus"]], "graphnet.data.extractors.combine_extractors": [[18, 1, 1, "", "CombinedExtractor"]], "graphnet.data.extractors.extractor": [[19, 1, 1, "", "Extractor"]], "graphnet.data.extractors.extractor.Extractor": [[19, 3, 1, "", "name"]], "graphnet.data.extractors.icecube": [[21, 0, 0, "-", "i3extractor"], [22, 0, 0, "-", "i3featureextractor"], [23, 0, 0, "-", "i3genericextractor"], [24, 0, 0, "-", "i3hybridrecoextractor"], [25, 0, 0, "-", "i3ntmuonlabelsextractor"], [26, 0, 0, "-", "i3particleextractor"], [27, 0, 0, "-", "i3pisaextractor"], [28, 0, 0, "-", "i3quesoextractor"], [29, 0, 0, "-", "i3retroextractor"], [30, 0, 0, "-", "i3splinempeextractor"], [31, 0, 0, "-", "i3truthextractor"], [32, 0, 0, "-", "i3tumextractor"], [33, 0, 0, "-", "utilities"]], "graphnet.data.extractors.icecube.i3extractor": [[21, 1, 1, "", "I3Extractor"]], "graphnet.data.extractors.icecube.i3extractor.I3Extractor": [[21, 4, 1, "", "set_gcd"]], "graphnet.data.extractors.icecube.i3featureextractor": [[22, 1, 1, "", "I3FeatureExtractor"], [22, 1, 1, "", "I3FeatureExtractorIceCube86"], [22, 1, 1, "", "I3FeatureExtractorIceCubeDeepCore"], [22, 1, 1, "", "I3FeatureExtractorIceCubeUpgrade"], [22, 1, 1, "", "I3PulseNoiseTruthFlagIceCubeUpgrade"]], "graphnet.data.extractors.icecube.i3genericextractor": [[23, 1, 1, "", "I3GenericExtractor"]], "graphnet.data.extractors.icecube.i3hybridrecoextractor": [[24, 1, 1, "", "I3GalacticPlaneHybridRecoExtractor"]], "graphnet.data.extractors.icecube.i3ntmuonlabelsextractor": [[25, 1, 1, "", "I3NTMuonLabelExtractor"]], "graphnet.data.extractors.icecube.i3particleextractor": [[26, 1, 1, "", "I3ParticleExtractor"]], "graphnet.data.extractors.icecube.i3pisaextractor": [[27, 1, 1, "", "I3PISAExtractor"]], "graphnet.data.extractors.icecube.i3quesoextractor": [[28, 1, 1, "", "I3QUESOExtractor"]], "graphnet.data.extractors.icecube.i3retroextractor": [[29, 1, 1, "", "I3RetroExtractor"]], "graphnet.data.extractors.icecube.i3splinempeextractor": [[30, 1, 1, "", "I3SplineMPEICExtractor"]], "graphnet.data.extractors.icecube.i3truthextractor": [[31, 1, 1, "", "I3TruthExtractor"]], "graphnet.data.extractors.icecube.i3tumextractor": [[32, 1, 1, "", "I3TUMExtractor"]], "graphnet.data.extractors.icecube.utilities": [[34, 0, 0, "-", "collections"], [35, 0, 0, "-", "frames"], [36, 0, 0, "-", "i3_filters"], [37, 0, 0, "-", "types"]], "graphnet.data.extractors.icecube.utilities.collections": [[34, 5, 1, "", "flatten_nested_dictionary"], [34, 5, 1, "", "serialise"], [34, 5, 1, "", "transpose_list_of_dicts"]], "graphnet.data.extractors.icecube.utilities.frames": [[35, 5, 1, "", "frame_is_montecarlo"], [35, 5, 1, "", "frame_is_noise"], [35, 5, 1, "", "get_om_keys_and_pulseseries"]], "graphnet.data.extractors.icecube.utilities.i3_filters": [[36, 1, 1, "", "I3Filter"], [36, 1, 1, "", "I3FilterMask"], [36, 1, 1, "", "NullSplitI3Filter"]], "graphnet.data.extractors.icecube.utilities.types": [[37, 5, 1, "", "break_cyclic_recursion"], [37, 5, 1, "", "cast_object_to_pure_python"], [37, 5, 1, "", "cast_pulse_series_to_pure_python"], [37, 5, 1, "", "get_member_variables"], [37, 5, 1, "", "is_boost_class"], [37, 5, 1, "", "is_boost_enum"], [37, 5, 1, "", "is_icecube_class"], [37, 5, 1, "", "is_method"], [37, 5, 1, "", "is_type"]], "graphnet.data.extractors.internal": [[39, 0, 0, "-", "parquet_extractor"]], "graphnet.data.extractors.internal.parquet_extractor": [[39, 1, 1, "", "ParquetExtractor"]], "graphnet.data.extractors.liquido": [[41, 0, 0, "-", "h5_extractor"]], "graphnet.data.extractors.liquido.h5_extractor": [[41, 1, 1, "", "H5Extractor"], [41, 1, 1, "", "H5HitExtractor"], [41, 1, 1, "", "H5TruthExtractor"]], "graphnet.data.extractors.prometheus": [[43, 0, 0, "-", "prometheus_extractor"]], "graphnet.data.extractors.prometheus.prometheus_extractor": [[43, 1, 1, "", "PrometheusExtractor"], [43, 1, 1, "", "PrometheusFeatureExtractor"], [43, 1, 1, "", "PrometheusTruthExtractor"]], "graphnet.data.parquet": [[45, 0, 0, "-", "deprecated_methods"]], "graphnet.data.parquet.deprecated_methods": [[45, 1, 1, "", "ParquetDataConverter"]], "graphnet.data.pre_configured": [[47, 0, 0, "-", "dataconverters"]], "graphnet.data.pre_configured.dataconverters": [[47, 1, 1, "", "I3ToParquetConverter"], [47, 1, 1, "", "I3ToSQLiteConverter"], [47, 1, 1, "", "ParquetToSQLiteConverter"]], "graphnet.data.readers": [[49, 0, 0, "-", "graphnet_file_reader"], [50, 0, 0, "-", "i3reader"], [51, 0, 0, "-", "internal_parquet_reader"], [52, 0, 0, "-", "liquido_reader"], [53, 0, 0, "-", "prometheus_reader"]], "graphnet.data.readers.graphnet_file_reader": [[49, 1, 1, "", "GraphNeTFileReader"]], "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader": [[49, 3, 1, "", "accepted_extractors"], [49, 3, 1, "", "accepted_file_extensions"], [49, 3, 1, "", "extracor_names"], [49, 4, 1, "", "find_files"], [49, 4, 1, "", "set_extractors"], [49, 4, 1, "", "validate_files"]], "graphnet.data.readers.i3reader": [[50, 1, 1, "", "I3Reader"]], "graphnet.data.readers.i3reader.I3Reader": [[50, 4, 1, "", "find_files"]], "graphnet.data.readers.internal_parquet_reader": [[51, 1, 1, "", "ParquetReader"]], "graphnet.data.readers.internal_parquet_reader.ParquetReader": [[51, 4, 1, "", "find_files"]], "graphnet.data.readers.liquido_reader": [[52, 1, 1, "", "LiquidOReader"]], "graphnet.data.readers.liquido_reader.LiquidOReader": [[52, 4, 1, "", "find_files"]], "graphnet.data.readers.prometheus_reader": [[53, 1, 1, "", "PrometheusReader"]], "graphnet.data.readers.prometheus_reader.PrometheusReader": [[53, 4, 1, "", "find_files"]], "graphnet.data.sqlite": [[55, 0, 0, "-", "deprecated_methods"]], "graphnet.data.sqlite.deprecated_methods": [[55, 1, 1, "", "SQLiteDataConverter"]], "graphnet.data.utilities": [[57, 0, 0, "-", "parquet_to_sqlite"], [58, 0, 0, "-", "random"], [59, 0, 0, "-", "sqlite_utilities"], [60, 0, 0, "-", "string_selection_resolver"]], "graphnet.data.utilities.random": [[58, 5, 1, "", "pairwise_shuffle"]], "graphnet.data.utilities.sqlite_utilities": [[59, 5, 1, "", "attach_index"], [59, 5, 1, "", "create_table"], [59, 5, 1, "", "create_table_and_save_to_sql"], [59, 5, 1, "", "database_exists"], [59, 5, 1, "", "database_table_exists"], [59, 5, 1, "", "get_primary_keys"], [59, 5, 1, "", "query_database"], [59, 5, 1, "", "run_sql_code"], [59, 5, 1, "", "save_to_sql"]], "graphnet.data.utilities.string_selection_resolver": [[60, 1, 1, "", "StringSelectionResolver"]], "graphnet.data.utilities.string_selection_resolver.StringSelectionResolver": [[60, 4, 1, "", "resolve"]], "graphnet.data.writers": [[62, 0, 0, "-", "graphnet_writer"], [63, 0, 0, "-", "parquet_writer"], [64, 0, 0, "-", "sqlite_writer"]], "graphnet.data.writers.graphnet_writer": [[62, 1, 1, "", "GraphNeTWriter"]], "graphnet.data.writers.graphnet_writer.GraphNeTWriter": [[62, 3, 1, "", "expects_merged_dataframes"], [62, 3, 1, "", "file_extension"], [62, 4, 1, "", "merge_files"]], "graphnet.data.writers.parquet_writer": [[63, 1, 1, "", "ParquetWriter"]], "graphnet.data.writers.parquet_writer.ParquetWriter": [[63, 4, 1, "", "merge_files"]], "graphnet.data.writers.sqlite_writer": [[64, 1, 1, "", "SQLiteWriter"]], "graphnet.data.writers.sqlite_writer.SQLiteWriter": [[64, 4, 1, "", "merge_files"]], "graphnet.datasets": [[66, 0, 0, "-", "prometheus_datasets"], [67, 0, 0, "-", "test_dataset"]], "graphnet.datasets.prometheus_datasets": [[66, 1, 1, "", "BaikalGVDSmall"], [66, 1, 1, "", "PONESmall"], [66, 1, 1, "", "PublicPrometheusDataset"], [66, 1, 1, "", "TRIDENTSmall"]], "graphnet.datasets.test_dataset": [[67, 1, 1, "", "TestDataset"]], "graphnet.deployment": [[69, 0, 0, "-", "deployer"], [70, 0, 0, "-", "deployment_module"]], "graphnet.deployment.deployer": [[69, 1, 1, "", "Deployer"]], "graphnet.deployment.deployer.Deployer": [[69, 4, 1, "", "run"]], "graphnet.deployment.deployment_module": [[70, 1, 1, "", "DeploymentModule"]], "graphnet.deployment.icecube": [[74, 0, 0, "-", "cleaning_module"], [76, 0, 0, "-", "inference_module"]], "graphnet.deployment.icecube.cleaning_module": [[74, 1, 1, "", "I3PulseCleanerModule"]], "graphnet.deployment.icecube.inference_module": [[76, 1, 1, "", "I3InferenceModule"]], "graphnet.exceptions": [[78, 0, 0, "-", "exceptions"]], "graphnet.exceptions.exceptions": [[78, 6, 1, "", "ColumnMissingException"]], "graphnet.models": [[80, 0, 0, "-", "coarsening"], [81, 0, 0, "-", "components"], [85, 0, 0, "-", "detector"], [90, 0, 0, "-", "easy_model"], [91, 0, 0, "-", "gnn"], [100, 0, 0, "-", "graphs"], [109, 0, 0, "-", "model"], [110, 0, 0, "-", "normalizing_flow"], [111, 0, 0, "-", "rnn"], [113, 0, 0, "-", "standard_averaged_model"], [114, 0, 0, "-", "standard_model"], [115, 0, 0, "-", "task"], [119, 0, 0, "-", "transformer"], [121, 0, 0, "-", "utils"]], "graphnet.models.coarsening": [[80, 1, 1, "", "AttributeCoarsening"], [80, 1, 1, "", "Coarsening"], [80, 1, 1, "", "CustomDOMCoarsening"], [80, 1, 1, "", "DOMAndTimeWindowCoarsening"], [80, 1, 1, "", "DOMCoarsening"], [80, 5, 1, "", "unbatch_edge_index"]], "graphnet.models.coarsening.Coarsening": [[80, 4, 1, "", "forward"], [80, 2, 1, "", "reduce_options"]], "graphnet.models.components": [[82, 0, 0, "-", "embedding"], [83, 0, 0, "-", "layers"], [84, 0, 0, "-", "pool"]], "graphnet.models.components.embedding": [[82, 1, 1, "", "FourierEncoder"], [82, 1, 1, "", "SinusoidalPosEmb"], [82, 1, 1, "", "SpacetimeEncoder"]], "graphnet.models.components.embedding.FourierEncoder": [[82, 4, 1, "", "forward"]], "graphnet.models.components.embedding.SinusoidalPosEmb": [[82, 4, 1, "", "forward"]], "graphnet.models.components.embedding.SpacetimeEncoder": [[82, 4, 1, "", "forward"]], "graphnet.models.components.layers": [[83, 1, 1, "", "Attention_rel"], [83, 1, 1, "", "Block"], [83, 1, 1, "", "Block_rel"], [83, 1, 1, "", "DropPath"], [83, 1, 1, "", "DynEdgeConv"], [83, 1, 1, "", "DynTrans"], [83, 1, 1, "", "EdgeConvTito"], [83, 1, 1, "", "Mlp"]], "graphnet.models.components.layers.Attention_rel": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.Block": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.Block_rel": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.DropPath": [[83, 4, 1, "", "extra_repr"], [83, 4, 1, "", "forward"]], "graphnet.models.components.layers.DynEdgeConv": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.DynTrans": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.EdgeConvTito": [[83, 4, 1, "", "forward"], [83, 4, 1, "", "message"], [83, 4, 1, "", "reset_parameters"]], "graphnet.models.components.layers.Mlp": [[83, 4, 1, "", "forward"]], "graphnet.models.components.pool": [[84, 5, 1, "", "group_by"], [84, 5, 1, "", "group_pulses_to_dom"], [84, 5, 1, "", "group_pulses_to_pmt"], [84, 5, 1, "", "min_pool"], [84, 5, 1, "", "min_pool_x"], [84, 5, 1, "", "std_pool"], [84, 5, 1, "", "std_pool_x"], [84, 5, 1, "", "sum_pool"], [84, 5, 1, "", "sum_pool_and_distribute"], [84, 5, 1, "", "sum_pool_x"]], "graphnet.models.detector": [[86, 0, 0, "-", "detector"], [87, 0, 0, "-", "icecube"], [88, 0, 0, "-", "liquido"], [89, 0, 0, "-", "prometheus"]], "graphnet.models.detector.detector": [[86, 1, 1, "", "Detector"]], "graphnet.models.detector.detector.Detector": [[86, 4, 1, "", "feature_map"], [86, 4, 1, "", "forward"], [86, 3, 1, "", "geometry_table"], [86, 3, 1, "", "sensor_index_name"], [86, 3, 1, "", "sensor_position_names"], [86, 3, 1, "", "string_index_name"]], "graphnet.models.detector.icecube": [[87, 1, 1, "", "IceCube86"], [87, 1, 1, "", "IceCubeDeepCore"], [87, 1, 1, "", "IceCubeKaggle"], [87, 1, 1, "", "IceCubeUpgrade"]], "graphnet.models.detector.icecube.IceCube86": [[87, 4, 1, "", "feature_map"], [87, 2, 1, "", "geometry_table_path"], [87, 2, 1, "", "sensor_id_column"], [87, 2, 1, "", "string_id_column"], [87, 2, 1, "", "xyz"]], "graphnet.models.detector.icecube.IceCubeDeepCore": [[87, 4, 1, "", "feature_map"]], "graphnet.models.detector.icecube.IceCubeKaggle": [[87, 4, 1, "", "feature_map"], [87, 2, 1, "", "geometry_table_path"], [87, 2, 1, "", "sensor_id_column"], [87, 2, 1, "", "string_id_column"], [87, 2, 1, "", "xyz"]], "graphnet.models.detector.icecube.IceCubeUpgrade": [[87, 4, 1, "", "feature_map"], [87, 2, 1, "", "geometry_table_path"], [87, 2, 1, "", "sensor_id_column"], [87, 2, 1, "", "string_id_column"], [87, 2, 1, "", "xyz"]], "graphnet.models.detector.liquido": [[88, 1, 1, "", "LiquidO_v1"]], "graphnet.models.detector.liquido.LiquidO_v1": [[88, 4, 1, "", "feature_map"], [88, 2, 1, "", "geometry_table_path"], [88, 2, 1, "", "sensor_id_column"], [88, 2, 1, "", "string_id_column"], [88, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus": [[89, 1, 1, "", "ARCA115"], [89, 1, 1, "", "BaikalGVD8"], [89, 1, 1, "", "IceCube86Prometheus"], [89, 1, 1, "", "IceCubeDeepCore8"], [89, 1, 1, "", "IceCubeGen2"], [89, 1, 1, "", "IceCubeUpgrade7"], [89, 1, 1, "", "IceDemo81"], [89, 1, 1, "", "ORCA150"], [89, 1, 1, "", "ORCA150SuperDense"], [89, 1, 1, "", "PONETriangle"], [89, 1, 1, "", "Prometheus"], [89, 1, 1, "", "TRIDENT1211"], [89, 1, 1, "", "WaterDemo81"]], "graphnet.models.detector.prometheus.ARCA115": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.BaikalGVD8": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCube86Prometheus": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCubeDeepCore8": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCubeGen2": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCubeUpgrade7": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceDemo81": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.ORCA150": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.ORCA150SuperDense": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.PONETriangle": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.TRIDENT1211": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.WaterDemo81": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.easy_model": [[90, 1, 1, "", "EasySyntax"]], "graphnet.models.easy_model.EasySyntax": [[90, 4, 1, "", "compute_loss"], [90, 4, 1, "", "configure_optimizers"], [90, 4, 1, "", "fit"], [90, 4, 1, "", "forward"], [90, 4, 1, "", "inference"], [90, 4, 1, "", "predict"], [90, 4, 1, "", "predict_as_dataframe"], [90, 3, 1, "", "prediction_labels"], [90, 4, 1, "", "shared_step"], [90, 3, 1, "", "target_labels"], [90, 4, 1, "", "train"], [90, 4, 1, "", "training_step"], [90, 4, 1, "", "validate_tasks"], [90, 4, 1, "", "validation_step"]], "graphnet.models.gnn": [[92, 0, 0, "-", "RNN_tito"], [93, 0, 0, "-", "convnet"], [94, 0, 0, "-", "dynedge"], [95, 0, 0, "-", "dynedge_jinst"], [96, 0, 0, "-", "dynedge_kaggle_tito"], [97, 0, 0, "-", "gnn"], [98, 0, 0, "-", "icemix"], [99, 0, 0, "-", "particlenet"]], "graphnet.models.gnn.RNN_tito": [[92, 1, 1, "", "RNN_TITO"]], "graphnet.models.gnn.RNN_tito.RNN_TITO": [[92, 4, 1, "", "forward"]], "graphnet.models.gnn.convnet": [[93, 1, 1, "", "ConvNet"]], "graphnet.models.gnn.convnet.ConvNet": [[93, 4, 1, "", "forward"]], "graphnet.models.gnn.dynedge": [[94, 1, 1, "", "DynEdge"]], "graphnet.models.gnn.dynedge.DynEdge": [[94, 4, 1, "", "forward"]], "graphnet.models.gnn.dynedge_jinst": [[95, 1, 1, "", "DynEdgeJINST"]], "graphnet.models.gnn.dynedge_jinst.DynEdgeJINST": [[95, 4, 1, "", "forward"]], "graphnet.models.gnn.dynedge_kaggle_tito": [[96, 1, 1, "", "DynEdgeTITO"]], "graphnet.models.gnn.dynedge_kaggle_tito.DynEdgeTITO": [[96, 4, 1, "", "forward"]], "graphnet.models.gnn.gnn": [[97, 1, 1, "", "GNN"]], "graphnet.models.gnn.gnn.GNN": [[97, 4, 1, "", "forward"], [97, 3, 1, "", "nb_inputs"], [97, 3, 1, "", "nb_outputs"]], "graphnet.models.gnn.icemix": [[98, 1, 1, "", "DeepIce"]], "graphnet.models.gnn.icemix.DeepIce": [[98, 4, 1, "", "forward"], [98, 4, 1, "", "no_weight_decay"]], "graphnet.models.gnn.particlenet": [[99, 1, 1, "", "ParticleNeT"]], "graphnet.models.gnn.particlenet.ParticleNeT": [[99, 4, 1, "", "forward"]], "graphnet.models.graphs": [[101, 0, 0, "-", "edges"], [104, 0, 0, "-", "graph_definition"], [105, 0, 0, "-", "graphs"], [106, 0, 0, "-", "nodes"], [108, 0, 0, "-", "utils"]], "graphnet.models.graphs.edges": [[102, 0, 0, "-", "edges"], [103, 0, 0, "-", "minkowski"]], "graphnet.models.graphs.edges.edges": [[102, 1, 1, "", "EdgeDefinition"], [102, 1, 1, "", "EuclideanEdges"], [102, 1, 1, "", "KNNEdges"], [102, 1, 1, "", "RadialEdges"]], "graphnet.models.graphs.edges.edges.EdgeDefinition": [[102, 4, 1, "", "forward"]], "graphnet.models.graphs.edges.minkowski": [[103, 1, 1, "", "MinkowskiKNNEdges"], [103, 5, 1, "", "compute_minkowski_distance_mat"]], "graphnet.models.graphs.graph_definition": [[104, 1, 1, "", "GraphDefinition"]], "graphnet.models.graphs.graph_definition.GraphDefinition": [[104, 4, 1, "", "forward"]], "graphnet.models.graphs.graphs": [[105, 1, 1, "", "EdgelessGraph"], [105, 1, 1, "", "KNNGraph"]], "graphnet.models.graphs.nodes": [[107, 0, 0, "-", "nodes"]], "graphnet.models.graphs.nodes.nodes": [[107, 1, 1, "", "IceMixNodes"], [107, 1, 1, "", "NodeAsDOMTimeSeries"], [107, 1, 1, "", "NodeDefinition"], [107, 1, 1, "", "NodesAsPulses"], [107, 1, 1, "", "PercentileClusters"]], "graphnet.models.graphs.nodes.nodes.NodeDefinition": [[107, 4, 1, "", "forward"], [107, 3, 1, "", "nb_outputs"], [107, 4, 1, "", "set_number_of_inputs"], [107, 4, 1, "", "set_output_feature_names"]], "graphnet.models.graphs.utils": [[108, 5, 1, "", "cluster_summarize_with_percentiles"], [108, 5, 1, "", "gather_cluster_sequence"], [108, 5, 1, "", "ice_transparency"], [108, 5, 1, "", "identify_indices"], [108, 5, 1, "", "lex_sort"]], "graphnet.models.model": [[109, 1, 1, "", "Model"]], "graphnet.models.model.Model": [[109, 4, 1, "", "extra_repr"], [109, 4, 1, "", "extra_repr_recursive"], [109, 4, 1, "", "from_config"], [109, 4, 1, "", "load"], [109, 4, 1, "", "load_state_dict"], [109, 4, 1, "", "save"], [109, 4, 1, "", "save_state_dict"], [109, 4, 1, "", "set_verbose_print_recursively"], [109, 2, 1, "", "verbose_print"]], "graphnet.models.normalizing_flow": [[110, 1, 1, "", "NormalizingFlow"]], "graphnet.models.normalizing_flow.NormalizingFlow": [[110, 4, 1, "", "forward"], [110, 4, 1, "", "shared_step"], [110, 4, 1, "", "validate_tasks"]], "graphnet.models.rnn": [[112, 0, 0, "-", "node_rnn"]], "graphnet.models.rnn.node_rnn": [[112, 1, 1, "", "Node_RNN"]], "graphnet.models.rnn.node_rnn.Node_RNN": [[112, 4, 1, "", "clean_up_data_object"], [112, 4, 1, "", "forward"]], "graphnet.models.standard_averaged_model": [[113, 1, 1, "", "StandardAveragedModel"]], "graphnet.models.standard_averaged_model.StandardAveragedModel": [[113, 4, 1, "", "load_state_dict"], [113, 4, 1, "", "on_train_end"], [113, 4, 1, "", "optimizer_step"], [113, 4, 1, "", "training_step"], [113, 4, 1, "", "validation_step"]], "graphnet.models.standard_model": [[114, 1, 1, "", "StandardModel"]], "graphnet.models.standard_model.StandardModel": [[114, 4, 1, "", "compute_loss"], [114, 4, 1, "", "forward"], [114, 4, 1, "", "shared_step"], [114, 4, 1, "", "validate_tasks"]], "graphnet.models.task": [[116, 0, 0, "-", "classification"], [117, 0, 0, "-", "reconstruction"], [118, 0, 0, "-", "task"]], "graphnet.models.task.classification": [[116, 1, 1, "", "BinaryClassificationTask"], [116, 1, 1, "", "BinaryClassificationTaskLogits"], [116, 1, 1, "", "MulticlassClassificationTask"]], "graphnet.models.task.classification.BinaryClassificationTask": [[116, 2, 1, "", "default_prediction_labels"], [116, 2, 1, "", "default_target_labels"], [116, 2, 1, "", "nb_inputs"]], "graphnet.models.task.classification.BinaryClassificationTaskLogits": [[116, 2, 1, "", "default_prediction_labels"], [116, 2, 1, "", "default_target_labels"], [116, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction": [[117, 1, 1, "", "AzimuthReconstruction"], [117, 1, 1, "", "AzimuthReconstructionWithKappa"], [117, 1, 1, "", "DirectionReconstructionWithKappa"], [117, 1, 1, "", "EnergyReconstruction"], [117, 1, 1, "", "EnergyReconstructionWithPower"], [117, 1, 1, "", "EnergyReconstructionWithUncertainty"], [117, 1, 1, "", "EnergyTCReconstruction"], [117, 1, 1, "", "InelasticityReconstruction"], [117, 1, 1, "", "PositionReconstruction"], [117, 1, 1, "", "TimeReconstruction"], [117, 1, 1, "", "VertexReconstruction"], [117, 1, 1, "", "ZenithReconstruction"], [117, 1, 1, "", "ZenithReconstructionWithKappa"]], "graphnet.models.task.reconstruction.AzimuthReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyReconstructionWithPower": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyTCReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.InelasticityReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.PositionReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.TimeReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.VertexReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.ZenithReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.task": [[118, 1, 1, "", "IdentityTask"], [118, 1, 1, "", "LearnedTask"], [118, 1, 1, "", "StandardFlowTask"], [118, 1, 1, "", "StandardLearnedTask"], [118, 1, 1, "", "Task"]], "graphnet.models.task.task.IdentityTask": [[118, 3, 1, "", "default_prediction_labels"], [118, 3, 1, "", "default_target_labels"], [118, 3, 1, "", "nb_inputs"]], "graphnet.models.task.task.LearnedTask": [[118, 4, 1, "", "compute_loss"], [118, 4, 1, "", "forward"], [118, 3, 1, "", "nb_inputs"]], "graphnet.models.task.task.StandardFlowTask": [[118, 3, 1, "", "default_prediction_labels"], [118, 4, 1, "", "forward"], [118, 4, 1, "", "nb_inputs"]], "graphnet.models.task.task.StandardLearnedTask": [[118, 4, 1, "", "compute_loss"], [118, 3, 1, "", "nb_inputs"]], "graphnet.models.task.task.Task": [[118, 3, 1, "", "default_prediction_labels"], [118, 3, 1, "", "default_target_labels"], [118, 4, 1, "", "inference"], [118, 3, 1, "", "nb_inputs"], [118, 4, 1, "", "train_eval"]], "graphnet.models.transformer": [[120, 0, 0, "-", "iseecube"]], "graphnet.models.transformer.iseecube": [[120, 1, 1, "", "ISeeCube"]], "graphnet.models.transformer.iseecube.ISeeCube": [[120, 4, 1, "", "forward"]], "graphnet.models.utils": [[121, 5, 1, "", "array_to_sequence"], [121, 5, 1, "", "calculate_distance_matrix"], [121, 5, 1, "", "calculate_xyzt_homophily"], [121, 5, 1, "", "get_fields"], [121, 5, 1, "", "knn_graph_batch"]], "graphnet.training": [[123, 0, 0, "-", "callbacks"], [124, 0, 0, "-", "labels"], [125, 0, 0, "-", "loss_functions"], [126, 0, 0, "-", "utils"], [127, 0, 0, "-", "weight_fitting"]], "graphnet.training.callbacks": [[123, 1, 1, "", "GraphnetEarlyStopping"], [123, 1, 1, "", "PiecewiseLinearLR"], [123, 1, 1, "", "ProgressBar"]], "graphnet.training.callbacks.GraphnetEarlyStopping": [[123, 4, 1, "", "on_fit_end"], [123, 4, 1, "", "on_train_epoch_end"], [123, 4, 1, "", "on_validation_end"], [123, 4, 1, "", "setup"]], "graphnet.training.callbacks.PiecewiseLinearLR": [[123, 4, 1, "", "get_lr"]], "graphnet.training.callbacks.ProgressBar": [[123, 4, 1, "", "get_metrics"], [123, 4, 1, "", "init_predict_tqdm"], [123, 4, 1, "", "init_test_tqdm"], [123, 4, 1, "", "init_train_tqdm"], [123, 4, 1, "", "init_validation_tqdm"], [123, 4, 1, "", "on_train_epoch_end"], [123, 4, 1, "", "on_train_epoch_start"]], "graphnet.training.labels": [[124, 1, 1, "", "Direction"], [124, 1, 1, "", "Label"], [124, 1, 1, "", "Track"]], "graphnet.training.labels.Label": [[124, 3, 1, "", "key"]], "graphnet.training.loss_functions": [[125, 1, 1, "", "BinaryCrossEntropyLoss"], [125, 1, 1, "", "CrossEntropyLoss"], [125, 1, 1, "", "EnsembleLoss"], [125, 1, 1, "", "EuclideanDistanceLoss"], [125, 1, 1, "", "LogCMK"], [125, 1, 1, "", "LogCoshLoss"], [125, 1, 1, "", "LossFunction"], [125, 1, 1, "", "MSELoss"], [125, 1, 1, "", "RMSELoss"], [125, 1, 1, "", "RMSEVonMisesFisher3DLoss"], [125, 1, 1, "", "VonMisesFisher2DLoss"], [125, 1, 1, "", "VonMisesFisher3DLoss"], [125, 1, 1, "", "VonMisesFisherLoss"]], "graphnet.training.loss_functions.LogCMK": [[125, 4, 1, "", "backward"], [125, 4, 1, "", "forward"]], "graphnet.training.loss_functions.LossFunction": [[125, 4, 1, "", "forward"]], "graphnet.training.loss_functions.VonMisesFisherLoss": [[125, 4, 1, "", "log_cmk"], [125, 4, 1, "", "log_cmk_approx"], [125, 4, 1, "", "log_cmk_exact"]], "graphnet.training.utils": [[126, 5, 1, "", "collate_fn"], [126, 1, 1, "", "collator_sequence_buckleting"], [126, 5, 1, "", "get_predictions"], [126, 5, 1, "", "make_dataloader"], [126, 5, 1, "", "make_train_validation_dataloader"], [126, 5, 1, "", "save_results"], [126, 5, 1, "", "save_selection"]], "graphnet.training.weight_fitting": [[127, 1, 1, "", "BjoernLow"], [127, 1, 1, "", "Uniform"], [127, 1, 1, "", "WeightFitter"]], "graphnet.training.weight_fitting.WeightFitter": [[127, 4, 1, "", "fit"]], "graphnet.utilities": [[129, 0, 0, "-", "argparse"], [130, 0, 0, "-", "config"], [137, 0, 0, "-", "decorators"], [138, 0, 0, "-", "deprecation_tools"], [139, 0, 0, "-", "filesys"], [140, 0, 0, "-", "imports"], [141, 0, 0, "-", "logging"], [142, 0, 0, "-", "maths"]], "graphnet.utilities.argparse": [[129, 1, 1, "", "ArgumentParser"], [129, 1, 1, "", "Options"]], "graphnet.utilities.argparse.ArgumentParser": [[129, 2, 1, "", "standard_arguments"], [129, 4, 1, "", "with_standard_arguments"]], "graphnet.utilities.argparse.Options": [[129, 4, 1, "", "contains"], [129, 4, 1, "", "pop_default"]], "graphnet.utilities.config": [[131, 0, 0, "-", "base_config"], [132, 0, 0, "-", "configurable"], [133, 0, 0, "-", "dataset_config"], [134, 0, 0, "-", "model_config"], [135, 0, 0, "-", "parsing"], [136, 0, 0, "-", "training_config"]], "graphnet.utilities.config.base_config": [[131, 1, 1, "", "BaseConfig"], [131, 5, 1, "", "get_all_argument_values"]], "graphnet.utilities.config.base_config.BaseConfig": [[131, 4, 1, "", "as_dict"], [131, 4, 1, "", "dump"], [131, 4, 1, "", "load"], [131, 2, 1, "", "model_computed_fields"], [131, 2, 1, "", "model_config"], [131, 2, 1, "", "model_fields"]], "graphnet.utilities.config.configurable": [[132, 1, 1, "", "Configurable"]], "graphnet.utilities.config.configurable.Configurable": [[132, 3, 1, "", "config"], [132, 4, 1, "", "from_config"], [132, 4, 1, "", "save_config"]], "graphnet.utilities.config.dataset_config": [[133, 1, 1, "", "DatasetConfig"], [133, 1, 1, "", "DatasetConfigSaverABCMeta"], [133, 1, 1, "", "DatasetConfigSaverMeta"], [133, 5, 1, "", "save_dataset_config"]], "graphnet.utilities.config.dataset_config.DatasetConfig": [[133, 4, 1, "", "as_dict"], [133, 2, 1, "", "features"], [133, 2, 1, "", "graph_definition"], [133, 2, 1, "", "index_column"], [133, 2, 1, "", "labels"], [133, 2, 1, "", "loss_weight_column"], [133, 2, 1, "", "loss_weight_default_value"], [133, 2, 1, "", "loss_weight_table"], [133, 2, 1, "", "model_computed_fields"], [133, 2, 1, "", "model_config"], [133, 2, 1, "", "model_fields"], [133, 2, 1, "", "node_truth"], [133, 2, 1, "", "node_truth_table"], [133, 2, 1, "", "path"], [133, 2, 1, "", "pulsemaps"], [133, 2, 1, "", "seed"], [133, 2, 1, "", "selection"], [133, 2, 1, "", "string_selection"], [133, 2, 1, "", "truth"], [133, 2, 1, "", "truth_table"]], "graphnet.utilities.config.model_config": [[134, 1, 1, "", "ModelConfig"], [134, 1, 1, "", "ModelConfigSaverABC"], [134, 1, 1, "", "ModelConfigSaverMeta"], [134, 5, 1, "", "save_model_config"]], "graphnet.utilities.config.model_config.ModelConfig": [[134, 2, 1, "", "arguments"], [134, 4, 1, "", "as_dict"], [134, 2, 1, "", "class_name"], [134, 2, 1, "", "model_computed_fields"], [134, 2, 1, "", "model_config"], [134, 2, 1, "", "model_fields"]], "graphnet.utilities.config.parsing": [[135, 5, 1, "", "get_all_grapnet_classes"], [135, 5, 1, "", "get_graphnet_classes"], [135, 5, 1, "", "is_graphnet_class"], [135, 5, 1, "", "is_graphnet_module"], [135, 5, 1, "", "list_all_submodules"], [135, 5, 1, "", "traverse_and_apply"]], "graphnet.utilities.config.training_config": [[136, 1, 1, "", "TrainingConfig"]], "graphnet.utilities.config.training_config.TrainingConfig": [[136, 2, 1, "", "dataloader"], [136, 2, 1, "", "early_stopping_patience"], [136, 2, 1, "", "fit"], [136, 2, 1, "", "model_computed_fields"], [136, 2, 1, "", "model_config"], [136, 2, 1, "", "model_fields"], [136, 2, 1, "", "target"]], "graphnet.utilities.deprecation_tools": [[138, 5, 1, "", "rename_state_dict_entries"]], "graphnet.utilities.filesys": [[139, 5, 1, "", "find_i3_files"], [139, 5, 1, "", "has_extension"], [139, 5, 1, "", "is_gcd_file"], [139, 5, 1, "", "is_i3_file"]], "graphnet.utilities.imports": [[140, 5, 1, "", "has_icecube_package"], [140, 5, 1, "", "has_jammy_flows_package"], [140, 5, 1, "", "has_torch_package"], [140, 5, 1, "", "requires_icecube"]], "graphnet.utilities.logging": [[141, 1, 1, "", "Logger"], [141, 1, 1, "", "RepeatFilter"]], "graphnet.utilities.logging.Logger": [[141, 4, 1, "", "critical"], [141, 4, 1, "", "debug"], [141, 4, 1, "", "error"], [141, 3, 1, "", "file_handlers"], [141, 3, 1, "", "handlers"], [141, 4, 1, "", "info"], [141, 4, 1, "", "setLevel"], [141, 3, 1, "", "stream_handlers"], [141, 4, 1, "", "warning"], [141, 4, 1, "", "warning_once"]], "graphnet.utilities.logging.RepeatFilter": [[141, 4, 1, "", "filter"], [141, 2, 1, "", "nb_repeats_allowed"]], "graphnet.utilities.maths": [[142, 5, 1, "", "eps_like"]]}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "attribute", "Python attribute"], "3": ["py", "property", "Python property"], "4": ["py", "method", "Python method"], "5": ["py", "function", "Python function"], "6": ["py", "exception", "Python exception"]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:attribute", "3": "py:property", "4": "py:method", "5": "py:function", "6": "py:exception"}, "terms": {"": [0, 7, 8, 9, 11, 13, 16, 34, 45, 47, 49, 52, 53, 55, 62, 64, 69, 82, 86, 90, 93, 94, 99, 104, 110, 118, 121, 123, 127, 129, 133, 134, 141, 142, 145, 146, 147, 148, 150, 151, 152], "0": [9, 11, 13, 16, 45, 47, 50, 55, 60, 74, 80, 83, 84, 92, 93, 94, 96, 99, 102, 103, 105, 108, 112, 118, 121, 124, 125, 126, 133, 146, 147, 149, 150, 152], "000": 146, "001": [147, 152], "01": [147, 152], "0221": 147, "02_data": 147, "03042": 95, "03762": 82, "04616": 125, "04_ensemble_dataset": 147, "05": 125, "06": 144, "06166": 102, "08570": 99, "0e04": 150, "0e4": 150, "1": [0, 7, 9, 11, 13, 14, 19, 34, 45, 47, 55, 60, 63, 66, 69, 80, 83, 84, 92, 94, 96, 98, 99, 102, 103, 105, 108, 112, 116, 117, 118, 121, 123, 124, 125, 126, 127, 133, 145, 146, 147, 148, 149, 151, 152], "10": [9, 66, 87, 88, 89, 107, 108, 129, 146, 147, 150, 152], "100": 146, "1000": [118, 146, 147], "10000": [11, 13, 16, 60, 82], "1088": 147, "11": [147, 149], "12": [60, 98, 120, 133, 146, 147], "120": 147, "128": [82, 93, 94, 96, 99, 129, 146, 147, 152], "13": 60, "14": [60, 133, 146, 147], "1536": 120, "15674": 82, "16": [14, 60, 82, 92, 99, 120, 133, 146, 147, 152], "17": [14, 147], "1706": 82, "1748": 147, "1809": 102, "1812": 125, "1902": 99, "192": 98, "196": 120, "1e6": 118, "2": [9, 34, 45, 55, 83, 84, 92, 94, 96, 99, 102, 105, 108, 112, 117, 121, 125, 133, 146, 147, 149, 152], "20": [11, 13, 16, 60, 141, 147, 149, 150, 152], "200": [146, 150], "200000": 63, "2018": 144, "2019": 125, "2020": [0, 148, 151], "2023": 14, "21": [144, 146, 147], "2209": 95, "2310": 82, "256": [94, 96, 99, 120], "26": 146, "2d": 125, "2nd": [14, 82, 98], "3": [84, 92, 93, 96, 103, 108, 112, 117, 120, 121, 125, 144, 147, 149, 150], "30": 150, "300": [146, 150], "32": [14, 82, 98, 120], "336": [94, 96], "384": [82, 98, 120], "39": [0, 148, 151], "3d": [117, 125], "4": [14, 83, 95, 98, 117, 147, 150, 152], "40": 150, "400": 64, "42": 9, "5": [11, 13, 16, 60, 92, 112, 125, 129, 145, 146, 147, 149, 150, 152], "50": [107, 108, 129, 150], "500": [108, 150], "50000": [60, 133, 146, 147], "5001": 146, "59": 149, "6": [82, 84, 98, 120], "64": [92, 99], "7": [74, 84], "700": 125, "768": 107, "8": [83, 84, 92, 94, 96, 105, 112, 125, 126, 144, 146, 147, 149, 152], "80": [147, 152], "86": [22, 87], "890778": [0, 148, 151], "9": 9, "90": [107, 108], "A": [5, 7, 9, 11, 14, 36, 49, 50, 51, 52, 53, 59, 64, 66, 67, 69, 70, 74, 84, 90, 104, 105, 108, 109, 110, 114, 116, 118, 121, 125, 127, 131, 133, 134, 136, 145, 146, 147, 150, 152], "AND": [14, 125], "AS": [14, 125], "As": [94, 99, 152], "BE": [14, 125], "BUT": [14, 125], "But": 152, "By": [0, 45, 47, 50, 55, 118, 146, 147, 148, 151, 152], "FOR": [14, 125], "For": [14, 37, 107, 123, 146, 147, 152], "IN": [14, 125], "If": [5, 11, 13, 14, 21, 23, 36, 64, 66, 67, 82, 83, 94, 98, 99, 104, 107, 108, 109, 118, 123, 125, 127, 144, 145, 147, 152], "In": [45, 47, 49, 50, 55, 62, 133, 134, 145, 147, 149], "It": [1, 5, 34, 59, 74, 82, 108, 116, 118, 144, 146, 147, 152], "NO": [14, 125], "NOT": [14, 59, 125, 147], "No": [0, 147, 148, 151], "OF": [14, 125], "ONE": 66, "OR": [14, 125], "On": 5, "One": 147, "Or": 146, "Such": 59, "THE": [14, 125], "TO": [14, 125], "That": [11, 13, 16, 94, 99, 117, 124, 147, 152], "The": [0, 7, 9, 11, 13, 14, 16, 18, 34, 37, 45, 47, 55, 59, 62, 63, 64, 69, 70, 74, 76, 80, 82, 83, 84, 92, 94, 96, 98, 99, 102, 104, 108, 110, 112, 116, 117, 118, 120, 121, 123, 124, 125, 138, 145, 146, 148, 150, 151], "Then": [5, 144], "There": [147, 152], "These": [0, 49, 62, 64, 104, 144, 146, 147, 148, 150, 151, 152], "To": [146, 147, 149, 150, 152], "WITH": [14, 125], "Will": [5, 66, 67, 69, 74, 76, 102, 145], "With": [147, 150, 152], "_": 147, "__": [34, 37, 147], "_____________________": [14, 125], "__call__": [19, 21, 49, 70, 145, 146, 147, 150], "__fields__": [131, 133, 134, 136], "__init__": [133, 134, 145, 146, 147, 152], "_accepted_extractor": [145, 150], "_accepted_file_extens": [145, 150], "_and_": [94, 99], "_column_nam": 145, "_construct_edg": 102, "_definition_": 147, "_extractor": [145, 150], "_extractor_nam": [145, 150], "_file_extens": 145, "_file_hash": 5, "_fit_weight": 127, "_forward": 152, "_indic": [11, 13], "_layer": 152, "_lrschedul": 123, "_may_": [11, 13], "_merge_datafram": 145, "_pred": 118, "_save_fil": 145, "_sensor_tim": 150, "_sensor_xyz": 150, "_tabl": 145, "_task": [90, 110, 114], "_verify_column": 145, "_x_": 147, "a__b": 34, "ab": [60, 99, 125, 133, 146, 147], "abc": [7, 11, 19, 49, 62, 69, 109, 124, 127, 132, 133, 134], "abcmeta": [133, 134], "abil": 146, "abl": [34, 107, 110, 145, 147, 149, 150, 152], "about": [109, 131, 133, 134, 136, 146, 147, 150], "abov": [14, 125, 127, 146, 147, 150, 152], "absopt": 107, "absorpt": 108, "abstract": [1, 5, 11, 62, 86, 97, 104, 118, 132, 147], "abstractmethod": 146, "acceler": 1, "accept": [49, 144, 152], "accepted_extractor": [49, 145], "accepted_file_extens": [49, 145], "access": [124, 146], "accompani": [45, 47, 50, 55, 147], "accord": [80, 84, 102, 104, 105, 108, 125], "achiev": 149, "achitectur": 152, "across": [1, 2, 11, 13, 16, 37, 56, 69, 84, 90, 114, 125, 128, 129, 130, 141, 150], "act": [118, 125, 147, 152], "action": [14, 125], "activ": [83, 90, 92, 94, 99, 107, 112, 118, 144], "activation_lay": [94, 99], "actual": [147, 152], "ad": [7, 11, 13, 16, 22, 45, 47, 55, 82, 94, 98, 107, 108], "adam": [110, 147, 152], "adapt": [147, 152], "add": [11, 83, 94, 99, 129, 138, 144, 147, 150], "add_batchnorm_lay": 99, "add_count": [107, 108], "add_global_variables_after_pool": [94, 147, 152], "add_ice_properti": 107, "add_inactive_sensor": 104, "add_label": [11, 146, 147], "add_norm_lay": 94, "add_to_databas": 127, "addit": [49, 62, 80, 83, 90, 125, 127, 145, 147, 152], "additional_attribut": [90, 126, 147, 152], "address": 152, "adher": [144, 152], "adjac": 86, "adjust": 152, "advanc": [1, 84], "after": [9, 83, 92, 94, 96, 99, 123, 129, 133, 146, 147, 152], "again": [147, 152], "against": 5, "aggr": 83, "aggreg": [83, 84], "agnost": [0, 148, 151, 152], "agreement": [0, 144, 148, 151], "ai": 147, "aim": [0, 1, 144, 147, 148, 151], "algorithm": 26, "all": [1, 5, 11, 13, 14, 16, 18, 19, 21, 23, 36, 59, 64, 66, 67, 74, 82, 83, 84, 86, 94, 97, 99, 103, 104, 109, 118, 125, 127, 131, 132, 133, 134, 135, 136, 141, 144, 145, 146, 147, 150, 152], "allow": [0, 5, 39, 68, 79, 84, 123, 131, 136, 146, 147, 148, 151, 152], "along": [108, 147, 152], "alongsid": [147, 152], "alreadi": 59, "also": [7, 11, 13, 16, 60, 92, 133, 145, 146, 147, 150, 152], "alter": 104, "altern": [94, 125, 144], "alwai": 126, "amount": 92, "an": [0, 14, 19, 37, 45, 47, 50, 55, 60, 104, 105, 112, 113, 125, 139, 141, 144, 145, 147, 148, 149, 150, 151, 152], "anaconda": 149, "analys": [68, 147], "analysi": 69, "angl": [117, 124, 147, 152], "ani": [6, 7, 8, 9, 11, 13, 14, 16, 34, 35, 36, 37, 49, 51, 52, 53, 62, 64, 74, 80, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 125, 127, 129, 131, 132, 133, 134, 135, 136, 141, 146, 147, 152], "annot": [133, 134, 136], "anoth": [14, 133, 134, 146, 147], "anyth": 144, "api": [143, 145, 147], "appear": [69, 146, 147], "append": 104, "appli": [7, 11, 13, 16, 45, 47, 48, 49, 55, 69, 83, 84, 90, 92, 93, 94, 95, 96, 97, 98, 99, 108, 110, 112, 114, 116, 118, 120, 125, 135, 145, 146, 147], "applic": [34, 146, 147, 152], "appropri": [59, 118, 147], "approx": 125, "approxim": 64, "ar": [0, 1, 4, 5, 11, 13, 14, 16, 21, 23, 36, 37, 49, 60, 62, 63, 64, 69, 74, 83, 84, 92, 94, 96, 99, 100, 101, 102, 104, 105, 106, 107, 108, 112, 116, 125, 127, 133, 134, 144, 145, 146, 147, 148, 150, 151, 152], "arbitrari": [0, 148, 151], "arca": 89, "arca115": [85, 89], "architectur": [1, 93, 94, 95, 96, 99, 110, 112, 120, 147, 152], "archiv": 126, "area": 1, "arg": [11, 13, 16, 18, 36, 80, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 125, 129, 131, 141, 145, 150], "argpars": [1, 128], "argument": [5, 9, 14, 63, 66, 67, 98, 110, 123, 127, 129, 131, 133, 134, 136, 146, 147, 150, 152], "argumentpars": [128, 129], "aris": [14, 125], "arrai": [19, 31, 34, 107, 108, 121, 145, 146, 147, 150], "array_to_sequ": [79, 121], "arriv": 146, "art": [0, 148, 151], "articl": 147, "artifact": [147, 152], "arxiv": [82, 99, 102, 125], "as_dict": [131, 133, 134, 147, 152], "assert": [145, 146], "assertionerror": 145, "assign": [7, 11, 13, 16, 80, 84, 105, 144, 145], "associ": [14, 74, 76, 104, 108, 117, 125, 145, 146, 147, 150, 152], "assort": 142, "assum": [5, 74, 82, 86, 104, 108, 118, 121], "atmospher": 146, "attach": 59, "attach_index": [56, 59], "attempt": [21, 147], "attent": [82, 83, 98, 120], "attention_rel": [81, 83], "attn_drop": 83, "attn_head_dim": 83, "attn_mask": 83, "attribut": [5, 11, 13, 16, 80, 118, 146, 147, 152], "attributecoarsen": [79, 80], "author": [14, 93, 95, 125], "auto": 118, "autom": 144, "automat": [23, 63, 82, 104, 125, 144, 145, 147, 150], "automatic_log_bin": 127, "auxiliari": [4, 82, 147, 152], "avail": [5, 7, 23, 66, 67, 116, 117, 118, 140, 145, 146, 147, 149, 150, 152], "available_backend": 5, "available_t": 145, "averag": [84, 113, 125], "avg": 80, "avg_pool": 80, "avg_pool_x": 80, "avoid": [13, 141, 144], "awai": [1, 147], "azimiuth": 124, "azimuth": [4, 117, 124], "azimuth_kappa": 117, "azimuth_kei": 124, "azimuth_pr": 117, "azimuthreconstruct": [115, 117], "azimuthreconstructionwithkappa": [115, 117], "b": [34, 80, 84, 121, 147, 150, 152], "backbon": [110, 147], "backend": [5, 12, 15, 61, 63, 66, 67, 150], "backward": [108, 125], "baikal": 66, "baikalgvd8": [85, 89], "baikalgvdsmal": [65, 66], "bar": 123, "base": [0, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 36, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 60, 62, 63, 64, 66, 67, 69, 70, 74, 76, 78, 80, 82, 83, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 136, 140, 141, 145, 146, 147, 148, 151, 152], "base_config": [128, 130], "baseclass": 69, "baseconfig": [130, 131, 132, 133, 134, 136], "basemodel": [131, 133, 134], "basi": 152, "basic": [1, 147], "batch": [0, 8, 13, 14, 63, 80, 83, 84, 90, 99, 110, 112, 114, 121, 126, 129, 146, 148, 151], "batch_idx": [90, 110, 113, 114, 121], "batch_siz": [8, 9, 14, 121, 126, 146, 147, 152], "batch_split": 126, "batchsampl": 14, "becaus": [58, 147, 152], "been": [5, 74, 125, 144, 152], "befor": [11, 13, 94, 103, 112, 118, 123], "behavior": 145, "behaviour": 123, "behind": [147, 152], "being": [21, 74, 82, 116, 118, 146, 147, 152], "beitv2": 83, "belong": 121, "below": [5, 60, 107, 127, 144, 145, 147, 148, 150, 151, 152], "benchmark": 5, "besid": 146, "bessel": 125, "best": [0, 123, 144, 148, 151], "better": 144, "between": [39, 66, 82, 90, 100, 101, 102, 103, 106, 110, 114, 118, 121, 123, 125, 127, 133, 134, 147, 152], "bia": [83, 120], "bias": [147, 152], "big": [147, 152], "biject": 145, "bin": [14, 127], "binari": [114, 116, 125, 152], "binaryclassificationtask": [115, 116, 147, 152], "binaryclassificationtasklogit": [115, 116], "binarycrossentropyloss": [122, 125], "bjoernlow": [122, 127], "black": 144, "blob": [14, 125, 147], "block": [0, 1, 81, 83, 99, 147, 148, 151], "block_rel": [81, 83], "boilerpl": 152, "bool": [8, 14, 35, 36, 37, 59, 60, 62, 74, 82, 83, 90, 92, 94, 96, 98, 99, 104, 107, 108, 109, 114, 120, 123, 125, 126, 127, 129, 135, 138, 139, 140, 141], "boost": 37, "border": 31, "both": [0, 23, 110, 114, 118, 147, 148, 150, 151, 152], "bottleneck": 14, "boundari": 31, "box": [145, 147, 152], "branch": 144, "break_cyclic_recurs": [33, 37], "broken": [45, 47, 50, 55], "bucket": [14, 120, 126], "bucket_width": 14, "bug": [144, 147], "build": [0, 1, 79, 86, 102, 103, 107, 108, 109, 110, 131, 133, 134, 147, 148, 151, 152], "built": [0, 79, 104, 110, 146, 147, 148, 150, 151, 152], "c": [14, 21, 34, 84, 103, 125, 147], "c_": 125, "cach": 13, "cache_s": 13, "calcul": [74, 82, 90, 102, 105, 107, 110, 114, 121, 124, 125, 146, 147, 152], "calculate_distance_matrix": [79, 121], "calculate_xyzt_homophili": [79, 121], "calibr": [35, 37], "call": [7, 14, 23, 37, 82, 84, 118, 123, 127, 141, 145, 147, 150, 152], "callabl": [8, 11, 37, 83, 84, 86, 87, 88, 89, 104, 113, 118, 126, 127, 131, 133, 134, 135, 140, 150], "callback": [1, 90, 122, 147, 152], "can": [0, 1, 5, 9, 11, 13, 14, 16, 19, 23, 26, 74, 82, 84, 104, 110, 127, 129, 131, 133, 134, 144, 145, 146, 147, 148, 150, 151, 152], "cannot": [37, 112, 127, 131, 136], "cap": 127, "capabl": [0, 114, 148, 151], "captur": [147, 152], "care": 146, "carlo": 35, "cascad": 117, "case": [11, 13, 16, 23, 45, 47, 50, 55, 74, 84, 108, 118, 145, 146, 147, 149, 152], "cast": [23, 37], "cast_object_to_pure_python": [33, 37], "cast_pulse_series_to_pure_python": [33, 37], "caus": 147, "caveat": [147, 152], "cc": 124, "cd": 149, "center": 102, "centr": 102, "central": [147, 149], "certain": 147, "cfg": 11, "cframe": 21, "chain": [0, 1, 68, 79, 90, 110, 114, 125, 148, 149, 151], "chang": [125, 144, 147, 152], "charg": [4, 14, 82, 92, 107, 108, 112, 125, 146, 147, 152], "charge_column": 107, "check": [8, 35, 36, 37, 49, 59, 107, 129, 139, 140, 144, 150], "checkpoint": 147, "checkpointing_bas": 147, "chenli2049": 120, "cherenkov": [107, 108, 147, 150, 152], "choic": [146, 147, 152], "choos": [147, 152], "chosen": [102, 108, 141, 146], "chunk": [13, 14, 145], "chunk_siz": 13, "chunks_per_seg": 14, "citat": 5, "cite": 5, "ckpt": [147, 152], "ckpt_path": 90, "claim": [14, 125], "clash": 141, "class": [4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 60, 62, 63, 64, 66, 67, 69, 70, 74, 76, 80, 82, 83, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 141, 144, 145, 146], "class_nam": [11, 36, 49, 51, 52, 53, 62, 134, 141, 146, 147, 152], "classif": [1, 79, 114, 115, 118, 125, 147, 152], "classifi": [116, 146, 147, 152], "classmethod": [8, 11, 109, 125, 131, 147, 152], "classvar": [131, 133, 134, 136], "clean": [74, 144, 149], "clean_up_data_object": 112, "cleaning_modul": [68, 73], "cleanup": 9, "clear": [141, 146], "cli": 129, "clone": 149, "close": 9, "closest": 123, "cloud": [147, 152], "cls_tocken": 98, "cluster": [80, 83, 84, 92, 94, 96, 99, 107, 108, 112], "cluster_column": 108, "cluster_index": 84, "cluster_indic": 108, "cluster_on": [107, 108], "cluster_summarize_with_percentil": [100, 108], "cnn": [147, 152], "coarsen": [1, 79, 84], "code": [0, 31, 45, 55, 59, 104, 133, 134, 145, 146, 147, 148, 150, 151, 152], "coincid": 107, "collabor": [1, 147, 152], "collate_fn": [3, 8, 122, 126], "collator_sequence_bucklet": [122, 126], "collect": [11, 20, 33, 125, 142, 147, 152], "column": [7, 11, 13, 16, 19, 41, 43, 45, 47, 55, 59, 63, 64, 70, 76, 78, 82, 86, 90, 92, 102, 104, 105, 107, 108, 112, 116, 117, 118, 121, 125, 127, 145, 146, 147, 150, 152], "column_nam": [41, 145], "column_offset": 108, "columnmissingexcept": [11, 13, 77, 78], "com": [14, 98, 110, 120, 125, 147, 149], "combin": [18, 34, 47, 92, 114, 125, 133, 152], "combine_extractor": [3, 17], "combinedextractor": [17, 18], "come": [5, 90, 118, 145, 146, 147, 152], "command": 129, "comment": 5, "commit": 144, "common": [0, 1, 125, 133, 134, 137, 140, 146, 147, 148, 151], "compar": [147, 152], "comparison": [26, 125], "compat": [49, 60, 90, 110, 114, 118, 145, 146, 147, 152], "competit": [82, 83, 87, 96, 98], "complet": [0, 14, 79, 147, 148, 149, 151, 152], "complex": [0, 79, 147, 148, 151], "compon": [0, 1, 79, 82, 83, 84, 90, 109, 110, 114, 147, 148, 151, 152], "compos": [147, 152], "composit": 141, "comprehens": 147, "compress": [5, 146], "compris": [0, 148, 151], "comput": [70, 83, 90, 103, 114, 118, 121, 125, 131, 133, 134, 136, 146, 147], "compute_loss": [90, 114, 118], "compute_minkowski_distance_mat": [101, 103], "computedfieldinfo": [131, 133, 134, 136], "con": [147, 152], "concatdataset": 11, "concaten": [11, 34, 94], "concept": 144, "conceptu": [145, 147], "concret": 147, "condit": [14, 110, 118, 125], "condition_on": 110, "confid": 147, "config": [1, 8, 60, 123, 125, 128, 129, 131, 132, 133, 134, 135, 136, 146, 147, 152], "config_dir": [147, 152], "configdict": [131, 133, 134, 136], "configur": [0, 1, 9, 11, 46, 47, 70, 79, 90, 109, 128, 130, 131, 133, 134, 136, 141, 145, 147, 148, 151, 152], "configure_optim": 90, "conflict": 147, "conform": [131, 133, 134, 136], "conjunct": [19, 118], "conn": 147, "connect": [0, 9, 14, 102, 103, 104, 107, 125, 146, 147, 148, 151], "consequ": 109, "consid": [74, 92, 146, 147, 150], "consist": [82, 129, 141, 144, 147, 152], "consortium": [0, 148, 151], "constant": [1, 3, 118, 143, 146, 147, 152], "constitut": [63, 146], "constraint": [90, 147], "construct": [5, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 36, 39, 41, 43, 49, 51, 52, 53, 60, 62, 63, 64, 66, 67, 70, 80, 81, 82, 83, 86, 87, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 106, 107, 108, 109, 112, 113, 114, 116, 117, 118, 120, 123, 124, 125, 126, 127, 129, 132, 133, 134, 141, 145, 146, 147, 152], "constructor": [145, 146, 147], "consult": 152, "consum": 147, "consumpt": 146, "conta": 14, "contain": [0, 5, 6, 7, 11, 13, 14, 16, 17, 18, 21, 34, 35, 38, 39, 40, 43, 45, 47, 49, 50, 51, 55, 59, 62, 63, 64, 65, 66, 69, 70, 74, 76, 78, 90, 94, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110, 114, 118, 121, 125, 127, 129, 145, 146, 147, 148, 150, 151, 152], "containeris": 1, "content": [145, 152], "context": 67, "continu": [0, 125, 147, 148, 151], "contract": [14, 125], "contribut": [0, 125, 147, 148, 151], "contributor": 144, "conveni": [1, 144, 147, 152], "convent": [45, 47, 50, 55], "convers": [7, 38, 39, 43, 45, 55, 107, 146, 147, 150], "convert": [0, 1, 3, 5, 7, 13, 21, 34, 36, 45, 46, 47, 55, 57, 63, 65, 121, 145, 146, 147, 148, 149, 150, 151], "converteddataset": 5, "convnet": [79, 91, 147], "convolut": [83, 93, 94, 95, 96, 99], "coo": 146, "coordin": [31, 86, 103, 107, 108, 121, 147], "copi": [14, 125, 146], "copyright": [14, 125], "core": 97, "correct": 125, "correpond": 58, "correspond": [11, 13, 16, 34, 37, 58, 94, 99, 104, 108, 127, 131, 133, 134, 136, 139, 146, 147, 150, 152], "cosh": 125, "could": [144, 147, 152], "counterpart": 146, "cover": 60, "cpu": [7, 14, 45, 47, 55, 70], "creat": [5, 9, 14, 59, 104, 105, 107, 131, 132, 136, 144, 146, 152], "create_t": [56, 59], "create_table_and_save_to_sql": [56, 59], "creator": 5, "critic": [141, 147, 150], "cross": 125, "crossentropyloss": [122, 125], "csv": [126, 133, 146, 147, 150, 152], "ctx": 125, "cuda": 149, "curat": 5, "curated_datamodul": [1, 3], "curateddataset": [3, 5, 66, 67], "curi": [0, 148, 151], "current": [60, 112, 123, 144, 147], "curv": 127, "custom": [11, 49, 77, 104, 123, 152], "custom_label_funct": 104, "customdomcoarsen": [79, 80], "customis": 123, "cut": 126, "d": [34, 103, 104, 107, 121, 144, 150], "damag": [14, 125], "data": [0, 1, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 41, 42, 43, 45, 47, 48, 49, 50, 51, 52, 53, 55, 56, 58, 59, 60, 61, 62, 63, 64, 66, 67, 80, 82, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 104, 105, 107, 110, 112, 113, 114, 118, 120, 121, 124, 126, 129, 131, 133, 136, 140, 143, 146, 147, 148, 151, 152], "data_path": 104, "data_sourc": 14, "databas": [5, 16, 59, 64, 127, 146, 147], "database_exist": [56, 59], "database_indic": 126, "database_nam": 64, "database_path": [59, 127], "database_table_exist": [56, 59], "dataclass": [1, 3, 35], "dataconfig": [133, 146], "dataconvert": [1, 3, 46, 62, 63, 64, 147, 150], "dataformat": [61, 64], "datafram": [59, 60, 62, 86, 90, 126, 127, 145, 147, 150, 152], "dataload": [1, 3, 5, 9, 13, 66, 67, 90, 104, 126, 136, 146, 147, 152], "datamodul": [1, 3, 5], "datarepresent": 110, "dataset": [1, 3, 5, 8, 9, 12, 13, 14, 15, 16, 25, 60, 63, 66, 67, 78, 92, 104, 112, 129, 133, 143, 150, 152], "dataset_1": [146, 147], "dataset_2": [146, 147], "dataset_3": [146, 147], "dataset_arg": 9, "dataset_config": [128, 130, 147, 152], "dataset_config_path": [147, 152], "dataset_dir": 5, "dataset_refer": 9, "datasetconfig": [8, 11, 60, 130, 133, 146, 152], "datasetconfigsav": 133, "datasetconfigsaverabcmeta": [130, 133], "datasetconfigsavermeta": [130, 133], "db": [64, 126, 127, 146, 147], "db_count_norm": 127, "ddp": [147, 152], "de": 34, "deactiv": [90, 118], "deal": [14, 125], "debug": [141, 147], "decai": 98, "decor": [1, 128, 140], "dedic": 144, "deem": 37, "deep": [0, 5, 62, 64, 83, 96, 98, 145, 147, 148, 149, 150, 151, 152], "deepcopi": 138, "deepcor": [4, 22, 87], "deepic": [91, 98], "def": [145, 146, 147, 150, 152], "default": [5, 7, 9, 11, 13, 14, 16, 21, 23, 31, 34, 43, 45, 47, 50, 55, 59, 63, 64, 66, 67, 69, 70, 74, 76, 82, 83, 84, 92, 93, 94, 95, 96, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 118, 120, 121, 123, 124, 125, 127, 129, 131, 133, 139, 146, 147], "default_prediction_label": [116, 117, 118, 152], "default_target_label": [116, 117, 118, 152], "default_typ": 59, "defin": [5, 11, 13, 16, 60, 66, 67, 70, 74, 76, 84, 100, 101, 102, 104, 106, 108, 110, 126, 131, 133, 134, 136, 146, 147, 150, 152], "definit": [102, 104, 105, 107, 109, 118, 144, 147, 152], "deleg": 141, "deliv": 90, "demo_ic": 89, "demo_wat": 89, "denot": [19, 123, 124, 145, 150], "dens": 84, "depend": [0, 82, 145, 146, 147, 148, 151, 152], "deploi": [0, 1, 68, 70, 147, 148, 149, 151], "deploy": [0, 1, 70, 74, 76, 104, 143, 147, 148, 150, 151, 152], "deployment_modul": [1, 68], "deploymentmodul": [68, 69, 70, 76], "deprec": [44, 45, 54, 55, 138], "deprecated_method": [3, 44, 54, 68, 71], "deprecation_tool": [1, 128], "depth": [83, 98, 108, 120], "depth_rel": 98, "describ": [5, 144, 147], "descript": [5, 109, 129], "design": [1, 147, 150], "desir": [127, 139], "detail": [1, 5, 92, 109, 110, 118, 123, 146, 147, 149, 150, 152], "detector": [0, 1, 31, 79, 87, 88, 89, 104, 105, 107, 146, 147, 148, 151, 152], "detector_respons": 147, "determin": [69, 92], "develop": [0, 1, 144, 146, 147, 148, 149, 150, 151, 152], "deviat": [104, 105, 108], "devic": 70, "df": [59, 145], "dfg": [0, 148, 151], "dict": [5, 8, 9, 11, 13, 16, 23, 34, 37, 59, 70, 86, 87, 88, 89, 90, 98, 104, 105, 107, 109, 110, 113, 123, 126, 129, 131, 133, 134, 135, 136, 138, 145, 146, 147, 150], "dictionari": [11, 13, 16, 19, 34, 35, 37, 49, 59, 104, 105, 109, 131, 133, 134, 136, 145, 150], "did": 14, "differ": [0, 11, 13, 16, 19, 21, 39, 40, 41, 43, 49, 50, 51, 105, 126, 144, 145, 146, 147, 148, 150, 151, 152], "difficult": 146, "diffier": [147, 152], "digit": 82, "dim": [82, 83], "dimenion": [94, 96, 99], "dimens": [82, 83, 87, 88, 89, 92, 93, 94, 96, 98, 99, 108, 112, 118, 120, 121, 125, 150, 152], "dimension": [82, 83, 146, 152], "dir": 139, "dir_with_fil": [145, 150], "dir_x_pr": 117, "dir_y_pr": 117, "dir_z_pr": 117, "direct": [96, 108, 116, 117, 118, 122, 124, 146, 150], "direction_kappa": 117, "directionreconstructionwithkappa": [115, 117, 147, 152], "directli": [0, 94, 99, 145, 147, 148, 150, 151, 152], "directori": [5, 7, 45, 47, 49, 50, 51, 52, 53, 55, 62, 63, 66, 67, 123, 139, 145, 147, 152], "dirti": 147, "discard_empty_ev": 74, "disconnect": 146, "discuss": 144, "disk": [145, 146, 147], "distanc": [102, 103, 105, 121], "distribut": [14, 84, 94, 110, 117, 125, 127, 149, 152], "distribution_strategi": 90, "ditto": 125, "diverg": 125, "divid": [69, 118], "dk": 5, "dl": [147, 152], "dnn": [25, 32], "do": [0, 14, 70, 74, 125, 133, 134, 144, 146, 147, 148, 151, 152], "do_shuffl": [3, 8], "doc": 147, "docformatt": 144, "docker": 1, "docstr": 144, "document": [14, 110, 125, 150, 152], "doe": [37, 116, 118, 134, 145, 146, 147, 152], "doesn": 59, "dom": [8, 11, 13, 16, 80, 84, 92, 107, 108, 112, 126, 147, 152], "dom_i": [4, 87, 107], "dom_numb": 4, "dom_tim": [4, 107], "dom_typ": 4, "dom_x": [4, 87, 107], "dom_z": [4, 87, 107], "domain": [0, 1, 3, 68, 147, 148, 151], "domandtimewindowcoarsen": [79, 80], "domcoarsen": [79, 80], "don": [123, 145], "done": [23, 84, 141, 144, 145, 147, 150], "dot": 83, "download": [5, 66, 67, 149], "download_dir": [5, 66, 67], "downsid": 146, "draw": 14, "drawn": [100, 101, 105, 106, 147, 152], "drhb": [14, 98], "drop": [14, 83, 93], "drop_last": 14, "drop_path": 83, "drop_prob": 83, "dropout": [83, 92, 99, 112], "dropout_prob": 83, "dropout_ratio": 93, "dropout_readout": 99, "droppath": [81, 83], "dtype": [11, 13, 16, 104, 105, 142, 146, 147, 152], "due": [146, 147, 152], "dummy_pid": [146, 147], "dump": [131, 133, 134, 145, 146, 147], "duplciat": 123, "duplic": 107, "dure": [83, 98, 104, 118, 123, 150], "dynam": [23, 83, 94, 95, 96, 99, 147, 152], "dynedg": [74, 76, 79, 91, 95, 96, 98, 99, 147, 152], "dynedge_arg": 98, "dynedge_jinst": [79, 91], "dynedge_kaggle_tito": [79, 91], "dynedge_layer_s": [94, 99, 147, 152], "dynedgeconv": [81, 83, 94, 99], "dynedgejinst": [91, 95], "dynedgetito": [91, 92, 96], "dyntran": [81, 83, 92, 96], "dyntrans1": 83, "dyntrans_layer_s": [92, 96], "e": [1, 5, 8, 9, 11, 13, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, 37, 39, 43, 59, 60, 64, 70, 74, 76, 80, 82, 83, 84, 86, 87, 88, 89, 93, 97, 102, 104, 105, 107, 108, 109, 110, 113, 114, 116, 117, 118, 121, 123, 124, 125, 127, 131, 141, 144, 145, 146, 147, 149, 152], "each": [5, 14, 23, 34, 37, 58, 59, 63, 64, 69, 70, 80, 82, 83, 84, 87, 88, 89, 92, 94, 96, 99, 102, 104, 105, 107, 108, 112, 116, 118, 121, 123, 125, 126, 139, 145, 146, 147, 150, 152], "earli": [123, 129], "early_stopping_pati": [90, 136], "earlystop": 123, "easi": [0, 145, 146, 147, 148, 151, 152], "easili": [1, 147, 152], "easy_model": [1, 79], "easysyntax": [79, 90, 110, 114], "ed": 125, "edg": [79, 83, 84, 94, 95, 96, 99, 100, 103, 104, 105, 106, 107, 121, 146, 147, 152], "edge_attr": [146, 147], "edge_definit": 104, "edge_index": [80, 83, 121, 146, 147], "edgeconv": 83, "edgeconvtito": [81, 83], "edgedefinit": [100, 101, 102, 103, 104, 105, 106, 147, 152], "edgelessgraph": [100, 105], "effect": [123, 144, 147, 152], "effici": 14, "effort": [144, 146, 150], "either": [0, 5, 9, 11, 16, 21, 66, 67, 125, 145, 147, 148, 151], "elast": 4, "element": [11, 13, 19, 34, 37, 90, 110, 114, 121, 126, 135, 145, 147, 150], "elementwis": 125, "elimin": 74, "els": [74, 124, 145, 150], "ema": 113, "embed": [79, 81, 92, 98, 112, 116, 118, 120], "embedding_dim": [92, 112], "empti": 74, "en": 147, "enabl": [0, 3, 90, 148, 151], "encod": [82, 124], "encount": 147, "encourag": [144, 147], "end": [0, 1, 14, 123, 147, 148, 151], "energi": [4, 117, 118, 127, 146, 147, 150], "energy_cascad": [4, 117], "energy_cascade_pr": 117, "energy_pr": 117, "energy_reco": 76, "energy_sigma": 117, "energy_track": [4, 117], "energy_track_pr": 117, "energyreconstruct": [115, 117, 147, 152], "energyreconstructionwithpow": [115, 117], "energyreconstructionwithuncertainti": [115, 117, 147], "energytcreconstruct": [115, 117], "engin": [0, 148, 151], "enough": 109, "ensemble_dataset": [146, 147], "ensembledataset": [10, 11, 133, 146, 147], "ensembleloss": [122, 125], "ensur": [37, 58, 125, 141, 144, 152], "entir": [11, 13, 109, 145, 147, 152], "entiti": [147, 152], "entri": [74, 76, 94, 99, 121, 129, 150], "entropi": 125, "enum": 37, "env": 149, "environ": [50, 149], "ep": [142, 147, 152], "epoch": [113, 123, 129], "eps_lik": [128, 142], "equival": [37, 147, 152], "erda": [5, 66], "erdahost": 67, "erdahosteddataset": [3, 5, 66, 67], "error": [125, 141, 144, 145, 147], "especi": 74, "establish": 152, "etc": [0, 14, 125, 141, 146, 147, 148, 150, 151], "euclidean": [102, 144], "euclideandistanceloss": [122, 125], "euclideanedg": [101, 102], "european": [0, 148, 151], "eval": [109, 149], "evalu": [5, 110, 118], "even": 58, "event": [0, 1, 5, 7, 9, 11, 13, 14, 16, 18, 28, 43, 45, 47, 55, 59, 60, 63, 64, 66, 67, 74, 82, 84, 92, 104, 107, 108, 114, 118, 120, 121, 124, 125, 126, 127, 133, 145, 147, 148, 150, 151, 152], "event_no": [7, 11, 13, 16, 45, 47, 55, 59, 60, 63, 64, 127, 133, 146, 147, 152], "event_truth": 5, "events_per_batch": 63, "everi": [99, 110, 145, 147, 150], "everyth": [147, 152], "everytim": 144, "exact": [95, 125, 152], "exactli": [125, 141, 146], "exampl": [7, 14, 34, 60, 80, 84, 108, 110, 121, 125, 133, 134, 145, 146, 149], "example_energy_reconstruction_model": [129, 147, 152], "exce": 127, "exceed": 64, "except": [1, 143, 145], "exclud": 23, "exclude_kei": 23, "excluding_valu": 121, "execut": 59, "exist": [0, 11, 13, 16, 59, 79, 110, 124, 133, 146, 147, 148, 151, 152], "exist_ok": [147, 152], "expand": [0, 147, 148, 151], "expans": 98, "expect": [59, 60, 62, 74, 76, 104, 107, 146, 147, 152], "expects_merged_datafram": 62, "experi": [0, 1, 5, 6, 7, 48, 49, 70, 122, 145, 147, 148, 151], "experiment": 152, "expert": 1, "explain": 147, "explicitli": [126, 131, 136], "exponenti": 125, "export": [145, 146, 147, 150, 152], "expos": 1, "express": [14, 109, 125], "extend": [0, 1, 145, 146, 148, 151], "extens": [1, 5, 49, 62, 139], "extern": [146, 147], "extra": [83, 152], "extra_repr": [83, 109], "extra_repr_recurs": 109, "extracor_nam": 49, "extract": [7, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 35, 39, 41, 42, 43, 58, 74, 76, 118, 121, 145, 147, 150], "extractor": [1, 3, 7, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 47, 48, 49, 55, 74, 76], "extractor_nam": [18, 19, 21, 23, 26, 39, 41, 43, 145, 150], "f": [84, 145, 147, 152], "f1": 84, "f2": 84, "f_absorpt": 108, "f_scatter": 108, "factor": [83, 108, 123, 125, 147, 152], "fail": 18, "fals": [14, 36, 74, 82, 83, 94, 98, 99, 104, 109, 120, 123, 125, 127, 133, 147, 152], "fanci": 147, "fashion": 1, "fast": [0, 146, 147, 148, 151], "faster": [0, 145, 146, 148, 151], "favorit": 149, "favourit": 147, "fbeezabg5a": 5, "fc": 84, "featur": [1, 3, 4, 5, 11, 13, 16, 22, 64, 66, 67, 74, 76, 82, 83, 84, 86, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 106, 107, 108, 112, 116, 120, 121, 126, 133, 144, 146, 147, 150, 152], "feature_idx": 108, "feature_map": [86, 87, 88, 89, 150], "feature_nam": 108, "features_subset": [83, 92, 94, 96, 99, 112, 147, 152], "feedforward": 83, "feel": 147, "fetch": 129, "few": [0, 79, 144, 145, 146, 147, 148, 151, 152], "fiber_id": 88, "field": [110, 121, 124, 131, 133, 134, 136, 138, 145, 146, 147, 150], "fieldinfo": [131, 133, 134, 136], "figur": 0, "file": [0, 1, 3, 5, 7, 11, 13, 14, 16, 19, 21, 34, 36, 39, 40, 41, 42, 43, 45, 47, 49, 50, 51, 52, 53, 55, 57, 58, 62, 63, 64, 69, 70, 74, 76, 104, 109, 123, 125, 126, 129, 130, 131, 132, 133, 134, 139, 141, 145, 146, 147, 148, 149, 150, 151, 152], "file_extens": 62, "file_handl": 141, "file_path": [126, 145, 150], "file_read": [7, 145, 150], "filehandl": 141, "filenam": 139, "fileread": [19, 49], "files_list": 58, "filesi": [1, 128], "fill": [5, 14], "filter": [36, 45, 47, 50, 55, 141, 150], "filter_ani": 36, "filter_nam": 36, "filtermask": 36, "final": [0, 7, 84, 123, 133, 146, 147, 148, 151], "find": [21, 103, 139, 146, 147, 150, 152], "find_fil": [49, 50, 51, 52, 53, 145], "find_i3_fil": [128, 139], "first": [82, 92, 103, 112, 123, 126, 144, 147, 150], "fisher": 125, "fit": [9, 14, 90, 125, 127, 136, 147, 152], "fit_weight": 127, "five": 146, "fix": [60, 147], "flag": [22, 74], "flake8": 144, "flatten": 34, "flatten_nested_dictionari": [33, 34], "flexibil": 152, "flexibl": 60, "float": [11, 13, 16, 74, 83, 90, 92, 93, 99, 102, 103, 104, 105, 107, 108, 112, 118, 123, 125, 126, 127, 133, 146], "float32": [11, 13, 16, 104, 105], "float64": 125, "flow": [110, 118, 152], "flow_lay": [110, 118], "flowchart": [0, 148, 151], "fly": [146, 147], "fn": [11, 37, 131, 135], "fn_kwarg": 135, "folder": [45, 47, 50, 51, 52, 53, 55, 69, 145], "folk": 147, "follow": [14, 90, 94, 99, 110, 114, 125, 127, 144, 145, 146, 147], "fork": 144, "form": [0, 19, 79, 116, 131, 136, 145, 146, 148, 151, 152], "format": [0, 1, 3, 5, 7, 11, 34, 38, 39, 49, 51, 62, 63, 64, 82, 109, 112, 133, 144, 145, 146, 147, 148, 149, 150, 151, 152], "forward": [80, 82, 83, 86, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 104, 107, 110, 112, 114, 118, 120, 125, 152], "found": [37, 45, 47, 50, 55, 63, 108, 125, 146, 147], "four": 82, "fourier": 82, "fourierencod": [81, 82, 98, 120], "fraction": [93, 112, 126], "frame": [20, 21, 23, 33, 36, 37, 76], "frame_is_montecarlo": [33, 35], "frame_is_nois": [33, 35], "framework": [0, 147, 148, 151], "free": [0, 14, 125, 147, 148, 151], "freeli": 147, "frequenc": 82, "friendli": [0, 62, 64, 145, 147, 148, 149, 151], "from": [0, 1, 5, 7, 8, 9, 11, 13, 14, 16, 19, 20, 21, 23, 25, 26, 28, 34, 35, 36, 37, 39, 41, 42, 43, 49, 50, 52, 53, 57, 62, 64, 66, 67, 82, 84, 96, 98, 102, 104, 107, 108, 109, 110, 113, 116, 117, 118, 121, 123, 124, 125, 131, 132, 133, 134, 136, 141, 144, 145, 146, 147, 148, 150, 151, 152], "from_config": [11, 109, 132, 133, 134, 146, 147, 152], "from_dataset_config": [8, 147, 152], "full": [63, 147, 152], "fulli": [145, 147, 152], "func": 147, "function": [0, 7, 8, 11, 14, 21, 37, 39, 43, 58, 59, 74, 76, 80, 83, 84, 87, 88, 89, 94, 99, 104, 108, 109, 110, 118, 121, 125, 126, 128, 133, 134, 135, 138, 139, 140, 142, 146, 148, 150, 151, 152], "fund": [0, 148, 151], "furnish": [14, 125], "further": 74, "furthermor": 112, "g": [1, 5, 11, 13, 16, 18, 19, 21, 31, 34, 37, 59, 60, 64, 74, 76, 84, 104, 107, 108, 118, 121, 125, 127, 141, 144, 146, 147, 149, 152], "galatict": 24, "gamma_1": 83, "gamma_2": 83, "gather": [14, 108], "gather_cluster_sequ": [100, 108], "gather_len_matched_bucket": [10, 14], "gcd": [21, 35, 45, 47, 50, 55, 58, 74, 76, 139], "gcd_dict": [35, 37], "gcd_file": [6, 21, 74, 76], "gcd_list": [58, 139], "gcd_rescu": [45, 47, 50, 55, 139], "gcd_shuffl": 58, "gelu": 83, "gener": [0, 5, 9, 11, 13, 14, 16, 23, 36, 49, 62, 66, 69, 74, 76, 82, 100, 101, 104, 105, 106, 116, 125, 127, 146, 147, 148, 150, 151, 152], "geometr": 147, "geometri": [66, 86, 104, 152], "geometry_t": [86, 87, 88, 89, 150], "geometry_table_path": [87, 88, 89, 150], "germani": [0, 148, 151], "get": [19, 35, 59, 86, 123, 126, 147, 152], "get_all_argument_valu": [130, 131], "get_all_grapnet_class": [130, 135], "get_field": [79, 121], "get_graphnet_class": [130, 135], "get_lr": 123, "get_map_funct": 7, "get_member_vari": [33, 37], "get_metr": 123, "get_om_keys_and_pulseseri": [33, 35], "get_predict": [122, 126], "get_primary_kei": [56, 59], "gev": 66, "gframe": 21, "gggt": [110, 118], "git": 149, "github": [14, 98, 110, 118, 120, 125, 147, 149], "given": [5, 11, 14, 16, 21, 64, 66, 67, 82, 84, 102, 118, 125, 127, 129, 146, 150], "glob": 145, "global": [2, 4, 92, 94, 96, 99, 109, 147], "global_index": 7, "global_pooling_schem": [92, 94, 96, 99, 147, 152], "gnn": [1, 79, 92, 93, 94, 95, 96, 98, 99, 104, 110, 112, 120, 147, 152], "go": [14, 144, 147], "googl": 144, "got": 145, "gpu": [90, 129, 147, 149, 152], "grab": 118, "grad_output": 125, "gradient_clip_v": 90, "grant": [0, 14, 125, 148, 151], "graph": [0, 1, 8, 11, 13, 16, 79, 83, 84, 86, 101, 102, 103, 104, 106, 107, 108, 112, 121, 124, 126, 144, 146, 147, 148, 151, 152], "graph_definit": [5, 11, 13, 16, 66, 67, 79, 100, 110, 126, 133, 146, 147, 152], "graph_definiton": 146, "graphdefinit": [5, 11, 13, 16, 66, 67, 100, 101, 104, 105, 106, 110, 126, 144, 146, 147], "graphnet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 56, 58, 59, 60, 62, 63, 64, 66, 67, 68, 69, 70, 74, 76, 77, 78, 79, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142, 144, 145, 146, 148, 149, 150, 151, 152], "graphnet_file_read": [3, 48, 145, 150], "graphnet_model": 123, "graphnet_writ": [3, 61], "graphnetdatamodul": [3, 5, 9], "graphnetearlystop": [122, 123], "graphnetfileread": [7, 48, 49, 50, 51, 52, 53, 145], "graphnetfilesavemethod": [62, 64], "graphnetwrit": [7, 61, 62, 63, 64, 145], "grapnet": [135, 147], "greatli": [147, 152], "group": [0, 14, 84, 147, 148, 151], "group_bi": [81, 84], "group_pulses_to_dom": [81, 84], "group_pulses_to_pmt": [81, 84], "groupbi": 84, "guarante": [147, 152], "guid": 144, "guidelin": 144, "gvd": [66, 89], "gz": 5, "h5": [41, 52, 145], "h5_extractor": [17, 40], "h5extractor": [7, 40, 41, 49, 145], "h5hitextractor": [40, 41, 145], "h5py": 145, "h5truthextractor": [40, 41, 145], "ha": [0, 5, 37, 59, 74, 93, 108, 125, 139, 145, 146, 147, 148, 149, 150, 151, 152], "had": 150, "hadron": 117, "hand": [23, 146, 147], "handi": 58, "handl": [23, 125, 129, 138, 141, 145, 146, 147], "handler": 141, "happen": [127, 146, 150], "hard": [31, 107], "has_extens": [128, 139], "has_icecube_packag": [128, 140], "has_jammy_flows_packag": [128, 140], "has_torch_packag": [128, 140], "have": [1, 5, 13, 23, 45, 47, 50, 55, 59, 60, 64, 84, 98, 104, 108, 118, 144, 146, 147, 150, 152], "head": [83, 92, 96, 98, 118, 120, 152], "head_dim": 83, "head_siz": 98, "heavi": 145, "help": [74, 76, 129, 144, 146, 147, 150, 152], "here": [104, 144, 146, 147, 149, 150, 152], "herebi": [14, 125], "hidden": [82, 83, 92, 94, 95, 99, 112], "hidden_dim": [98, 120], "hidden_featur": 83, "hidden_s": [112, 116, 117, 118, 147, 152], "high": [0, 147, 148, 151], "higher": 146, "highest_protocol": 145, "hint": 144, "hit": [8, 126, 146, 147, 150], "hitdata": 41, "hlc": 107, "hlc_name": 107, "hold": [104, 145, 150, 152], "holder": [14, 125], "home": [87, 88, 89, 129, 145, 150], "homophili": 121, "hook": 144, "horizon": [0, 148, 151], "host": [5, 66, 150], "how": [5, 14, 100, 101, 106, 145, 147, 152], "howev": [45, 47, 50, 55, 146, 147], "html": [110, 118, 147], "http": [5, 14, 98, 99, 102, 110, 118, 120, 125, 144, 147, 149], "human": 147, "hybrid": 24, "hyperparamet": [134, 147, 152], "i": [0, 1, 5, 9, 11, 13, 14, 16, 18, 19, 21, 23, 34, 35, 36, 37, 39, 41, 43, 45, 47, 50, 55, 58, 59, 60, 63, 64, 69, 74, 76, 80, 82, 83, 84, 93, 94, 98, 99, 102, 104, 105, 107, 108, 110, 112, 114, 117, 118, 121, 123, 124, 125, 126, 127, 129, 131, 134, 135, 136, 138, 139, 140, 141, 144, 145, 146, 147, 148, 149, 150, 151, 152], "i3": [1, 21, 35, 36, 37, 45, 47, 50, 55, 58, 69, 74, 76, 139, 147, 149], "i3_fil": [6, 21], "i3_filt": [20, 33, 45, 47, 50, 55], "i3_list": [58, 139], "i3_shuffl": 58, "i3calibr": 35, "i3deploy": [6, 68, 73], "i3extractor": [7, 17, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 45, 47, 49, 55], "i3featureextractor": [4, 17, 20, 74, 76], "i3featureextractoricecube86": [20, 22], "i3featureextractoricecubedeepcor": [20, 22], "i3featureextractoricecubeupgrad": [20, 22], "i3fileset": [3, 6, 49, 50], "i3filt": [33, 36, 45, 47, 50, 55], "i3filtermask": [33, 36], "i3fram": [20, 23, 35, 37, 74, 76], "i3galacticplanehybridrecoextractor": [20, 24], "i3genericextractor": [17, 20], "i3hybridrecoextractor": [17, 20], "i3inferencemodul": [73, 74, 76], "i3mctre": 31, "i3modul": [1, 68, 70], "i3ntmuonlabelextractor": [20, 25], "i3ntmuonlabelsextractor": [17, 20], "i3particl": 26, "i3particleextractor": [17, 20], "i3pisaextractor": [17, 20], "i3pulsecleanermodul": [73, 74], "i3pulsenoisetruthflagicecubeupgrad": [20, 22], "i3quesoextractor": [17, 20], "i3read": [3, 45, 47, 48, 55], "i3retroextractor": [17, 20], "i3splinempeextractor": [17, 20], "i3splinempeicextractor": [20, 30], "i3toparquetconvert": [45, 46, 47], "i3tosqliteconvert": [46, 47, 55], "i3truthextractor": [4, 17, 20], "i3tumextractor": [17, 20], "ic": [96, 98, 107], "ice_arg": 107, "ice_transpar": [100, 108], "icecub": [1, 3, 14, 17, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 45, 47, 50, 55, 68, 74, 76, 79, 83, 85, 96, 98, 107, 108, 140, 147, 152], "icecube86": [4, 85, 87, 89], "icecube86prometheu": [85, 89], "icecube_deepcor": 89, "icecube_gen2": 89, "icecube_upgrad": [87, 89], "icecubedeepcor": [85, 87], "icecubedeepcore8": [85, 89], "icecubegen2": [85, 89], "icecubekaggl": [85, 87], "icecubeupgrad": [85, 87], "icecubeupgrade7": [85, 89], "icedemo81": [85, 89], "icemix": [79, 91], "icemixnod": [106, 107], "icetrai": [35, 37, 45, 47, 50, 55, 70, 140, 149], "icetray_verbos": [45, 47, 50, 55], "id": [5, 7, 9, 13, 45, 47, 55, 64, 86, 104, 126, 145, 146, 147, 150], "id_column": 107, "ideal": 152, "ident": [84, 118], "identifi": [7, 11, 13, 16, 31, 107, 108, 121, 133, 134, 150], "identify_indic": [100, 108], "identitytask": [115, 116, 118], "ie": 92, "ignor": [11, 13, 16, 37, 63], "illustr": [0, 144, 145, 148, 151], "imag": [0, 1, 144, 147, 148, 151, 152], "impact": 98, "implement": [1, 5, 14, 19, 21, 49, 62, 70, 83, 92, 93, 94, 95, 96, 98, 99, 102, 112, 120, 125, 144, 145, 147, 152], "impli": [14, 125], "import": [0, 1, 5, 59, 79, 128, 145, 146, 147, 148, 150, 151, 152], "impos": [11, 13, 90], "improv": [0, 1, 129, 147, 148, 151, 152], "in_featur": 83, "inaccur": 108, "inact": 104, "includ": [1, 5, 13, 14, 66, 67, 83, 90, 107, 125, 131, 144, 146, 147, 150, 152], "include_dynedg": 98, "incompat": 147, "incomplet": 14, "incorpor": 82, "increas": [0, 123, 148, 151], "indent": 109, "independ": [69, 145], "index": [1, 7, 11, 13, 16, 37, 59, 63, 84, 86, 92, 103, 108, 112, 123, 146, 147, 152], "index_column": [7, 11, 13, 16, 45, 47, 55, 59, 60, 63, 64, 126, 127, 133, 146, 147], "indic": [14, 60, 78, 84, 92, 103, 108, 112, 118, 123, 125, 129, 144, 147, 152], "indicesfor": 35, "indici": [11, 13, 16, 35, 60], "individu": [0, 11, 13, 16, 84, 94, 121, 146, 148, 151, 152], "industri": [0, 3, 148, 151], "inelast": [4, 117], "inelasticity_pr": 117, "inelasticityreconstruct": [115, 117], "inf": 121, "infer": [0, 1, 64, 68, 70, 74, 76, 90, 118, 147, 148, 151], "inference_modul": [68, 73], "info": [141, 147], "inform": [5, 11, 13, 16, 18, 19, 21, 23, 31, 39, 41, 43, 66, 67, 104, 107, 108, 109, 145, 146, 147, 150, 152], "ingest": [0, 1, 3, 85, 148, 151], "inherit": [5, 19, 21, 37, 49, 62, 86, 107, 125, 141, 145, 146, 147, 152], "init_fn": [133, 134], "init_global_index": [3, 7], "init_predict_tqdm": 123, "init_test_tqdm": 123, "init_train_tqdm": 123, "init_validation_tqdm": 123, "init_valu": 83, "initi": [7, 36, 50, 64, 69, 83, 92, 98, 103], "initial_st": 43, "initialis": [134, 147, 152], "injection_azimuth": [4, 146, 147], "injection_bjorkeni": [4, 146, 147], "injection_bjorkenx": [4, 146, 147], "injection_column_depth": [4, 146, 147], "injection_energi": [4, 146, 147], "injection_interaction_typ": [4, 146, 147], "injection_position_i": [4, 146, 147], "injection_position_x": [4, 146, 147], "injection_position_z": [4, 146, 147], "injection_typ": [4, 146, 147], "injection_zenith": [4, 146, 147, 152], "innov": [0, 148, 151], "input": [5, 7, 11, 13, 16, 45, 47, 49, 50, 55, 62, 66, 67, 69, 74, 76, 82, 83, 87, 92, 93, 94, 95, 96, 97, 98, 99, 104, 105, 107, 110, 112, 116, 118, 120, 121, 131, 136, 138, 145, 146, 147, 150, 152], "input_dim": [83, 152], "input_dir": [145, 150], "input_featur": [86, 104], "input_feature_nam": [86, 104, 105, 107], "input_fil": [49, 69], "ins": 86, "insid": 146, "inspect": [147, 152], "inspir": 99, "instal": [144, 147], "instanc": [11, 19, 21, 31, 37, 39, 41, 43, 45, 47, 50, 55, 104, 109, 124, 126, 132, 134, 145, 146, 147, 152], "instanti": [7, 9, 134, 145, 146, 150], "instead": [21, 45, 47, 50, 55, 110, 125, 147, 152], "int": [5, 7, 8, 9, 11, 13, 14, 16, 25, 28, 36, 45, 47, 49, 50, 51, 52, 53, 55, 60, 62, 63, 64, 69, 82, 83, 84, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 125, 126, 127, 129, 133, 136, 141, 145, 152], "integ": [59, 92, 94, 95, 99, 125, 146, 147], "integer_primary_kei": 59, "integr": 152, "intend": [92, 112, 147], "interact": [117, 124, 146, 147], "interaction_kei": 124, "interaction_tim": [4, 117], "interaction_time_pr": 117, "interaction_typ": [4, 124], "interchang": [147, 152], "interfac": [0, 133, 134, 147, 148, 149, 150, 151], "interim": [7, 61, 62, 63, 64, 145], "intermedi": [0, 1, 3, 7, 11, 93, 147, 148, 151], "intern": [3, 17, 39, 47, 51], "internal_parquet_read": [3, 48], "interpol": [108, 123], "interpret": 116, "interv": [82, 147, 152], "intract": 146, "introduc": 147, "introduct": [110, 118], "intuit": [141, 152], "invers": 118, "invert": 118, "involv": 60, "io": [110, 118, 144, 147], "iop": 147, "iopscienc": 147, "is_boost_class": [33, 37], "is_boost_enum": [33, 37], "is_gcd_fil": [128, 139], "is_graphnet_class": [130, 135], "is_graphnet_modul": [130, 135], "is_i3_fil": [128, 139], "is_icecube_class": [33, 37], "is_method": [33, 37], "is_typ": [33, 37], "iseecub": [79, 119], "isinst": 145, "isn": 37, "isol": 105, "issu": [147, 152], "iter": 11, "its": [37, 112, 146, 147, 152], "itself": [37, 118, 145, 147, 152], "iv": 125, "jammy_flow": [110, 118, 140], "job": 150, "join": [145, 147], "json": [34, 133, 146, 147], "just": [5, 84, 145, 146, 147, 152], "k": [83, 92, 94, 96, 99, 102, 105, 112, 121, 125], "kaggl": [4, 82, 83, 87, 96, 98], "kappa": [117, 125], "kappa_switch": 125, "karg": [109, 113], "keep": [19, 21, 39, 41, 43, 107, 145], "kei": [11, 23, 34, 35, 37, 59, 64, 83, 84, 107, 124, 133, 134, 145, 146, 147, 150], "kept": 36, "key_padding_mask": 83, "keyword": [123, 131, 136], "kind": [14, 125, 150], "km3net": [147, 152], "knn_graph_batch": [79, 121], "knnedg": [101, 102], "knngraph": [100, 105, 146, 147, 152], "know": 150, "known": 84, "kv": 83, "kwarg": [7, 8, 11, 13, 16, 36, 49, 51, 52, 53, 62, 80, 83, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 123, 125, 127, 131, 133, 134, 141], "l": [108, 121], "label": [1, 11, 13, 16, 25, 28, 90, 93, 104, 114, 118, 122, 126, 133], "lai": 147, "lambda": [109, 147, 152], "land": 147, "larg": [0, 92, 125, 146, 148, 151], "larger": 145, "largest": 108, "last": [14, 94, 99, 112, 116, 117, 118, 123, 126, 152], "last_epoch": 123, "lastli": 150, "latent": [82, 92, 94, 96, 98, 99, 110, 112, 116, 117, 118, 120, 152], "latest": 147, "layer": [0, 79, 81, 84, 92, 93, 94, 95, 96, 98, 99, 110, 112, 116, 117, 118, 148, 151], "layer_s": 83, "layer_size_scal": 95, "layernorm": 83, "ldot": [80, 84], "lead": [146, 147], "learn": [0, 1, 5, 62, 64, 74, 76, 110, 114, 116, 118, 123, 145, 147, 148, 149, 150, 151, 152], "learnabl": [83, 91, 92, 93, 94, 95, 96, 97, 98, 99, 112, 118, 120, 152], "learnedtask": [115, 118], "least": [13, 144, 146, 147], "leav": 123, "len": [11, 13, 108, 145, 146], "length": [11, 13, 14, 37, 107, 108, 121, 123], "lenmatchbatchsampl": [10, 14], "less": [8, 126, 147, 152], "let": [147, 150, 152], "level": [0, 5, 11, 13, 16, 18, 31, 36, 43, 45, 47, 49, 50, 51, 52, 53, 55, 59, 62, 63, 66, 67, 80, 84, 98, 114, 141, 146, 147, 148, 150, 151], "leverag": 1, "lex_sort": [100, 108], "liabil": [14, 125], "liabl": [14, 125], "lib": [87, 88, 89, 129], "licens": [14, 125], "lift": 145, "light": 103, "lightn": [9, 123, 147, 152], "lightningdatamodul": 9, "lightningmodul": [82, 83, 109, 123, 141, 147, 152], "like": [14, 19, 37, 84, 103, 110, 118, 121, 125, 142, 144, 146, 147, 149, 152], "limit": [14, 107, 125], "line": [123, 129, 145, 146, 150], "linear": [94, 99, 152], "linearli": 123, "liquid": 88, "liquido": [3, 4, 17, 41, 52, 79, 85, 145], "liquido_read": [3, 48], "liquido_v1": [85, 88], "liquidoread": [48, 52, 145], "list": [5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 23, 31, 34, 36, 37, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 74, 76, 80, 83, 84, 86, 90, 92, 94, 96, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 118, 121, 123, 125, 126, 127, 133, 135, 136, 139, 141, 145, 146, 150], "list_all_submodul": [130, 135], "ljvmiranda921": 144, "load": [0, 8, 11, 58, 70, 109, 113, 131, 133, 146, 147, 148, 150, 151], "load_from_checkpoint": [147, 152], "load_modul": [10, 11, 109], "load_state_dict": [109, 113, 147, 152], "loaded_model": [147, 152], "local": [80, 87, 88, 89, 107, 129, 147, 149, 152], "lock": 13, "log": [0, 1, 117, 122, 123, 125, 128, 146, 147, 148, 151, 152], "log10": [118, 127, 147, 152], "log_cmk": 125, "log_cmk_approx": 125, "log_cmk_exact": 125, "log_every_n_step": [90, 147, 152], "log_fold": [36, 49, 51, 52, 53, 62, 141], "log_model": [147, 152], "logcmk": [122, 125], "logcoshloss": [122, 125, 147, 152], "logger": [7, 9, 11, 14, 19, 36, 49, 51, 52, 53, 60, 62, 69, 70, 90, 102, 109, 124, 127, 128, 141, 147, 152], "loggeradapt": 141, "logic": 146, "logit": [116, 125, 152], "logrecord": 141, "long": 146, "longev": [0, 148, 151], "longtensor": [80, 84, 121], "look": [23, 146, 147], "lookup": 135, "loop": [147, 152], "loss": [11, 13, 16, 90, 104, 110, 114, 118, 123, 125, 129, 147, 152], "loss_factor": 125, "loss_funct": [1, 118, 122, 147, 152], "loss_weight": [104, 118, 147, 152], "loss_weight_column": [11, 13, 16, 104, 126, 133], "loss_weight_default_valu": [11, 13, 16, 104, 133], "loss_weight_t": [11, 13, 16, 126, 133], "lossfunct": [118, 122, 125, 147], "lot": 144, "lower": [0, 147, 148, 151], "lr": [147, 152], "m": [103, 108, 125], "machin": 1, "made": [147, 152], "magnitud": [0, 148, 151], "mai": [49, 60, 70, 107, 118, 146, 147, 149, 152], "main": [1, 14, 91, 144, 147], "mainli": 37, "major": [114, 118], "make": [0, 7, 107, 127, 133, 134, 144, 145, 146, 147, 148, 150, 151, 152], "make_dataload": [122, 126], "make_train_validation_dataload": [122, 126], "makedir": [147, 152], "manag": [0, 122, 145, 147, 148, 151], "mandatori": 82, "mangl": 37, "mani": [64, 145, 147, 152], "manipul": [34, 100, 101, 106], "map": [7, 11, 13, 16, 22, 23, 59, 87, 88, 89, 104, 105, 118, 131, 133, 134, 136, 147, 150, 152], "mari": [0, 148, 151], "martin": 93, "mask": [14, 104, 121], "masked_entri": 121, "master": 125, "match": [14, 49, 104, 127, 139, 142, 145], "math": [1, 83, 128], "mathbb": 84, "mathbf": [80, 84], "matic": 118, "matric": 83, "matrix": [84, 102, 103, 121, 125, 146], "max": [80, 83, 94, 96, 99, 125, 127, 129, 147, 152], "max_activ": 107, "max_epoch": [90, 147, 152], "max_pool": [80, 84], "max_pool_x": [80, 84], "max_puls": 107, "max_rel_po": 120, "max_table_s": 64, "max_weight": 127, "maximum": [64, 84, 107, 108, 118, 120, 129], "mc": [23, 59], "mc_truth": [19, 43, 146, 147], "mctree": [31, 35], "md": 147, "mean": [0, 11, 13, 16, 79, 94, 96, 99, 108, 125, 134, 145, 146, 147, 148, 151, 152], "meaning": 82, "meant": [145, 147, 152], "measur": [107, 108, 121, 147, 150], "mechan": 83, "meet": 118, "member": [21, 23, 37, 49, 107, 133, 134, 141, 145, 150], "memori": [13, 146], "mention": 147, "merchant": [14, 125], "merg": [7, 14, 62, 63, 64, 125, 145, 146, 150], "merge_fil": [7, 62, 63, 64, 145, 150], "merged_database_nam": 64, "messag": [83, 123, 141, 147], "messagepass": 83, "metaclass": [133, 134], "metadata": [131, 133, 134, 136], "metaproject": 149, "meter": 147, "meth": 147, "method": [5, 7, 9, 11, 13, 14, 16, 19, 21, 33, 34, 35, 37, 44, 45, 49, 54, 55, 62, 63, 64, 66, 67, 70, 83, 84, 86, 98, 108, 117, 125, 127, 145, 147, 152], "metric": [92, 94, 96, 99, 103, 112, 123, 147, 152], "might": [146, 147, 152], "mileston": [123, 147, 152], "million": [64, 66], "min": [80, 84, 94, 96, 99, 127, 147, 152], "min_pool": [80, 81, 84], "min_pool_x": [80, 81, 84], "mind": 147, "minh": 93, "mini": 126, "minim": [90, 110, 146, 147, 150, 152], "minimum": [107, 118], "minkowski": [100, 101], "minkowskiknnedg": [101, 103], "minu": 125, "mise": 125, "miss": 78, "mit": [14, 125], "mix": 18, "ml": [0, 1, 148, 151], "mlp": [81, 82, 83, 94, 98, 99, 120, 152], "mlp_dim": [82, 120], "mlp_ratio": [83, 98], "mode": [90, 118], "model": [0, 1, 5, 68, 70, 74, 76, 80, 81, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 110, 112, 113, 114, 115, 116, 117, 118, 120, 121, 122, 123, 125, 126, 129, 131, 133, 134, 136, 143, 145, 146, 148, 149, 150, 151], "model_computed_field": [131, 133, 134, 136], "model_config": [70, 74, 76, 128, 130, 131, 133, 136, 147, 152], "model_config_path": [147, 152], "model_field": [131, 133, 134, 136], "model_nam": [74, 76], "modelconfig": [70, 74, 76, 109, 130, 133, 134], "modelconfigsav": 134, "modelconfigsaverabc": [130, 134], "modelconfigsavermeta": [130, 134], "modif": [147, 152], "modifi": [14, 125, 147, 152], "modul": [0, 3, 6, 7, 11, 17, 18, 37, 38, 40, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 61, 62, 64, 68, 69, 74, 78, 79, 82, 83, 85, 91, 100, 101, 103, 104, 105, 106, 109, 111, 115, 119, 122, 128, 130, 133, 134, 135, 136, 140, 145, 147, 148, 151, 152], "modular": [0, 79, 145, 147, 148, 151, 152], "moduletyp": 135, "mont": 35, "more": [1, 11, 13, 14, 58, 59, 92, 109, 133, 134, 141, 146, 147, 152], "most": [0, 1, 60, 103, 118, 145, 148, 150, 151, 152], "mryab": 125, "mseloss": [122, 125], "msg": 141, "mulitpli": 125, "multi": [83, 94, 99, 114], "multiclassclassificationtask": [115, 116, 147], "multiheadattent": [14, 83], "multiindex": 150, "multipl": [11, 13, 16, 18, 82, 108, 123, 125, 133, 141, 152], "multipli": [83, 123], "multiprocess": [7, 14, 45, 47, 55, 145], "multiprocessing_context": [13, 14], "muon": [25, 146, 152], "must": [13, 18, 49, 50, 59, 62, 80, 123, 125, 127, 144, 145, 146, 147, 150], "my": [146, 147, 150], "my_custom_label": [146, 147], "my_databas": 64, "my_fil": [145, 150], "my_geometry_t": 150, "my_outdir": [145, 150], "my_tabl": 150, "mycustomlabel": [146, 147], "mydetector": 150, "myexperi": 150, "myextractor": 150, "mygraphnetmodel": 152, "mymodel": 152, "mypi": 144, "mypicklewrit": 145, "myread": 150, "n": [14, 19, 80, 84, 103, 121, 125, 146, 147, 150], "n_1": 84, "n_b": 84, "n_cluster": 108, "n_event": [145, 150], "n_featur": [82, 98, 120], "n_freq": 82, "n_head": [83, 92, 96], "n_pmt": 108, "n_puls": [107, 150], "n_rel": 98, "n_worker": 69, "name": [4, 5, 7, 8, 11, 13, 16, 18, 19, 21, 22, 24, 25, 27, 28, 29, 30, 31, 32, 34, 36, 37, 39, 41, 43, 45, 47, 49, 51, 52, 53, 55, 59, 62, 63, 64, 70, 74, 76, 86, 104, 105, 107, 110, 112, 118, 121, 124, 127, 129, 131, 133, 134, 135, 136, 141, 144, 145, 146, 147, 150, 152], "namespac": [4, 109, 133, 134], "nan": 108, "narg": 129, "nb_dom": 121, "nb_file": 7, "nb_input": [92, 93, 94, 95, 96, 97, 99, 112, 116, 117, 118, 147, 152], "nb_intermedi": 93, "nb_nearest_neighbour": [102, 103, 105, 146, 147, 152], "nb_neighbor": 83, "nb_neighbour": [92, 94, 96, 99, 112, 147, 152], "nb_output": [93, 95, 97, 107, 116, 117, 118, 147, 152], "nb_repeats_allow": 141, "ndarrai": [11, 13, 31, 104, 108, 127, 145], "nearest": [92, 94, 96, 99, 102, 103, 105, 112, 121, 147, 152], "nearli": 152, "necessari": [0, 9, 34, 144, 148, 151], "need": [0, 5, 9, 34, 64, 79, 82, 109, 112, 125, 138, 145, 146, 147, 148, 149, 150, 151, 152], "negat": 84, "neighbour": [83, 92, 94, 96, 99, 102, 103, 105, 112, 121, 147, 152], "nest": 34, "nester": 34, "network": [1, 83, 93, 111, 152], "neural": [1, 111, 152], "neutrino": [0, 1, 21, 43, 50, 83, 96, 98, 108, 120, 146, 147, 148, 150, 151, 152], "new": [0, 1, 18, 83, 107, 131, 136, 144, 145, 147, 148, 151, 152], "new_features_nam": 107, "new_phras": 138, "nfdi": [0, 148, 151], "nn": [0, 79, 83, 102, 105, 148, 151, 152], "no_weight_decai": 98, "node": [11, 13, 16, 79, 80, 84, 92, 93, 94, 96, 99, 100, 101, 102, 104, 105, 112, 121, 146, 147, 152], "node_definit": [104, 105, 146, 147, 152], "node_feature_nam": [107, 146, 147, 152], "node_level": 126, "node_rnn": [79, 92, 111], "node_truth": [11, 13, 16, 126, 133], "node_truth_t": [11, 13, 16, 126, 133, 147], "nodeasdomtimeseri": [106, 107], "nodedefinit": [104, 105, 106, 107, 147, 152], "nodesaspuls": [104, 106, 107, 146, 147, 152], "nodetimernn": 112, "nois": [22, 35, 74, 147], "non": [9, 34, 37, 59, 92, 118, 125, 147], "none": [5, 7, 8, 9, 11, 13, 14, 16, 21, 23, 31, 35, 36, 37, 45, 47, 49, 50, 51, 52, 53, 55, 59, 60, 62, 63, 64, 66, 67, 69, 70, 76, 83, 84, 90, 92, 94, 96, 98, 99, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 118, 123, 125, 126, 127, 129, 131, 132, 133, 135, 139, 141, 145, 146, 147, 150, 152], "nonetyp": 133, "noninfring": [14, 125], "norm_lay": 83, "normal": [83, 94, 99, 108, 110, 118, 150], "normalizing_flow": [1, 79], "normalizingflow": [79, 110, 118], "northeren": 25, "note": [11, 13, 16, 50, 63, 64, 108, 134, 147], "notebook": 144, "notic": [14, 64, 121, 125], "notimplementederror": 145, "now": [147, 150, 152], "np": [127, 145], "null": [36, 59, 146, 147, 152], "nullspliti3filt": [33, 36, 45, 47, 50, 55], "num": 129, "num_class": 125, "num_edg": 146, "num_edge_featur": 146, "num_featur": 146, "num_head": [83, 120], "num_lay": [112, 120], "num_nod": 146, "num_puls": 107, "num_register_token": 120, "num_row": [104, 146], "num_sampl": 14, "num_work": [7, 8, 9, 14, 47, 63, 126, 145, 146, 147, 150, 152], "number": [0, 5, 7, 11, 13, 14, 16, 19, 45, 47, 55, 60, 63, 64, 69, 82, 83, 84, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 112, 116, 117, 118, 120, 121, 123, 126, 127, 129, 145, 146, 147, 148, 150, 151], "numer": [118, 150], "numpi": 108, "numu": 124, "numucc": 124, "o": [0, 88, 118, 145, 147, 148, 149, 151, 152], "obj": [34, 37, 135], "object": [4, 6, 11, 13, 14, 16, 23, 34, 37, 80, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 125, 126, 129, 131, 133, 134, 136, 141, 146, 147, 152], "observ": 150, "observatori": [21, 50], "obtain": [14, 84, 125], "occur": [8, 126], "oerso": 95, "offer": 146, "offset": [107, 108], "ofintern": 38, "often": 146, "old_phras": 138, "om": [35, 37], "omit": 152, "on_fit_end": 123, "on_train_end": 113, "on_train_epoch_end": 123, "on_train_epoch_start": 123, "on_validation_end": 123, "onc": [141, 147, 149], "one": [11, 13, 21, 59, 74, 84, 133, 134, 139, 144, 145, 146, 147, 150, 152], "ones": 113, "onli": [0, 1, 11, 13, 16, 64, 79, 84, 92, 118, 127, 131, 134, 136, 140, 145, 146, 147, 148, 150, 151, 152], "open": [0, 49, 144, 145, 146, 147, 148, 149, 150, 151], "opensciencegrid": 149, "oper": [14, 80, 83, 91, 94], "oppos": 146, "optic": [37, 108], "optim": [90, 110, 113, 123, 147, 152], "optimis": [0, 1, 147, 148, 151, 152], "optimizer_class": [110, 147, 152], "optimizer_closur": 113, "optimizer_kwarg": [110, 147, 152], "optimizer_step": 113, "optimzi": 110, "option": [5, 7, 9, 11, 13, 14, 16, 21, 31, 59, 64, 66, 67, 70, 76, 82, 83, 84, 92, 94, 96, 98, 99, 103, 104, 105, 107, 108, 109, 110, 112, 118, 123, 125, 127, 128, 129, 131, 133, 139, 145, 146, 147, 150, 152], "orca": 89, "orca150": [85, 89, 152], "orca150superdens": [85, 89], "orca_150": 89, "order": [0, 34, 49, 69, 80, 107, 121, 125, 147, 148, 151], "ordinari": 152, "ordinarili": 150, "org": [99, 102, 125, 147, 149], "orient": [0, 79, 148, 151], "origin": [14, 98, 146, 152], "ot": 125, "other": [14, 26, 59, 102, 125, 144, 146, 147, 152], "otherwis": [14, 37, 125], "our": [147, 150], "out": [5, 11, 13, 14, 94, 115, 125, 141, 144, 145, 146, 147, 150, 152], "out_featur": 83, "outdir": [7, 45, 47, 55, 145, 147, 150, 152], "outer": 34, "outlin": [150, 152], "output": [19, 64, 69, 70, 82, 83, 90, 92, 93, 94, 95, 97, 99, 104, 107, 108, 112, 116, 117, 118, 127, 133, 134, 145, 150, 152], "output_dim": [82, 152], "output_dir": [62, 63, 64, 145], "output_fil": 7, "output_file_path": 145, "output_fold": [6, 69], "outsid": [67, 144], "over": [103, 107, 145, 146], "overal": 125, "overhead": 150, "overrid": [9, 123], "overridden": 107, "overview": [0, 148, 151], "overwrit": [70, 123], "overwritten": [49, 129, 131], "own": [144, 147], "ownership": 144, "p": [35, 66, 125, 145], "p11003": 147, "packag": [0, 1, 58, 118, 135, 139, 140, 144, 147, 148, 151, 152], "pad": [104, 108, 121], "padding_valu": [25, 28, 121], "pair": [21, 45, 47, 50, 55, 82], "pairwis": [103, 121], "pairwise_shuffl": [56, 58], "panda": [60, 127, 145, 147, 150, 152], "paper": 125, "paradigm": [147, 152], "parallel": [7, 45, 47, 55, 145, 150], "param": [14, 39, 41, 43], "paramet": [5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 74, 76, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142], "parent": [34, 147], "parent_kei": 34, "parquet": [1, 3, 5, 10, 13, 39, 42, 43, 45, 47, 51, 53, 55, 57, 63, 66, 67, 87, 88, 89, 145, 146, 147, 150], "parquet_dataset": [10, 12, 146], "parquet_extractor": [17, 38], "parquet_to_sqlit": [3, 56], "parquet_writ": [3, 61], "parquetdataconvert": [44, 45], "parquetdataset": [9, 12, 13, 145, 147], "parquetextractor": [7, 38, 39, 41, 47, 49], "parquetread": [48, 51], "parquettosqliteconvert": [46, 47], "parquetwrit": [13, 39, 47, 61, 63, 145, 146, 150], "pars": [23, 128, 129, 130, 131, 136, 145], "parse_graph_definit": [10, 11], "parse_label": [10, 11], "part": [145, 147, 149, 150], "particl": [31, 59, 124, 146, 147, 150], "particlenet": [79, 91], "particular": [14, 125, 144], "particularli": [146, 147, 152], "partit": 64, "partli": [0, 148, 151], "pass": [11, 16, 82, 83, 90, 92, 93, 94, 95, 96, 97, 98, 99, 104, 110, 112, 114, 118, 120, 123, 125, 127, 144, 145, 146, 147, 150, 152], "path": [5, 11, 13, 16, 21, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 64, 69, 74, 76, 83, 104, 109, 113, 123, 126, 129, 131, 132, 133, 139, 145, 146, 147, 150, 152], "path_to_arrai": 150, "path_to_geometry_t": 150, "patienc": 129, "pd": [145, 147, 150], "pdf": [102, 110], "pdg": 124, "penal": 125, "peopl": [147, 152], "pep257": 144, "pep8": 144, "per": [11, 13, 16, 23, 59, 83, 84, 92, 112, 118, 125, 127, 146, 147], "percentil": [107, 108], "percentileclust": [106, 107], "perceptron": [83, 94, 99], "perform": [0, 9, 80, 82, 83, 84, 90, 91, 92, 94, 96, 99, 107, 110, 112, 113, 114, 116, 118, 126, 147, 148, 151, 152], "permiss": [14, 125], "permit": [14, 125], "persistent_work": [8, 126], "person": [5, 14, 125], "perturb": [104, 105], "perturbation_dict": [104, 105], "pframe": [45, 47, 50, 55], "philosophi": [147, 152], "photon": [43, 146, 147], "phrase": 138, "phyic": 1, "physic": [0, 1, 21, 35, 37, 68, 74, 76, 79, 115, 118, 146, 147, 148, 151, 152], "physicist": [0, 1, 147, 148, 151], "physicst": 1, "pick": 146, "pickl": [145, 147, 150, 152], "pid": [4, 60, 124, 133, 146], "pid_kei": 124, "piecewiselinearlr": [122, 123, 147, 152], "pip": [144, 149], "pisa": 27, "place": [14, 82, 98, 138, 144], "plai": 1, "plane": [24, 125], "pleas": [145, 146, 147, 150], "plot": 146, "plug": 1, "pmt": [84, 108, 146, 147], "pmt_area": 4, "pmt_dir_i": 4, "pmt_dir_x": 4, "pmt_dir_z": 4, "pmt_number": 4, "point": [5, 30, 110, 124, 125, 126, 147, 150, 152], "pole": 96, "pone": 89, "pone_triangl": 89, "ponesmal": [65, 66], "ponetriangl": [85, 89], "pool": [7, 79, 80, 81, 92, 94, 96, 99], "pop_default": 129, "popular": 152, "port": 147, "portabl": [0, 147, 148, 151, 152], "portion": [14, 125], "pos_x": 147, "posit": [74, 82, 83, 84, 98, 108, 117, 120, 131, 136, 146, 150], "position_i": 4, "position_x": 4, "position_x_pr": 117, "position_y_pr": 117, "position_z": 4, "position_z_pr": 117, "positionreconstruct": [115, 117], "possibl": [0, 34, 64, 144, 148, 150, 151], "post": [92, 94, 96, 99], "post_processing_layer_s": [92, 94, 96, 147, 152], "posterior": 110, "pow": [147, 152], "power": [145, 147, 152], "pr": 112, "practic": [0, 144, 148, 151], "pre": [0, 5, 46, 47, 65, 86, 104, 124, 144, 146, 147, 148, 151, 152], "pre_configur": [1, 3, 47], "precis": 125, "precommit": 144, "preconfigur": 47, "pred": [90, 114, 118], "predict": [0, 9, 26, 30, 32, 74, 76, 90, 93, 98, 110, 114, 116, 118, 125, 126, 147, 148, 151, 152], "predict_as_datafram": [90, 147, 152], "prediction_column": [70, 76, 90, 126], "prediction_kei": 125, "prediction_label": [90, 118, 147, 152], "prefer": 103, "prefetch_factor": 8, "prepar": [0, 5, 9, 125, 146, 148, 151], "prepare_data": [5, 9], "preprocess": 147, "present": [11, 13, 21, 36, 121, 129, 139, 140, 146, 152], "previou": [123, 147, 152], "primari": [59, 64, 146, 147], "primary_hadron_1_direction_phi": [4, 146, 147], "primary_hadron_1_direction_theta": [4, 146, 147], "primary_hadron_1_energi": [4, 146, 147], "primary_hadron_1_position_i": [4, 146, 147], "primary_hadron_1_position_x": [4, 146, 147], "primary_hadron_1_position_z": [4, 146, 147], "primary_hadron_1_typ": [4, 146, 147], "primary_key_rescu": 64, "primary_lepton_1_direction_phi": [4, 146, 147], "primary_lepton_1_direction_theta": [4, 146, 147], "primary_lepton_1_energi": [4, 146, 147], "primary_lepton_1_position_i": [4, 146, 147], "primary_lepton_1_position_x": [4, 146, 147], "primary_lepton_1_position_z": [4, 146, 147], "primary_lepton_1_typ": [4, 146, 147], "principl": [1, 147], "print": [5, 109, 123, 141], "prior": 146, "prioriti": 144, "privat": 127, "pro": [147, 152], "probabl": [83, 125, 152], "problem": [0, 102, 144, 146, 147, 148, 151, 152], "procedur": 9, "proceedur": 64, "process": [1, 7, 14, 45, 47, 55, 74, 82, 86, 92, 94, 96, 99, 144, 145, 147, 152], "process_posit": 123, "produc": [5, 49, 82, 110, 114, 124, 127, 146, 147], "product": [8, 83, 126], "programm": [0, 148, 151], "progress": 123, "progressbar": [122, 123, 147, 152], "proj_drop": 83, "project": [0, 53, 83, 144, 147, 148, 151, 152], "prometheu": [3, 4, 17, 43, 53, 66, 79, 85, 146, 147, 152], "prometheus_dataset": [1, 65], "prometheus_extractor": [17, 42], "prometheus_read": [3, 48], "prometheusextractor": [7, 42, 43, 49], "prometheusfeatureextractor": [42, 43], "prometheusread": [48, 53], "prometheustruthextractor": [42, 43], "prompt": 147, "prone": 147, "proof": [147, 152], "properti": [5, 9, 11, 13, 14, 19, 26, 37, 49, 62, 84, 86, 90, 97, 107, 108, 118, 124, 132, 141, 145], "protocol": 145, "prototyp": 88, "proven": [19, 21, 39, 41, 43, 145], "provid": [0, 1, 7, 11, 13, 14, 16, 74, 79, 98, 104, 109, 110, 125, 144, 145, 146, 147, 148, 151, 152], "pth": [147, 152], "public": [66, 86, 127], "publicprometheusdataset": [65, 66], "publish": [14, 125, 147, 152], "puls": [5, 11, 13, 16, 18, 22, 23, 35, 37, 43, 59, 74, 80, 84, 98, 104, 107, 108, 114, 120, 121, 146, 147, 150, 152], "pulse_truth": 5, "pulsemap": [5, 11, 13, 16, 22, 66, 67, 74, 76, 126, 133, 146, 147], "pulsemap_extractor": [74, 76], "pulseseri": 35, "pulsmap": [74, 76], "punch4nfdi": [0, 148, 151], "pure": [7, 19, 20, 23, 37], "purpos": [0, 14, 79, 125, 148, 150, 151], "put": [64, 147, 152], "py": [14, 125, 147], "py3": 149, "pydant": [131, 133, 134, 136], "pydantic_cor": [131, 136], "pydocstyl": 144, "pyg": [146, 147, 152], "pylint": 144, "python": [0, 1, 7, 19, 20, 23, 34, 37, 144, 147, 148, 149, 151, 152], "python3": [87, 88, 89, 129], "pytorch": [16, 123, 147, 149, 152], "pytorch_lightn": [90, 123, 141, 147, 152], "pytorchlightn": 147, "q": 83, "qk_scale": 83, "qkv_bia": 83, "qualiti": [0, 147, 148, 151], "quantiti": [27, 118, 121, 147], "queri": [11, 13, 16, 59, 60, 64, 83, 146, 147], "query_databas": [56, 59], "query_t": [11, 13, 16, 146], "queso": 28, "question": 147, "quick": 147, "r": [84, 102, 145, 147, 149, 150], "radial": 102, "radialedg": [101, 102], "radiat": [107, 108, 147, 152], "radiu": [102, 147], "rais": [11, 13, 21, 23, 109, 110, 131, 136, 145], "random": [3, 11, 13, 16, 56, 60, 63, 107, 133, 146, 147], "randomchunksampl": [10, 14], "randomli": [14, 60, 104, 105, 134, 147, 152], "rang": [14, 118, 148, 150, 151, 152], "rare": 145, "rasmu": [0, 95, 148, 151], "rate": [110, 123], "rather": [118, 141, 147, 152], "ratio": [9, 83, 98], "raw": [0, 107, 108, 146, 147, 148, 150, 151, 152], "rde": 4, "re": [132, 146, 147, 150, 152], "reach": [146, 150], "read": [0, 3, 7, 11, 13, 16, 34, 48, 50, 51, 52, 53, 86, 94, 115, 145, 146, 147, 148, 150, 151], "read_csv": 150, "read_sql": 147, "readabl": 147, "reader": [1, 3, 47, 49, 50, 51, 52, 53, 150], "readi": [65, 150, 152], "readm": 147, "readout": [92, 94, 96, 99], "readout_layer_s": [92, 94, 96, 99, 147, 152], "readthedoc": 147, "receiv": [0, 148, 151, 152], "reciev": [62, 145, 150, 152], "recommend": [147, 149, 150, 152], "reconstruct": [0, 1, 22, 24, 25, 29, 30, 32, 68, 79, 96, 112, 115, 118, 146, 147, 148, 151], "record": 141, "recov": 118, "recreat": [146, 147, 152], "recurr": 111, "recurs": [23, 37, 45, 47, 49, 50, 55, 109, 135, 139], "reduc": [147, 152], "reduce_opt": 80, "refer": [9, 89, 110, 133, 146, 147, 150, 152], "refresh_r": 123, "regardless": [146, 147, 152], "regist": 120, "regress": 114, "regular": [37, 83, 147, 152], "rel": [83, 98, 120], "rel_pos_bia": 83, "rel_pos_bucket": 120, "relat": [58, 139, 150], "relev": [1, 37, 58, 139, 144], "reli": [50, 110], "reload": 152, "relu": 99, "remain": 146, "remaining_batch": 14, "remov": [8, 45, 55, 104, 126, 129, 150], "renam": 138, "rename_state_dict_entri": [128, 138], "repeat": [104, 141], "repeat_label": 104, "repeatfilt": [128, 141], "replac": [131, 133, 134, 136, 138], "repo": 144, "repositori": 144, "repres": [84, 92, 104, 105, 107, 108, 121, 131, 133, 134, 145, 146, 147, 150, 152], "represent": [5, 11, 13, 16, 37, 66, 67, 82, 83, 84, 105, 109, 110, 112, 146, 147, 150, 152], "reproduc": [133, 134, 152], "repurpos": 152, "requir": [0, 21, 27, 39, 43, 59, 107, 116, 118, 125, 133, 134, 136, 144, 145, 146, 147, 148, 149, 150, 151, 152], "requires_icecub": [128, 140], "research": [0, 147, 148, 151], "reset": 83, "reset_paramet": 83, "resolv": [11, 13, 16, 60], "respect": [126, 147, 150], "respons": [146, 147], "restrict": [14, 118, 125, 152], "result": [14, 59, 63, 84, 105, 108, 123, 125, 126, 135, 147, 150, 152], "retriev": [86, 145, 146], "retro": 29, "return": [5, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 34, 35, 37, 49, 50, 51, 52, 53, 58, 59, 60, 62, 63, 64, 69, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 138, 139, 140, 141, 142, 145, 146, 147, 150, 152], "return_discard": 37, "return_el": 125, "reusabl": [0, 148, 151], "reuseabl": [147, 152], "review": 144, "rhel_7_x86_64": 149, "right": [14, 125, 147], "rmse": 125, "rmseloss": [122, 125], "rmsevonmisesfisher3dloss": [122, 125], "rng": 58, "rnn": [1, 79, 92, 112], "rnn_dropout": 92, "rnn_dynedg": 92, "rnn_hidden_s": 92, "rnn_layer": 92, "rnn_tito": [79, 91], "role": 152, "root": 125, "roughli": 146, "row": [59, 64, 104, 108, 121, 146, 147, 150, 152], "run": [1, 14, 50, 69, 145, 147, 149, 150, 152], "run_sql_cod": [56, 59], "runner": [87, 88, 89, 129], "runtim": [124, 149], "runtimeerror": 21, "ryabinin": 125, "sai": [147, 152], "same": [18, 37, 59, 80, 84, 108, 116, 121, 123, 135, 141, 146, 147, 152], "sampl": [14, 60, 83, 104, 105, 107, 147, 152], "sampler": [3, 10], "satisfi": [0, 145, 148, 151], "save": [7, 19, 21, 34, 39, 41, 43, 45, 47, 55, 59, 61, 62, 64, 109, 123, 125, 126, 127, 131, 132, 133, 134, 145, 147, 150], "save_config": [132, 147, 152], "save_dataset_config": [130, 133], "save_dir": [123, 147, 152], "save_fil": [62, 145], "save_method": [7, 145, 150], "save_model_config": [130, 134], "save_result": [122, 126], "save_select": [122, 126], "save_state_dict": [109, 147, 152], "save_to_sql": [56, 59], "scalabl": 146, "scalar": [11, 13, 19, 121, 125], "scale": [82, 83, 95, 98, 103, 104, 107, 108, 118, 120, 125, 146, 152], "scaled_emb": [98, 120], "scatter": [107, 108], "schedul": 110, "scheduler_class": [110, 147, 152], "scheduler_config": [110, 147, 152], "scheduler_kwarg": [110, 147, 152], "schema": 147, "scheme": [92, 94, 96, 99, 145], "scientif": [0, 1, 148, 151], "scope": 144, "script": [147, 152], "search": [45, 47, 49, 50, 51, 52, 53, 55, 139, 145], "sec": 125, "second": 103, "section": 147, "see": [82, 92, 102, 104, 110, 118, 123, 144, 146, 147, 149], "seed": [9, 11, 13, 16, 60, 104, 105, 126, 133, 146, 147], "seen": 82, "select": [5, 8, 9, 11, 13, 14, 16, 28, 60, 126, 127, 133, 144, 147, 150], "selection_nam": 8, "self": [11, 13, 90, 104, 110, 114, 131, 136, 145, 146, 147, 150, 152], "sell": [14, 125], "send": 118, "sensor": [86, 104, 146, 147, 150, 152], "sensor_i": 150, "sensor_id": [87, 89, 150], "sensor_id_column": [87, 88, 89, 150], "sensor_index_nam": 86, "sensor_mask": 104, "sensor_pos_i": [4, 89, 146, 147, 152], "sensor_pos_x": [4, 89, 146, 147, 152], "sensor_pos_z": [4, 89, 146, 147, 152], "sensor_position_nam": 86, "sensor_string_id": 89, "sensor_tim": 150, "sensor_x": [146, 150], "sensor_z": 150, "separ": [34, 103, 123, 147, 149], "seper": [112, 146], "seq_length": [82, 98, 120, 121], "sequenc": [14, 69, 82, 83, 108, 121, 126, 147, 152], "sequenti": [11, 13], "sequential_index": [11, 13, 16], "seri": [11, 13, 16, 22, 23, 35, 37, 59, 74, 92, 107, 112, 146, 147, 152], "serial": [145, 146], "serialis": [33, 34, 147, 152], "serv": 146, "session": [133, 134, 146, 147, 152], "set": [3, 6, 9, 13, 21, 23, 45, 47, 49, 50, 55, 62, 82, 83, 98, 107, 108, 109, 118, 124, 126, 144, 145, 147, 150, 152], "set_extractor": 49, "set_gcd": 21, "set_index": 150, "set_number_of_input": 107, "set_output_feature_nam": 107, "set_verbose_print_recurs": 109, "setlevel": 141, "setup": [9, 123, 149], "setuptool": 149, "sever": [147, 152], "sh": 149, "shall": [14, 125], "shape": [19, 103, 104, 107, 121, 125, 145, 146], "share": [90, 110, 114, 147, 152], "share_redirect": 5, "shared_step": [90, 110, 114], "sharelink": 5, "shell": 149, "should": [8, 11, 13, 16, 19, 21, 34, 60, 67, 70, 83, 84, 92, 98, 104, 105, 112, 121, 125, 126, 131, 133, 134, 136, 144, 145, 146, 147, 149, 150, 152], "show": [60, 123, 147], "shown": 147, "shuffl": [8, 9, 58, 63, 126, 146], "shutdown": 9, "sid": 5, "sigmoid": 152, "sign": 125, "signal": [74, 152], "signatur": [23, 37], "signific": 146, "significantli": 146, "signup": 147, "similar": [14, 23, 37, 107, 147, 152], "similarli": [37, 145, 146, 147, 152], "simpl": [0, 79, 90, 147, 148, 151, 152], "simplecoarsen": 80, "simplest": [147, 152], "simpli": [147, 152], "simul": [35, 43, 53, 66, 74, 147, 150], "sinc": [14, 74, 125, 147], "singl": [5, 11, 18, 62, 64, 84, 94, 99, 108, 124, 127, 133, 134, 145, 146, 147, 150, 152], "sinusoid": [82, 98, 120], "sinusoidalposemb": [81, 82], "sipm_i": [4, 88], "sipm_id": 88, "sipm_x": [4, 88], "sipm_z": [4, 88], "situat": 144, "size": [13, 14, 64, 82, 83, 84, 92, 94, 95, 96, 98, 99, 121, 129, 146], "skip": [36, 94, 99, 147], "skip_readout": [94, 99], "sklearn": [147, 152], "sk\u0142odowska": [0, 148, 151], "slack": 147, "slice": [83, 94, 99], "slower": 64, "small": [125, 146, 147, 152], "smaller": [62, 145], "smooth": 144, "snippet": [147, 152], "so": [14, 125, 146, 147, 149, 150, 152], "soft": 82, "softmax": 125, "softwar": [0, 14, 50, 125, 148, 151], "solut": [82, 83, 96, 98, 144], "solv": [1, 144, 152], "some": [11, 13, 14, 16, 45, 47, 50, 55, 104, 108, 146, 147], "someth": [147, 152], "somewhat": 147, "sort": [104, 108], "sort_bi": 104, "sota": 5, "sourc": [0, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 74, 76, 78, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142, 144, 146, 147, 148, 151], "south": 96, "space": [82, 102, 103, 118, 127], "space_coord": 103, "spacetim": 82, "spacetimeencod": [81, 82], "sparsetensor": 83, "spatial": 108, "spawn": [13, 14], "special": [23, 74, 112, 121], "specialis": [147, 152], "specif": [0, 1, 3, 5, 6, 7, 11, 13, 16, 17, 19, 22, 37, 48, 49, 50, 59, 64, 68, 70, 78, 80, 84, 85, 86, 87, 88, 89, 91, 92, 97, 102, 104, 107, 111, 115, 116, 117, 118, 119, 125, 144, 145, 146, 147, 148, 150, 151, 152], "specifi": [11, 13, 14, 16, 60, 80, 108, 110, 118, 123, 146, 147, 150, 152], "speed": [74, 103, 146], "sphere": 102, "spite": 125, "splinemp": 30, "split": [0, 9, 36, 64, 80, 148, 151], "split_se": 9, "splitinicepuls": 59, "sql": 127, "sqlite": [1, 3, 5, 9, 10, 16, 47, 55, 57, 59, 64, 66, 67, 146, 147], "sqlite3": 147, "sqlite_dataset": [10, 15, 146], "sqlite_util": [3, 56], "sqlite_writ": [3, 61], "sqlitedataconvert": [54, 55], "sqlitedatas": 146, "sqlitedataset": [9, 15, 16, 145], "sqlitewrit": [61, 64, 145, 146], "squar": 125, "src": [14, 147], "stabl": [117, 118], "stage": [9, 123], "standalon": 112, "standard": [0, 3, 4, 36, 60, 70, 87, 88, 89, 92, 104, 105, 107, 110, 113, 114, 118, 129, 144, 147, 148, 150, 151, 152], "standard_argu": 129, "standard_averaged_model": [1, 79], "standard_model": [1, 79, 147], "standardaveragedmodel": [79, 113], "standardaveragemodel": 113, "standardflowtask": [115, 118], "standardis": 85, "standardlearnedtask": [115, 116, 117, 118, 152], "standardmodel": [79, 90, 113, 114], "start": [14, 31, 144, 147, 150, 152], "state": [0, 70, 92, 112, 138, 148, 151], "state_dict": [70, 74, 76, 109, 113, 138, 147], "static": [125, 144], "std": 84, "std_pool": [81, 84], "std_pool_x": [81, 84], "stdout": 123, "step": [90, 110, 113, 114, 121, 123, 147, 150, 152], "still": 133, "stochast": 83, "stop": [31, 123, 129], "stopped_muon": 4, "store": [11, 13, 16, 59, 62, 63, 64, 124, 145, 146, 147, 150, 152], "str": [5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 74, 76, 83, 84, 86, 87, 88, 89, 90, 92, 94, 96, 98, 99, 104, 105, 107, 108, 109, 110, 113, 118, 121, 123, 124, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 139, 141, 145, 150], "straightforward": 146, "strategi": [147, 152], "stream_handl": 141, "streamhandl": 141, "streamlin": 1, "string": [4, 5, 11, 13, 16, 34, 60, 84, 86, 87, 104, 109, 110, 118, 131, 147, 150, 152], "string_id": 150, "string_id_column": [87, 88, 89, 150], "string_index_nam": 86, "string_mask": 104, "string_select": [11, 13, 16, 126, 133], "string_selection_resolv": [3, 56], "stringselectionresolv": [56, 60], "strongli": [147, 152], "structur": [90, 135, 145, 146, 147, 152], "style": 144, "sub": 147, "subclass": [0, 5, 79, 90, 145, 146, 147, 148, 151, 152], "subfold": [45, 47, 50, 55], "subject": [14, 98, 125], "sublicens": [14, 125], "submit": 98, "submodul": [1, 3, 10, 12, 15, 17, 20, 33, 38, 40, 42, 44, 46, 48, 54, 56, 61, 65, 68, 71, 73, 77, 79, 81, 85, 91, 100, 101, 106, 111, 115, 119, 122, 128, 130, 135], "subpackag": [1, 3, 10, 17, 20, 68, 79, 100, 128], "subsampl": [63, 146], "subsequ": 147, "subset": [11, 13, 16, 83, 92, 94, 96, 99, 112, 147], "substanti": [14, 125], "suggest": [90, 125, 147], "suit": [0, 110, 118, 147, 148, 151], "suitabl": [1, 150], "sum": [80, 84, 90, 94, 96, 99, 114, 127, 147, 152], "sum_pool": [80, 81, 84], "sum_pool_and_distribut": [81, 84], "sum_pool_x": [80, 81, 84], "summar": [74, 76, 107, 108], "summari": [107, 108], "summaris": [147, 152], "summariz": 152, "summarization_indic": 108, "super": [145, 146, 147, 152], "supervis": [114, 118, 152], "support": [0, 7, 37, 118, 144, 145, 146, 147, 148, 151], "suppos": [5, 108, 146, 150], "sure": [144, 145], "swa": 113, "swapabl": 147, "switch": [125, 147, 152], "synchron": 7, "syntax": [60, 90, 125, 146, 147], "system": [139, 147, 152], "t": [4, 37, 59, 123, 125, 145, 146, 147, 150, 152], "t_co": 8, "tabl": [5, 11, 13, 16, 18, 19, 21, 39, 41, 43, 49, 59, 63, 64, 86, 104, 127, 145, 146, 147], "table_nam": [43, 59], "table_without_index": 150, "tackl": 152, "tag": [126, 144], "take": [37, 84, 108, 112, 144, 146], "talk": 147, "tar": 5, "target": [90, 110, 116, 118, 125, 136, 147, 152], "target_label": [90, 110, 118, 147, 152], "target_norm": 118, "target_pr": [116, 152], "task": [0, 1, 9, 79, 90, 114, 116, 117, 125, 144, 147, 148, 151], "team": [144, 146, 147, 149, 150, 152], "teardown": 9, "technic": [0, 148, 150, 151], "techniqu": [0, 148, 151, 152], "telescop": [0, 1, 147, 148, 150, 151, 152], "tend": 64, "tensor": [11, 13, 16, 70, 80, 82, 83, 84, 86, 90, 92, 93, 94, 95, 96, 97, 98, 99, 103, 107, 110, 112, 113, 114, 118, 120, 121, 125, 138, 142, 146, 147, 150, 152], "term": [83, 125, 152], "termin": 147, "test": [5, 9, 60, 66, 67, 118, 126, 133, 140, 144, 146, 147, 152], "test_dataload": 9, "test_dataloader_kwarg": [5, 9, 66, 67], "test_dataset": [1, 65], "test_funct": 140, "test_select": [9, 133, 146, 147], "test_siz": 126, "testdataset": [65, 67], "tev": 66, "than": [0, 8, 118, 126, 141, 146, 147, 148, 151, 152], "thei": [69, 145, 146, 147, 152], "them": [0, 1, 34, 70, 79, 94, 118, 146, 147, 148, 150, 151, 152], "themselv": [1, 133, 134, 147, 152], "therebi": [1, 133, 134, 147, 152], "therefor": [34, 50, 145, 146, 147, 150, 152], "thi": [0, 3, 5, 7, 9, 11, 13, 14, 16, 18, 19, 21, 23, 37, 39, 41, 43, 45, 47, 49, 50, 55, 58, 59, 63, 64, 67, 74, 79, 82, 84, 90, 92, 94, 98, 99, 103, 104, 105, 107, 108, 110, 112, 114, 116, 117, 118, 121, 123, 125, 126, 127, 131, 133, 134, 136, 141, 144, 145, 146, 147, 148, 149, 150, 151, 152], "thing": 147, "thoglu": [110, 118], "those": [21, 146, 147], "thread": 13, "three": [99, 108, 125, 152], "threshold": [0, 74, 148, 151], "through": [0, 116, 117, 118, 125, 145, 147, 148, 151, 152], "throw": 145, "thu": [134, 152], "ti": 146, "time": [0, 4, 59, 80, 82, 84, 92, 103, 107, 108, 112, 117, 121, 127, 141, 146, 147, 148, 150, 151], "time_column": 107, "time_coord": 103, "time_lik": 103, "time_like_weight": 103, "time_series_column": [92, 112], "time_window": 80, "timereconstruct": [115, 117], "tini": 147, "tito": [83, 92, 96], "to_config": 152, "to_csv": [147, 152], "to_parquet": 150, "todo": 147, "togeth": [0, 14, 79, 102, 125, 148, 151], "token": 120, "too": [147, 152], "tool": [0, 1, 148, 151], "top": 152, "torch": [0, 11, 13, 16, 79, 83, 104, 105, 109, 110, 140, 146, 147, 148, 149, 150, 151, 152], "torch_cpu": 149, "torch_geometr": [84, 121, 146, 147, 152], "torch_lightn": 152, "tort": [14, 125], "total": [121, 126, 127, 146, 147, 150], "total_energi": [4, 146, 147, 152], "tqdmprogressbar": 123, "track": [0, 19, 21, 25, 39, 41, 43, 66, 117, 122, 124, 144, 145, 147, 148, 151], "tradit": [0, 148, 151], "train": [0, 1, 5, 7, 9, 10, 60, 65, 66, 67, 68, 74, 83, 90, 98, 104, 110, 113, 114, 121, 123, 124, 125, 126, 127, 129, 133, 134, 136, 143, 145, 146, 147, 148, 150, 151], "train_batch": [90, 113], "train_dataload": [9, 90, 147, 152], "train_dataloader_kwarg": [5, 9, 66, 67], "train_ev": 118, "train_select": [133, 146, 147], "train_val_split": 9, "trainabl": 134, "trainer": [90, 123, 126, 147, 152], "trainer_kwarg": 90, "training_config": [128, 130, 147, 152], "training_example_data_sqlit": [129, 146, 147, 152], "training_step": [90, 113], "trainingconfig": [130, 136, 147, 152], "transform": [1, 79, 83, 84, 96, 98, 112, 118, 120, 127, 147, 152], "transform_infer": [118, 147, 152], "transform_prediction_and_target": [118, 147, 152], "transform_support": [118, 147, 152], "transform_target": [118, 147, 152], "transit": 138, "transpar": [133, 134, 144, 147, 152], "transpos": 34, "transpose_list_of_dict": [33, 34], "traverse_and_appli": [130, 135], "treat": [92, 112], "tree": [23, 147], "tri": [23, 37], "triangl": 89, "trident": [66, 89], "trident1211": [85, 89], "tridentsmal": [65, 66], "trigger": [23, 146, 147, 152], "trivial": [37, 118], "true": [36, 59, 74, 92, 94, 96, 98, 99, 104, 107, 109, 123, 125, 127, 133, 134, 136, 139, 145, 146, 147, 152], "trust": [109, 147, 152], "truth": [3, 4, 5, 11, 13, 16, 22, 31, 43, 59, 63, 66, 67, 104, 118, 126, 127, 133, 146, 150, 152], "truth_dict": 104, "truth_label": 146, "truth_tabl": [5, 11, 13, 16, 63, 126, 127, 133, 146, 147], "truthdata": 41, "try": [37, 145], "tum": [25, 32], "tupl": [7, 11, 13, 14, 16, 35, 37, 59, 83, 92, 94, 96, 99, 108, 118, 121, 126, 129, 138], "turn": [108, 144], "tutorial_output": [147, 152], "two": [8, 94, 123, 125, 126, 145, 146, 147, 150], "txt": 149, "type": [0, 5, 7, 8, 9, 11, 13, 14, 16, 20, 21, 33, 34, 35, 41, 43, 49, 50, 51, 52, 53, 58, 59, 60, 62, 63, 64, 69, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 138, 139, 140, 141, 142, 144, 145, 146, 147, 148, 150, 151], "typic": [0, 34, 112, 146, 148, 150, 151], "u": [146, 150], "ultra": 146, "unaccur": 125, "unambigu": [133, 134], "unbatch_edge_index": [79, 80], "uncertainti": [117, 147, 152], "uncompress": 146, "under": [0, 147, 148, 150, 151, 152], "unfamiliar": 152, "uniform": [122, 127], "uniformweightfitt": 127, "union": [0, 7, 8, 9, 11, 13, 16, 23, 34, 37, 45, 47, 49, 50, 51, 52, 53, 55, 69, 70, 74, 76, 80, 83, 84, 90, 92, 94, 99, 104, 105, 110, 114, 118, 133, 136, 139, 145, 148, 150, 151], "uniqu": [11, 13, 16, 59, 107, 121, 133, 147, 150, 152], "unit": [0, 7, 67, 103, 140, 144, 148, 151], "univers": 96, "unlik": 146, "unscal": 152, "untransform": 116, "up": [0, 74, 144, 148, 151], "updat": [99, 112, 113, 121, 123, 147, 149, 152], "upgrad": [4, 22, 87, 147, 149], "upon": [110, 152], "us": [0, 1, 2, 4, 5, 7, 8, 9, 11, 12, 13, 14, 15, 16, 18, 19, 21, 26, 31, 33, 34, 39, 41, 43, 45, 47, 49, 50, 54, 55, 56, 59, 60, 62, 63, 64, 66, 67, 68, 70, 74, 76, 79, 82, 83, 84, 86, 90, 92, 94, 95, 96, 98, 99, 102, 104, 105, 107, 108, 109, 110, 112, 115, 116, 117, 118, 120, 121, 123, 124, 125, 127, 128, 129, 130, 133, 134, 135, 140, 141, 144, 145, 148, 149, 150, 151], "usabl": [0, 148, 151], "usag": [110, 118, 129], "use_cach": 60, "use_global_featur": [92, 96], "use_post_processing_lay": [92, 96], "user": [0, 5, 79, 90, 123, 146, 147, 148, 149, 151, 152], "usual": 146, "util": [1, 3, 17, 20, 34, 35, 36, 37, 57, 58, 59, 60, 79, 100, 122, 129, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142, 143, 146, 147, 149, 152], "v": 83, "v1": [131, 133, 134, 136, 149], "v4": 149, "val_batch": [90, 113], "val_dataload": [9, 90], "valid": [5, 9, 37, 60, 66, 67, 90, 110, 113, 114, 118, 123, 125, 129, 131, 136, 146, 147, 152], "validate_fil": 49, "validate_task": [90, 110, 114], "validation_dataloader_kwarg": [5, 9, 66, 67], "validation_step": [90, 113], "validationerror": [131, 136], "valu": [11, 13, 16, 31, 34, 59, 83, 84, 99, 103, 104, 105, 118, 121, 124, 125, 129, 131, 152], "valueerror": [23, 109, 110], "var": 117, "var1": 19, "var_n": 19, "variabl": [19, 21, 23, 37, 49, 94, 107, 108, 121, 127, 141, 145, 150, 152], "varieti": 147, "variou": [1, 61, 147], "vast": [114, 118], "vector": [80, 83, 84, 125, 145, 152], "verbos": [45, 47, 50, 55, 90, 114, 123], "verbose_print": 109, "veri": [60, 146, 147, 152], "verifi": [90, 110, 114], "versa": 123, "version": [84, 108, 118, 123, 144, 147, 152], "vertex": [117, 147], "vertex_i": 4, "vertex_x": 4, "vertex_z": 4, "vertexreconstruct": [115, 117], "viabl": 150, "vice": 123, "virtual": 149, "visit": 150, "vmf": 117, "vmf_loss": 125, "vmfs_factor": 125, "volum": 31, "von": 125, "vonmisesfisher2dloss": [122, 125, 147, 152], "vonmisesfisher3dloss": [122, 125], "vonmisesfisherloss": [122, 125], "w": [147, 152], "wa": [0, 7, 98, 146, 147, 148, 150, 151, 152], "wai": [14, 37, 60, 114, 144, 147, 150, 152], "wandb": [147, 152], "wandb_dir": [147, 152], "wandb_logg": [147, 152], "wandblogg": [147, 152], "want": [146, 147, 149, 150, 152], "warn": [141, 147], "warning_onc": [141, 147], "warranti": [14, 125], "waterdemo81": [85, 89], "wb": 145, "we": [34, 37, 60, 108, 110, 144, 147, 149, 150, 152], "weight": [11, 13, 16, 74, 76, 83, 98, 104, 118, 125, 127, 134, 147, 152], "weight_fit": [1, 122], "weight_nam": 127, "weightfitt": [122, 127], "well": [144, 147, 152], "wether": 99, "what": [1, 82, 104, 144, 147, 152], "whatev": 147, "wheel": 149, "when": [0, 11, 13, 14, 16, 34, 36, 59, 74, 83, 92, 94, 96, 99, 112, 124, 141, 144, 145, 146, 147, 148, 149, 150, 151, 152], "whenev": 149, "where": [19, 45, 47, 50, 55, 104, 105, 107, 108, 112, 121, 124, 145, 146, 147, 150, 152], "wherea": [127, 146], "whether": [8, 14, 35, 37, 59, 82, 83, 92, 94, 96, 98, 99, 109, 120, 125, 135, 139, 140, 147], "which": [0, 5, 11, 13, 16, 19, 21, 22, 31, 35, 39, 41, 43, 60, 62, 64, 69, 80, 84, 94, 99, 104, 105, 108, 109, 110, 116, 118, 121, 125, 126, 129, 145, 146, 147, 148, 151, 152], "while": [0, 23, 90, 123, 144, 146, 148, 151], "who": [5, 138, 147, 152], "whom": [14, 125], "whose": 74, "wide": [14, 110, 152], "width": 14, "willing": [146, 150], "window": [80, 146, 147], "wise": 84, "wish": [0, 69, 144, 148, 151], "with_standard_argu": 129, "within": [31, 80, 83, 84, 94, 99, 102, 147, 152], "without": [1, 14, 102, 105, 107, 125, 146, 149], "work": [0, 4, 35, 92, 144, 145, 146, 147, 148, 151, 152], "worker": [6, 7, 14, 45, 55, 58, 63, 69, 129, 141], "workflow": [0, 148, 151], "would": [144, 146, 147, 150, 152], "wrap": [123, 133, 134], "write": [63, 74, 76, 145, 147, 152], "writer": [1, 3, 47, 62, 63, 64, 150], "written": [47, 69, 145], "wrt": 118, "www": 147, "x": [4, 31, 82, 83, 84, 87, 103, 107, 108, 112, 118, 121, 125, 127, 146, 147, 150, 152], "x8": 146, "x_i": 83, "x_j": 83, "x_low": 127, "xyz": [86, 87, 88, 89, 107, 108, 146, 150], "xyz_coord": 121, "xyzt": 121, "y": [4, 31, 82, 87, 103, 121], "yaml": [131, 132, 147], "yield": [0, 94, 99, 125, 148, 151], "yml": [60, 129, 133, 134, 146, 147, 152], "you": [64, 69, 82, 110, 133, 134, 144, 146, 147, 149, 150, 152], "your": [105, 110, 144, 145, 146, 147, 149], "yourself": 144, "z": [4, 31, 82, 87, 103, 107, 108, 121], "z_name": 107, "z_offset": [107, 108], "z_scale": [107, 108], "zenith": [4, 117, 124, 147, 152], "zenith_kappa": 117, "zenith_kei": 124, "zenith_pr": 117, "zenithreconstruct": [115, 117], "zenithreconstructionwithkappa": [115, 117, 147, 152], "\u00f8rs\u00f8e": [0, 148, 151]}, "titles": ["Usage", "API", "constants", "data", "constants", "curated_datamodule", "dataclasses", "dataconverter", "dataloader", "datamodule", "dataset", "dataset", "parquet", "parquet_dataset", "samplers", "sqlite", "sqlite_dataset", "extractors", "combine_extractors", "extractor", "icecube", "i3extractor", "i3featureextractor", "i3genericextractor", "i3hybridrecoextractor", "i3ntmuonlabelsextractor", "i3particleextractor", "i3pisaextractor", "i3quesoextractor", "i3retroextractor", "i3splinempeextractor", "i3truthextractor", "i3tumextractor", "utilities", "collections", "frames", "i3_filters", "types", "internal", "parquet_extractor", "liquido", "h5_extractor", "prometheus", "prometheus_extractor", "parquet", "deprecated_methods", "pre_configured", "dataconverters", "readers", "graphnet_file_reader", "i3reader", "internal_parquet_reader", "liquido_reader", "prometheus_reader", "sqlite", "deprecated_methods", "utilities", "parquet_to_sqlite", "random", "sqlite_utilities", "string_selection_resolver", "writers", "graphnet_writer", "parquet_writer", "sqlite_writer", "datasets", "prometheus_datasets", "test_dataset", "deployment", "deployer", "deployment_module", "i3modules", "deprecated_methods", "icecube", "cleaning_module", "i3deployer", "inference_module", "exceptions", "exceptions", "models", "coarsening", "components", "embedding", "layers", "pool", "detector", "detector", "icecube", "liquido", "prometheus", "easy_model", "gnn", "RNN_tito", "convnet", "dynedge", "dynedge_jinst", "dynedge_kaggle_tito", "gnn", "icemix", "particlenet", "graphs", "edges", "edges", "minkowski", "graph_definition", "graphs", "nodes", "nodes", "utils", "model", "normalizing_flow", "rnn", "node_rnn", "standard_averaged_model", "standard_model", "task", "classification", "reconstruction", "task", "transformer", "iseecube", "utils", "training", "callbacks", "labels", "loss_functions", "utils", "weight_fitting", "utilities", "argparse", "config", "base_config", "configurable", "dataset_config", "model_config", "parsing", "training_config", "decorators", "deprecation_tools", "filesys", "imports", "logging", "maths", "src", "Contributing To GraphNeT", "Data Conversion in GraphNeT", "Datasets In GraphNeT", "GraphNeT tutorial", "GraphNeT", "Installation", "Integrating New Experiments into GraphNeT", "GraphNeT", "Models In GraphNeT", "<no title>"], "titleterms": {"1": 150, "2": 150, "In": [146, 152], "The": [147, 152], "To": 144, "acknowledg": 0, "ad": [146, 147, 150, 152], "advanc": 147, "api": 1, "appendix": 147, "appli": 150, "argpars": 129, "backbon": 152, "base_config": 131, "befor": 150, "callback": 123, "checkpoint": 152, "choos": 146, "class": [147, 150, 152], "classif": 116, "cleaning_modul": 74, "coarsen": 80, "code": 144, "collect": 34, "combin": [146, 147], "combine_extractor": 18, "compon": 81, "config": 130, "configur": 132, "constant": [2, 4], "content": 147, "contribut": 144, "convent": 144, "convers": 145, "convnet": 93, "creat": 147, "curated_datamodul": 5, "custom": [146, 147], "cvmf": 149, "data": [3, 145, 150], "dataclass": 6, "dataconfig": 147, "dataconvert": [7, 47, 145], "dataload": 8, "datamodul": 9, "dataset": [10, 11, 65, 146, 147], "dataset_config": 133, "datasetconfig": 147, "decor": 137, "deploy": [68, 69], "deployment_modul": 70, "deprecated_method": [45, 55, 72], "deprecation_tool": 138, "detector": [85, 86, 150], "dynedg": 94, "dynedge_jinst": 95, "dynedge_kaggle_tito": 96, "easy_model": 90, "edg": [101, 102], "embed": 82, "energi": 152, "event": 146, "exampl": [147, 150, 152], "except": [77, 78], "experi": [150, 152], "extractor": [17, 19, 145, 150], "filesi": 139, "frame": 35, "function": 147, "geometri": 150, "github": 144, "gnn": [91, 97], "graph": [100, 105], "graph_definit": 104, "graphdefinit": 152, "graphnet": 147, "graphnet_file_read": 49, "graphnet_writ": 62, "graphnetfileread": 150, "graphnetgraphnet": [144, 145, 146, 148, 150, 151, 152], "h5_extractor": 41, "i3_filt": 36, "i3deploy": 75, "i3extractor": 21, "i3featureextractor": 22, "i3genericextractor": 23, "i3hybridrecoextractor": 24, "i3modul": 71, "i3ntmuonlabelsextractor": 25, "i3particleextractor": 26, "i3pisaextractor": 27, "i3quesoextractor": 28, "i3read": 50, "i3retroextractor": 29, "i3splinempeextractor": 30, "i3truthextractor": 31, "i3tumextractor": 32, "icecub": [20, 73, 87, 149], "icemix": 98, "implement": [146, 150], "import": 140, "index": 150, "inference_modul": 76, "instal": 149, "instanti": 152, "integr": 150, "intern": 38, "internal_parquet_read": 51, "introduct": 147, "iseecub": 120, "issu": 144, "label": [124, 146, 147], "layer": 83, "liquido": [40, 88], "liquido_read": 52, "load": 152, "log": 141, "loss_funct": 125, "math": 142, "minkowski": 103, "model": [79, 109, 147, 152], "model_config": 134, "modelconfig": [147, 152], "multi": 150, "multipl": [146, 147], "new": [146, 150], "node": [106, 107], "node_rnn": 112, "normalizing_flow": 110, "overview": 147, "own": [150, 152], "parquet": [12, 44], "parquet_dataset": 13, "parquet_extractor": 39, "parquet_to_sqlit": 57, "parquet_writ": 63, "parquetdataset": 146, "pars": 135, "particlenet": 99, "pool": 84, "pre_configur": 46, "prometheu": [42, 89], "prometheus_dataset": 66, "prometheus_extractor": 43, "prometheus_read": 53, "pull": 144, "qualiti": 144, "quick": 149, "random": 58, "reader": [48, 145], "reconstruct": [117, 152], "reproduc": 147, "request": 144, "rnn": 111, "rnn_tito": 92, "sampler": 14, "save": 152, "select": 146, "sqlite": [15, 54], "sqlite_dataset": 16, "sqlite_util": 59, "sqlite_writ": 64, "sqlitedataset": [146, 147], "src": 143, "standard_averaged_model": 113, "standard_model": 114, "standardmodel": [147, 152], "start": 149, "state_dict": 152, "string_selection_resolv": 60, "subset": 146, "support": 150, "syntax": 152, "tabl": 150, "task": [115, 118, 152], "test_dataset": 67, "track": 152, "train": [122, 152], "training_config": 136, "transform": 119, "truth": 147, "tutori": 147, "type": 37, "us": [146, 147, 152], "usag": 0, "util": [33, 56, 108, 121, 126, 128], "v": 146, "weight_fit": 127, "write": 150, "writer": [61, 145], "your": [150, 152]}}) \ No newline at end of file +Search.setIndex({"alltitles": {"1) Adding Support for Your Data": [[150, "adding-support-for-your-data"]], "2) Implementing a Detector Class": [[150, "implementing-a-detector-class"]], "API": [[1, null]], "Acknowledgements": [[0, "acknowledgements"]], "Adding Your Own Model": [[152, "adding-your-own-model"]], "Adding custom Labels": [[146, "adding-custom-labels"]], "Adding custom truth labels": [[147, "adding-custom-truth-labels"]], "Advanced Functionality in SQLiteDataset": [[147, "advanced-functionality-in-sqlitedataset"]], "Appendix": [[147, "appendix"]], "Choosing a subset of events using selection": [[146, "choosing-a-subset-of-events-using-selection"]], "Code quality": [[144, "code-quality"]], "Combining Multiple Datasets": [[146, "combining-multiple-datasets"], [147, "combining-multiple-datasets"]], "Contents": [[147, "contents"]], "Contributing To GraphNeTgraphnet": [[144, null]], "Conventions": [[144, "conventions"]], "Creating reproducible Datasets using DatasetConfig": [[147, "creating-reproducible-datasets-using-datasetconfig"]], "Creating reproducible Models using ModelConfig": [[147, "creating-reproducible-models-using-modelconfig"]], "Data Conversion in GraphNeTgraphnet": [[145, null]], "DataConverter": [[145, "dataconverter"]], "Dataset": [[146, "dataset"]], "Datasets In GraphNeTgraphnet": [[146, null]], "Example DataConfig": [[147, "example-dataconfig"]], "Example ModelConfig": [[147, "example-modelconfig"]], "Example of geometry table before applying multi-index": [[150, "id1"]], "Example: Energy Reconstruction using ModelConfig": [[152, "example-energy-reconstruction-using-modelconfig"]], "Experiment Tracking": [[152, "experiment-tracking"]], "Extractors": [[145, "extractors"]], "GitHub issues": [[144, "github-issues"]], "GraphDefinition, backbone & Task": [[152, "graphdefinition-backbone-task"]], "GraphNeT tutorial": [[147, null]], "GraphNeTgraphnet": [[148, null], [151, null]], "Implementing a new Dataset": [[146, "implementing-a-new-dataset"]], "Installation": [[149, null]], "Installation in CVMFS (IceCube)": [[149, "installation-in-cvmfs-icecube"]], "Instantiating a StandardModel": [[152, "instantiating-a-standardmodel"]], "Integrating New Experiments into GraphNeTgraphnet": [[150, null]], "Introduction": [[147, "introduction"]], "Model.save": [[152, "model-save"]], "ModelConfig and state_dict": [[152, "modelconfig-and-state-dict"]], "Models In GraphNeTgraphnet": [[152, null]], "Overview of GraphNeT": [[147, "overview-of-graphnet"]], "Pull requests": [[144, "pull-requests"]], "Quick Start": [[149, "quick-start"]], "RNN_tito": [[92, null]], "Readers": [[145, "readers"]], "SQLiteDataset & ParquetDataset": [[146, "sqlitedataset-parquetdataset"]], "SQLiteDataset vs. ParquetDataset": [[146, "sqlitedataset-vs-parquetdataset"]], "Saving, loading, and checkpointing Models": [[152, "saving-loading-and-checkpointing-models"]], "The Model class": [[147, "the-model-class"], [152, "the-model-class"]], "The StandardModel class": [[147, "the-standardmodel-class"], [152, "the-standardmodel-class"]], "Training Syntax for StandardModel": [[152, "training-syntax-for-standardmodel"]], "Usage": [[0, null]], "Using checkpoints": [[152, "using-checkpoints"]], "Writers": [[145, "writers"]], "Writing your own Extractor and GraphNeTFileReader": [[150, "writing-your-own-extractor-and-graphnetfilereader"]], "argparse": [[129, null]], "base_config": [[131, null]], "callbacks": [[123, null]], "classification": [[116, null]], "cleaning_module": [[74, null]], "coarsening": [[80, null]], "collections": [[34, null]], "combine_extractors": [[18, null]], "components": [[81, null]], "config": [[130, null]], "configurable": [[132, null]], "constants": [[2, null], [4, null]], "convnet": [[93, null]], "curated_datamodule": [[5, null]], "data": [[3, null]], "dataclasses": [[6, null]], "dataconverter": [[7, null]], "dataconverters": [[47, null]], "dataloader": [[8, null]], "datamodule": [[9, null]], "dataset": [[10, null], [11, null]], "dataset_config": [[133, null]], "datasets": [[65, null]], "decorators": [[137, null]], "deployer": [[69, null]], "deployment": [[68, null]], "deployment_module": [[70, null]], "deprecated_methods": [[45, null], [55, null], [72, null]], "deprecation_tools": [[138, null]], "detector": [[85, null], [86, null]], "dynedge": [[94, null]], "dynedge_jinst": [[95, null]], "dynedge_kaggle_tito": [[96, null]], "easy_model": [[90, null]], "edges": [[101, null], [102, null]], "embedding": [[82, null]], "exceptions": [[77, null], [78, null]], "extractor": [[19, null]], "extractors": [[17, null]], "filesys": [[139, null]], "frames": [[35, null]], "gnn": [[91, null], [97, null]], "graph_definition": [[104, null]], "graphnet_file_reader": [[49, null]], "graphnet_writer": [[62, null]], "graphs": [[100, null], [105, null]], "h5_extractor": [[41, null]], "i3_filters": [[36, null]], "i3deployer": [[75, null]], "i3extractor": [[21, null]], "i3featureextractor": [[22, null]], "i3genericextractor": [[23, null]], "i3hybridrecoextractor": [[24, null]], "i3modules": [[71, null]], "i3ntmuonlabelsextractor": [[25, null]], "i3particleextractor": [[26, null]], "i3pisaextractor": [[27, null]], "i3quesoextractor": [[28, null]], "i3reader": [[50, null]], "i3retroextractor": [[29, null]], "i3splinempeextractor": [[30, null]], "i3truthextractor": [[31, null]], "i3tumextractor": [[32, null]], "icecube": [[20, null], [73, null], [87, null]], "icemix": [[98, null]], "imports": [[140, null]], "inference_module": [[76, null]], "internal": [[38, null]], "internal_parquet_reader": [[51, null]], "iseecube": [[120, null]], "labels": [[124, null]], "layers": [[83, null]], "liquido": [[40, null], [88, null]], "liquido_reader": [[52, null]], "logging": [[141, null]], "loss_functions": [[125, null]], "maths": [[142, null]], "minkowski": [[103, null]], "model": [[109, null]], "model_config": [[134, null]], "models": [[79, null]], "node_rnn": [[112, null]], "nodes": [[106, null], [107, null]], "normalizing_flow": [[110, null]], "parquet": [[12, null], [44, null]], "parquet_dataset": [[13, null]], "parquet_extractor": [[39, null]], "parquet_to_sqlite": [[57, null]], "parquet_writer": [[63, null]], "parsing": [[135, null]], "particlenet": [[99, null]], "pool": [[84, null]], "pre_configured": [[46, null]], "prometheus": [[42, null], [89, null]], "prometheus_datasets": [[66, null]], "prometheus_extractor": [[43, null]], "prometheus_reader": [[53, null]], "random": [[58, null]], "readers": [[48, null]], "reconstruction": [[117, null]], "rnn": [[111, null]], "samplers": [[14, null]], "sqlite": [[15, null], [54, null]], "sqlite_dataset": [[16, null]], "sqlite_utilities": [[59, null]], "sqlite_writer": [[64, null]], "src": [[143, null]], "standard_averaged_model": [[113, null]], "standard_model": [[114, null]], "string_selection_resolver": [[60, null]], "task": [[115, null], [118, null]], "test_dataset": [[67, null]], "training": [[122, null]], "training_config": [[136, null]], "transformer": [[119, null]], "types": [[37, null]], "utilities": [[33, null], [56, null], [128, null]], "utils": [[108, null], [121, null], [126, null]], "weight_fitting": [[127, null]], "writers": [[61, null]]}, "docnames": ["about/about", "api/graphnet", "api/graphnet.constants", "api/graphnet.data", "api/graphnet.data.constants", "api/graphnet.data.curated_datamodule", "api/graphnet.data.dataclasses", "api/graphnet.data.dataconverter", "api/graphnet.data.dataloader", "api/graphnet.data.datamodule", "api/graphnet.data.dataset", "api/graphnet.data.dataset.dataset", "api/graphnet.data.dataset.parquet", "api/graphnet.data.dataset.parquet.parquet_dataset", "api/graphnet.data.dataset.samplers", "api/graphnet.data.dataset.sqlite", "api/graphnet.data.dataset.sqlite.sqlite_dataset", "api/graphnet.data.extractors", "api/graphnet.data.extractors.combine_extractors", "api/graphnet.data.extractors.extractor", "api/graphnet.data.extractors.icecube", "api/graphnet.data.extractors.icecube.i3extractor", "api/graphnet.data.extractors.icecube.i3featureextractor", "api/graphnet.data.extractors.icecube.i3genericextractor", "api/graphnet.data.extractors.icecube.i3hybridrecoextractor", "api/graphnet.data.extractors.icecube.i3ntmuonlabelsextractor", "api/graphnet.data.extractors.icecube.i3particleextractor", "api/graphnet.data.extractors.icecube.i3pisaextractor", "api/graphnet.data.extractors.icecube.i3quesoextractor", "api/graphnet.data.extractors.icecube.i3retroextractor", "api/graphnet.data.extractors.icecube.i3splinempeextractor", "api/graphnet.data.extractors.icecube.i3truthextractor", "api/graphnet.data.extractors.icecube.i3tumextractor", "api/graphnet.data.extractors.icecube.utilities", "api/graphnet.data.extractors.icecube.utilities.collections", "api/graphnet.data.extractors.icecube.utilities.frames", "api/graphnet.data.extractors.icecube.utilities.i3_filters", "api/graphnet.data.extractors.icecube.utilities.types", "api/graphnet.data.extractors.internal", "api/graphnet.data.extractors.internal.parquet_extractor", "api/graphnet.data.extractors.liquido", "api/graphnet.data.extractors.liquido.h5_extractor", "api/graphnet.data.extractors.prometheus", "api/graphnet.data.extractors.prometheus.prometheus_extractor", "api/graphnet.data.parquet", "api/graphnet.data.parquet.deprecated_methods", "api/graphnet.data.pre_configured", "api/graphnet.data.pre_configured.dataconverters", "api/graphnet.data.readers", "api/graphnet.data.readers.graphnet_file_reader", "api/graphnet.data.readers.i3reader", "api/graphnet.data.readers.internal_parquet_reader", "api/graphnet.data.readers.liquido_reader", "api/graphnet.data.readers.prometheus_reader", "api/graphnet.data.sqlite", "api/graphnet.data.sqlite.deprecated_methods", "api/graphnet.data.utilities", "api/graphnet.data.utilities.parquet_to_sqlite", "api/graphnet.data.utilities.random", "api/graphnet.data.utilities.sqlite_utilities", "api/graphnet.data.utilities.string_selection_resolver", "api/graphnet.data.writers", "api/graphnet.data.writers.graphnet_writer", "api/graphnet.data.writers.parquet_writer", "api/graphnet.data.writers.sqlite_writer", "api/graphnet.datasets", "api/graphnet.datasets.prometheus_datasets", "api/graphnet.datasets.test_dataset", "api/graphnet.deployment", "api/graphnet.deployment.deployer", "api/graphnet.deployment.deployment_module", "api/graphnet.deployment.i3modules", "api/graphnet.deployment.i3modules.deprecated_methods", "api/graphnet.deployment.icecube", "api/graphnet.deployment.icecube.cleaning_module", "api/graphnet.deployment.icecube.i3deployer", "api/graphnet.deployment.icecube.inference_module", "api/graphnet.exceptions", "api/graphnet.exceptions.exceptions", "api/graphnet.models", "api/graphnet.models.coarsening", "api/graphnet.models.components", "api/graphnet.models.components.embedding", "api/graphnet.models.components.layers", "api/graphnet.models.components.pool", "api/graphnet.models.detector", "api/graphnet.models.detector.detector", "api/graphnet.models.detector.icecube", "api/graphnet.models.detector.liquido", "api/graphnet.models.detector.prometheus", "api/graphnet.models.easy_model", "api/graphnet.models.gnn", "api/graphnet.models.gnn.RNN_tito", "api/graphnet.models.gnn.convnet", "api/graphnet.models.gnn.dynedge", "api/graphnet.models.gnn.dynedge_jinst", "api/graphnet.models.gnn.dynedge_kaggle_tito", "api/graphnet.models.gnn.gnn", "api/graphnet.models.gnn.icemix", "api/graphnet.models.gnn.particlenet", "api/graphnet.models.graphs", "api/graphnet.models.graphs.edges", "api/graphnet.models.graphs.edges.edges", "api/graphnet.models.graphs.edges.minkowski", "api/graphnet.models.graphs.graph_definition", "api/graphnet.models.graphs.graphs", "api/graphnet.models.graphs.nodes", "api/graphnet.models.graphs.nodes.nodes", "api/graphnet.models.graphs.utils", "api/graphnet.models.model", "api/graphnet.models.normalizing_flow", "api/graphnet.models.rnn", "api/graphnet.models.rnn.node_rnn", "api/graphnet.models.standard_averaged_model", "api/graphnet.models.standard_model", "api/graphnet.models.task", "api/graphnet.models.task.classification", "api/graphnet.models.task.reconstruction", "api/graphnet.models.task.task", "api/graphnet.models.transformer", "api/graphnet.models.transformer.iseecube", "api/graphnet.models.utils", "api/graphnet.training", "api/graphnet.training.callbacks", "api/graphnet.training.labels", "api/graphnet.training.loss_functions", "api/graphnet.training.utils", "api/graphnet.training.weight_fitting", "api/graphnet.utilities", "api/graphnet.utilities.argparse", "api/graphnet.utilities.config", "api/graphnet.utilities.config.base_config", "api/graphnet.utilities.config.configurable", "api/graphnet.utilities.config.dataset_config", "api/graphnet.utilities.config.model_config", "api/graphnet.utilities.config.parsing", "api/graphnet.utilities.config.training_config", "api/graphnet.utilities.decorators", "api/graphnet.utilities.deprecation_tools", "api/graphnet.utilities.filesys", "api/graphnet.utilities.imports", "api/graphnet.utilities.logging", "api/graphnet.utilities.maths", "api/modules", "contribute/contribute", "data_conversion/data_conversion", "datasets/datasets", "getting_started/getting_started", "index", "installation/install", "integration/integration", "intro/intro", "models/models", "substitutions"], "envversion": {"sphinx": 64, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinx.ext.todo": 2, "sphinx.ext.viewcode": 1}, "filenames": ["about/about.rst", "api/graphnet.rst", "api/graphnet.constants.rst", "api/graphnet.data.rst", "api/graphnet.data.constants.rst", "api/graphnet.data.curated_datamodule.rst", "api/graphnet.data.dataclasses.rst", "api/graphnet.data.dataconverter.rst", "api/graphnet.data.dataloader.rst", "api/graphnet.data.datamodule.rst", "api/graphnet.data.dataset.rst", "api/graphnet.data.dataset.dataset.rst", "api/graphnet.data.dataset.parquet.rst", "api/graphnet.data.dataset.parquet.parquet_dataset.rst", "api/graphnet.data.dataset.samplers.rst", "api/graphnet.data.dataset.sqlite.rst", "api/graphnet.data.dataset.sqlite.sqlite_dataset.rst", "api/graphnet.data.extractors.rst", "api/graphnet.data.extractors.combine_extractors.rst", "api/graphnet.data.extractors.extractor.rst", "api/graphnet.data.extractors.icecube.rst", "api/graphnet.data.extractors.icecube.i3extractor.rst", "api/graphnet.data.extractors.icecube.i3featureextractor.rst", "api/graphnet.data.extractors.icecube.i3genericextractor.rst", "api/graphnet.data.extractors.icecube.i3hybridrecoextractor.rst", "api/graphnet.data.extractors.icecube.i3ntmuonlabelsextractor.rst", "api/graphnet.data.extractors.icecube.i3particleextractor.rst", "api/graphnet.data.extractors.icecube.i3pisaextractor.rst", "api/graphnet.data.extractors.icecube.i3quesoextractor.rst", "api/graphnet.data.extractors.icecube.i3retroextractor.rst", "api/graphnet.data.extractors.icecube.i3splinempeextractor.rst", "api/graphnet.data.extractors.icecube.i3truthextractor.rst", "api/graphnet.data.extractors.icecube.i3tumextractor.rst", "api/graphnet.data.extractors.icecube.utilities.rst", "api/graphnet.data.extractors.icecube.utilities.collections.rst", "api/graphnet.data.extractors.icecube.utilities.frames.rst", "api/graphnet.data.extractors.icecube.utilities.i3_filters.rst", "api/graphnet.data.extractors.icecube.utilities.types.rst", "api/graphnet.data.extractors.internal.rst", "api/graphnet.data.extractors.internal.parquet_extractor.rst", "api/graphnet.data.extractors.liquido.rst", "api/graphnet.data.extractors.liquido.h5_extractor.rst", "api/graphnet.data.extractors.prometheus.rst", "api/graphnet.data.extractors.prometheus.prometheus_extractor.rst", "api/graphnet.data.parquet.rst", "api/graphnet.data.parquet.deprecated_methods.rst", "api/graphnet.data.pre_configured.rst", "api/graphnet.data.pre_configured.dataconverters.rst", "api/graphnet.data.readers.rst", "api/graphnet.data.readers.graphnet_file_reader.rst", "api/graphnet.data.readers.i3reader.rst", "api/graphnet.data.readers.internal_parquet_reader.rst", "api/graphnet.data.readers.liquido_reader.rst", "api/graphnet.data.readers.prometheus_reader.rst", "api/graphnet.data.sqlite.rst", "api/graphnet.data.sqlite.deprecated_methods.rst", "api/graphnet.data.utilities.rst", "api/graphnet.data.utilities.parquet_to_sqlite.rst", "api/graphnet.data.utilities.random.rst", "api/graphnet.data.utilities.sqlite_utilities.rst", "api/graphnet.data.utilities.string_selection_resolver.rst", "api/graphnet.data.writers.rst", "api/graphnet.data.writers.graphnet_writer.rst", "api/graphnet.data.writers.parquet_writer.rst", "api/graphnet.data.writers.sqlite_writer.rst", "api/graphnet.datasets.rst", "api/graphnet.datasets.prometheus_datasets.rst", "api/graphnet.datasets.test_dataset.rst", "api/graphnet.deployment.rst", "api/graphnet.deployment.deployer.rst", "api/graphnet.deployment.deployment_module.rst", "api/graphnet.deployment.i3modules.rst", "api/graphnet.deployment.i3modules.deprecated_methods.rst", "api/graphnet.deployment.icecube.rst", "api/graphnet.deployment.icecube.cleaning_module.rst", "api/graphnet.deployment.icecube.i3deployer.rst", "api/graphnet.deployment.icecube.inference_module.rst", "api/graphnet.exceptions.rst", "api/graphnet.exceptions.exceptions.rst", "api/graphnet.models.rst", "api/graphnet.models.coarsening.rst", "api/graphnet.models.components.rst", "api/graphnet.models.components.embedding.rst", "api/graphnet.models.components.layers.rst", "api/graphnet.models.components.pool.rst", "api/graphnet.models.detector.rst", "api/graphnet.models.detector.detector.rst", "api/graphnet.models.detector.icecube.rst", "api/graphnet.models.detector.liquido.rst", "api/graphnet.models.detector.prometheus.rst", "api/graphnet.models.easy_model.rst", "api/graphnet.models.gnn.rst", "api/graphnet.models.gnn.RNN_tito.rst", "api/graphnet.models.gnn.convnet.rst", "api/graphnet.models.gnn.dynedge.rst", "api/graphnet.models.gnn.dynedge_jinst.rst", "api/graphnet.models.gnn.dynedge_kaggle_tito.rst", "api/graphnet.models.gnn.gnn.rst", "api/graphnet.models.gnn.icemix.rst", "api/graphnet.models.gnn.particlenet.rst", "api/graphnet.models.graphs.rst", "api/graphnet.models.graphs.edges.rst", "api/graphnet.models.graphs.edges.edges.rst", "api/graphnet.models.graphs.edges.minkowski.rst", "api/graphnet.models.graphs.graph_definition.rst", "api/graphnet.models.graphs.graphs.rst", "api/graphnet.models.graphs.nodes.rst", "api/graphnet.models.graphs.nodes.nodes.rst", "api/graphnet.models.graphs.utils.rst", "api/graphnet.models.model.rst", "api/graphnet.models.normalizing_flow.rst", "api/graphnet.models.rnn.rst", "api/graphnet.models.rnn.node_rnn.rst", "api/graphnet.models.standard_averaged_model.rst", "api/graphnet.models.standard_model.rst", "api/graphnet.models.task.rst", "api/graphnet.models.task.classification.rst", "api/graphnet.models.task.reconstruction.rst", "api/graphnet.models.task.task.rst", "api/graphnet.models.transformer.rst", "api/graphnet.models.transformer.iseecube.rst", "api/graphnet.models.utils.rst", "api/graphnet.training.rst", "api/graphnet.training.callbacks.rst", "api/graphnet.training.labels.rst", "api/graphnet.training.loss_functions.rst", "api/graphnet.training.utils.rst", "api/graphnet.training.weight_fitting.rst", "api/graphnet.utilities.rst", "api/graphnet.utilities.argparse.rst", "api/graphnet.utilities.config.rst", "api/graphnet.utilities.config.base_config.rst", "api/graphnet.utilities.config.configurable.rst", "api/graphnet.utilities.config.dataset_config.rst", "api/graphnet.utilities.config.model_config.rst", "api/graphnet.utilities.config.parsing.rst", "api/graphnet.utilities.config.training_config.rst", "api/graphnet.utilities.decorators.rst", "api/graphnet.utilities.deprecation_tools.rst", "api/graphnet.utilities.filesys.rst", "api/graphnet.utilities.imports.rst", "api/graphnet.utilities.logging.rst", "api/graphnet.utilities.maths.rst", "api/modules.rst", "contribute/contribute.rst", "data_conversion/data_conversion.rst", "datasets/datasets.rst", "getting_started/getting_started.md", "index.rst", "installation/install.rst", "integration/integration.rst", "intro/intro.rst", "models/models.rst", "substitutions.rst"], "indexentries": {"accepted_extractors (graphnet.data.readers.graphnet_file_reader.graphnetfilereader property)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.accepted_extractors", false]], "accepted_file_extensions (graphnet.data.readers.graphnet_file_reader.graphnetfilereader property)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.accepted_file_extensions", false]], "add_charge_threshold_summary() (graphnet.models.graphs.utils.cluster_and_pad method)": [[108, "graphnet.models.graphs.utils.cluster_and_pad.add_charge_threshold_summary", false]], "add_counts() (graphnet.models.graphs.utils.cluster_and_pad method)": [[108, "graphnet.models.graphs.utils.cluster_and_pad.add_counts", false]], "add_label() (graphnet.data.dataset.dataset.dataset method)": [[11, "graphnet.data.dataset.dataset.Dataset.add_label", false]], "add_mean() (graphnet.models.graphs.utils.cluster_and_pad method)": [[108, "graphnet.models.graphs.utils.cluster_and_pad.add_mean", false]], "add_percentile_summary() (graphnet.models.graphs.utils.cluster_and_pad method)": [[108, "graphnet.models.graphs.utils.cluster_and_pad.add_percentile_summary", false]], "add_std() (graphnet.models.graphs.utils.cluster_and_pad method)": [[108, "graphnet.models.graphs.utils.cluster_and_pad.add_std", false]], "add_sum_charge() (graphnet.models.graphs.utils.cluster_and_pad method)": [[108, "graphnet.models.graphs.utils.cluster_and_pad.add_sum_charge", false]], "arca115 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.ARCA115", false]], "argumentparser (class in graphnet.utilities.argparse)": [[129, "graphnet.utilities.argparse.ArgumentParser", false]], "arguments (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.arguments", false]], "array_to_sequence() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.array_to_sequence", false]], "as_dict() (graphnet.utilities.config.base_config.baseconfig method)": [[131, "graphnet.utilities.config.base_config.BaseConfig.as_dict", false]], "as_dict() (graphnet.utilities.config.dataset_config.datasetconfig method)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.as_dict", false]], "as_dict() (graphnet.utilities.config.model_config.modelconfig method)": [[134, "graphnet.utilities.config.model_config.ModelConfig.as_dict", false]], "attach_index() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.attach_index", false]], "attention_rel (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Attention_rel", false]], "attributecoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.AttributeCoarsening", false]], "available_backends (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.available_backends", false]], "azimuthreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction", false]], "azimuthreconstructionwithkappa (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa", false]], "backward() (graphnet.training.loss_functions.logcmk static method)": [[125, "graphnet.training.loss_functions.LogCMK.backward", false]], "baikalgvd8 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8", false]], "baikalgvdsmall (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.BaikalGVDSmall", false]], "baseconfig (class in graphnet.utilities.config.base_config)": [[131, "graphnet.utilities.config.base_config.BaseConfig", false]], "binaryclassificationtask (class in graphnet.models.task.classification)": [[116, "graphnet.models.task.classification.BinaryClassificationTask", false]], "binaryclassificationtasklogits (class in graphnet.models.task.classification)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits", false]], "binarycrossentropyloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.BinaryCrossEntropyLoss", false]], "bjoernlow (class in graphnet.training.weight_fitting)": [[127, "graphnet.training.weight_fitting.BjoernLow", false]], "block (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Block", false]], "block_rel (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Block_rel", false]], "break_cyclic_recursion() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.break_cyclic_recursion", false]], "calculate_distance_matrix() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.calculate_distance_matrix", false]], "calculate_xyzt_homophily() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.calculate_xyzt_homophily", false]], "cast_object_to_pure_python() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.cast_object_to_pure_python", false]], "cast_pulse_series_to_pure_python() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.cast_pulse_series_to_pure_python", false]], "chunk_sizes (graphnet.data.dataset.parquet.parquet_dataset.parquetdataset property)": [[13, "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset.chunk_sizes", false]], "chunks (graphnet.data.dataset.samplers.randomchunksampler property)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler.chunks", false]], "citation (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.citation", false]], "class_name (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.class_name", false]], "clean_up_data_object() (graphnet.models.rnn.node_rnn.node_rnn method)": [[112, "graphnet.models.rnn.node_rnn.Node_RNN.clean_up_data_object", false]], "cluster_and_pad (class in graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.cluster_and_pad", false]], "cluster_summarize_with_percentiles() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.cluster_summarize_with_percentiles", false]], "coarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.Coarsening", false]], "collate_fn() (in module graphnet.data.dataloader)": [[8, "graphnet.data.dataloader.collate_fn", false]], "collate_fn() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.collate_fn", false]], "collator_sequence_buckleting (class in graphnet.training.utils)": [[126, "graphnet.training.utils.collator_sequence_buckleting", false]], "columnmissingexception": [[78, "graphnet.exceptions.exceptions.ColumnMissingException", false]], "combinedextractor (class in graphnet.data.extractors.combine_extractors)": [[18, "graphnet.data.extractors.combine_extractors.CombinedExtractor", false]], "comments (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.comments", false]], "compute_loss() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.compute_loss", false]], "compute_loss() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.compute_loss", false]], "compute_loss() (graphnet.models.task.task.learnedtask method)": [[118, "graphnet.models.task.task.LearnedTask.compute_loss", false]], "compute_loss() (graphnet.models.task.task.standardlearnedtask method)": [[118, "graphnet.models.task.task.StandardLearnedTask.compute_loss", false]], "compute_minkowski_distance_mat() (in module graphnet.models.graphs.edges.minkowski)": [[103, "graphnet.models.graphs.edges.minkowski.compute_minkowski_distance_mat", false]], "concatenate() (graphnet.data.dataset.dataset.dataset class method)": [[11, "graphnet.data.dataset.dataset.Dataset.concatenate", false]], "config (graphnet.utilities.config.configurable.configurable property)": [[132, "graphnet.utilities.config.configurable.Configurable.config", false]], "configurable (class in graphnet.utilities.config.configurable)": [[132, "graphnet.utilities.config.configurable.Configurable", false]], "configure_optimizers() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.configure_optimizers", false]], "contains() (graphnet.utilities.argparse.options method)": [[129, "graphnet.utilities.argparse.Options.contains", false]], "convnet (class in graphnet.models.gnn.convnet)": [[93, "graphnet.models.gnn.convnet.ConvNet", false]], "create_table() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.create_table", false]], "create_table_and_save_to_sql() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.create_table_and_save_to_sql", false]], "creator (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.creator", false]], "critical() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.critical", false]], "crossentropyloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.CrossEntropyLoss", false]], "curateddataset (class in graphnet.data.curated_datamodule)": [[5, "graphnet.data.curated_datamodule.CuratedDataset", false]], "customdomcoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.CustomDOMCoarsening", false]], "data_source (graphnet.data.dataset.samplers.randomchunksampler property)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler.data_source", false]], "database_exists() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.database_exists", false]], "database_table_exists() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.database_table_exists", false]], "dataconverter (class in graphnet.data.dataconverter)": [[7, "graphnet.data.dataconverter.DataConverter", false]], "dataloader (class in graphnet.data.dataloader)": [[8, "graphnet.data.dataloader.DataLoader", false]], "dataloader (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.dataloader", false]], "dataset (class in graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.Dataset", false]], "dataset_dir (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.dataset_dir", false]], "datasetconfig (class in graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig", false]], "datasetconfigsaverabcmeta (class in graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfigSaverABCMeta", false]], "datasetconfigsavermeta (class in graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfigSaverMeta", false]], "debug() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.debug", false]], "deepcore (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.DEEPCORE", false]], "deepcore (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.DEEPCORE", false]], "deepice (class in graphnet.models.gnn.icemix)": [[98, "graphnet.models.gnn.icemix.DeepIce", false]], "default_prediction_labels (graphnet.models.task.classification.binaryclassificationtask attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTask.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.classification.binaryclassificationtasklogits attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.azimuthreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.azimuthreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.directionreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energyreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energyreconstructionwithpower attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energyreconstructionwithuncertainty attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.energytcreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.inelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.positionreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.timereconstruction attribute)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.vertexreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.visibleinelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VisibleInelasticityReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.zenithreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.reconstruction.zenithreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.task.identitytask property)": [[118, "graphnet.models.task.task.IdentityTask.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.task.standardflowtask property)": [[118, "graphnet.models.task.task.StandardFlowTask.default_prediction_labels", false]], "default_prediction_labels (graphnet.models.task.task.task property)": [[118, "graphnet.models.task.task.Task.default_prediction_labels", false]], "default_target_labels (graphnet.models.task.classification.binaryclassificationtask attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTask.default_target_labels", false]], "default_target_labels (graphnet.models.task.classification.binaryclassificationtasklogits attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.azimuthreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.azimuthreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.directionreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energyreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energyreconstructionwithpower attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energyreconstructionwithuncertainty attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.energytcreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.inelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.positionreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.timereconstruction attribute)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.vertexreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.visibleinelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VisibleInelasticityReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.zenithreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction.default_target_labels", false]], "default_target_labels (graphnet.models.task.reconstruction.zenithreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa.default_target_labels", false]], "default_target_labels (graphnet.models.task.task.identitytask property)": [[118, "graphnet.models.task.task.IdentityTask.default_target_labels", false]], "default_target_labels (graphnet.models.task.task.task property)": [[118, "graphnet.models.task.task.Task.default_target_labels", false]], "deployer (class in graphnet.deployment.deployer)": [[69, "graphnet.deployment.deployer.Deployer", false]], "deploymentmodule (class in graphnet.deployment.deployment_module)": [[70, "graphnet.deployment.deployment_module.DeploymentModule", false]], "description() (graphnet.data.curated_datamodule.curateddataset method)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.description", false]], "detector (class in graphnet.models.detector.detector)": [[86, "graphnet.models.detector.detector.Detector", false]], "direction (class in graphnet.training.labels)": [[124, "graphnet.training.labels.Direction", false]], "directionreconstructionwithkappa (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa", false]], "do_shuffle() (in module graphnet.data.dataloader)": [[8, "graphnet.data.dataloader.do_shuffle", false]], "domandtimewindowcoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.DOMAndTimeWindowCoarsening", false]], "domcoarsening (class in graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.DOMCoarsening", false]], "droppath (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.DropPath", false]], "dump() (graphnet.utilities.config.base_config.baseconfig method)": [[131, "graphnet.utilities.config.base_config.BaseConfig.dump", false]], "dynedge (class in graphnet.models.gnn.dynedge)": [[94, "graphnet.models.gnn.dynedge.DynEdge", false]], "dynedgeconv (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.DynEdgeConv", false]], "dynedgejinst (class in graphnet.models.gnn.dynedge_jinst)": [[95, "graphnet.models.gnn.dynedge_jinst.DynEdgeJINST", false]], "dynedgetito (class in graphnet.models.gnn.dynedge_kaggle_tito)": [[96, "graphnet.models.gnn.dynedge_kaggle_tito.DynEdgeTITO", false]], "dyntrans (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.DynTrans", false]], "early_stopping_patience (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.early_stopping_patience", false]], "easysyntax (class in graphnet.models.easy_model)": [[90, "graphnet.models.easy_model.EasySyntax", false]], "edgeconvtito (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.EdgeConvTito", false]], "edgedefinition (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.EdgeDefinition", false]], "edgelessgraph (class in graphnet.models.graphs.graphs)": [[105, "graphnet.models.graphs.graphs.EdgelessGraph", false]], "energyreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction", false]], "energyreconstructionwithpower (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower", false]], "energyreconstructionwithuncertainty (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty", false]], "energytcreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction", false]], "ensembledataset (class in graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.EnsembleDataset", false]], "ensembleloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.EnsembleLoss", false]], "eps_like() (in module graphnet.utilities.maths)": [[142, "graphnet.utilities.maths.eps_like", false]], "erdahosteddataset (class in graphnet.data.curated_datamodule)": [[5, "graphnet.data.curated_datamodule.ERDAHostedDataset", false]], "error() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.error", false]], "euclideandistanceloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.EuclideanDistanceLoss", false]], "euclideanedges (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.EuclideanEdges", false]], "event_truth (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.event_truth", false]], "events (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.events", false]], "expects_merged_dataframes (graphnet.data.writers.graphnet_writer.graphnetwriter property)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter.expects_merged_dataframes", false]], "experiment (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.experiment", false]], "extra_repr() (graphnet.models.components.layers.droppath method)": [[83, "graphnet.models.components.layers.DropPath.extra_repr", false]], "extra_repr() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.extra_repr", false]], "extra_repr_recursive() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.extra_repr_recursive", false]], "extracor_names (graphnet.data.readers.graphnet_file_reader.graphnetfilereader property)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.extracor_names", false]], "extractor (class in graphnet.data.extractors.extractor)": [[19, "graphnet.data.extractors.extractor.Extractor", false]], "feature_map() (graphnet.models.detector.detector.detector method)": [[86, "graphnet.models.detector.detector.Detector.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecube86 method)": [[87, "graphnet.models.detector.icecube.IceCube86.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecubedeepcore method)": [[87, "graphnet.models.detector.icecube.IceCubeDeepCore.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecubekaggle method)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.feature_map", false]], "feature_map() (graphnet.models.detector.icecube.icecubeupgrade method)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.feature_map", false]], "feature_map() (graphnet.models.detector.liquido.liquido_v1 method)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.arca115 method)": [[89, "graphnet.models.detector.prometheus.ARCA115.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.baikalgvd8 method)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecube86prometheus method)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecubedeepcore8 method)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecubegen2 method)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icecubeupgrade7 method)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.icedemo81 method)": [[89, "graphnet.models.detector.prometheus.IceDemo81.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.orca150 method)": [[89, "graphnet.models.detector.prometheus.ORCA150.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.orca150superdense method)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.ponetriangle method)": [[89, "graphnet.models.detector.prometheus.PONETriangle.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.trident1211 method)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.feature_map", false]], "feature_map() (graphnet.models.detector.prometheus.waterdemo81 method)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.feature_map", false]], "features (class in graphnet.data.constants)": [[4, "graphnet.data.constants.FEATURES", false]], "features (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.features", false]], "features (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.features", false]], "file_extension (graphnet.data.writers.graphnet_writer.graphnetwriter property)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter.file_extension", false]], "file_handlers (graphnet.utilities.logging.logger property)": [[141, "graphnet.utilities.logging.Logger.file_handlers", false]], "filter() (graphnet.utilities.logging.repeatfilter method)": [[141, "graphnet.utilities.logging.RepeatFilter.filter", false]], "find_files() (graphnet.data.readers.graphnet_file_reader.graphnetfilereader method)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.find_files", false]], "find_files() (graphnet.data.readers.i3reader.i3reader method)": [[50, "graphnet.data.readers.i3reader.I3Reader.find_files", false]], "find_files() (graphnet.data.readers.internal_parquet_reader.parquetreader method)": [[51, "graphnet.data.readers.internal_parquet_reader.ParquetReader.find_files", false]], "find_files() (graphnet.data.readers.liquido_reader.liquidoreader method)": [[52, "graphnet.data.readers.liquido_reader.LiquidOReader.find_files", false]], "find_files() (graphnet.data.readers.prometheus_reader.prometheusreader method)": [[53, "graphnet.data.readers.prometheus_reader.PrometheusReader.find_files", false]], "find_i3_files() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.find_i3_files", false]], "fit (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.fit", false]], "fit() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.fit", false]], "fit() (graphnet.training.weight_fitting.weightfitter method)": [[127, "graphnet.training.weight_fitting.WeightFitter.fit", false]], "flatten_nested_dictionary() (in module graphnet.data.extractors.icecube.utilities.collections)": [[34, "graphnet.data.extractors.icecube.utilities.collections.flatten_nested_dictionary", false]], "forward() (graphnet.models.coarsening.coarsening method)": [[80, "graphnet.models.coarsening.Coarsening.forward", false]], "forward() (graphnet.models.components.embedding.fourierencoder method)": [[82, "graphnet.models.components.embedding.FourierEncoder.forward", false]], "forward() (graphnet.models.components.embedding.sinusoidalposemb method)": [[82, "graphnet.models.components.embedding.SinusoidalPosEmb.forward", false]], "forward() (graphnet.models.components.embedding.spacetimeencoder method)": [[82, "graphnet.models.components.embedding.SpacetimeEncoder.forward", false]], "forward() (graphnet.models.components.layers.attention_rel method)": [[83, "graphnet.models.components.layers.Attention_rel.forward", false]], "forward() (graphnet.models.components.layers.block method)": [[83, "graphnet.models.components.layers.Block.forward", false]], "forward() (graphnet.models.components.layers.block_rel method)": [[83, "graphnet.models.components.layers.Block_rel.forward", false]], "forward() (graphnet.models.components.layers.droppath method)": [[83, "graphnet.models.components.layers.DropPath.forward", false]], "forward() (graphnet.models.components.layers.dynedgeconv method)": [[83, "graphnet.models.components.layers.DynEdgeConv.forward", false]], "forward() (graphnet.models.components.layers.dyntrans method)": [[83, "graphnet.models.components.layers.DynTrans.forward", false]], "forward() (graphnet.models.components.layers.edgeconvtito method)": [[83, "graphnet.models.components.layers.EdgeConvTito.forward", false]], "forward() (graphnet.models.components.layers.mlp method)": [[83, "graphnet.models.components.layers.Mlp.forward", false]], "forward() (graphnet.models.detector.detector.detector method)": [[86, "graphnet.models.detector.detector.Detector.forward", false]], "forward() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.forward", false]], "forward() (graphnet.models.gnn.convnet.convnet method)": [[93, "graphnet.models.gnn.convnet.ConvNet.forward", false]], "forward() (graphnet.models.gnn.dynedge.dynedge method)": [[94, "graphnet.models.gnn.dynedge.DynEdge.forward", false]], "forward() (graphnet.models.gnn.dynedge_jinst.dynedgejinst method)": [[95, "graphnet.models.gnn.dynedge_jinst.DynEdgeJINST.forward", false]], "forward() (graphnet.models.gnn.dynedge_kaggle_tito.dynedgetito method)": [[96, "graphnet.models.gnn.dynedge_kaggle_tito.DynEdgeTITO.forward", false]], "forward() (graphnet.models.gnn.gnn.gnn method)": [[97, "graphnet.models.gnn.gnn.GNN.forward", false]], "forward() (graphnet.models.gnn.icemix.deepice method)": [[98, "graphnet.models.gnn.icemix.DeepIce.forward", false]], "forward() (graphnet.models.gnn.particlenet.particlenet method)": [[99, "graphnet.models.gnn.particlenet.ParticleNeT.forward", false]], "forward() (graphnet.models.gnn.rnn_tito.rnn_tito method)": [[92, "graphnet.models.gnn.RNN_tito.RNN_TITO.forward", false]], "forward() (graphnet.models.graphs.edges.edges.edgedefinition method)": [[102, "graphnet.models.graphs.edges.edges.EdgeDefinition.forward", false]], "forward() (graphnet.models.graphs.graph_definition.graphdefinition method)": [[104, "graphnet.models.graphs.graph_definition.GraphDefinition.forward", false]], "forward() (graphnet.models.graphs.nodes.nodes.nodedefinition method)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.forward", false]], "forward() (graphnet.models.normalizing_flow.normalizingflow method)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow.forward", false]], "forward() (graphnet.models.rnn.node_rnn.node_rnn method)": [[112, "graphnet.models.rnn.node_rnn.Node_RNN.forward", false]], "forward() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.forward", false]], "forward() (graphnet.models.task.task.learnedtask method)": [[118, "graphnet.models.task.task.LearnedTask.forward", false]], "forward() (graphnet.models.task.task.standardflowtask method)": [[118, "graphnet.models.task.task.StandardFlowTask.forward", false]], "forward() (graphnet.models.transformer.iseecube.iseecube method)": [[120, "graphnet.models.transformer.iseecube.ISeeCube.forward", false]], "forward() (graphnet.training.loss_functions.logcmk static method)": [[125, "graphnet.training.loss_functions.LogCMK.forward", false]], "forward() (graphnet.training.loss_functions.lossfunction method)": [[125, "graphnet.training.loss_functions.LossFunction.forward", false]], "fourierencoder (class in graphnet.models.components.embedding)": [[82, "graphnet.models.components.embedding.FourierEncoder", false]], "frame_is_montecarlo() (in module graphnet.data.extractors.icecube.utilities.frames)": [[35, "graphnet.data.extractors.icecube.utilities.frames.frame_is_montecarlo", false]], "frame_is_noise() (in module graphnet.data.extractors.icecube.utilities.frames)": [[35, "graphnet.data.extractors.icecube.utilities.frames.frame_is_noise", false]], "from_config() (graphnet.data.dataset.dataset.dataset class method)": [[11, "graphnet.data.dataset.dataset.Dataset.from_config", false]], "from_config() (graphnet.models.model.model class method)": [[109, "graphnet.models.model.Model.from_config", false]], "from_config() (graphnet.utilities.config.configurable.configurable method)": [[132, "graphnet.utilities.config.configurable.Configurable.from_config", false]], "from_dataset_config() (graphnet.data.dataloader.dataloader class method)": [[8, "graphnet.data.dataloader.DataLoader.from_dataset_config", false]], "gather_cluster_sequence() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.gather_cluster_sequence", false]], "gather_len_matched_buckets() (in module graphnet.data.dataset.samplers)": [[14, "graphnet.data.dataset.samplers.gather_len_matched_buckets", false]], "gcd_file (graphnet.data.dataclasses.i3fileset attribute)": [[6, "graphnet.data.dataclasses.I3FileSet.gcd_file", false]], "gcd_file (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.gcd_file", false]], "geometry_table (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.geometry_table", false]], "geometry_table_path (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.geometry_table_path", false]], "geometry_table_path (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.geometry_table_path", false]], "get_all_argument_values() (in module graphnet.utilities.config.base_config)": [[131, "graphnet.utilities.config.base_config.get_all_argument_values", false]], "get_all_grapnet_classes() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.get_all_grapnet_classes", false]], "get_fields() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.get_fields", false]], "get_graphnet_classes() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.get_graphnet_classes", false]], "get_lr() (graphnet.training.callbacks.piecewiselinearlr method)": [[123, "graphnet.training.callbacks.PiecewiseLinearLR.get_lr", false]], "get_map_function() (graphnet.data.dataconverter.dataconverter method)": [[7, "graphnet.data.dataconverter.DataConverter.get_map_function", false]], "get_member_variables() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.get_member_variables", false]], "get_metrics() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.get_metrics", false]], "get_om_keys_and_pulseseries() (in module graphnet.data.extractors.icecube.utilities.frames)": [[35, "graphnet.data.extractors.icecube.utilities.frames.get_om_keys_and_pulseseries", false]], "get_predictions() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.get_predictions", false]], "get_primary_keys() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.get_primary_keys", false]], "gnn (class in graphnet.models.gnn.gnn)": [[97, "graphnet.models.gnn.gnn.GNN", false]], "graph_definition (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.graph_definition", false]], "graphdefinition (class in graphnet.models.graphs.graph_definition)": [[104, "graphnet.models.graphs.graph_definition.GraphDefinition", false]], "graphnet": [[1, "module-graphnet", false]], "graphnet.constants": [[2, "module-graphnet.constants", false]], "graphnet.data": [[3, "module-graphnet.data", false]], "graphnet.data.constants": [[4, "module-graphnet.data.constants", false]], "graphnet.data.curated_datamodule": [[5, "module-graphnet.data.curated_datamodule", false]], "graphnet.data.dataclasses": [[6, "module-graphnet.data.dataclasses", false]], "graphnet.data.dataconverter": [[7, "module-graphnet.data.dataconverter", false]], "graphnet.data.dataloader": [[8, "module-graphnet.data.dataloader", false]], "graphnet.data.datamodule": [[9, "module-graphnet.data.datamodule", false]], "graphnet.data.dataset": [[10, "module-graphnet.data.dataset", false]], "graphnet.data.dataset.dataset": [[11, "module-graphnet.data.dataset.dataset", false]], "graphnet.data.dataset.parquet": [[12, "module-graphnet.data.dataset.parquet", false]], "graphnet.data.dataset.parquet.parquet_dataset": [[13, "module-graphnet.data.dataset.parquet.parquet_dataset", false]], "graphnet.data.dataset.samplers": [[14, "module-graphnet.data.dataset.samplers", false]], "graphnet.data.dataset.sqlite": [[15, "module-graphnet.data.dataset.sqlite", false]], "graphnet.data.dataset.sqlite.sqlite_dataset": [[16, "module-graphnet.data.dataset.sqlite.sqlite_dataset", false]], "graphnet.data.extractors": [[17, "module-graphnet.data.extractors", false]], "graphnet.data.extractors.combine_extractors": [[18, "module-graphnet.data.extractors.combine_extractors", false]], "graphnet.data.extractors.extractor": [[19, "module-graphnet.data.extractors.extractor", false]], "graphnet.data.extractors.icecube": [[20, "module-graphnet.data.extractors.icecube", false]], "graphnet.data.extractors.icecube.i3extractor": [[21, "module-graphnet.data.extractors.icecube.i3extractor", false]], "graphnet.data.extractors.icecube.i3featureextractor": [[22, "module-graphnet.data.extractors.icecube.i3featureextractor", false]], "graphnet.data.extractors.icecube.i3genericextractor": [[23, "module-graphnet.data.extractors.icecube.i3genericextractor", false]], "graphnet.data.extractors.icecube.i3hybridrecoextractor": [[24, "module-graphnet.data.extractors.icecube.i3hybridrecoextractor", false]], "graphnet.data.extractors.icecube.i3ntmuonlabelsextractor": [[25, "module-graphnet.data.extractors.icecube.i3ntmuonlabelsextractor", false]], "graphnet.data.extractors.icecube.i3particleextractor": [[26, "module-graphnet.data.extractors.icecube.i3particleextractor", false]], "graphnet.data.extractors.icecube.i3pisaextractor": [[27, "module-graphnet.data.extractors.icecube.i3pisaextractor", false]], "graphnet.data.extractors.icecube.i3quesoextractor": [[28, "module-graphnet.data.extractors.icecube.i3quesoextractor", false]], "graphnet.data.extractors.icecube.i3retroextractor": [[29, "module-graphnet.data.extractors.icecube.i3retroextractor", false]], "graphnet.data.extractors.icecube.i3splinempeextractor": [[30, "module-graphnet.data.extractors.icecube.i3splinempeextractor", false]], "graphnet.data.extractors.icecube.i3truthextractor": [[31, "module-graphnet.data.extractors.icecube.i3truthextractor", false]], "graphnet.data.extractors.icecube.i3tumextractor": [[32, "module-graphnet.data.extractors.icecube.i3tumextractor", false]], "graphnet.data.extractors.icecube.utilities": [[33, "module-graphnet.data.extractors.icecube.utilities", false]], "graphnet.data.extractors.icecube.utilities.collections": [[34, "module-graphnet.data.extractors.icecube.utilities.collections", false]], "graphnet.data.extractors.icecube.utilities.frames": [[35, "module-graphnet.data.extractors.icecube.utilities.frames", false]], "graphnet.data.extractors.icecube.utilities.i3_filters": [[36, "module-graphnet.data.extractors.icecube.utilities.i3_filters", false]], "graphnet.data.extractors.icecube.utilities.types": [[37, "module-graphnet.data.extractors.icecube.utilities.types", false]], "graphnet.data.extractors.internal": [[38, "module-graphnet.data.extractors.internal", false]], "graphnet.data.extractors.internal.parquet_extractor": [[39, "module-graphnet.data.extractors.internal.parquet_extractor", false]], "graphnet.data.extractors.liquido": [[40, "module-graphnet.data.extractors.liquido", false]], "graphnet.data.extractors.liquido.h5_extractor": [[41, "module-graphnet.data.extractors.liquido.h5_extractor", false]], "graphnet.data.extractors.prometheus": [[42, "module-graphnet.data.extractors.prometheus", false]], "graphnet.data.extractors.prometheus.prometheus_extractor": [[43, "module-graphnet.data.extractors.prometheus.prometheus_extractor", false]], "graphnet.data.parquet": [[44, "module-graphnet.data.parquet", false]], "graphnet.data.parquet.deprecated_methods": [[45, "module-graphnet.data.parquet.deprecated_methods", false]], "graphnet.data.pre_configured": [[46, "module-graphnet.data.pre_configured", false]], "graphnet.data.pre_configured.dataconverters": [[47, "module-graphnet.data.pre_configured.dataconverters", false]], "graphnet.data.readers": [[48, "module-graphnet.data.readers", false]], "graphnet.data.readers.graphnet_file_reader": [[49, "module-graphnet.data.readers.graphnet_file_reader", false]], "graphnet.data.readers.i3reader": [[50, "module-graphnet.data.readers.i3reader", false]], "graphnet.data.readers.internal_parquet_reader": [[51, "module-graphnet.data.readers.internal_parquet_reader", false]], "graphnet.data.readers.liquido_reader": [[52, "module-graphnet.data.readers.liquido_reader", false]], "graphnet.data.readers.prometheus_reader": [[53, "module-graphnet.data.readers.prometheus_reader", false]], "graphnet.data.sqlite": [[54, "module-graphnet.data.sqlite", false]], "graphnet.data.sqlite.deprecated_methods": [[55, "module-graphnet.data.sqlite.deprecated_methods", false]], "graphnet.data.utilities": [[56, "module-graphnet.data.utilities", false]], "graphnet.data.utilities.parquet_to_sqlite": [[57, "module-graphnet.data.utilities.parquet_to_sqlite", false]], "graphnet.data.utilities.random": [[58, "module-graphnet.data.utilities.random", false]], "graphnet.data.utilities.sqlite_utilities": [[59, "module-graphnet.data.utilities.sqlite_utilities", false]], "graphnet.data.utilities.string_selection_resolver": [[60, "module-graphnet.data.utilities.string_selection_resolver", false]], "graphnet.data.writers": [[61, "module-graphnet.data.writers", false]], "graphnet.data.writers.graphnet_writer": [[62, "module-graphnet.data.writers.graphnet_writer", false]], "graphnet.data.writers.parquet_writer": [[63, "module-graphnet.data.writers.parquet_writer", false]], "graphnet.data.writers.sqlite_writer": [[64, "module-graphnet.data.writers.sqlite_writer", false]], "graphnet.datasets": [[65, "module-graphnet.datasets", false]], "graphnet.datasets.prometheus_datasets": [[66, "module-graphnet.datasets.prometheus_datasets", false]], "graphnet.datasets.test_dataset": [[67, "module-graphnet.datasets.test_dataset", false]], "graphnet.deployment": [[68, "module-graphnet.deployment", false]], "graphnet.deployment.deployer": [[69, "module-graphnet.deployment.deployer", false]], "graphnet.deployment.deployment_module": [[70, "module-graphnet.deployment.deployment_module", false]], "graphnet.deployment.i3modules": [[71, "module-graphnet.deployment.i3modules", false]], "graphnet.deployment.i3modules.deprecated_methods": [[72, "module-graphnet.deployment.i3modules.deprecated_methods", false]], "graphnet.deployment.icecube": [[73, "module-graphnet.deployment.icecube", false]], "graphnet.deployment.icecube.cleaning_module": [[74, "module-graphnet.deployment.icecube.cleaning_module", false]], "graphnet.deployment.icecube.i3deployer": [[75, "module-graphnet.deployment.icecube.i3deployer", false]], "graphnet.deployment.icecube.inference_module": [[76, "module-graphnet.deployment.icecube.inference_module", false]], "graphnet.exceptions": [[77, "module-graphnet.exceptions", false]], "graphnet.exceptions.exceptions": [[78, "module-graphnet.exceptions.exceptions", false]], "graphnet.models": [[79, "module-graphnet.models", false]], "graphnet.models.coarsening": [[80, "module-graphnet.models.coarsening", false]], "graphnet.models.components": [[81, "module-graphnet.models.components", false]], "graphnet.models.components.embedding": [[82, "module-graphnet.models.components.embedding", false]], "graphnet.models.components.layers": [[83, "module-graphnet.models.components.layers", false]], "graphnet.models.components.pool": [[84, "module-graphnet.models.components.pool", false]], "graphnet.models.detector": [[85, "module-graphnet.models.detector", false]], "graphnet.models.detector.detector": [[86, "module-graphnet.models.detector.detector", false]], "graphnet.models.detector.icecube": [[87, "module-graphnet.models.detector.icecube", false]], "graphnet.models.detector.liquido": [[88, "module-graphnet.models.detector.liquido", false]], "graphnet.models.detector.prometheus": [[89, "module-graphnet.models.detector.prometheus", false]], "graphnet.models.easy_model": [[90, "module-graphnet.models.easy_model", false]], "graphnet.models.gnn": [[91, "module-graphnet.models.gnn", false]], "graphnet.models.gnn.convnet": [[93, "module-graphnet.models.gnn.convnet", false]], "graphnet.models.gnn.dynedge": [[94, "module-graphnet.models.gnn.dynedge", false]], "graphnet.models.gnn.dynedge_jinst": [[95, "module-graphnet.models.gnn.dynedge_jinst", false]], "graphnet.models.gnn.dynedge_kaggle_tito": [[96, "module-graphnet.models.gnn.dynedge_kaggle_tito", false]], "graphnet.models.gnn.gnn": [[97, "module-graphnet.models.gnn.gnn", false]], "graphnet.models.gnn.icemix": [[98, "module-graphnet.models.gnn.icemix", false]], "graphnet.models.gnn.particlenet": [[99, "module-graphnet.models.gnn.particlenet", false]], "graphnet.models.gnn.rnn_tito": [[92, "module-graphnet.models.gnn.RNN_tito", false]], "graphnet.models.graphs": [[100, "module-graphnet.models.graphs", false]], "graphnet.models.graphs.edges": [[101, "module-graphnet.models.graphs.edges", false]], "graphnet.models.graphs.edges.edges": [[102, "module-graphnet.models.graphs.edges.edges", false]], "graphnet.models.graphs.edges.minkowski": [[103, "module-graphnet.models.graphs.edges.minkowski", false]], "graphnet.models.graphs.graph_definition": [[104, "module-graphnet.models.graphs.graph_definition", false]], "graphnet.models.graphs.graphs": [[105, "module-graphnet.models.graphs.graphs", false]], "graphnet.models.graphs.nodes": [[106, "module-graphnet.models.graphs.nodes", false]], "graphnet.models.graphs.nodes.nodes": [[107, "module-graphnet.models.graphs.nodes.nodes", false]], "graphnet.models.graphs.utils": [[108, "module-graphnet.models.graphs.utils", false]], "graphnet.models.model": [[109, "module-graphnet.models.model", false]], "graphnet.models.normalizing_flow": [[110, "module-graphnet.models.normalizing_flow", false]], "graphnet.models.rnn": [[111, "module-graphnet.models.rnn", false]], "graphnet.models.rnn.node_rnn": [[112, "module-graphnet.models.rnn.node_rnn", false]], "graphnet.models.standard_averaged_model": [[113, "module-graphnet.models.standard_averaged_model", false]], "graphnet.models.standard_model": [[114, "module-graphnet.models.standard_model", false]], "graphnet.models.task": [[115, "module-graphnet.models.task", false]], "graphnet.models.task.classification": [[116, "module-graphnet.models.task.classification", false]], "graphnet.models.task.reconstruction": [[117, "module-graphnet.models.task.reconstruction", false]], "graphnet.models.task.task": [[118, "module-graphnet.models.task.task", false]], "graphnet.models.transformer": [[119, "module-graphnet.models.transformer", false]], "graphnet.models.transformer.iseecube": [[120, "module-graphnet.models.transformer.iseecube", false]], "graphnet.models.utils": [[121, "module-graphnet.models.utils", false]], "graphnet.training": [[122, "module-graphnet.training", false]], "graphnet.training.callbacks": [[123, "module-graphnet.training.callbacks", false]], "graphnet.training.labels": [[124, "module-graphnet.training.labels", false]], "graphnet.training.loss_functions": [[125, "module-graphnet.training.loss_functions", false]], "graphnet.training.utils": [[126, "module-graphnet.training.utils", false]], "graphnet.training.weight_fitting": [[127, "module-graphnet.training.weight_fitting", false]], "graphnet.utilities": [[128, "module-graphnet.utilities", false]], "graphnet.utilities.argparse": [[129, "module-graphnet.utilities.argparse", false]], "graphnet.utilities.config": [[130, "module-graphnet.utilities.config", false]], "graphnet.utilities.config.base_config": [[131, "module-graphnet.utilities.config.base_config", false]], "graphnet.utilities.config.configurable": [[132, "module-graphnet.utilities.config.configurable", false]], "graphnet.utilities.config.dataset_config": [[133, "module-graphnet.utilities.config.dataset_config", false]], "graphnet.utilities.config.model_config": [[134, "module-graphnet.utilities.config.model_config", false]], "graphnet.utilities.config.parsing": [[135, "module-graphnet.utilities.config.parsing", false]], "graphnet.utilities.config.training_config": [[136, "module-graphnet.utilities.config.training_config", false]], "graphnet.utilities.decorators": [[137, "module-graphnet.utilities.decorators", false]], "graphnet.utilities.deprecation_tools": [[138, "module-graphnet.utilities.deprecation_tools", false]], "graphnet.utilities.filesys": [[139, "module-graphnet.utilities.filesys", false]], "graphnet.utilities.imports": [[140, "module-graphnet.utilities.imports", false]], "graphnet.utilities.logging": [[141, "module-graphnet.utilities.logging", false]], "graphnet.utilities.maths": [[142, "module-graphnet.utilities.maths", false]], "graphnetdatamodule (class in graphnet.data.datamodule)": [[9, "graphnet.data.datamodule.GraphNeTDataModule", false]], "graphnetearlystopping (class in graphnet.training.callbacks)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping", false]], "graphnetfilereader (class in graphnet.data.readers.graphnet_file_reader)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader", false]], "graphneti3deployer (class in graphnet.deployment.i3modules.deprecated_methods)": [[72, "graphnet.deployment.i3modules.deprecated_methods.GraphNeTI3Deployer", false]], "graphnetwriter (class in graphnet.data.writers.graphnet_writer)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter", false]], "group_by() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.group_by", false]], "group_pulses_to_dom() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.group_pulses_to_dom", false]], "group_pulses_to_pmt() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.group_pulses_to_pmt", false]], "h5extractor (class in graphnet.data.extractors.liquido.h5_extractor)": [[41, "graphnet.data.extractors.liquido.h5_extractor.H5Extractor", false]], "h5hitextractor (class in graphnet.data.extractors.liquido.h5_extractor)": [[41, "graphnet.data.extractors.liquido.h5_extractor.H5HitExtractor", false]], "h5truthextractor (class in graphnet.data.extractors.liquido.h5_extractor)": [[41, "graphnet.data.extractors.liquido.h5_extractor.H5TruthExtractor", false]], "handlers (graphnet.utilities.logging.logger property)": [[141, "graphnet.utilities.logging.Logger.handlers", false]], "has_extension() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.has_extension", false]], "has_icecube_package() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.has_icecube_package", false]], "has_jammy_flows_package() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.has_jammy_flows_package", false]], "has_torch_package() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.has_torch_package", false]], "i3_file (graphnet.data.dataclasses.i3fileset attribute)": [[6, "graphnet.data.dataclasses.I3FileSet.i3_file", false]], "i3_files (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.i3_files", false]], "i3deployer (class in graphnet.deployment.icecube.i3deployer)": [[75, "graphnet.deployment.icecube.i3deployer.I3Deployer", false]], "i3extractor (class in graphnet.data.extractors.icecube.i3extractor)": [[21, "graphnet.data.extractors.icecube.i3extractor.I3Extractor", false]], "i3featureextractor (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractor", false]], "i3featureextractoricecube86 (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractorIceCube86", false]], "i3featureextractoricecubedeepcore (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractorIceCubeDeepCore", false]], "i3featureextractoricecubeupgrade (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3FeatureExtractorIceCubeUpgrade", false]], "i3fileset (class in graphnet.data.dataclasses)": [[6, "graphnet.data.dataclasses.I3FileSet", false]], "i3filter (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.I3Filter", false]], "i3filtermask (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.I3FilterMask", false]], "i3galacticplanehybridrecoextractor (class in graphnet.data.extractors.icecube.i3hybridrecoextractor)": [[24, "graphnet.data.extractors.icecube.i3hybridrecoextractor.I3GalacticPlaneHybridRecoExtractor", false]], "i3genericextractor (class in graphnet.data.extractors.icecube.i3genericextractor)": [[23, "graphnet.data.extractors.icecube.i3genericextractor.I3GenericExtractor", false]], "i3inferencemodule (class in graphnet.deployment.icecube.inference_module)": [[76, "graphnet.deployment.icecube.inference_module.I3InferenceModule", false]], "i3ntmuonlabelextractor (class in graphnet.data.extractors.icecube.i3ntmuonlabelsextractor)": [[25, "graphnet.data.extractors.icecube.i3ntmuonlabelsextractor.I3NTMuonLabelExtractor", false]], "i3particleextractor (class in graphnet.data.extractors.icecube.i3particleextractor)": [[26, "graphnet.data.extractors.icecube.i3particleextractor.I3ParticleExtractor", false]], "i3pisaextractor (class in graphnet.data.extractors.icecube.i3pisaextractor)": [[27, "graphnet.data.extractors.icecube.i3pisaextractor.I3PISAExtractor", false]], "i3pulsecleanermodule (class in graphnet.deployment.icecube.cleaning_module)": [[74, "graphnet.deployment.icecube.cleaning_module.I3PulseCleanerModule", false]], "i3pulsenoisetruthflagicecubeupgrade (class in graphnet.data.extractors.icecube.i3featureextractor)": [[22, "graphnet.data.extractors.icecube.i3featureextractor.I3PulseNoiseTruthFlagIceCubeUpgrade", false]], "i3quesoextractor (class in graphnet.data.extractors.icecube.i3quesoextractor)": [[28, "graphnet.data.extractors.icecube.i3quesoextractor.I3QUESOExtractor", false]], "i3reader (class in graphnet.data.readers.i3reader)": [[50, "graphnet.data.readers.i3reader.I3Reader", false]], "i3retroextractor (class in graphnet.data.extractors.icecube.i3retroextractor)": [[29, "graphnet.data.extractors.icecube.i3retroextractor.I3RetroExtractor", false]], "i3splinempeicextractor (class in graphnet.data.extractors.icecube.i3splinempeextractor)": [[30, "graphnet.data.extractors.icecube.i3splinempeextractor.I3SplineMPEICExtractor", false]], "i3toparquetconverter (class in graphnet.data.pre_configured.dataconverters)": [[47, "graphnet.data.pre_configured.dataconverters.I3ToParquetConverter", false]], "i3tosqliteconverter (class in graphnet.data.pre_configured.dataconverters)": [[47, "graphnet.data.pre_configured.dataconverters.I3ToSQLiteConverter", false]], "i3truthextractor (class in graphnet.data.extractors.icecube.i3truthextractor)": [[31, "graphnet.data.extractors.icecube.i3truthextractor.I3TruthExtractor", false]], "i3tumextractor (class in graphnet.data.extractors.icecube.i3tumextractor)": [[32, "graphnet.data.extractors.icecube.i3tumextractor.I3TUMExtractor", false]], "ice_transparency() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.ice_transparency", false]], "icecube86 (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCube86", false]], "icecube86 (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.ICECUBE86", false]], "icecube86 (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.ICECUBE86", false]], "icecube86prometheus (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus", false]], "icecubedeepcore (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCubeDeepCore", false]], "icecubedeepcore8 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8", false]], "icecubegen2 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2", false]], "icecubekaggle (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle", false]], "icecubeupgrade (class in graphnet.models.detector.icecube)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade", false]], "icecubeupgrade7 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7", false]], "icedemo81 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.IceDemo81", false]], "icemixnodes (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.IceMixNodes", false]], "identify_indices() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.identify_indices", false]], "identitytask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.IdentityTask", false]], "index_column (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.index_column", false]], "inelasticityreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction", false]], "inference() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.inference", false]], "inference() (graphnet.models.task.task.task method)": [[118, "graphnet.models.task.task.Task.inference", false]], "info() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.info", false]], "init_global_index() (in module graphnet.data.dataconverter)": [[7, "graphnet.data.dataconverter.init_global_index", false]], "init_predict_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_predict_tqdm", false]], "init_test_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_test_tqdm", false]], "init_train_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_train_tqdm", false]], "init_validation_tqdm() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.init_validation_tqdm", false]], "is_boost_class() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_boost_class", false]], "is_boost_enum() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_boost_enum", false]], "is_gcd_file() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.is_gcd_file", false]], "is_graphnet_class() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.is_graphnet_class", false]], "is_graphnet_module() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.is_graphnet_module", false]], "is_i3_file() (in module graphnet.utilities.filesys)": [[139, "graphnet.utilities.filesys.is_i3_file", false]], "is_icecube_class() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_icecube_class", false]], "is_method() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_method", false]], "is_type() (in module graphnet.data.extractors.icecube.utilities.types)": [[37, "graphnet.data.extractors.icecube.utilities.types.is_type", false]], "iseecube (class in graphnet.models.transformer.iseecube)": [[120, "graphnet.models.transformer.iseecube.ISeeCube", false]], "kaggle (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.KAGGLE", false]], "kaggle (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.KAGGLE", false]], "key (graphnet.training.labels.label property)": [[124, "graphnet.training.labels.Label.key", false]], "knn_graph_batch() (in module graphnet.models.utils)": [[121, "graphnet.models.utils.knn_graph_batch", false]], "knnedges (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.KNNEdges", false]], "knngraph (class in graphnet.models.graphs.graphs)": [[105, "graphnet.models.graphs.graphs.KNNGraph", false]], "label (class in graphnet.training.labels)": [[124, "graphnet.training.labels.Label", false]], "labels (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.labels", false]], "learnedtask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.LearnedTask", false]], "lenmatchbatchsampler (class in graphnet.data.dataset.samplers)": [[14, "graphnet.data.dataset.samplers.LenMatchBatchSampler", false]], "lex_sort() (in module graphnet.models.graphs.utils)": [[108, "graphnet.models.graphs.utils.lex_sort", false]], "liquido (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.LIQUIDO", false]], "liquido (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.LIQUIDO", false]], "liquido_v1 (class in graphnet.models.detector.liquido)": [[88, "graphnet.models.detector.liquido.LiquidO_v1", false]], "liquidoreader (class in graphnet.data.readers.liquido_reader)": [[52, "graphnet.data.readers.liquido_reader.LiquidOReader", false]], "list_all_submodules() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.list_all_submodules", false]], "load() (graphnet.models.model.model class method)": [[109, "graphnet.models.model.Model.load", false]], "load() (graphnet.utilities.config.base_config.baseconfig class method)": [[131, "graphnet.utilities.config.base_config.BaseConfig.load", false]], "load_module() (in module graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.load_module", false]], "load_state_dict() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.load_state_dict", false]], "load_state_dict() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.load_state_dict", false]], "log_cmk() (graphnet.training.loss_functions.vonmisesfisherloss class method)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss.log_cmk", false]], "log_cmk_approx() (graphnet.training.loss_functions.vonmisesfisherloss class method)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss.log_cmk_approx", false]], "log_cmk_exact() (graphnet.training.loss_functions.vonmisesfisherloss class method)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss.log_cmk_exact", false]], "logcmk (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.LogCMK", false]], "logcoshloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.LogCoshLoss", false]], "logger (class in graphnet.utilities.logging)": [[141, "graphnet.utilities.logging.Logger", false]], "loss_weight_column (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.loss_weight_column", false]], "loss_weight_default_value (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.loss_weight_default_value", false]], "loss_weight_table (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.loss_weight_table", false]], "lossfunction (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.LossFunction", false]], "maeloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.MAELoss", false]], "make_dataloader() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.make_dataloader", false]], "make_train_validation_dataloader() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.make_train_validation_dataloader", false]], "merge_files() (graphnet.data.dataconverter.dataconverter method)": [[7, "graphnet.data.dataconverter.DataConverter.merge_files", false]], "merge_files() (graphnet.data.writers.graphnet_writer.graphnetwriter method)": [[62, "graphnet.data.writers.graphnet_writer.GraphNeTWriter.merge_files", false]], "merge_files() (graphnet.data.writers.parquet_writer.parquetwriter method)": [[63, "graphnet.data.writers.parquet_writer.ParquetWriter.merge_files", false]], "merge_files() (graphnet.data.writers.sqlite_writer.sqlitewriter method)": [[64, "graphnet.data.writers.sqlite_writer.SQLiteWriter.merge_files", false]], "message() (graphnet.models.components.layers.edgeconvtito method)": [[83, "graphnet.models.components.layers.EdgeConvTito.message", false]], "min_pool() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.min_pool", false]], "min_pool_x() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.min_pool_x", false]], "minkowskiknnedges (class in graphnet.models.graphs.edges.minkowski)": [[103, "graphnet.models.graphs.edges.minkowski.MinkowskiKNNEdges", false]], "mlp (class in graphnet.models.components.layers)": [[83, "graphnet.models.components.layers.Mlp", false]], "model (class in graphnet.models.model)": [[109, "graphnet.models.model.Model", false]], "model_config (graphnet.utilities.config.base_config.baseconfig attribute)": [[131, "graphnet.utilities.config.base_config.BaseConfig.model_config", false]], "model_config (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.model_config", false]], "model_config (graphnet.utilities.config.model_config.modelconfig attribute)": [[134, "graphnet.utilities.config.model_config.ModelConfig.model_config", false]], "model_config (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.model_config", false]], "modelconfig (class in graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.ModelConfig", false]], "modelconfigsaverabc (class in graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.ModelConfigSaverABC", false]], "modelconfigsavermeta (class in graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.ModelConfigSaverMeta", false]], "module": [[1, "module-graphnet", false], [2, "module-graphnet.constants", false], [3, "module-graphnet.data", false], [4, "module-graphnet.data.constants", false], [5, "module-graphnet.data.curated_datamodule", false], [6, "module-graphnet.data.dataclasses", false], [7, "module-graphnet.data.dataconverter", false], [8, "module-graphnet.data.dataloader", false], [9, "module-graphnet.data.datamodule", false], [10, "module-graphnet.data.dataset", false], [11, "module-graphnet.data.dataset.dataset", false], [12, "module-graphnet.data.dataset.parquet", false], [13, "module-graphnet.data.dataset.parquet.parquet_dataset", false], [14, "module-graphnet.data.dataset.samplers", false], [15, "module-graphnet.data.dataset.sqlite", false], [16, "module-graphnet.data.dataset.sqlite.sqlite_dataset", false], [17, "module-graphnet.data.extractors", false], [18, "module-graphnet.data.extractors.combine_extractors", false], [19, "module-graphnet.data.extractors.extractor", false], [20, "module-graphnet.data.extractors.icecube", false], [21, "module-graphnet.data.extractors.icecube.i3extractor", false], [22, "module-graphnet.data.extractors.icecube.i3featureextractor", false], [23, "module-graphnet.data.extractors.icecube.i3genericextractor", false], [24, "module-graphnet.data.extractors.icecube.i3hybridrecoextractor", false], [25, "module-graphnet.data.extractors.icecube.i3ntmuonlabelsextractor", false], [26, "module-graphnet.data.extractors.icecube.i3particleextractor", false], [27, "module-graphnet.data.extractors.icecube.i3pisaextractor", false], [28, "module-graphnet.data.extractors.icecube.i3quesoextractor", false], [29, "module-graphnet.data.extractors.icecube.i3retroextractor", false], [30, "module-graphnet.data.extractors.icecube.i3splinempeextractor", false], [31, "module-graphnet.data.extractors.icecube.i3truthextractor", false], [32, "module-graphnet.data.extractors.icecube.i3tumextractor", false], [33, "module-graphnet.data.extractors.icecube.utilities", false], [34, "module-graphnet.data.extractors.icecube.utilities.collections", false], [35, "module-graphnet.data.extractors.icecube.utilities.frames", false], [36, "module-graphnet.data.extractors.icecube.utilities.i3_filters", false], [37, "module-graphnet.data.extractors.icecube.utilities.types", false], [38, "module-graphnet.data.extractors.internal", false], [39, "module-graphnet.data.extractors.internal.parquet_extractor", false], [40, "module-graphnet.data.extractors.liquido", false], [41, "module-graphnet.data.extractors.liquido.h5_extractor", false], [42, "module-graphnet.data.extractors.prometheus", false], [43, "module-graphnet.data.extractors.prometheus.prometheus_extractor", false], [44, "module-graphnet.data.parquet", false], [45, "module-graphnet.data.parquet.deprecated_methods", false], [46, "module-graphnet.data.pre_configured", false], [47, "module-graphnet.data.pre_configured.dataconverters", false], [48, "module-graphnet.data.readers", false], [49, "module-graphnet.data.readers.graphnet_file_reader", false], [50, "module-graphnet.data.readers.i3reader", false], [51, "module-graphnet.data.readers.internal_parquet_reader", false], [52, "module-graphnet.data.readers.liquido_reader", false], [53, "module-graphnet.data.readers.prometheus_reader", false], [54, "module-graphnet.data.sqlite", false], [55, "module-graphnet.data.sqlite.deprecated_methods", false], [56, "module-graphnet.data.utilities", false], [57, "module-graphnet.data.utilities.parquet_to_sqlite", false], [58, "module-graphnet.data.utilities.random", false], [59, "module-graphnet.data.utilities.sqlite_utilities", false], [60, "module-graphnet.data.utilities.string_selection_resolver", false], [61, "module-graphnet.data.writers", false], [62, "module-graphnet.data.writers.graphnet_writer", false], [63, "module-graphnet.data.writers.parquet_writer", false], [64, "module-graphnet.data.writers.sqlite_writer", false], [65, "module-graphnet.datasets", false], [66, "module-graphnet.datasets.prometheus_datasets", false], [67, "module-graphnet.datasets.test_dataset", false], [68, "module-graphnet.deployment", false], [69, "module-graphnet.deployment.deployer", false], [70, "module-graphnet.deployment.deployment_module", false], [71, "module-graphnet.deployment.i3modules", false], [72, "module-graphnet.deployment.i3modules.deprecated_methods", false], [73, "module-graphnet.deployment.icecube", false], [74, "module-graphnet.deployment.icecube.cleaning_module", false], [75, "module-graphnet.deployment.icecube.i3deployer", false], [76, "module-graphnet.deployment.icecube.inference_module", false], [77, "module-graphnet.exceptions", false], [78, "module-graphnet.exceptions.exceptions", false], [79, "module-graphnet.models", false], [80, "module-graphnet.models.coarsening", false], [81, "module-graphnet.models.components", false], [82, "module-graphnet.models.components.embedding", false], [83, "module-graphnet.models.components.layers", false], [84, "module-graphnet.models.components.pool", false], [85, "module-graphnet.models.detector", false], [86, "module-graphnet.models.detector.detector", false], [87, "module-graphnet.models.detector.icecube", false], [88, "module-graphnet.models.detector.liquido", false], [89, "module-graphnet.models.detector.prometheus", false], [90, "module-graphnet.models.easy_model", false], [91, "module-graphnet.models.gnn", false], [92, "module-graphnet.models.gnn.RNN_tito", false], [93, "module-graphnet.models.gnn.convnet", false], [94, "module-graphnet.models.gnn.dynedge", false], [95, "module-graphnet.models.gnn.dynedge_jinst", false], [96, "module-graphnet.models.gnn.dynedge_kaggle_tito", false], [97, "module-graphnet.models.gnn.gnn", false], [98, "module-graphnet.models.gnn.icemix", false], [99, "module-graphnet.models.gnn.particlenet", false], [100, "module-graphnet.models.graphs", false], [101, "module-graphnet.models.graphs.edges", false], [102, "module-graphnet.models.graphs.edges.edges", false], [103, "module-graphnet.models.graphs.edges.minkowski", false], [104, "module-graphnet.models.graphs.graph_definition", false], [105, "module-graphnet.models.graphs.graphs", false], [106, "module-graphnet.models.graphs.nodes", false], [107, "module-graphnet.models.graphs.nodes.nodes", false], [108, "module-graphnet.models.graphs.utils", false], [109, "module-graphnet.models.model", false], [110, "module-graphnet.models.normalizing_flow", false], [111, "module-graphnet.models.rnn", false], [112, "module-graphnet.models.rnn.node_rnn", false], [113, "module-graphnet.models.standard_averaged_model", false], [114, "module-graphnet.models.standard_model", false], [115, "module-graphnet.models.task", false], [116, "module-graphnet.models.task.classification", false], [117, "module-graphnet.models.task.reconstruction", false], [118, "module-graphnet.models.task.task", false], [119, "module-graphnet.models.transformer", false], [120, "module-graphnet.models.transformer.iseecube", false], [121, "module-graphnet.models.utils", false], [122, "module-graphnet.training", false], [123, "module-graphnet.training.callbacks", false], [124, "module-graphnet.training.labels", false], [125, "module-graphnet.training.loss_functions", false], [126, "module-graphnet.training.utils", false], [127, "module-graphnet.training.weight_fitting", false], [128, "module-graphnet.utilities", false], [129, "module-graphnet.utilities.argparse", false], [130, "module-graphnet.utilities.config", false], [131, "module-graphnet.utilities.config.base_config", false], [132, "module-graphnet.utilities.config.configurable", false], [133, "module-graphnet.utilities.config.dataset_config", false], [134, "module-graphnet.utilities.config.model_config", false], [135, "module-graphnet.utilities.config.parsing", false], [136, "module-graphnet.utilities.config.training_config", false], [137, "module-graphnet.utilities.decorators", false], [138, "module-graphnet.utilities.deprecation_tools", false], [139, "module-graphnet.utilities.filesys", false], [140, "module-graphnet.utilities.imports", false], [141, "module-graphnet.utilities.logging", false], [142, "module-graphnet.utilities.maths", false]], "modules (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.modules", false]], "mseloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.MSELoss", false]], "multiclassclassificationtask (class in graphnet.models.task.classification)": [[116, "graphnet.models.task.classification.MulticlassClassificationTask", false]], "name (graphnet.data.extractors.extractor.extractor property)": [[19, "graphnet.data.extractors.extractor.Extractor.name", false]], "nb_inputs (graphnet.models.gnn.gnn.gnn property)": [[97, "graphnet.models.gnn.gnn.GNN.nb_inputs", false]], "nb_inputs (graphnet.models.task.classification.binaryclassificationtask attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.classification.binaryclassificationtasklogits attribute)": [[116, "graphnet.models.task.classification.BinaryClassificationTaskLogits.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.azimuthreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.azimuthreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.directionreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energyreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energyreconstructionwithpower attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithPower.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energyreconstructionwithuncertainty attribute)": [[117, "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.energytcreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.EnergyTCReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.inelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.InelasticityReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.positionreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.timereconstruction attribute)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.vertexreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.visibleinelasticityreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.VisibleInelasticityReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.zenithreconstruction attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction.nb_inputs", false]], "nb_inputs (graphnet.models.task.reconstruction.zenithreconstructionwithkappa attribute)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.identitytask property)": [[118, "graphnet.models.task.task.IdentityTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.learnedtask property)": [[118, "graphnet.models.task.task.LearnedTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.standardlearnedtask property)": [[118, "graphnet.models.task.task.StandardLearnedTask.nb_inputs", false]], "nb_inputs (graphnet.models.task.task.task property)": [[118, "graphnet.models.task.task.Task.nb_inputs", false]], "nb_inputs() (graphnet.models.task.task.standardflowtask method)": [[118, "graphnet.models.task.task.StandardFlowTask.nb_inputs", false]], "nb_outputs (graphnet.models.gnn.gnn.gnn property)": [[97, "graphnet.models.gnn.gnn.GNN.nb_outputs", false]], "nb_outputs (graphnet.models.graphs.nodes.nodes.nodedefinition property)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.nb_outputs", false]], "nb_repeats_allowed (graphnet.utilities.logging.repeatfilter attribute)": [[141, "graphnet.utilities.logging.RepeatFilter.nb_repeats_allowed", false]], "no_weight_decay() (graphnet.models.gnn.icemix.deepice method)": [[98, "graphnet.models.gnn.icemix.DeepIce.no_weight_decay", false]], "node_rnn (class in graphnet.models.rnn.node_rnn)": [[112, "graphnet.models.rnn.node_rnn.Node_RNN", false]], "node_truth (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.node_truth", false]], "node_truth_table (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.node_truth_table", false]], "nodeasdomtimeseries (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.NodeAsDOMTimeSeries", false]], "nodedefinition (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition", false]], "nodesaspulses (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.NodesAsPulses", false]], "normalizingflow (class in graphnet.models.normalizing_flow)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow", false]], "nullspliti3filter (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.NullSplitI3Filter", false]], "num_samples (graphnet.data.dataset.samplers.randomchunksampler property)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler.num_samples", false]], "on_fit_end() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.on_fit_end", false]], "on_train_end() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.on_train_end", false]], "on_train_epoch_end() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.on_train_epoch_end", false]], "on_train_epoch_end() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.on_train_epoch_end", false]], "on_train_epoch_start() (graphnet.training.callbacks.progressbar method)": [[123, "graphnet.training.callbacks.ProgressBar.on_train_epoch_start", false]], "on_validation_end() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.on_validation_end", false]], "optimizer_step() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.optimizer_step", false]], "options (class in graphnet.utilities.argparse)": [[129, "graphnet.utilities.argparse.Options", false]], "orca150 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.ORCA150", false]], "orca150superdense (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense", false]], "output_folder (graphnet.data.dataclasses.settings attribute)": [[6, "graphnet.data.dataclasses.Settings.output_folder", false]], "pairwise_shuffle() (in module graphnet.data.utilities.random)": [[58, "graphnet.data.utilities.random.pairwise_shuffle", false]], "parquetdataconverter (class in graphnet.data.parquet.deprecated_methods)": [[45, "graphnet.data.parquet.deprecated_methods.ParquetDataConverter", false]], "parquetdataset (class in graphnet.data.dataset.parquet.parquet_dataset)": [[13, "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset", false]], "parquetextractor (class in graphnet.data.extractors.internal.parquet_extractor)": [[39, "graphnet.data.extractors.internal.parquet_extractor.ParquetExtractor", false]], "parquetreader (class in graphnet.data.readers.internal_parquet_reader)": [[51, "graphnet.data.readers.internal_parquet_reader.ParquetReader", false]], "parquettosqliteconverter (class in graphnet.data.pre_configured.dataconverters)": [[47, "graphnet.data.pre_configured.dataconverters.ParquetToSQLiteConverter", false]], "parquetwriter (class in graphnet.data.writers.parquet_writer)": [[63, "graphnet.data.writers.parquet_writer.ParquetWriter", false]], "parse_graph_definition() (in module graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.parse_graph_definition", false]], "parse_labels() (in module graphnet.data.dataset.dataset)": [[11, "graphnet.data.dataset.dataset.parse_labels", false]], "particlenet (class in graphnet.models.gnn.particlenet)": [[99, "graphnet.models.gnn.particlenet.ParticleNeT", false]], "path (graphnet.data.dataset.dataset.dataset property)": [[11, "graphnet.data.dataset.dataset.Dataset.path", false]], "path (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.path", false]], "percentileclusters (class in graphnet.models.graphs.nodes.nodes)": [[107, "graphnet.models.graphs.nodes.nodes.PercentileClusters", false]], "piecewiselinearlr (class in graphnet.training.callbacks)": [[123, "graphnet.training.callbacks.PiecewiseLinearLR", false]], "ponesmall (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.PONESmall", false]], "ponetriangle (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.PONETriangle", false]], "pop_default() (graphnet.utilities.argparse.options method)": [[129, "graphnet.utilities.argparse.Options.pop_default", false]], "positionreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.PositionReconstruction", false]], "predict() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.predict", false]], "predict_as_dataframe() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.predict_as_dataframe", false]], "prediction_labels (graphnet.models.easy_model.easysyntax property)": [[90, "graphnet.models.easy_model.EasySyntax.prediction_labels", false]], "prepare_data() (graphnet.data.curated_datamodule.curateddataset method)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.prepare_data", false]], "prepare_data() (graphnet.data.curated_datamodule.erdahosteddataset method)": [[5, "graphnet.data.curated_datamodule.ERDAHostedDataset.prepare_data", false]], "prepare_data() (graphnet.data.datamodule.graphnetdatamodule method)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.prepare_data", false]], "progressbar (class in graphnet.training.callbacks)": [[123, "graphnet.training.callbacks.ProgressBar", false]], "prometheus (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.Prometheus", false]], "prometheus (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.PROMETHEUS", false]], "prometheus (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.PROMETHEUS", false]], "prometheusextractor (class in graphnet.data.extractors.prometheus.prometheus_extractor)": [[43, "graphnet.data.extractors.prometheus.prometheus_extractor.PrometheusExtractor", false]], "prometheusfeatureextractor (class in graphnet.data.extractors.prometheus.prometheus_extractor)": [[43, "graphnet.data.extractors.prometheus.prometheus_extractor.PrometheusFeatureExtractor", false]], "prometheusreader (class in graphnet.data.readers.prometheus_reader)": [[53, "graphnet.data.readers.prometheus_reader.PrometheusReader", false]], "prometheustruthextractor (class in graphnet.data.extractors.prometheus.prometheus_extractor)": [[43, "graphnet.data.extractors.prometheus.prometheus_extractor.PrometheusTruthExtractor", false]], "publicprometheusdataset (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.PublicPrometheusDataset", false]], "pulse_truth (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.pulse_truth", false]], "pulsemaps (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.pulsemaps", false]], "pulsemaps (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.pulsemaps", false]], "query_database() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.query_database", false]], "query_table() (graphnet.data.dataset.dataset.dataset method)": [[11, "graphnet.data.dataset.dataset.Dataset.query_table", false]], "query_table() (graphnet.data.dataset.parquet.parquet_dataset.parquetdataset method)": [[13, "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset.query_table", false]], "query_table() (graphnet.data.dataset.sqlite.sqlite_dataset.sqlitedataset method)": [[16, "graphnet.data.dataset.sqlite.sqlite_dataset.SQLiteDataset.query_table", false]], "radialedges (class in graphnet.models.graphs.edges.edges)": [[102, "graphnet.models.graphs.edges.edges.RadialEdges", false]], "randomchunksampler (class in graphnet.data.dataset.samplers)": [[14, "graphnet.data.dataset.samplers.RandomChunkSampler", false]], "reduce_options (graphnet.models.coarsening.coarsening attribute)": [[80, "graphnet.models.coarsening.Coarsening.reduce_options", false]], "rename_state_dict_entries() (in module graphnet.utilities.deprecation_tools)": [[138, "graphnet.utilities.deprecation_tools.rename_state_dict_entries", false]], "repeatfilter (class in graphnet.utilities.logging)": [[141, "graphnet.utilities.logging.RepeatFilter", false]], "requires_icecube() (in module graphnet.utilities.imports)": [[140, "graphnet.utilities.imports.requires_icecube", false]], "reset_parameters() (graphnet.models.components.layers.edgeconvtito method)": [[83, "graphnet.models.components.layers.EdgeConvTito.reset_parameters", false]], "resolve() (graphnet.data.utilities.string_selection_resolver.stringselectionresolver method)": [[60, "graphnet.data.utilities.string_selection_resolver.StringSelectionResolver.resolve", false]], "rmseloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.RMSELoss", false]], "rmsevonmisesfisher3dloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.RMSEVonMisesFisher3DLoss", false]], "rnn_tito (class in graphnet.models.gnn.rnn_tito)": [[92, "graphnet.models.gnn.RNN_tito.RNN_TITO", false]], "run() (graphnet.deployment.deployer.deployer method)": [[69, "graphnet.deployment.deployer.Deployer.run", false]], "run_sql_code() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.run_sql_code", false]], "save() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.save", false]], "save_config() (graphnet.utilities.config.configurable.configurable method)": [[132, "graphnet.utilities.config.configurable.Configurable.save_config", false]], "save_dataset_config() (in module graphnet.utilities.config.dataset_config)": [[133, "graphnet.utilities.config.dataset_config.save_dataset_config", false]], "save_model_config() (in module graphnet.utilities.config.model_config)": [[134, "graphnet.utilities.config.model_config.save_model_config", false]], "save_results() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.save_results", false]], "save_selection() (in module graphnet.training.utils)": [[126, "graphnet.training.utils.save_selection", false]], "save_state_dict() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.save_state_dict", false]], "save_to_sql() (in module graphnet.data.utilities.sqlite_utilities)": [[59, "graphnet.data.utilities.sqlite_utilities.save_to_sql", false]], "seed (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.seed", false]], "selection (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.selection", false]], "sensor_id_column (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.sensor_id_column", false]], "sensor_id_column (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.sensor_id_column", false]], "sensor_index_name (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.sensor_index_name", false]], "sensor_position_names (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.sensor_position_names", false]], "serialise() (in module graphnet.data.extractors.icecube.utilities.collections)": [[34, "graphnet.data.extractors.icecube.utilities.collections.serialise", false]], "set_extractors() (graphnet.data.readers.graphnet_file_reader.graphnetfilereader method)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.set_extractors", false]], "set_gcd() (graphnet.data.extractors.icecube.i3extractor.i3extractor method)": [[21, "graphnet.data.extractors.icecube.i3extractor.I3Extractor.set_gcd", false]], "set_gcd() (graphnet.data.extractors.icecube.i3truthextractor.i3truthextractor method)": [[31, "graphnet.data.extractors.icecube.i3truthextractor.I3TruthExtractor.set_gcd", false]], "set_number_of_inputs() (graphnet.models.graphs.nodes.nodes.nodedefinition method)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.set_number_of_inputs", false]], "set_output_feature_names() (graphnet.models.graphs.nodes.nodes.nodedefinition method)": [[107, "graphnet.models.graphs.nodes.nodes.NodeDefinition.set_output_feature_names", false]], "set_verbose_print_recursively() (graphnet.models.model.model method)": [[109, "graphnet.models.model.Model.set_verbose_print_recursively", false]], "setlevel() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.setLevel", false]], "settings (class in graphnet.data.dataclasses)": [[6, "graphnet.data.dataclasses.Settings", false]], "setup() (graphnet.data.datamodule.graphnetdatamodule method)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.setup", false]], "setup() (graphnet.training.callbacks.graphnetearlystopping method)": [[123, "graphnet.training.callbacks.GraphnetEarlyStopping.setup", false]], "shared_step() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.shared_step", false]], "shared_step() (graphnet.models.normalizing_flow.normalizingflow method)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow.shared_step", false]], "shared_step() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.shared_step", false]], "sinusoidalposemb (class in graphnet.models.components.embedding)": [[82, "graphnet.models.components.embedding.SinusoidalPosEmb", false]], "spacetimeencoder (class in graphnet.models.components.embedding)": [[82, "graphnet.models.components.embedding.SpacetimeEncoder", false]], "sqlitedataconverter (class in graphnet.data.sqlite.deprecated_methods)": [[55, "graphnet.data.sqlite.deprecated_methods.SQLiteDataConverter", false]], "sqlitedataset (class in graphnet.data.dataset.sqlite.sqlite_dataset)": [[16, "graphnet.data.dataset.sqlite.sqlite_dataset.SQLiteDataset", false]], "sqlitewriter (class in graphnet.data.writers.sqlite_writer)": [[64, "graphnet.data.writers.sqlite_writer.SQLiteWriter", false]], "standard_arguments (graphnet.utilities.argparse.argumentparser attribute)": [[129, "graphnet.utilities.argparse.ArgumentParser.standard_arguments", false]], "standardaveragedmodel (class in graphnet.models.standard_averaged_model)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel", false]], "standardflowtask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.StandardFlowTask", false]], "standardlearnedtask (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.StandardLearnedTask", false]], "standardmodel (class in graphnet.models.standard_model)": [[114, "graphnet.models.standard_model.StandardModel", false]], "std_pool() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.std_pool", false]], "std_pool_x() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.std_pool_x", false]], "stream_handlers (graphnet.utilities.logging.logger property)": [[141, "graphnet.utilities.logging.Logger.stream_handlers", false]], "string_id_column (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.string_id_column", false]], "string_id_column (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.string_id_column", false]], "string_id_column (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.string_id_column", false]], "string_id_column (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.string_id_column", false]], "string_id_column (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.string_id_column", false]], "string_index_name (graphnet.models.detector.detector.detector property)": [[86, "graphnet.models.detector.detector.Detector.string_index_name", false]], "string_selection (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.string_selection", false]], "stringselectionresolver (class in graphnet.data.utilities.string_selection_resolver)": [[60, "graphnet.data.utilities.string_selection_resolver.StringSelectionResolver", false]], "subeventstreami3filter (class in graphnet.data.extractors.icecube.utilities.i3_filters)": [[36, "graphnet.data.extractors.icecube.utilities.i3_filters.SubEventStreamI3Filter", false]], "sum_pool() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.sum_pool", false]], "sum_pool_and_distribute() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.sum_pool_and_distribute", false]], "sum_pool_x() (in module graphnet.models.components.pool)": [[84, "graphnet.models.components.pool.sum_pool_x", false]], "target (graphnet.utilities.config.training_config.trainingconfig attribute)": [[136, "graphnet.utilities.config.training_config.TrainingConfig.target", false]], "target_labels (graphnet.models.easy_model.easysyntax property)": [[90, "graphnet.models.easy_model.EasySyntax.target_labels", false]], "task (class in graphnet.models.task.task)": [[118, "graphnet.models.task.task.Task", false]], "teardown() (graphnet.data.datamodule.graphnetdatamodule method)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.teardown", false]], "test_dataloader (graphnet.data.datamodule.graphnetdatamodule property)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.test_dataloader", false]], "testdataset (class in graphnet.datasets.test_dataset)": [[67, "graphnet.datasets.test_dataset.TestDataset", false]], "timereconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.TimeReconstruction", false]], "track (class in graphnet.training.labels)": [[124, "graphnet.training.labels.Track", false]], "train() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.train", false]], "train_dataloader (graphnet.data.datamodule.graphnetdatamodule property)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.train_dataloader", false]], "train_eval() (graphnet.models.task.task.task method)": [[118, "graphnet.models.task.task.Task.train_eval", false]], "training_step() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.training_step", false]], "training_step() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.training_step", false]], "trainingconfig (class in graphnet.utilities.config.training_config)": [[136, "graphnet.utilities.config.training_config.TrainingConfig", false]], "transpose_list_of_dicts() (in module graphnet.data.extractors.icecube.utilities.collections)": [[34, "graphnet.data.extractors.icecube.utilities.collections.transpose_list_of_dicts", false]], "traverse_and_apply() (in module graphnet.utilities.config.parsing)": [[135, "graphnet.utilities.config.parsing.traverse_and_apply", false]], "trident1211 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211", false]], "tridentsmall (class in graphnet.datasets.prometheus_datasets)": [[66, "graphnet.datasets.prometheus_datasets.TRIDENTSmall", false]], "truth (class in graphnet.data.constants)": [[4, "graphnet.data.constants.TRUTH", false]], "truth (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.truth", false]], "truth_table (graphnet.data.curated_datamodule.curateddataset property)": [[5, "graphnet.data.curated_datamodule.CuratedDataset.truth_table", false]], "truth_table (graphnet.data.dataset.dataset.dataset property)": [[11, "graphnet.data.dataset.dataset.Dataset.truth_table", false]], "truth_table (graphnet.utilities.config.dataset_config.datasetconfig attribute)": [[133, "graphnet.utilities.config.dataset_config.DatasetConfig.truth_table", false]], "unbatch_edge_index() (in module graphnet.models.coarsening)": [[80, "graphnet.models.coarsening.unbatch_edge_index", false]], "uniform (class in graphnet.training.weight_fitting)": [[127, "graphnet.training.weight_fitting.Uniform", false]], "upgrade (graphnet.data.constants.features attribute)": [[4, "graphnet.data.constants.FEATURES.UPGRADE", false]], "upgrade (graphnet.data.constants.truth attribute)": [[4, "graphnet.data.constants.TRUTH.UPGRADE", false]], "val_dataloader (graphnet.data.datamodule.graphnetdatamodule property)": [[9, "graphnet.data.datamodule.GraphNeTDataModule.val_dataloader", false]], "validate_files() (graphnet.data.readers.graphnet_file_reader.graphnetfilereader method)": [[49, "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader.validate_files", false]], "validate_tasks() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.validate_tasks", false]], "validate_tasks() (graphnet.models.normalizing_flow.normalizingflow method)": [[110, "graphnet.models.normalizing_flow.NormalizingFlow.validate_tasks", false]], "validate_tasks() (graphnet.models.standard_model.standardmodel method)": [[114, "graphnet.models.standard_model.StandardModel.validate_tasks", false]], "validation_step() (graphnet.models.easy_model.easysyntax method)": [[90, "graphnet.models.easy_model.EasySyntax.validation_step", false]], "validation_step() (graphnet.models.standard_averaged_model.standardaveragedmodel method)": [[113, "graphnet.models.standard_averaged_model.StandardAveragedModel.validation_step", false]], "verbose_print (graphnet.models.model.model attribute)": [[109, "graphnet.models.model.Model.verbose_print", false]], "vertexreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.VertexReconstruction", false]], "visibleinelasticityreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.VisibleInelasticityReconstruction", false]], "vonmisesfisher2dloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.VonMisesFisher2DLoss", false]], "vonmisesfisher3dloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.VonMisesFisher3DLoss", false]], "vonmisesfisherloss (class in graphnet.training.loss_functions)": [[125, "graphnet.training.loss_functions.VonMisesFisherLoss", false]], "warning() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.warning", false]], "warning_once() (graphnet.utilities.logging.logger method)": [[141, "graphnet.utilities.logging.Logger.warning_once", false]], "waterdemo81 (class in graphnet.models.detector.prometheus)": [[89, "graphnet.models.detector.prometheus.WaterDemo81", false]], "weightfitter (class in graphnet.training.weight_fitting)": [[127, "graphnet.training.weight_fitting.WeightFitter", false]], "with_standard_arguments() (graphnet.utilities.argparse.argumentparser method)": [[129, "graphnet.utilities.argparse.ArgumentParser.with_standard_arguments", false]], "xyz (graphnet.models.detector.icecube.icecube86 attribute)": [[87, "graphnet.models.detector.icecube.IceCube86.xyz", false]], "xyz (graphnet.models.detector.icecube.icecubekaggle attribute)": [[87, "graphnet.models.detector.icecube.IceCubeKaggle.xyz", false]], "xyz (graphnet.models.detector.icecube.icecubeupgrade attribute)": [[87, "graphnet.models.detector.icecube.IceCubeUpgrade.xyz", false]], "xyz (graphnet.models.detector.liquido.liquido_v1 attribute)": [[88, "graphnet.models.detector.liquido.LiquidO_v1.xyz", false]], "xyz (graphnet.models.detector.prometheus.arca115 attribute)": [[89, "graphnet.models.detector.prometheus.ARCA115.xyz", false]], "xyz (graphnet.models.detector.prometheus.baikalgvd8 attribute)": [[89, "graphnet.models.detector.prometheus.BaikalGVD8.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecube86prometheus attribute)": [[89, "graphnet.models.detector.prometheus.IceCube86Prometheus.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecubedeepcore8 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeDeepCore8.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecubegen2 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeGen2.xyz", false]], "xyz (graphnet.models.detector.prometheus.icecubeupgrade7 attribute)": [[89, "graphnet.models.detector.prometheus.IceCubeUpgrade7.xyz", false]], "xyz (graphnet.models.detector.prometheus.icedemo81 attribute)": [[89, "graphnet.models.detector.prometheus.IceDemo81.xyz", false]], "xyz (graphnet.models.detector.prometheus.orca150 attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150.xyz", false]], "xyz (graphnet.models.detector.prometheus.orca150superdense attribute)": [[89, "graphnet.models.detector.prometheus.ORCA150SuperDense.xyz", false]], "xyz (graphnet.models.detector.prometheus.ponetriangle attribute)": [[89, "graphnet.models.detector.prometheus.PONETriangle.xyz", false]], "xyz (graphnet.models.detector.prometheus.trident1211 attribute)": [[89, "graphnet.models.detector.prometheus.TRIDENT1211.xyz", false]], "xyz (graphnet.models.detector.prometheus.waterdemo81 attribute)": [[89, "graphnet.models.detector.prometheus.WaterDemo81.xyz", false]], "zenithreconstruction (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.ZenithReconstruction", false]], "zenithreconstructionwithkappa (class in graphnet.models.task.reconstruction)": [[117, "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa", false]]}, "objects": {"": [[1, 0, 0, "-", "graphnet"]], "graphnet": [[2, 0, 0, "-", "constants"], [3, 0, 0, "-", "data"], [65, 0, 0, "-", "datasets"], [68, 0, 0, "-", "deployment"], [77, 0, 0, "-", "exceptions"], [79, 0, 0, "-", "models"], [122, 0, 0, "-", "training"], [128, 0, 0, "-", "utilities"]], "graphnet.data": [[4, 0, 0, "-", "constants"], [5, 0, 0, "-", "curated_datamodule"], [6, 0, 0, "-", "dataclasses"], [7, 0, 0, "-", "dataconverter"], [8, 0, 0, "-", "dataloader"], [9, 0, 0, "-", "datamodule"], [10, 0, 0, "-", "dataset"], [17, 0, 0, "-", "extractors"], [44, 0, 0, "-", "parquet"], [46, 0, 0, "-", "pre_configured"], [48, 0, 0, "-", "readers"], [54, 0, 0, "-", "sqlite"], [56, 0, 0, "-", "utilities"], [61, 0, 0, "-", "writers"]], "graphnet.data.constants": [[4, 1, 1, "", "FEATURES"], [4, 1, 1, "", "TRUTH"]], "graphnet.data.constants.FEATURES": [[4, 2, 1, "", "DEEPCORE"], [4, 2, 1, "", "ICECUBE86"], [4, 2, 1, "", "KAGGLE"], [4, 2, 1, "", "LIQUIDO"], [4, 2, 1, "", "PROMETHEUS"], [4, 2, 1, "", "UPGRADE"]], "graphnet.data.constants.TRUTH": [[4, 2, 1, "", "DEEPCORE"], [4, 2, 1, "", "ICECUBE86"], [4, 2, 1, "", "KAGGLE"], [4, 2, 1, "", "LIQUIDO"], [4, 2, 1, "", "PROMETHEUS"], [4, 2, 1, "", "UPGRADE"]], "graphnet.data.curated_datamodule": [[5, 1, 1, "", "CuratedDataset"], [5, 1, 1, "", "ERDAHostedDataset"]], "graphnet.data.curated_datamodule.CuratedDataset": [[5, 3, 1, "", "available_backends"], [5, 3, 1, "", "citation"], [5, 3, 1, "", "comments"], [5, 3, 1, "", "creator"], [5, 3, 1, "", "dataset_dir"], [5, 4, 1, "", "description"], [5, 3, 1, "", "event_truth"], [5, 3, 1, "", "events"], [5, 3, 1, "", "experiment"], [5, 3, 1, "", "features"], [5, 4, 1, "", "prepare_data"], [5, 3, 1, "", "pulse_truth"], [5, 3, 1, "", "pulsemaps"], [5, 3, 1, "", "truth_table"]], "graphnet.data.curated_datamodule.ERDAHostedDataset": [[5, 4, 1, "", "prepare_data"]], "graphnet.data.dataclasses": [[6, 1, 1, "", "I3FileSet"], [6, 1, 1, "", "Settings"]], "graphnet.data.dataclasses.I3FileSet": [[6, 2, 1, "", "gcd_file"], [6, 2, 1, "", "i3_file"]], "graphnet.data.dataclasses.Settings": [[6, 2, 1, "", "gcd_file"], [6, 2, 1, "", "i3_files"], [6, 2, 1, "", "modules"], [6, 2, 1, "", "output_folder"]], "graphnet.data.dataconverter": [[7, 1, 1, "", "DataConverter"], [7, 5, 1, "", "init_global_index"]], "graphnet.data.dataconverter.DataConverter": [[7, 4, 1, "", "get_map_function"], [7, 4, 1, "", "merge_files"]], "graphnet.data.dataloader": [[8, 1, 1, "", "DataLoader"], [8, 5, 1, "", "collate_fn"], [8, 5, 1, "", "do_shuffle"]], "graphnet.data.dataloader.DataLoader": [[8, 4, 1, "", "from_dataset_config"]], "graphnet.data.datamodule": [[9, 1, 1, "", "GraphNeTDataModule"]], "graphnet.data.datamodule.GraphNeTDataModule": [[9, 4, 1, "", "prepare_data"], [9, 4, 1, "", "setup"], [9, 4, 1, "", "teardown"], [9, 3, 1, "", "test_dataloader"], [9, 3, 1, "", "train_dataloader"], [9, 3, 1, "", "val_dataloader"]], "graphnet.data.dataset": [[11, 0, 0, "-", "dataset"], [12, 0, 0, "-", "parquet"], [14, 0, 0, "-", "samplers"], [15, 0, 0, "-", "sqlite"]], "graphnet.data.dataset.dataset": [[11, 1, 1, "", "Dataset"], [11, 1, 1, "", "EnsembleDataset"], [11, 5, 1, "", "load_module"], [11, 5, 1, "", "parse_graph_definition"], [11, 5, 1, "", "parse_labels"]], "graphnet.data.dataset.dataset.Dataset": [[11, 4, 1, "", "add_label"], [11, 4, 1, "", "concatenate"], [11, 4, 1, "", "from_config"], [11, 3, 1, "", "path"], [11, 4, 1, "", "query_table"], [11, 3, 1, "", "truth_table"]], "graphnet.data.dataset.parquet": [[13, 0, 0, "-", "parquet_dataset"]], "graphnet.data.dataset.parquet.parquet_dataset": [[13, 1, 1, "", "ParquetDataset"]], "graphnet.data.dataset.parquet.parquet_dataset.ParquetDataset": [[13, 3, 1, "", "chunk_sizes"], [13, 4, 1, "", "query_table"]], "graphnet.data.dataset.samplers": [[14, 1, 1, "", "LenMatchBatchSampler"], [14, 1, 1, "", "RandomChunkSampler"], [14, 5, 1, "", "gather_len_matched_buckets"]], "graphnet.data.dataset.samplers.RandomChunkSampler": [[14, 3, 1, "", "chunks"], [14, 3, 1, "", "data_source"], [14, 3, 1, "", "num_samples"]], "graphnet.data.dataset.sqlite": [[16, 0, 0, "-", "sqlite_dataset"]], "graphnet.data.dataset.sqlite.sqlite_dataset": [[16, 1, 1, "", "SQLiteDataset"]], "graphnet.data.dataset.sqlite.sqlite_dataset.SQLiteDataset": [[16, 4, 1, "", "query_table"]], "graphnet.data.extractors": [[18, 0, 0, "-", "combine_extractors"], [19, 0, 0, "-", "extractor"], [20, 0, 0, "-", "icecube"], [38, 0, 0, "-", "internal"], [40, 0, 0, "-", "liquido"], [42, 0, 0, "-", "prometheus"]], "graphnet.data.extractors.combine_extractors": [[18, 1, 1, "", "CombinedExtractor"]], "graphnet.data.extractors.extractor": [[19, 1, 1, "", "Extractor"]], "graphnet.data.extractors.extractor.Extractor": [[19, 3, 1, "", "name"]], "graphnet.data.extractors.icecube": [[21, 0, 0, "-", "i3extractor"], [22, 0, 0, "-", "i3featureextractor"], [23, 0, 0, "-", "i3genericextractor"], [24, 0, 0, "-", "i3hybridrecoextractor"], [25, 0, 0, "-", "i3ntmuonlabelsextractor"], [26, 0, 0, "-", "i3particleextractor"], [27, 0, 0, "-", "i3pisaextractor"], [28, 0, 0, "-", "i3quesoextractor"], [29, 0, 0, "-", "i3retroextractor"], [30, 0, 0, "-", "i3splinempeextractor"], [31, 0, 0, "-", "i3truthextractor"], [32, 0, 0, "-", "i3tumextractor"], [33, 0, 0, "-", "utilities"]], "graphnet.data.extractors.icecube.i3extractor": [[21, 1, 1, "", "I3Extractor"]], "graphnet.data.extractors.icecube.i3extractor.I3Extractor": [[21, 4, 1, "", "set_gcd"]], "graphnet.data.extractors.icecube.i3featureextractor": [[22, 1, 1, "", "I3FeatureExtractor"], [22, 1, 1, "", "I3FeatureExtractorIceCube86"], [22, 1, 1, "", "I3FeatureExtractorIceCubeDeepCore"], [22, 1, 1, "", "I3FeatureExtractorIceCubeUpgrade"], [22, 1, 1, "", "I3PulseNoiseTruthFlagIceCubeUpgrade"]], "graphnet.data.extractors.icecube.i3genericextractor": [[23, 1, 1, "", "I3GenericExtractor"]], "graphnet.data.extractors.icecube.i3hybridrecoextractor": [[24, 1, 1, "", "I3GalacticPlaneHybridRecoExtractor"]], "graphnet.data.extractors.icecube.i3ntmuonlabelsextractor": [[25, 1, 1, "", "I3NTMuonLabelExtractor"]], "graphnet.data.extractors.icecube.i3particleextractor": [[26, 1, 1, "", "I3ParticleExtractor"]], "graphnet.data.extractors.icecube.i3pisaextractor": [[27, 1, 1, "", "I3PISAExtractor"]], "graphnet.data.extractors.icecube.i3quesoextractor": [[28, 1, 1, "", "I3QUESOExtractor"]], "graphnet.data.extractors.icecube.i3retroextractor": [[29, 1, 1, "", "I3RetroExtractor"]], "graphnet.data.extractors.icecube.i3splinempeextractor": [[30, 1, 1, "", "I3SplineMPEICExtractor"]], "graphnet.data.extractors.icecube.i3truthextractor": [[31, 1, 1, "", "I3TruthExtractor"]], "graphnet.data.extractors.icecube.i3truthextractor.I3TruthExtractor": [[31, 4, 1, "", "set_gcd"]], "graphnet.data.extractors.icecube.i3tumextractor": [[32, 1, 1, "", "I3TUMExtractor"]], "graphnet.data.extractors.icecube.utilities": [[34, 0, 0, "-", "collections"], [35, 0, 0, "-", "frames"], [36, 0, 0, "-", "i3_filters"], [37, 0, 0, "-", "types"]], "graphnet.data.extractors.icecube.utilities.collections": [[34, 5, 1, "", "flatten_nested_dictionary"], [34, 5, 1, "", "serialise"], [34, 5, 1, "", "transpose_list_of_dicts"]], "graphnet.data.extractors.icecube.utilities.frames": [[35, 5, 1, "", "frame_is_montecarlo"], [35, 5, 1, "", "frame_is_noise"], [35, 5, 1, "", "get_om_keys_and_pulseseries"]], "graphnet.data.extractors.icecube.utilities.i3_filters": [[36, 1, 1, "", "I3Filter"], [36, 1, 1, "", "I3FilterMask"], [36, 1, 1, "", "NullSplitI3Filter"], [36, 1, 1, "", "SubEventStreamI3Filter"]], "graphnet.data.extractors.icecube.utilities.types": [[37, 5, 1, "", "break_cyclic_recursion"], [37, 5, 1, "", "cast_object_to_pure_python"], [37, 5, 1, "", "cast_pulse_series_to_pure_python"], [37, 5, 1, "", "get_member_variables"], [37, 5, 1, "", "is_boost_class"], [37, 5, 1, "", "is_boost_enum"], [37, 5, 1, "", "is_icecube_class"], [37, 5, 1, "", "is_method"], [37, 5, 1, "", "is_type"]], "graphnet.data.extractors.internal": [[39, 0, 0, "-", "parquet_extractor"]], "graphnet.data.extractors.internal.parquet_extractor": [[39, 1, 1, "", "ParquetExtractor"]], "graphnet.data.extractors.liquido": [[41, 0, 0, "-", "h5_extractor"]], "graphnet.data.extractors.liquido.h5_extractor": [[41, 1, 1, "", "H5Extractor"], [41, 1, 1, "", "H5HitExtractor"], [41, 1, 1, "", "H5TruthExtractor"]], "graphnet.data.extractors.prometheus": [[43, 0, 0, "-", "prometheus_extractor"]], "graphnet.data.extractors.prometheus.prometheus_extractor": [[43, 1, 1, "", "PrometheusExtractor"], [43, 1, 1, "", "PrometheusFeatureExtractor"], [43, 1, 1, "", "PrometheusTruthExtractor"]], "graphnet.data.parquet": [[45, 0, 0, "-", "deprecated_methods"]], "graphnet.data.parquet.deprecated_methods": [[45, 1, 1, "", "ParquetDataConverter"]], "graphnet.data.pre_configured": [[47, 0, 0, "-", "dataconverters"]], "graphnet.data.pre_configured.dataconverters": [[47, 1, 1, "", "I3ToParquetConverter"], [47, 1, 1, "", "I3ToSQLiteConverter"], [47, 1, 1, "", "ParquetToSQLiteConverter"]], "graphnet.data.readers": [[49, 0, 0, "-", "graphnet_file_reader"], [50, 0, 0, "-", "i3reader"], [51, 0, 0, "-", "internal_parquet_reader"], [52, 0, 0, "-", "liquido_reader"], [53, 0, 0, "-", "prometheus_reader"]], "graphnet.data.readers.graphnet_file_reader": [[49, 1, 1, "", "GraphNeTFileReader"]], "graphnet.data.readers.graphnet_file_reader.GraphNeTFileReader": [[49, 3, 1, "", "accepted_extractors"], [49, 3, 1, "", "accepted_file_extensions"], [49, 3, 1, "", "extracor_names"], [49, 4, 1, "", "find_files"], [49, 4, 1, "", "set_extractors"], [49, 4, 1, "", "validate_files"]], "graphnet.data.readers.i3reader": [[50, 1, 1, "", "I3Reader"]], "graphnet.data.readers.i3reader.I3Reader": [[50, 4, 1, "", "find_files"]], "graphnet.data.readers.internal_parquet_reader": [[51, 1, 1, "", "ParquetReader"]], "graphnet.data.readers.internal_parquet_reader.ParquetReader": [[51, 4, 1, "", "find_files"]], "graphnet.data.readers.liquido_reader": [[52, 1, 1, "", "LiquidOReader"]], "graphnet.data.readers.liquido_reader.LiquidOReader": [[52, 4, 1, "", "find_files"]], "graphnet.data.readers.prometheus_reader": [[53, 1, 1, "", "PrometheusReader"]], "graphnet.data.readers.prometheus_reader.PrometheusReader": [[53, 4, 1, "", "find_files"]], "graphnet.data.sqlite": [[55, 0, 0, "-", "deprecated_methods"]], "graphnet.data.sqlite.deprecated_methods": [[55, 1, 1, "", "SQLiteDataConverter"]], "graphnet.data.utilities": [[57, 0, 0, "-", "parquet_to_sqlite"], [58, 0, 0, "-", "random"], [59, 0, 0, "-", "sqlite_utilities"], [60, 0, 0, "-", "string_selection_resolver"]], "graphnet.data.utilities.random": [[58, 5, 1, "", "pairwise_shuffle"]], "graphnet.data.utilities.sqlite_utilities": [[59, 5, 1, "", "attach_index"], [59, 5, 1, "", "create_table"], [59, 5, 1, "", "create_table_and_save_to_sql"], [59, 5, 1, "", "database_exists"], [59, 5, 1, "", "database_table_exists"], [59, 5, 1, "", "get_primary_keys"], [59, 5, 1, "", "query_database"], [59, 5, 1, "", "run_sql_code"], [59, 5, 1, "", "save_to_sql"]], "graphnet.data.utilities.string_selection_resolver": [[60, 1, 1, "", "StringSelectionResolver"]], "graphnet.data.utilities.string_selection_resolver.StringSelectionResolver": [[60, 4, 1, "", "resolve"]], "graphnet.data.writers": [[62, 0, 0, "-", "graphnet_writer"], [63, 0, 0, "-", "parquet_writer"], [64, 0, 0, "-", "sqlite_writer"]], "graphnet.data.writers.graphnet_writer": [[62, 1, 1, "", "GraphNeTWriter"]], "graphnet.data.writers.graphnet_writer.GraphNeTWriter": [[62, 3, 1, "", "expects_merged_dataframes"], [62, 3, 1, "", "file_extension"], [62, 4, 1, "", "merge_files"]], "graphnet.data.writers.parquet_writer": [[63, 1, 1, "", "ParquetWriter"]], "graphnet.data.writers.parquet_writer.ParquetWriter": [[63, 4, 1, "", "merge_files"]], "graphnet.data.writers.sqlite_writer": [[64, 1, 1, "", "SQLiteWriter"]], "graphnet.data.writers.sqlite_writer.SQLiteWriter": [[64, 4, 1, "", "merge_files"]], "graphnet.datasets": [[66, 0, 0, "-", "prometheus_datasets"], [67, 0, 0, "-", "test_dataset"]], "graphnet.datasets.prometheus_datasets": [[66, 1, 1, "", "BaikalGVDSmall"], [66, 1, 1, "", "PONESmall"], [66, 1, 1, "", "PublicPrometheusDataset"], [66, 1, 1, "", "TRIDENTSmall"]], "graphnet.datasets.test_dataset": [[67, 1, 1, "", "TestDataset"]], "graphnet.deployment": [[69, 0, 0, "-", "deployer"], [70, 0, 0, "-", "deployment_module"], [71, 0, 0, "-", "i3modules"], [73, 0, 0, "-", "icecube"]], "graphnet.deployment.deployer": [[69, 1, 1, "", "Deployer"]], "graphnet.deployment.deployer.Deployer": [[69, 4, 1, "", "run"]], "graphnet.deployment.deployment_module": [[70, 1, 1, "", "DeploymentModule"]], "graphnet.deployment.i3modules": [[72, 0, 0, "-", "deprecated_methods"]], "graphnet.deployment.i3modules.deprecated_methods": [[72, 1, 1, "", "GraphNeTI3Deployer"]], "graphnet.deployment.icecube": [[74, 0, 0, "-", "cleaning_module"], [75, 0, 0, "-", "i3deployer"], [76, 0, 0, "-", "inference_module"]], "graphnet.deployment.icecube.cleaning_module": [[74, 1, 1, "", "I3PulseCleanerModule"]], "graphnet.deployment.icecube.i3deployer": [[75, 1, 1, "", "I3Deployer"]], "graphnet.deployment.icecube.inference_module": [[76, 1, 1, "", "I3InferenceModule"]], "graphnet.exceptions": [[78, 0, 0, "-", "exceptions"]], "graphnet.exceptions.exceptions": [[78, 6, 1, "", "ColumnMissingException"]], "graphnet.models": [[80, 0, 0, "-", "coarsening"], [81, 0, 0, "-", "components"], [85, 0, 0, "-", "detector"], [90, 0, 0, "-", "easy_model"], [91, 0, 0, "-", "gnn"], [100, 0, 0, "-", "graphs"], [109, 0, 0, "-", "model"], [110, 0, 0, "-", "normalizing_flow"], [111, 0, 0, "-", "rnn"], [113, 0, 0, "-", "standard_averaged_model"], [114, 0, 0, "-", "standard_model"], [115, 0, 0, "-", "task"], [119, 0, 0, "-", "transformer"], [121, 0, 0, "-", "utils"]], "graphnet.models.coarsening": [[80, 1, 1, "", "AttributeCoarsening"], [80, 1, 1, "", "Coarsening"], [80, 1, 1, "", "CustomDOMCoarsening"], [80, 1, 1, "", "DOMAndTimeWindowCoarsening"], [80, 1, 1, "", "DOMCoarsening"], [80, 5, 1, "", "unbatch_edge_index"]], "graphnet.models.coarsening.Coarsening": [[80, 4, 1, "", "forward"], [80, 2, 1, "", "reduce_options"]], "graphnet.models.components": [[82, 0, 0, "-", "embedding"], [83, 0, 0, "-", "layers"], [84, 0, 0, "-", "pool"]], "graphnet.models.components.embedding": [[82, 1, 1, "", "FourierEncoder"], [82, 1, 1, "", "SinusoidalPosEmb"], [82, 1, 1, "", "SpacetimeEncoder"]], "graphnet.models.components.embedding.FourierEncoder": [[82, 4, 1, "", "forward"]], "graphnet.models.components.embedding.SinusoidalPosEmb": [[82, 4, 1, "", "forward"]], "graphnet.models.components.embedding.SpacetimeEncoder": [[82, 4, 1, "", "forward"]], "graphnet.models.components.layers": [[83, 1, 1, "", "Attention_rel"], [83, 1, 1, "", "Block"], [83, 1, 1, "", "Block_rel"], [83, 1, 1, "", "DropPath"], [83, 1, 1, "", "DynEdgeConv"], [83, 1, 1, "", "DynTrans"], [83, 1, 1, "", "EdgeConvTito"], [83, 1, 1, "", "Mlp"]], "graphnet.models.components.layers.Attention_rel": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.Block": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.Block_rel": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.DropPath": [[83, 4, 1, "", "extra_repr"], [83, 4, 1, "", "forward"]], "graphnet.models.components.layers.DynEdgeConv": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.DynTrans": [[83, 4, 1, "", "forward"]], "graphnet.models.components.layers.EdgeConvTito": [[83, 4, 1, "", "forward"], [83, 4, 1, "", "message"], [83, 4, 1, "", "reset_parameters"]], "graphnet.models.components.layers.Mlp": [[83, 4, 1, "", "forward"]], "graphnet.models.components.pool": [[84, 5, 1, "", "group_by"], [84, 5, 1, "", "group_pulses_to_dom"], [84, 5, 1, "", "group_pulses_to_pmt"], [84, 5, 1, "", "min_pool"], [84, 5, 1, "", "min_pool_x"], [84, 5, 1, "", "std_pool"], [84, 5, 1, "", "std_pool_x"], [84, 5, 1, "", "sum_pool"], [84, 5, 1, "", "sum_pool_and_distribute"], [84, 5, 1, "", "sum_pool_x"]], "graphnet.models.detector": [[86, 0, 0, "-", "detector"], [87, 0, 0, "-", "icecube"], [88, 0, 0, "-", "liquido"], [89, 0, 0, "-", "prometheus"]], "graphnet.models.detector.detector": [[86, 1, 1, "", "Detector"]], "graphnet.models.detector.detector.Detector": [[86, 4, 1, "", "feature_map"], [86, 4, 1, "", "forward"], [86, 3, 1, "", "geometry_table"], [86, 3, 1, "", "sensor_index_name"], [86, 3, 1, "", "sensor_position_names"], [86, 3, 1, "", "string_index_name"]], "graphnet.models.detector.icecube": [[87, 1, 1, "", "IceCube86"], [87, 1, 1, "", "IceCubeDeepCore"], [87, 1, 1, "", "IceCubeKaggle"], [87, 1, 1, "", "IceCubeUpgrade"]], "graphnet.models.detector.icecube.IceCube86": [[87, 4, 1, "", "feature_map"], [87, 2, 1, "", "geometry_table_path"], [87, 2, 1, "", "sensor_id_column"], [87, 2, 1, "", "string_id_column"], [87, 2, 1, "", "xyz"]], "graphnet.models.detector.icecube.IceCubeDeepCore": [[87, 4, 1, "", "feature_map"]], "graphnet.models.detector.icecube.IceCubeKaggle": [[87, 4, 1, "", "feature_map"], [87, 2, 1, "", "geometry_table_path"], [87, 2, 1, "", "sensor_id_column"], [87, 2, 1, "", "string_id_column"], [87, 2, 1, "", "xyz"]], "graphnet.models.detector.icecube.IceCubeUpgrade": [[87, 4, 1, "", "feature_map"], [87, 2, 1, "", "geometry_table_path"], [87, 2, 1, "", "sensor_id_column"], [87, 2, 1, "", "string_id_column"], [87, 2, 1, "", "xyz"]], "graphnet.models.detector.liquido": [[88, 1, 1, "", "LiquidO_v1"]], "graphnet.models.detector.liquido.LiquidO_v1": [[88, 4, 1, "", "feature_map"], [88, 2, 1, "", "geometry_table_path"], [88, 2, 1, "", "sensor_id_column"], [88, 2, 1, "", "string_id_column"], [88, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus": [[89, 1, 1, "", "ARCA115"], [89, 1, 1, "", "BaikalGVD8"], [89, 1, 1, "", "IceCube86Prometheus"], [89, 1, 1, "", "IceCubeDeepCore8"], [89, 1, 1, "", "IceCubeGen2"], [89, 1, 1, "", "IceCubeUpgrade7"], [89, 1, 1, "", "IceDemo81"], [89, 1, 1, "", "ORCA150"], [89, 1, 1, "", "ORCA150SuperDense"], [89, 1, 1, "", "PONETriangle"], [89, 1, 1, "", "Prometheus"], [89, 1, 1, "", "TRIDENT1211"], [89, 1, 1, "", "WaterDemo81"]], "graphnet.models.detector.prometheus.ARCA115": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.BaikalGVD8": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCube86Prometheus": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCubeDeepCore8": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCubeGen2": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceCubeUpgrade7": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.IceDemo81": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.ORCA150": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.ORCA150SuperDense": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.PONETriangle": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.TRIDENT1211": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.detector.prometheus.WaterDemo81": [[89, 4, 1, "", "feature_map"], [89, 2, 1, "", "geometry_table_path"], [89, 2, 1, "", "sensor_id_column"], [89, 2, 1, "", "string_id_column"], [89, 2, 1, "", "xyz"]], "graphnet.models.easy_model": [[90, 1, 1, "", "EasySyntax"]], "graphnet.models.easy_model.EasySyntax": [[90, 4, 1, "", "compute_loss"], [90, 4, 1, "", "configure_optimizers"], [90, 4, 1, "", "fit"], [90, 4, 1, "", "forward"], [90, 4, 1, "", "inference"], [90, 4, 1, "", "predict"], [90, 4, 1, "", "predict_as_dataframe"], [90, 3, 1, "", "prediction_labels"], [90, 4, 1, "", "shared_step"], [90, 3, 1, "", "target_labels"], [90, 4, 1, "", "train"], [90, 4, 1, "", "training_step"], [90, 4, 1, "", "validate_tasks"], [90, 4, 1, "", "validation_step"]], "graphnet.models.gnn": [[92, 0, 0, "-", "RNN_tito"], [93, 0, 0, "-", "convnet"], [94, 0, 0, "-", "dynedge"], [95, 0, 0, "-", "dynedge_jinst"], [96, 0, 0, "-", "dynedge_kaggle_tito"], [97, 0, 0, "-", "gnn"], [98, 0, 0, "-", "icemix"], [99, 0, 0, "-", "particlenet"]], "graphnet.models.gnn.RNN_tito": [[92, 1, 1, "", "RNN_TITO"]], "graphnet.models.gnn.RNN_tito.RNN_TITO": [[92, 4, 1, "", "forward"]], "graphnet.models.gnn.convnet": [[93, 1, 1, "", "ConvNet"]], "graphnet.models.gnn.convnet.ConvNet": [[93, 4, 1, "", "forward"]], "graphnet.models.gnn.dynedge": [[94, 1, 1, "", "DynEdge"]], "graphnet.models.gnn.dynedge.DynEdge": [[94, 4, 1, "", "forward"]], "graphnet.models.gnn.dynedge_jinst": [[95, 1, 1, "", "DynEdgeJINST"]], "graphnet.models.gnn.dynedge_jinst.DynEdgeJINST": [[95, 4, 1, "", "forward"]], "graphnet.models.gnn.dynedge_kaggle_tito": [[96, 1, 1, "", "DynEdgeTITO"]], "graphnet.models.gnn.dynedge_kaggle_tito.DynEdgeTITO": [[96, 4, 1, "", "forward"]], "graphnet.models.gnn.gnn": [[97, 1, 1, "", "GNN"]], "graphnet.models.gnn.gnn.GNN": [[97, 4, 1, "", "forward"], [97, 3, 1, "", "nb_inputs"], [97, 3, 1, "", "nb_outputs"]], "graphnet.models.gnn.icemix": [[98, 1, 1, "", "DeepIce"]], "graphnet.models.gnn.icemix.DeepIce": [[98, 4, 1, "", "forward"], [98, 4, 1, "", "no_weight_decay"]], "graphnet.models.gnn.particlenet": [[99, 1, 1, "", "ParticleNeT"]], "graphnet.models.gnn.particlenet.ParticleNeT": [[99, 4, 1, "", "forward"]], "graphnet.models.graphs": [[101, 0, 0, "-", "edges"], [104, 0, 0, "-", "graph_definition"], [105, 0, 0, "-", "graphs"], [106, 0, 0, "-", "nodes"], [108, 0, 0, "-", "utils"]], "graphnet.models.graphs.edges": [[102, 0, 0, "-", "edges"], [103, 0, 0, "-", "minkowski"]], "graphnet.models.graphs.edges.edges": [[102, 1, 1, "", "EdgeDefinition"], [102, 1, 1, "", "EuclideanEdges"], [102, 1, 1, "", "KNNEdges"], [102, 1, 1, "", "RadialEdges"]], "graphnet.models.graphs.edges.edges.EdgeDefinition": [[102, 4, 1, "", "forward"]], "graphnet.models.graphs.edges.minkowski": [[103, 1, 1, "", "MinkowskiKNNEdges"], [103, 5, 1, "", "compute_minkowski_distance_mat"]], "graphnet.models.graphs.graph_definition": [[104, 1, 1, "", "GraphDefinition"]], "graphnet.models.graphs.graph_definition.GraphDefinition": [[104, 4, 1, "", "forward"]], "graphnet.models.graphs.graphs": [[105, 1, 1, "", "EdgelessGraph"], [105, 1, 1, "", "KNNGraph"]], "graphnet.models.graphs.nodes": [[107, 0, 0, "-", "nodes"]], "graphnet.models.graphs.nodes.nodes": [[107, 1, 1, "", "IceMixNodes"], [107, 1, 1, "", "NodeAsDOMTimeSeries"], [107, 1, 1, "", "NodeDefinition"], [107, 1, 1, "", "NodesAsPulses"], [107, 1, 1, "", "PercentileClusters"]], "graphnet.models.graphs.nodes.nodes.NodeDefinition": [[107, 4, 1, "", "forward"], [107, 3, 1, "", "nb_outputs"], [107, 4, 1, "", "set_number_of_inputs"], [107, 4, 1, "", "set_output_feature_names"]], "graphnet.models.graphs.utils": [[108, 1, 1, "", "cluster_and_pad"], [108, 5, 1, "", "cluster_summarize_with_percentiles"], [108, 5, 1, "", "gather_cluster_sequence"], [108, 5, 1, "", "ice_transparency"], [108, 5, 1, "", "identify_indices"], [108, 5, 1, "", "lex_sort"]], "graphnet.models.graphs.utils.cluster_and_pad": [[108, 4, 1, "", "add_charge_threshold_summary"], [108, 4, 1, "", "add_counts"], [108, 4, 1, "", "add_mean"], [108, 4, 1, "", "add_percentile_summary"], [108, 4, 1, "", "add_std"], [108, 4, 1, "", "add_sum_charge"]], "graphnet.models.model": [[109, 1, 1, "", "Model"]], "graphnet.models.model.Model": [[109, 4, 1, "", "extra_repr"], [109, 4, 1, "", "extra_repr_recursive"], [109, 4, 1, "", "from_config"], [109, 4, 1, "", "load"], [109, 4, 1, "", "load_state_dict"], [109, 4, 1, "", "save"], [109, 4, 1, "", "save_state_dict"], [109, 4, 1, "", "set_verbose_print_recursively"], [109, 2, 1, "", "verbose_print"]], "graphnet.models.normalizing_flow": [[110, 1, 1, "", "NormalizingFlow"]], "graphnet.models.normalizing_flow.NormalizingFlow": [[110, 4, 1, "", "forward"], [110, 4, 1, "", "shared_step"], [110, 4, 1, "", "validate_tasks"]], "graphnet.models.rnn": [[112, 0, 0, "-", "node_rnn"]], "graphnet.models.rnn.node_rnn": [[112, 1, 1, "", "Node_RNN"]], "graphnet.models.rnn.node_rnn.Node_RNN": [[112, 4, 1, "", "clean_up_data_object"], [112, 4, 1, "", "forward"]], "graphnet.models.standard_averaged_model": [[113, 1, 1, "", "StandardAveragedModel"]], "graphnet.models.standard_averaged_model.StandardAveragedModel": [[113, 4, 1, "", "load_state_dict"], [113, 4, 1, "", "on_train_end"], [113, 4, 1, "", "optimizer_step"], [113, 4, 1, "", "training_step"], [113, 4, 1, "", "validation_step"]], "graphnet.models.standard_model": [[114, 1, 1, "", "StandardModel"]], "graphnet.models.standard_model.StandardModel": [[114, 4, 1, "", "compute_loss"], [114, 4, 1, "", "forward"], [114, 4, 1, "", "shared_step"], [114, 4, 1, "", "validate_tasks"]], "graphnet.models.task": [[116, 0, 0, "-", "classification"], [117, 0, 0, "-", "reconstruction"], [118, 0, 0, "-", "task"]], "graphnet.models.task.classification": [[116, 1, 1, "", "BinaryClassificationTask"], [116, 1, 1, "", "BinaryClassificationTaskLogits"], [116, 1, 1, "", "MulticlassClassificationTask"]], "graphnet.models.task.classification.BinaryClassificationTask": [[116, 2, 1, "", "default_prediction_labels"], [116, 2, 1, "", "default_target_labels"], [116, 2, 1, "", "nb_inputs"]], "graphnet.models.task.classification.BinaryClassificationTaskLogits": [[116, 2, 1, "", "default_prediction_labels"], [116, 2, 1, "", "default_target_labels"], [116, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction": [[117, 1, 1, "", "AzimuthReconstruction"], [117, 1, 1, "", "AzimuthReconstructionWithKappa"], [117, 1, 1, "", "DirectionReconstructionWithKappa"], [117, 1, 1, "", "EnergyReconstruction"], [117, 1, 1, "", "EnergyReconstructionWithPower"], [117, 1, 1, "", "EnergyReconstructionWithUncertainty"], [117, 1, 1, "", "EnergyTCReconstruction"], [117, 1, 1, "", "InelasticityReconstruction"], [117, 1, 1, "", "PositionReconstruction"], [117, 1, 1, "", "TimeReconstruction"], [117, 1, 1, "", "VertexReconstruction"], [117, 1, 1, "", "VisibleInelasticityReconstruction"], [117, 1, 1, "", "ZenithReconstruction"], [117, 1, 1, "", "ZenithReconstructionWithKappa"]], "graphnet.models.task.reconstruction.AzimuthReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.DirectionReconstructionWithKappa": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyReconstructionWithPower": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.EnergyTCReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.InelasticityReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.PositionReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.TimeReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.VertexReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.VisibleInelasticityReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.ZenithReconstruction": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.reconstruction.ZenithReconstructionWithKappa": [[117, 2, 1, "", "default_prediction_labels"], [117, 2, 1, "", "default_target_labels"], [117, 2, 1, "", "nb_inputs"]], "graphnet.models.task.task": [[118, 1, 1, "", "IdentityTask"], [118, 1, 1, "", "LearnedTask"], [118, 1, 1, "", "StandardFlowTask"], [118, 1, 1, "", "StandardLearnedTask"], [118, 1, 1, "", "Task"]], "graphnet.models.task.task.IdentityTask": [[118, 3, 1, "", "default_prediction_labels"], [118, 3, 1, "", "default_target_labels"], [118, 3, 1, "", "nb_inputs"]], "graphnet.models.task.task.LearnedTask": [[118, 4, 1, "", "compute_loss"], [118, 4, 1, "", "forward"], [118, 3, 1, "", "nb_inputs"]], "graphnet.models.task.task.StandardFlowTask": [[118, 3, 1, "", "default_prediction_labels"], [118, 4, 1, "", "forward"], [118, 4, 1, "", "nb_inputs"]], "graphnet.models.task.task.StandardLearnedTask": [[118, 4, 1, "", "compute_loss"], [118, 3, 1, "", "nb_inputs"]], "graphnet.models.task.task.Task": [[118, 3, 1, "", "default_prediction_labels"], [118, 3, 1, "", "default_target_labels"], [118, 4, 1, "", "inference"], [118, 3, 1, "", "nb_inputs"], [118, 4, 1, "", "train_eval"]], "graphnet.models.transformer": [[120, 0, 0, "-", "iseecube"]], "graphnet.models.transformer.iseecube": [[120, 1, 1, "", "ISeeCube"]], "graphnet.models.transformer.iseecube.ISeeCube": [[120, 4, 1, "", "forward"]], "graphnet.models.utils": [[121, 5, 1, "", "array_to_sequence"], [121, 5, 1, "", "calculate_distance_matrix"], [121, 5, 1, "", "calculate_xyzt_homophily"], [121, 5, 1, "", "get_fields"], [121, 5, 1, "", "knn_graph_batch"]], "graphnet.training": [[123, 0, 0, "-", "callbacks"], [124, 0, 0, "-", "labels"], [125, 0, 0, "-", "loss_functions"], [126, 0, 0, "-", "utils"], [127, 0, 0, "-", "weight_fitting"]], "graphnet.training.callbacks": [[123, 1, 1, "", "GraphnetEarlyStopping"], [123, 1, 1, "", "PiecewiseLinearLR"], [123, 1, 1, "", "ProgressBar"]], "graphnet.training.callbacks.GraphnetEarlyStopping": [[123, 4, 1, "", "on_fit_end"], [123, 4, 1, "", "on_train_epoch_end"], [123, 4, 1, "", "on_validation_end"], [123, 4, 1, "", "setup"]], "graphnet.training.callbacks.PiecewiseLinearLR": [[123, 4, 1, "", "get_lr"]], "graphnet.training.callbacks.ProgressBar": [[123, 4, 1, "", "get_metrics"], [123, 4, 1, "", "init_predict_tqdm"], [123, 4, 1, "", "init_test_tqdm"], [123, 4, 1, "", "init_train_tqdm"], [123, 4, 1, "", "init_validation_tqdm"], [123, 4, 1, "", "on_train_epoch_end"], [123, 4, 1, "", "on_train_epoch_start"]], "graphnet.training.labels": [[124, 1, 1, "", "Direction"], [124, 1, 1, "", "Label"], [124, 1, 1, "", "Track"]], "graphnet.training.labels.Label": [[124, 3, 1, "", "key"]], "graphnet.training.loss_functions": [[125, 1, 1, "", "BinaryCrossEntropyLoss"], [125, 1, 1, "", "CrossEntropyLoss"], [125, 1, 1, "", "EnsembleLoss"], [125, 1, 1, "", "EuclideanDistanceLoss"], [125, 1, 1, "", "LogCMK"], [125, 1, 1, "", "LogCoshLoss"], [125, 1, 1, "", "LossFunction"], [125, 1, 1, "", "MAELoss"], [125, 1, 1, "", "MSELoss"], [125, 1, 1, "", "RMSELoss"], [125, 1, 1, "", "RMSEVonMisesFisher3DLoss"], [125, 1, 1, "", "VonMisesFisher2DLoss"], [125, 1, 1, "", "VonMisesFisher3DLoss"], [125, 1, 1, "", "VonMisesFisherLoss"]], "graphnet.training.loss_functions.LogCMK": [[125, 4, 1, "", "backward"], [125, 4, 1, "", "forward"]], "graphnet.training.loss_functions.LossFunction": [[125, 4, 1, "", "forward"]], "graphnet.training.loss_functions.VonMisesFisherLoss": [[125, 4, 1, "", "log_cmk"], [125, 4, 1, "", "log_cmk_approx"], [125, 4, 1, "", "log_cmk_exact"]], "graphnet.training.utils": [[126, 5, 1, "", "collate_fn"], [126, 1, 1, "", "collator_sequence_buckleting"], [126, 5, 1, "", "get_predictions"], [126, 5, 1, "", "make_dataloader"], [126, 5, 1, "", "make_train_validation_dataloader"], [126, 5, 1, "", "save_results"], [126, 5, 1, "", "save_selection"]], "graphnet.training.weight_fitting": [[127, 1, 1, "", "BjoernLow"], [127, 1, 1, "", "Uniform"], [127, 1, 1, "", "WeightFitter"]], "graphnet.training.weight_fitting.WeightFitter": [[127, 4, 1, "", "fit"]], "graphnet.utilities": [[129, 0, 0, "-", "argparse"], [130, 0, 0, "-", "config"], [137, 0, 0, "-", "decorators"], [138, 0, 0, "-", "deprecation_tools"], [139, 0, 0, "-", "filesys"], [140, 0, 0, "-", "imports"], [141, 0, 0, "-", "logging"], [142, 0, 0, "-", "maths"]], "graphnet.utilities.argparse": [[129, 1, 1, "", "ArgumentParser"], [129, 1, 1, "", "Options"]], "graphnet.utilities.argparse.ArgumentParser": [[129, 2, 1, "", "standard_arguments"], [129, 4, 1, "", "with_standard_arguments"]], "graphnet.utilities.argparse.Options": [[129, 4, 1, "", "contains"], [129, 4, 1, "", "pop_default"]], "graphnet.utilities.config": [[131, 0, 0, "-", "base_config"], [132, 0, 0, "-", "configurable"], [133, 0, 0, "-", "dataset_config"], [134, 0, 0, "-", "model_config"], [135, 0, 0, "-", "parsing"], [136, 0, 0, "-", "training_config"]], "graphnet.utilities.config.base_config": [[131, 1, 1, "", "BaseConfig"], [131, 5, 1, "", "get_all_argument_values"]], "graphnet.utilities.config.base_config.BaseConfig": [[131, 4, 1, "", "as_dict"], [131, 4, 1, "", "dump"], [131, 4, 1, "", "load"], [131, 2, 1, "", "model_config"]], "graphnet.utilities.config.configurable": [[132, 1, 1, "", "Configurable"]], "graphnet.utilities.config.configurable.Configurable": [[132, 3, 1, "", "config"], [132, 4, 1, "", "from_config"], [132, 4, 1, "", "save_config"]], "graphnet.utilities.config.dataset_config": [[133, 1, 1, "", "DatasetConfig"], [133, 1, 1, "", "DatasetConfigSaverABCMeta"], [133, 1, 1, "", "DatasetConfigSaverMeta"], [133, 5, 1, "", "save_dataset_config"]], "graphnet.utilities.config.dataset_config.DatasetConfig": [[133, 4, 1, "", "as_dict"], [133, 2, 1, "", "features"], [133, 2, 1, "", "graph_definition"], [133, 2, 1, "", "index_column"], [133, 2, 1, "", "labels"], [133, 2, 1, "", "loss_weight_column"], [133, 2, 1, "", "loss_weight_default_value"], [133, 2, 1, "", "loss_weight_table"], [133, 2, 1, "", "model_config"], [133, 2, 1, "", "node_truth"], [133, 2, 1, "", "node_truth_table"], [133, 2, 1, "", "path"], [133, 2, 1, "", "pulsemaps"], [133, 2, 1, "", "seed"], [133, 2, 1, "", "selection"], [133, 2, 1, "", "string_selection"], [133, 2, 1, "", "truth"], [133, 2, 1, "", "truth_table"]], "graphnet.utilities.config.model_config": [[134, 1, 1, "", "ModelConfig"], [134, 1, 1, "", "ModelConfigSaverABC"], [134, 1, 1, "", "ModelConfigSaverMeta"], [134, 5, 1, "", "save_model_config"]], "graphnet.utilities.config.model_config.ModelConfig": [[134, 2, 1, "", "arguments"], [134, 4, 1, "", "as_dict"], [134, 2, 1, "", "class_name"], [134, 2, 1, "", "model_config"]], "graphnet.utilities.config.parsing": [[135, 5, 1, "", "get_all_grapnet_classes"], [135, 5, 1, "", "get_graphnet_classes"], [135, 5, 1, "", "is_graphnet_class"], [135, 5, 1, "", "is_graphnet_module"], [135, 5, 1, "", "list_all_submodules"], [135, 5, 1, "", "traverse_and_apply"]], "graphnet.utilities.config.training_config": [[136, 1, 1, "", "TrainingConfig"]], "graphnet.utilities.config.training_config.TrainingConfig": [[136, 2, 1, "", "dataloader"], [136, 2, 1, "", "early_stopping_patience"], [136, 2, 1, "", "fit"], [136, 2, 1, "", "model_config"], [136, 2, 1, "", "target"]], "graphnet.utilities.deprecation_tools": [[138, 5, 1, "", "rename_state_dict_entries"]], "graphnet.utilities.filesys": [[139, 5, 1, "", "find_i3_files"], [139, 5, 1, "", "has_extension"], [139, 5, 1, "", "is_gcd_file"], [139, 5, 1, "", "is_i3_file"]], "graphnet.utilities.imports": [[140, 5, 1, "", "has_icecube_package"], [140, 5, 1, "", "has_jammy_flows_package"], [140, 5, 1, "", "has_torch_package"], [140, 5, 1, "", "requires_icecube"]], "graphnet.utilities.logging": [[141, 1, 1, "", "Logger"], [141, 1, 1, "", "RepeatFilter"]], "graphnet.utilities.logging.Logger": [[141, 4, 1, "", "critical"], [141, 4, 1, "", "debug"], [141, 4, 1, "", "error"], [141, 3, 1, "", "file_handlers"], [141, 3, 1, "", "handlers"], [141, 4, 1, "", "info"], [141, 4, 1, "", "setLevel"], [141, 3, 1, "", "stream_handlers"], [141, 4, 1, "", "warning"], [141, 4, 1, "", "warning_once"]], "graphnet.utilities.logging.RepeatFilter": [[141, 4, 1, "", "filter"], [141, 2, 1, "", "nb_repeats_allowed"]], "graphnet.utilities.maths": [[142, 5, 1, "", "eps_like"]]}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "attribute", "Python attribute"], "3": ["py", "property", "Python property"], "4": ["py", "method", "Python method"], "5": ["py", "function", "Python function"], "6": ["py", "exception", "Python exception"]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:attribute", "3": "py:property", "4": "py:method", "5": "py:function", "6": "py:exception"}, "terms": {"": [0, 7, 8, 9, 11, 13, 16, 34, 45, 47, 49, 52, 53, 55, 62, 64, 69, 82, 86, 90, 93, 94, 99, 104, 110, 118, 121, 123, 127, 129, 133, 134, 141, 142, 145, 146, 147, 148, 150, 151, 152], "0": [9, 11, 13, 16, 31, 45, 47, 50, 55, 60, 74, 80, 83, 84, 92, 93, 94, 96, 99, 102, 103, 105, 108, 112, 118, 121, 124, 125, 126, 133, 146, 147, 149, 150, 152], "000": 146, "001": [147, 152], "01": [147, 152], "0221": 147, "02_data": 147, "03042": 95, "03762": 82, "04616": 125, "04_ensemble_dataset": 147, "05": 125, "06": 144, "06166": 102, "08570": 99, "0e04": 150, "0e4": 150, "1": [0, 7, 9, 11, 13, 14, 19, 34, 45, 47, 55, 60, 63, 66, 69, 72, 75, 80, 83, 84, 92, 94, 96, 98, 99, 102, 103, 105, 108, 112, 116, 117, 118, 121, 123, 124, 125, 126, 127, 133, 145, 146, 147, 148, 149, 151, 152], "10": [9, 66, 87, 88, 89, 107, 108, 129, 146, 147, 150, 152], "100": 146, "1000": [118, 146, 147], "10000": [11, 13, 16, 60, 82], "1088": 147, "10th": 108, "11": [147, 149], "12": [60, 98, 120, 133, 146, 147], "120": 147, "128": [82, 93, 94, 96, 99, 129, 146, 147, 152], "13": 60, "14": [60, 133, 146, 147], "1536": 120, "15674": 82, "16": [14, 60, 82, 92, 99, 120, 133, 146, 147, 152], "17": [14, 147], "1706": 82, "1748": 147, "1809": 102, "1812": 125, "1902": 99, "192": 98, "196": 120, "1e6": 118, "2": [9, 34, 45, 55, 83, 84, 92, 94, 96, 99, 102, 105, 108, 112, 117, 121, 125, 133, 146, 147, 149, 152], "20": [11, 13, 16, 60, 141, 147, 149, 150, 152], "200": [146, 150], "200000": 63, "2018": 144, "2019": 125, "2020": [0, 148, 151], "2023": 14, "21": [144, 146, 147], "2209": 95, "2310": 82, "256": [94, 96, 99, 120], "26": 146, "2d": 125, "2nd": [14, 82, 98], "3": [84, 92, 93, 96, 103, 108, 112, 117, 120, 121, 125, 144, 147, 149, 150], "30": 150, "300": [146, 150], "32": [14, 82, 98, 120], "336": [94, 96], "384": [82, 98, 120], "39": [0, 148, 151], "3d": [117, 125], "4": [14, 83, 95, 98, 108, 117, 147, 150, 152], "40": 150, "400": 64, "42": 9, "5": [11, 13, 16, 60, 92, 108, 112, 125, 129, 145, 146, 147, 149, 150, 152], "50": [107, 108, 129, 150], "500": [108, 150], "50000": [60, 133, 146, 147], "5001": 146, "50th": 108, "59": 149, "6": [82, 84, 98, 120], "64": [92, 99], "7": [74, 84], "700": 125, "768": 107, "8": [83, 84, 92, 94, 96, 105, 112, 125, 126, 144, 146, 147, 149, 152], "80": [147, 152], "86": [22, 87], "890778": [0, 148, 151], "9": 9, "90": [107, 108], "90th": 108, "A": [5, 7, 9, 11, 14, 36, 49, 50, 51, 52, 53, 59, 64, 66, 67, 69, 70, 74, 75, 84, 86, 87, 88, 89, 90, 104, 105, 108, 109, 110, 114, 116, 118, 121, 125, 127, 145, 146, 147, 150, 152], "AND": [14, 125], "AS": [14, 125], "As": [94, 99, 152], "BE": [14, 125], "BUT": [14, 125], "But": 152, "By": [0, 45, 47, 50, 55, 118, 146, 147, 148, 151, 152], "FOR": [14, 125], "For": [14, 37, 107, 123, 146, 147, 152], "IN": [14, 125], "If": [5, 11, 13, 14, 21, 23, 31, 36, 64, 66, 67, 82, 83, 94, 98, 99, 104, 107, 108, 109, 118, 123, 125, 127, 144, 145, 147, 152], "In": [45, 47, 49, 50, 55, 62, 133, 134, 145, 147, 149], "It": [1, 5, 34, 59, 74, 82, 108, 116, 118, 144, 146, 147, 152], "NO": [14, 125], "NOT": [14, 59, 125, 147], "No": [0, 147, 148, 151], "OF": [14, 125], "ONE": 66, "OR": [14, 125], "On": 5, "One": 147, "Or": 146, "Such": 59, "THE": [14, 125], "TO": [14, 125], "That": [11, 13, 16, 94, 99, 117, 124, 147, 152], "The": [0, 7, 9, 11, 13, 14, 16, 18, 34, 37, 45, 47, 55, 59, 62, 63, 64, 69, 70, 72, 74, 75, 76, 80, 82, 83, 84, 92, 94, 96, 98, 99, 102, 104, 108, 110, 112, 116, 117, 118, 120, 121, 123, 124, 125, 138, 145, 146, 148, 150, 151], "Then": [5, 144], "There": [147, 152], "These": [0, 49, 62, 64, 104, 144, 146, 147, 148, 150, 151, 152], "To": [146, 147, 149, 150, 152], "WITH": [14, 125], "Will": [5, 66, 67, 69, 72, 74, 75, 76, 102, 145], "With": [147, 150, 152], "_": 147, "__": [34, 37, 147], "_____________________": [14, 125], "__call__": [19, 21, 49, 70, 145, 146, 147, 150], "__init__": [133, 134, 145, 146, 147, 152], "_accepted_extractor": [145, 150], "_accepted_file_extens": [145, 150], "_and_": [94, 99], "_charge_sum": 108, "_charge_weight": 108, "_cluster_nam": 108, "_column_nam": 145, "_construct_edg": 102, "_count": 108, "_definition_": 147, "_extractor": [145, 150], "_extractor_nam": [145, 150], "_file_extens": 145, "_file_hash": 5, "_fit_weight": 127, "_forward": 152, "_indic": [11, 13], "_layer": 152, "_lrschedul": 123, "_may_": [11, 13], "_merge_datafram": 145, "_padded_x": 108, "_pred": 118, "_save_fil": 145, "_sensor_tim": 150, "_sensor_xyz": 150, "_tabl": 145, "_task": [90, 110, 114], "_verify_column": 145, "_x_": 147, "a__b": 34, "ab": [60, 99, 125, 133, 146, 147], "abc": [7, 11, 19, 49, 62, 69, 109, 124, 127, 132, 133, 134], "abcmeta": [133, 134], "abil": 146, "abl": [34, 107, 110, 145, 147, 149, 150, 152], "about": [109, 146, 147, 150], "abov": [14, 125, 127, 146, 147, 150, 152], "absolut": 125, "absopt": 107, "absorpt": 108, "abstract": [1, 5, 11, 62, 86, 97, 104, 118, 132, 147], "abstractmethod": 146, "acceler": 1, "accept": [49, 144, 152], "accepted_extractor": [49, 145], "accepted_file_extens": [49, 145], "access": [124, 146], "accompani": [45, 47, 50, 55, 147], "accord": [80, 84, 102, 104, 105, 108, 125], "achiev": 149, "achitectur": 152, "across": [1, 2, 11, 13, 16, 37, 56, 69, 72, 75, 84, 90, 114, 125, 128, 129, 130, 141, 150], "act": [118, 125, 147, 152], "action": [14, 125], "activ": [83, 90, 92, 94, 99, 107, 112, 118, 144], "activation_lay": [94, 99], "actual": [147, 152], "ad": [7, 11, 13, 16, 22, 45, 47, 55, 82, 94, 98, 107, 108], "adam": [110, 147, 152], "adapt": [147, 152], "add": [11, 83, 94, 99, 108, 129, 138, 144, 147, 150], "add_batchnorm_lay": 99, "add_charge_threshold_summari": 108, "add_count": [107, 108], "add_global_variables_after_pool": [94, 147, 152], "add_ice_properti": 107, "add_inactive_sensor": 104, "add_label": [11, 146, 147], "add_mean": 108, "add_norm_lay": 94, "add_percentile_summari": 108, "add_std": 108, "add_sum_charg": 108, "add_to_databas": 127, "addit": [49, 62, 80, 83, 90, 108, 125, 127, 145, 147, 152], "additional_attribut": [90, 126, 147, 152], "address": 152, "adher": [144, 152], "adjac": 86, "adjust": 152, "advanc": [1, 84], "after": [9, 83, 92, 94, 96, 99, 123, 129, 133, 146, 147, 152], "again": [147, 152], "against": 5, "aggr": 83, "aggreg": [83, 84, 108], "agnost": [0, 148, 151, 152], "agreement": [0, 144, 148, 151], "ai": 147, "aim": [0, 1, 144, 147, 148, 151], "algorithm": 26, "all": [1, 5, 11, 13, 14, 16, 18, 19, 21, 23, 36, 59, 64, 66, 67, 74, 82, 83, 84, 86, 94, 97, 99, 103, 104, 108, 109, 118, 125, 127, 131, 132, 133, 134, 135, 136, 141, 144, 145, 146, 147, 150, 152], "allow": [0, 5, 39, 68, 71, 79, 84, 123, 131, 136, 146, 147, 148, 151, 152], "along": [108, 147, 152], "alongsid": [147, 152], "alreadi": 59, "also": [7, 11, 13, 16, 60, 92, 133, 145, 146, 147, 150, 152], "alter": [104, 108], "altern": [94, 125, 144], "alwai": 126, "amount": 92, "an": [0, 14, 19, 37, 45, 47, 50, 55, 60, 71, 75, 104, 105, 112, 113, 125, 139, 141, 144, 145, 147, 148, 149, 150, 151, 152], "anaconda": 149, "analys": [68, 147], "analysi": [69, 75], "angl": [117, 124, 147, 152], "ani": [6, 7, 8, 9, 11, 13, 14, 16, 34, 35, 36, 37, 49, 51, 52, 53, 62, 64, 74, 80, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 125, 127, 129, 131, 132, 133, 134, 135, 136, 141, 146, 147, 152], "anoth": [14, 133, 134, 146, 147], "anyth": 144, "api": [143, 145, 147], "appear": [69, 72, 75, 146, 147], "append": 104, "appli": [7, 11, 13, 16, 45, 47, 48, 49, 55, 69, 72, 75, 83, 84, 90, 92, 93, 94, 95, 96, 97, 98, 99, 108, 110, 112, 114, 116, 118, 120, 125, 135, 145, 146, 147], "applic": [34, 146, 147, 152], "appropri": [59, 118, 147], "approx": 125, "approxim": 64, "ar": [0, 1, 4, 5, 11, 13, 14, 16, 21, 23, 31, 36, 37, 49, 60, 62, 63, 64, 69, 74, 75, 83, 84, 92, 94, 96, 99, 100, 101, 102, 104, 105, 106, 107, 108, 112, 116, 125, 127, 133, 134, 144, 145, 146, 147, 148, 150, 151, 152], "arbitrari": [0, 148, 151], "arca": 89, "arca115": [85, 89], "architectur": [1, 93, 94, 95, 96, 99, 110, 112, 120, 147, 152], "archiv": 126, "area": 1, "arg": [11, 13, 16, 18, 36, 80, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 125, 129, 131, 141, 145, 150], "argpars": [1, 128], "argument": [5, 9, 14, 63, 66, 67, 98, 110, 123, 127, 129, 131, 133, 134, 136, 146, 147, 150, 152], "argumentpars": [128, 129], "aris": [14, 125], "arrai": [19, 31, 34, 107, 108, 121, 145, 146, 147, 150], "array_to_sequ": [79, 121], "arriv": 146, "art": [0, 148, 151], "articl": 147, "artifact": [147, 152], "arxiv": [82, 99, 102, 125], "as_dict": [131, 133, 134, 147, 152], "assert": [145, 146], "assertionerror": 145, "assign": [7, 11, 13, 16, 80, 84, 105, 144, 145], "associ": [14, 74, 76, 104, 108, 117, 125, 145, 146, 147, 150, 152], "assort": 142, "assum": [5, 74, 82, 86, 104, 108, 118, 121], "atmospher": 146, "attach": 59, "attach_index": [56, 59], "attempt": [21, 31, 147], "attent": [82, 83, 98, 120], "attention_rel": [81, 83], "attn_drop": 83, "attn_head_dim": 83, "attn_mask": 83, "attribut": [5, 11, 13, 16, 80, 118, 146, 147, 152], "attributecoarsen": [79, 80], "author": [14, 93, 95, 125], "auto": 118, "autom": 144, "automat": [23, 63, 82, 104, 108, 125, 144, 145, 147, 150], "automatic_log_bin": 127, "auxiliari": [4, 82, 147, 152], "avail": [5, 7, 23, 66, 67, 116, 117, 118, 140, 145, 146, 147, 149, 150, 152], "available_backend": 5, "available_t": 145, "averag": [84, 113, 125], "avg": 80, "avg_pool": 80, "avg_pool_x": 80, "avoid": [13, 141, 144], "awai": [1, 147], "azimiuth": 124, "azimuth": [4, 117, 124], "azimuth_kappa": 117, "azimuth_kei": 124, "azimuth_pr": 117, "azimuthreconstruct": [115, 117], "azimuthreconstructionwithkappa": [115, 117], "b": [34, 80, 84, 121, 147, 150, 152], "backbon": [110, 147], "backend": [5, 12, 15, 61, 63, 66, 67, 150], "backward": [108, 125], "baikal": 66, "baikalgvd8": [85, 89], "baikalgvdsmal": [65, 66], "bar": 123, "base": [0, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 36, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 60, 62, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 78, 80, 82, 83, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 136, 140, 141, 145, 146, 147, 148, 151, 152], "base_config": [128, 130], "baseclass": [69, 75], "baseconfig": [130, 131, 132, 133, 134, 136], "basemodel": [131, 133, 134], "basi": 152, "basic": [1, 147], "batch": [0, 8, 13, 14, 63, 80, 83, 84, 90, 99, 110, 112, 114, 121, 126, 129, 146, 148, 151], "batch_idx": [90, 110, 113, 114, 121], "batch_siz": [8, 9, 14, 121, 126, 146, 147, 152], "batch_split": 126, "batchsampl": 14, "becaus": [58, 147, 152], "been": [5, 72, 74, 125, 144, 152], "befor": [11, 13, 94, 103, 112, 118, 123], "behavior": 145, "behaviour": 123, "behind": [147, 152], "being": [21, 31, 74, 82, 116, 118, 146, 147, 152], "beitv2": 83, "belong": 121, "below": [5, 60, 107, 127, 144, 145, 147, 148, 150, 151, 152], "benchmark": 5, "besid": 146, "bessel": 125, "best": [0, 123, 144, 148, 151], "better": 144, "between": [39, 66, 82, 90, 100, 101, 102, 103, 106, 110, 114, 118, 121, 123, 125, 127, 133, 134, 147, 152], "bia": [83, 120], "bias": [147, 152], "big": [147, 152], "biject": 145, "bin": [14, 127], "binari": [114, 116, 125, 152], "binaryclassificationtask": [115, 116, 147, 152], "binaryclassificationtasklogit": [115, 116], "binarycrossentropyloss": [122, 125], "bjoernlow": [122, 127], "black": 144, "blob": [14, 125, 147], "block": [0, 1, 81, 83, 99, 147, 148, 151], "block_rel": [81, 83], "boilerpl": 152, "bool": [8, 14, 35, 36, 37, 59, 60, 62, 74, 82, 83, 90, 92, 94, 96, 98, 99, 104, 107, 108, 109, 114, 120, 123, 125, 126, 127, 129, 135, 138, 139, 140, 141], "boost": 37, "border": 31, "both": [0, 23, 110, 114, 118, 147, 148, 150, 151, 152], "bottleneck": 14, "boundari": 31, "box": [145, 147, 152], "branch": 144, "break_cyclic_recurs": [33, 37], "broken": [45, 47, 50, 55], "bucket": [14, 120, 126], "bucket_width": 14, "bug": [144, 147], "build": [0, 1, 79, 86, 102, 103, 107, 108, 109, 110, 131, 133, 134, 147, 148, 151, 152], "built": [0, 79, 104, 110, 146, 147, 148, 150, 151, 152], "c": [14, 21, 31, 34, 84, 103, 125, 147], "c_": 125, "cach": 13, "cache_s": 13, "calcul": [74, 82, 90, 102, 105, 107, 108, 110, 114, 121, 124, 125, 146, 147, 152], "calculate_distance_matrix": [79, 121], "calculate_xyzt_homophili": [79, 121], "calibr": [35, 37], "call": [7, 14, 23, 37, 82, 84, 118, 123, 127, 141, 145, 147, 150, 152], "callabl": [8, 11, 37, 83, 84, 86, 87, 88, 89, 104, 113, 118, 126, 127, 131, 133, 134, 135, 140, 150], "callback": [1, 90, 122, 147, 152], "can": [0, 1, 5, 9, 11, 13, 14, 16, 19, 23, 26, 74, 82, 84, 104, 110, 127, 129, 131, 133, 134, 144, 145, 146, 147, 148, 150, 151, 152], "cannot": [37, 112, 127, 131, 136], "cap": 127, "capabl": [0, 114, 148, 151], "captur": [147, 152], "care": 146, "carlo": 35, "cascad": 117, "case": [11, 13, 16, 23, 45, 47, 50, 55, 74, 84, 108, 118, 145, 146, 147, 149, 152], "cast": [23, 37], "cast_object_to_pure_python": [33, 37], "cast_pulse_series_to_pure_python": [33, 37], "caus": 147, "caveat": [147, 152], "cc": 124, "cd": 149, "center": 102, "centr": 102, "central": [147, 149], "certain": 147, "cfg": 11, "cframe": [21, 31], "chain": [0, 1, 68, 71, 79, 90, 110, 114, 125, 148, 149, 151], "chang": [125, 144, 147, 152], "charg": [4, 14, 82, 92, 107, 108, 112, 125, 146, 147, 152], "charge_column": 107, "charge_index": 108, "check": [8, 35, 36, 37, 49, 59, 107, 129, 139, 140, 144, 150], "checkpoint": 147, "checkpointing_bas": 147, "chenli2049": 120, "cherenkov": [107, 108, 147, 150, 152], "choic": [146, 147, 152], "choos": [147, 152], "chosen": [102, 108, 141, 146], "chunk": [13, 14, 145], "chunk_siz": 13, "chunks_per_seg": 14, "citat": 5, "cite": 5, "ckpt": [147, 152], "ckpt_path": 90, "claim": [14, 125], "clash": 141, "class": [4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 60, 62, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 80, 82, 83, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 141, 144, 145, 146], "class_nam": [11, 36, 49, 51, 52, 53, 62, 134, 141, 146, 147, 152], "classif": [1, 79, 114, 115, 118, 125, 147, 152], "classifi": [116, 146, 147, 152], "classmethod": [8, 11, 109, 125, 131, 147, 152], "classvar": [131, 133, 134, 136], "clean": [74, 144, 149], "clean_up_data_object": 112, "cleaning_modul": [68, 73], "cleanup": 9, "clear": [141, 146], "cli": 129, "clone": 149, "close": 9, "closest": 123, "cloud": [147, 152], "cls_tocken": 98, "cluster": [80, 83, 84, 92, 94, 96, 99, 107, 108, 112], "cluster_and_pad": [100, 108], "cluster_class": 108, "cluster_column": 108, "cluster_index": 84, "cluster_indic": 108, "cluster_on": [107, 108], "cluster_summarize_with_percentil": [100, 108], "clustered_x": 108, "cnn": [147, 152], "coarsen": [1, 79, 84], "code": [0, 31, 45, 55, 59, 104, 133, 134, 145, 146, 147, 148, 150, 151, 152], "coincid": 107, "collabor": [1, 147, 152], "collate_fn": [3, 8, 122, 126], "collator_sequence_bucklet": [122, 126], "collect": [11, 20, 33, 71, 125, 142, 147, 152], "column": [7, 11, 13, 16, 19, 41, 43, 45, 47, 55, 59, 63, 64, 70, 76, 78, 82, 86, 90, 92, 102, 104, 105, 107, 108, 112, 116, 117, 118, 121, 125, 127, 145, 146, 147, 150, 152], "column_nam": [41, 145], "column_offset": 108, "columnmissingexcept": [11, 13, 77, 78], "com": [14, 98, 110, 120, 125, 147, 149], "combin": [18, 34, 47, 92, 114, 125, 133, 152], "combine_extractor": [3, 17], "combinedextractor": [17, 18], "come": [5, 90, 118, 145, 146, 147, 152], "command": 129, "comment": 5, "commit": 144, "common": [0, 1, 125, 133, 134, 137, 140, 146, 147, 148, 151], "compar": [147, 152], "comparison": [26, 125], "compat": [49, 60, 90, 110, 114, 118, 145, 146, 147, 152], "competit": [82, 83, 87, 96, 98], "complet": [0, 14, 79, 147, 148, 149, 151, 152], "complex": [0, 79, 147, 148, 151], "compon": [0, 1, 79, 82, 83, 84, 90, 109, 110, 114, 147, 148, 151, 152], "compos": [147, 152], "composit": 141, "comprehens": 147, "compress": [5, 146], "compris": [0, 148, 151], "comput": [70, 83, 90, 103, 108, 114, 118, 121, 125, 146, 147], "compute_loss": [90, 114, 118], "compute_minkowski_distance_mat": [101, 103], "con": [147, 152], "concatdataset": 11, "concaten": [11, 34, 94], "concept": 144, "conceptu": [145, 147], "concret": 147, "condit": [14, 110, 118, 125], "condition_on": 110, "confid": 147, "config": [1, 8, 60, 123, 125, 128, 129, 131, 132, 133, 134, 135, 136, 146, 147, 152], "config_dir": [147, 152], "configdict": [131, 133, 134, 136], "configur": [0, 1, 9, 11, 46, 47, 70, 71, 79, 90, 109, 128, 130, 131, 133, 134, 136, 141, 145, 147, 148, 151, 152], "configure_optim": 90, "conflict": 147, "conform": [131, 133, 134, 136], "conjunct": [19, 118], "conn": 147, "connect": [0, 9, 14, 102, 103, 104, 107, 125, 146, 147, 148, 151], "consequ": 109, "consid": [74, 92, 146, 147, 150], "consist": [82, 129, 141, 144, 147, 152], "consortium": [0, 148, 151], "constant": [1, 3, 118, 143, 146, 147, 152], "constitut": [63, 146], "constraint": [90, 147], "construct": [5, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 36, 39, 41, 43, 49, 51, 52, 53, 60, 62, 63, 64, 66, 67, 70, 80, 81, 82, 83, 86, 87, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 106, 107, 108, 109, 112, 113, 114, 116, 117, 118, 120, 123, 124, 125, 126, 127, 129, 132, 133, 134, 141, 145, 146, 147, 152], "constructor": [145, 146, 147], "consult": 152, "consum": 147, "consumpt": 146, "conta": 14, "contain": [0, 5, 6, 7, 11, 13, 14, 16, 17, 18, 21, 34, 35, 38, 39, 40, 43, 45, 47, 49, 50, 51, 55, 59, 62, 63, 64, 65, 66, 69, 70, 71, 72, 74, 75, 76, 78, 90, 94, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110, 114, 118, 121, 125, 127, 129, 145, 146, 147, 148, 150, 151, 152], "containeris": 1, "content": [145, 152], "context": 67, "continu": [0, 125, 147, 148, 151], "contract": [14, 125], "contribut": [0, 125, 147, 148, 151], "contributor": 144, "conveni": [1, 144, 147, 152], "convent": [45, 47, 50, 55], "convers": [7, 38, 39, 43, 45, 55, 107, 146, 147, 150], "convert": [0, 1, 3, 5, 7, 13, 21, 31, 34, 36, 45, 46, 47, 55, 57, 63, 65, 121, 145, 146, 147, 148, 149, 150, 151], "converteddataset": 5, "convex": 31, "convnet": [79, 91, 147], "convolut": [83, 93, 94, 95, 96, 99], "coo": 146, "coordin": [31, 86, 103, 107, 108, 121, 147], "copi": [14, 125, 146], "copyright": [14, 125], "core": 97, "correct": 125, "correpond": 58, "correspond": [11, 13, 16, 34, 37, 58, 94, 99, 104, 108, 127, 139, 146, 147, 150, 152], "cosh": 125, "could": [144, 147, 152], "count": 108, "counterpart": 146, "cover": 60, "cpu": [7, 14, 45, 47, 55, 70], "creat": [5, 9, 14, 59, 104, 105, 107, 108, 131, 132, 136, 144, 146, 152], "create_t": [56, 59], "create_table_and_save_to_sql": [56, 59], "creator": 5, "critic": [141, 147, 150], "cross": 125, "crossentropyloss": [122, 125], "csv": [126, 133, 146, 147, 150, 152], "ctx": 125, "cuda": 149, "cumul": 108, "curat": 5, "curated_datamodul": [1, 3], "curateddataset": [3, 5, 66, 67], "curi": [0, 148, 151], "current": [60, 112, 123, 144, 147], "curv": 127, "custom": [11, 49, 77, 104, 123, 152], "custom_label_funct": 104, "customdomcoarsen": [79, 80], "customis": 123, "cut": 126, "d": [34, 103, 104, 107, 121, 144, 150], "damag": [14, 125], "data": [0, 1, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 41, 42, 43, 45, 47, 48, 49, 50, 51, 52, 53, 55, 56, 58, 59, 60, 61, 62, 63, 64, 66, 67, 80, 82, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 104, 105, 107, 108, 110, 112, 113, 114, 118, 120, 121, 124, 126, 129, 131, 133, 136, 140, 143, 146, 147, 148, 151, 152], "data_path": 104, "data_sourc": 14, "databas": [5, 16, 59, 64, 127, 146, 147], "database_exist": [56, 59], "database_indic": 126, "database_nam": 64, "database_path": [59, 127], "database_table_exist": [56, 59], "dataclass": [1, 3, 35], "dataconfig": [133, 146], "dataconvert": [1, 3, 46, 62, 63, 64, 147, 150], "dataformat": [61, 64], "datafram": [59, 60, 62, 86, 90, 126, 127, 145, 147, 150, 152], "dataload": [1, 3, 5, 9, 13, 66, 67, 90, 104, 126, 136, 146, 147, 152], "datamodul": [1, 3, 5], "datarepresent": 110, "dataset": [1, 3, 5, 8, 9, 12, 13, 14, 15, 16, 25, 60, 63, 66, 67, 78, 92, 104, 112, 129, 133, 143, 150, 152], "dataset_1": [146, 147], "dataset_2": [146, 147], "dataset_3": [146, 147], "dataset_arg": 9, "dataset_config": [128, 130, 147, 152], "dataset_config_path": [147, 152], "dataset_dir": 5, "dataset_refer": 9, "datasetconfig": [8, 11, 60, 130, 133, 146, 152], "datasetconfigsav": 133, "datasetconfigsaverabcmeta": [130, 133], "datasetconfigsavermeta": [130, 133], "db": [64, 126, 127, 146, 147], "db_count_norm": 127, "ddp": [147, 152], "de": 34, "deactiv": [90, 118], "deal": [14, 125], "debug": [141, 147], "decai": 98, "decor": [1, 128, 140], "dedic": 144, "deem": 37, "deep": [0, 5, 62, 64, 83, 96, 98, 145, 147, 148, 149, 150, 151, 152], "deepcopi": 138, "deepcor": [4, 22, 87], "deepic": [91, 98], "def": [145, 146, 147, 150, 152], "default": [5, 7, 9, 11, 13, 14, 16, 21, 23, 31, 34, 43, 45, 47, 50, 55, 59, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 82, 83, 84, 86, 87, 88, 89, 92, 93, 94, 95, 96, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 118, 120, 121, 123, 124, 125, 127, 129, 131, 139, 146, 147], "default_prediction_label": [116, 117, 118, 152], "default_target_label": [116, 117, 118, 152], "default_typ": 59, "defin": [5, 11, 13, 16, 31, 60, 66, 67, 70, 74, 76, 84, 100, 101, 102, 104, 106, 108, 110, 126, 133, 146, 147, 150, 152], "definit": [102, 104, 105, 107, 109, 118, 144, 147, 152], "deleg": 141, "deliv": 90, "demo_ic": 89, "demo_wat": 89, "denot": [19, 123, 124, 145, 150], "dens": 84, "depend": [0, 82, 145, 146, 147, 148, 151, 152], "deploi": [0, 1, 68, 70, 147, 148, 149, 151], "deploy": [0, 1, 70, 72, 73, 74, 75, 76, 104, 143, 147, 148, 150, 151, 152], "deployment_modul": [1, 68], "deploymentmodul": [68, 69, 70, 72, 75, 76], "deprec": [44, 45, 54, 55, 72, 138], "deprecated_method": [3, 44, 54, 68, 71], "deprecation_tool": [1, 128], "depth": [83, 98, 108, 120], "depth_rel": 98, "describ": [5, 144, 147], "descript": [5, 109, 129], "design": [1, 147, 150], "desir": [127, 139], "detail": [1, 5, 92, 109, 110, 118, 123, 146, 147, 149, 150, 152], "detector": [0, 1, 31, 71, 79, 87, 88, 89, 104, 105, 107, 146, 147, 148, 151, 152], "detector_respons": 147, "determin": [69, 72, 75, 92], "develop": [0, 1, 144, 146, 147, 148, 149, 150, 151, 152], "deviat": [104, 105, 108], "devic": 70, "df": [59, 145], "dfg": [0, 148, 151], "dict": [5, 8, 9, 11, 13, 16, 23, 34, 37, 59, 70, 86, 87, 88, 89, 90, 98, 104, 105, 107, 109, 110, 113, 123, 126, 129, 131, 133, 134, 135, 136, 138, 145, 146, 147, 150], "dictionari": [11, 13, 16, 19, 34, 35, 37, 49, 59, 104, 105, 109, 131, 133, 134, 136, 145, 150], "did": 14, "differ": [0, 11, 13, 16, 19, 21, 39, 40, 41, 43, 49, 50, 51, 71, 105, 126, 144, 145, 146, 147, 148, 150, 151, 152], "difficult": 146, "diffier": [147, 152], "digit": 82, "dim": [82, 83], "dimenion": [94, 96, 99], "dimens": [82, 83, 87, 88, 89, 92, 93, 94, 96, 98, 99, 108, 112, 118, 120, 121, 125, 150, 152], "dimension": [82, 83, 146, 152], "dir": 139, "dir_with_fil": [145, 150], "dir_x_pr": 117, "dir_y_pr": 117, "dir_z_pr": 117, "direct": [96, 108, 116, 117, 118, 122, 124, 146, 150], "direction_kappa": 117, "directionreconstructionwithkappa": [115, 117, 147, 152], "directli": [0, 94, 99, 145, 147, 148, 150, 151, 152], "directori": [5, 7, 45, 47, 49, 50, 51, 52, 53, 55, 62, 63, 66, 67, 123, 139, 145, 147, 152], "dirti": 147, "discard_empty_ev": 74, "disconnect": 146, "discuss": 144, "disk": [145, 146, 147], "distanc": [31, 102, 103, 105, 121], "distribut": [14, 84, 94, 110, 117, 125, 127, 149, 152], "distribution_strategi": 90, "ditto": 125, "diverg": 125, "divid": [69, 72, 75, 108, 118], "dk": 5, "dl": [147, 152], "dnn": [25, 32], "do": [0, 14, 70, 74, 125, 133, 134, 144, 146, 147, 148, 151, 152], "do_shuffl": [3, 8], "doc": 147, "docformatt": 144, "docker": 1, "docstr": 144, "document": [14, 110, 125, 150, 152], "doe": [37, 116, 118, 134, 145, 146, 147, 152], "doesn": 59, "dom": [8, 11, 13, 16, 80, 84, 92, 107, 108, 112, 126, 147, 152], "dom_i": [4, 87, 107], "dom_numb": 4, "dom_tim": [4, 107], "dom_typ": 4, "dom_x": [4, 87, 107], "dom_z": [4, 87, 107], "domain": [0, 1, 3, 68, 147, 148, 151], "domandtimewindowcoarsen": [79, 80], "domcoarsen": [79, 80], "don": [123, 145], "done": [23, 84, 141, 144, 145, 147, 150], "dot": 83, "download": [5, 66, 67, 149], "download_dir": [5, 66, 67], "downsid": 146, "draw": 14, "drawn": [100, 101, 105, 106, 147, 152], "drhb": [14, 98], "drop": [14, 83, 93], "drop_last": 14, "drop_path": 83, "drop_prob": 83, "dropout": [83, 92, 99, 112], "dropout_prob": 83, "dropout_ratio": 93, "dropout_readout": 99, "droppath": [81, 83], "dtype": [11, 13, 16, 104, 105, 142, 146, 147, 152], "due": [146, 147, 152], "dummy_pid": [146, 147], "dump": [131, 133, 134, 145, 146, 147], "duplciat": 123, "duplic": 107, "dure": [83, 98, 104, 118, 123, 150], "dynam": [23, 83, 94, 95, 96, 99, 147, 152], "dynedg": [74, 76, 79, 91, 95, 96, 98, 99, 147, 152], "dynedge_arg": 98, "dynedge_jinst": [79, 91], "dynedge_kaggle_tito": [79, 91], "dynedge_layer_s": [94, 99, 147, 152], "dynedgeconv": [81, 83, 94, 99], "dynedgejinst": [91, 95], "dynedgetito": [91, 92, 96], "dyntran": [81, 83, 92, 96], "dyntrans1": 83, "dyntrans_layer_s": [92, 96], "e": [1, 5, 8, 9, 11, 13, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, 37, 39, 43, 59, 60, 64, 70, 74, 76, 80, 82, 83, 84, 86, 87, 88, 89, 93, 97, 102, 104, 105, 107, 108, 109, 110, 113, 114, 116, 117, 118, 121, 123, 124, 125, 127, 131, 141, 144, 145, 146, 147, 149, 152], "each": [5, 14, 23, 34, 37, 58, 59, 63, 64, 69, 70, 72, 75, 80, 82, 83, 84, 87, 88, 89, 92, 94, 96, 99, 102, 104, 105, 107, 108, 112, 116, 118, 121, 123, 125, 126, 139, 145, 146, 147, 150, 152], "earli": [123, 129], "early_stopping_pati": [90, 136], "earlystop": 123, "easi": [0, 145, 146, 147, 148, 151, 152], "easili": [1, 147, 152], "easy_model": [1, 79], "easysyntax": [79, 90, 110, 114], "ed": 125, "edg": [79, 83, 84, 94, 95, 96, 99, 100, 103, 104, 105, 106, 107, 121, 146, 147, 152], "edge_attr": [146, 147], "edge_definit": 104, "edge_index": [80, 83, 121, 146, 147], "edgeconv": 83, "edgeconvtito": [81, 83], "edgedefinit": [100, 101, 102, 103, 104, 105, 106, 147, 152], "edgelessgraph": [100, 105], "effect": [123, 144, 147, 152], "effici": 14, "effort": [144, 146, 150], "either": [0, 5, 9, 11, 16, 21, 31, 66, 67, 125, 145, 147, 148, 151], "elast": 4, "element": [11, 13, 19, 34, 37, 90, 110, 114, 121, 126, 135, 145, 147, 150], "elementwis": 125, "elimin": 74, "els": [74, 124, 145, 150], "ema": 113, "embed": [79, 81, 92, 98, 112, 116, 118, 120], "embedding_dim": [92, 112], "empti": 74, "en": 147, "enabl": [0, 3, 90, 107, 148, 151], "encod": [82, 124], "encount": 147, "encourag": [144, 147], "end": [0, 1, 14, 108, 123, 147, 148, 151], "energi": [4, 117, 118, 127, 146, 147, 150], "energy_cascad": [4, 117], "energy_cascade_pr": 117, "energy_pr": 117, "energy_reco": 76, "energy_sigma": 117, "energy_track": [4, 117], "energy_track_pr": 117, "energyreconstruct": [115, 117, 147, 152], "energyreconstructionwithpow": [115, 117], "energyreconstructionwithuncertainti": [115, 117, 147], "energytcreconstruct": [115, 117], "engin": [0, 148, 151], "enough": 109, "ensemble_dataset": [146, 147], "ensembledataset": [10, 11, 133, 146, 147], "ensembleloss": [122, 125], "ensur": [37, 58, 125, 141, 144, 152], "entir": [11, 13, 109, 145, 147, 152], "entiti": [147, 152], "entri": [74, 76, 94, 99, 121, 129, 150], "entropi": 125, "enum": 37, "env": 149, "environ": [50, 149], "ep": [142, 147, 152], "epoch": [113, 123, 129], "eps_lik": [128, 142], "equival": [37, 147, 152], "erda": [5, 66], "erdahost": 67, "erdahosteddataset": [3, 5, 66, 67], "error": [125, 141, 144, 145, 147], "especi": 74, "establish": 152, "etc": [0, 14, 125, 141, 146, 147, 148, 150, 151], "euclidean": [102, 144], "euclideandistanceloss": [122, 125], "euclideanedg": [101, 102], "european": [0, 148, 151], "eval": [109, 149], "evalu": [5, 110, 118], "even": 58, "event": [0, 1, 5, 7, 9, 11, 13, 14, 16, 18, 28, 31, 43, 45, 47, 55, 59, 60, 63, 64, 66, 67, 74, 82, 84, 92, 104, 107, 108, 114, 118, 120, 121, 124, 125, 126, 127, 133, 145, 147, 148, 150, 151, 152], "event_no": [7, 11, 13, 16, 45, 47, 55, 59, 60, 63, 64, 127, 133, 146, 147, 152], "event_truth": 5, "events_per_batch": 63, "everi": [99, 110, 145, 147, 150], "everyth": [147, 152], "everytim": 144, "exact": [95, 125, 152], "exactli": [125, 141, 146], "exampl": [7, 14, 34, 60, 80, 84, 108, 110, 121, 125, 133, 134, 145, 146, 149], "example_energy_reconstruction_model": [129, 147, 152], "exce": 127, "exceed": 64, "except": [1, 143, 145], "exclud": 23, "exclude_kei": 23, "excluding_valu": 121, "execut": 59, "exist": [0, 11, 13, 16, 59, 79, 110, 124, 133, 146, 147, 148, 151, 152], "exist_ok": [147, 152], "expand": [0, 147, 148, 151], "expans": 98, "expect": [59, 60, 62, 74, 76, 104, 107, 146, 147, 152], "expects_merged_datafram": 62, "experi": [0, 1, 5, 6, 7, 48, 49, 70, 122, 145, 147, 148, 151], "experiment": 152, "expert": 1, "explain": 147, "explicitli": [126, 131, 136], "exponenti": 125, "export": [145, 146, 147, 150, 152], "expos": 1, "express": [14, 109, 125], "extend": [0, 1, 31, 145, 146, 148, 151], "extend_boundari": 31, "extens": [1, 5, 49, 62, 139], "extern": [146, 147], "extra": [83, 152], "extra_repr": [83, 109], "extra_repr_recurs": 109, "extracor_nam": 49, "extract": [7, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 35, 39, 41, 42, 43, 58, 74, 76, 118, 121, 145, 147, 150], "extractor": [1, 3, 7, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 47, 48, 49, 55, 74, 76], "extractor_nam": [18, 19, 21, 23, 26, 39, 41, 43, 145, 150], "f": [84, 145, 147, 152], "f1": 84, "f2": 84, "f_absorpt": 108, "f_scatter": 108, "factor": [83, 108, 123, 125, 147, 152], "fail": 18, "fals": [14, 36, 74, 82, 83, 94, 98, 99, 104, 107, 109, 120, 123, 125, 127, 147, 152], "fanci": 147, "fashion": 1, "fast": [0, 146, 147, 148, 151], "faster": [0, 145, 146, 148, 151], "favorit": 149, "favourit": 147, "fbeezabg5a": 5, "fc": 84, "featur": [1, 3, 4, 5, 11, 13, 16, 22, 64, 66, 67, 74, 76, 82, 83, 84, 86, 87, 88, 89, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 106, 107, 108, 112, 116, 120, 121, 126, 133, 144, 146, 147, 150, 152], "feature_idx": 108, "feature_map": [86, 87, 88, 89, 150], "feature_nam": 108, "features_subset": [83, 92, 94, 96, 99, 112, 147, 152], "feedforward": 83, "feel": 147, "fetch": 129, "few": [0, 79, 144, 145, 146, 147, 148, 151, 152], "fiber_id": 88, "field": [110, 121, 124, 131, 136, 138, 145, 146, 147, 150], "figur": 0, "file": [0, 1, 3, 5, 7, 11, 13, 14, 16, 19, 21, 31, 34, 36, 39, 40, 41, 42, 43, 45, 47, 49, 50, 51, 52, 53, 55, 57, 58, 62, 63, 64, 69, 70, 72, 74, 75, 76, 104, 109, 123, 125, 126, 129, 130, 131, 132, 133, 134, 139, 141, 145, 146, 147, 148, 149, 150, 151, 152], "file_extens": 62, "file_handl": 141, "file_path": [126, 145, 150], "file_read": [7, 145, 150], "filehandl": 141, "filenam": 139, "fileread": [19, 49], "files_list": 58, "filesi": [1, 128], "fill": [5, 14], "filter": [36, 45, 47, 50, 55, 141, 150], "filter_ani": 36, "filter_nam": 36, "filtermask": 36, "final": [0, 7, 84, 123, 133, 146, 147, 148, 151], "find": [21, 31, 103, 139, 146, 147, 150, 152], "find_fil": [49, 50, 51, 52, 53, 145], "find_i3_fil": [128, 139], "first": [82, 92, 103, 107, 112, 123, 126, 144, 147, 150], "fisher": 125, "fit": [9, 14, 90, 125, 127, 136, 147, 152], "fit_weight": 127, "five": 146, "fix": [60, 147], "flag": [22, 74], "flake8": 144, "flatten": 34, "flatten_nested_dictionari": [33, 34], "flexibil": 152, "flexibl": 60, "float": [11, 13, 16, 31, 74, 83, 90, 92, 93, 99, 102, 103, 104, 105, 107, 108, 112, 118, 123, 125, 126, 127, 133, 146], "float32": [11, 13, 16, 104, 105], "float64": 125, "flow": [110, 118, 152], "flow_lay": [110, 118], "flowchart": [0, 148, 151], "fly": [146, 147], "fn": [11, 37, 131, 135], "fn_kwarg": 135, "folder": [45, 47, 50, 51, 52, 53, 55, 69, 145], "folk": 147, "follow": [14, 90, 94, 99, 110, 114, 125, 127, 144, 145, 146, 147], "fork": 144, "form": [0, 19, 79, 116, 131, 136, 145, 146, 148, 151, 152], "format": [0, 1, 3, 5, 7, 11, 34, 38, 39, 49, 51, 62, 63, 64, 82, 109, 112, 133, 144, 145, 146, 147, 148, 149, 150, 151, 152], "forward": [80, 82, 83, 86, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 104, 107, 110, 112, 114, 118, 120, 125, 152], "found": [37, 45, 47, 50, 55, 63, 108, 125, 146, 147], "four": 82, "fourier": 82, "fourierencod": [81, 82, 98, 120], "fraction": [93, 112, 126], "frame": [20, 21, 23, 31, 33, 36, 37, 76], "frame_is_montecarlo": [33, 35], "frame_is_nois": [33, 35], "framework": [0, 147, 148, 151], "free": [0, 14, 125, 147, 148, 151], "freeli": 147, "frequenc": 82, "friendli": [0, 62, 64, 145, 147, 148, 149, 151], "from": [0, 1, 5, 7, 8, 9, 11, 13, 14, 16, 19, 20, 21, 23, 25, 26, 28, 31, 34, 35, 36, 37, 39, 41, 42, 43, 49, 50, 52, 53, 57, 62, 64, 66, 67, 82, 84, 86, 87, 88, 89, 96, 98, 102, 104, 107, 108, 109, 110, 113, 116, 117, 118, 121, 123, 124, 125, 131, 132, 134, 136, 141, 144, 145, 146, 147, 148, 150, 151, 152], "from_config": [11, 109, 132, 133, 134, 146, 147, 152], "from_dataset_config": [8, 147, 152], "full": [63, 147, 152], "fulli": [145, 147, 152], "func": 147, "function": [0, 7, 8, 11, 14, 21, 37, 39, 43, 58, 59, 74, 76, 80, 83, 84, 86, 87, 88, 89, 94, 99, 104, 108, 109, 110, 118, 121, 125, 126, 128, 133, 134, 135, 138, 139, 140, 142, 146, 148, 150, 151, 152], "fund": [0, 148, 151], "furnish": [14, 125], "further": [74, 108], "furthermor": 112, "g": [1, 5, 11, 13, 16, 18, 19, 21, 31, 34, 37, 59, 60, 64, 74, 76, 84, 104, 107, 108, 118, 121, 125, 127, 141, 144, 146, 147, 149, 152], "galatict": 24, "gamma_1": 83, "gamma_2": 83, "gather": [14, 108], "gather_cluster_sequ": [100, 108], "gather_len_matched_bucket": [10, 14], "gcd": [21, 31, 35, 45, 47, 50, 55, 58, 72, 74, 75, 76, 139], "gcd_dict": [35, 37], "gcd_file": [6, 21, 31, 72, 74, 75, 76], "gcd_list": [58, 139], "gcd_rescu": [45, 47, 50, 55, 139], "gcd_shuffl": 58, "gelu": 83, "gener": [0, 5, 9, 11, 13, 14, 16, 23, 36, 49, 62, 66, 69, 74, 75, 76, 82, 100, 101, 104, 105, 106, 108, 116, 125, 127, 146, 147, 148, 150, 151, 152], "geometr": 147, "geometri": [66, 86, 104, 152], "geometry_t": [86, 87, 88, 89, 150], "geometry_table_path": [87, 88, 89, 150], "germani": [0, 148, 151], "get": [19, 35, 59, 86, 108, 123, 126, 147, 152], "get_all_argument_valu": [130, 131], "get_all_grapnet_class": [130, 135], "get_field": [79, 121], "get_graphnet_class": [130, 135], "get_lr": 123, "get_map_funct": 7, "get_member_vari": [33, 37], "get_metr": 123, "get_om_keys_and_pulseseri": [33, 35], "get_predict": [122, 126], "get_primary_kei": [56, 59], "gev": 66, "gframe": [21, 31], "gggt": [110, 118], "git": 149, "github": [14, 98, 110, 118, 120, 125, 147, 149], "given": [5, 11, 14, 16, 21, 31, 64, 66, 67, 82, 84, 102, 118, 125, 127, 129, 146, 150], "glob": 145, "global": [2, 4, 92, 94, 96, 99, 109, 147], "global_index": 7, "global_pooling_schem": [92, 94, 96, 99, 147, 152], "gnn": [1, 71, 79, 92, 93, 94, 95, 96, 98, 99, 104, 110, 112, 120, 147, 152], "go": [14, 144, 147], "googl": 144, "got": 145, "gpu": [90, 129, 147, 149, 152], "grab": 118, "grad_output": 125, "gradient_clip_v": 90, "grant": [0, 14, 125, 148, 151], "graph": [0, 1, 8, 11, 13, 16, 79, 83, 84, 86, 101, 102, 103, 104, 106, 107, 108, 112, 121, 124, 126, 144, 146, 147, 148, 151, 152], "graph_definit": [5, 11, 13, 16, 66, 67, 79, 100, 110, 126, 133, 146, 147, 152], "graph_definiton": 146, "graphdefinit": [5, 11, 13, 16, 66, 67, 100, 101, 104, 105, 106, 110, 126, 144, 146, 147], "graphnet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 56, 58, 59, 60, 62, 63, 64, 66, 67, 68, 69, 70, 72, 74, 75, 76, 77, 78, 79, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142, 144, 145, 146, 148, 149, 150, 151, 152], "graphnet_file_read": [3, 48, 145, 150], "graphnet_model": 123, "graphnet_modul": 72, "graphnet_writ": [3, 61], "graphnetdatamodul": [3, 5, 9], "graphnetearlystop": [122, 123], "graphnetfileread": [7, 48, 49, 50, 51, 52, 53, 145], "graphnetfilesavemethod": [62, 64], "graphneti3deploy": [71, 72], "graphnetwrit": [7, 61, 62, 63, 64, 145], "grapnet": [135, 147], "greatli": [147, 152], "group": [0, 14, 84, 147, 148, 151], "group_bi": [81, 84], "group_pulses_to_dom": [81, 84], "group_pulses_to_pmt": [81, 84], "groupbi": 84, "guarante": [147, 152], "guid": 144, "guidelin": 144, "gvd": [66, 89], "gz": 5, "h5": [41, 52, 145], "h5_extractor": [17, 40], "h5extractor": [7, 40, 41, 49, 145], "h5hitextractor": [40, 41, 145], "h5py": 145, "h5truthextractor": [40, 41, 145], "ha": [0, 5, 37, 59, 72, 74, 93, 108, 125, 139, 145, 146, 147, 148, 149, 150, 151, 152], "had": 150, "hadron": 117, "hand": [23, 146, 147], "handi": 58, "handl": [23, 125, 129, 138, 141, 145, 146, 147], "handler": 141, "happen": [108, 127, 146, 150], "hard": [31, 107], "has_extens": [128, 139], "has_icecube_packag": [128, 140], "has_jammy_flows_packag": [128, 140], "has_torch_packag": [128, 140], "have": [1, 5, 13, 23, 45, 47, 50, 55, 59, 60, 64, 84, 98, 104, 108, 118, 144, 146, 147, 150, 152], "head": [83, 92, 96, 98, 118, 120, 152], "head_dim": 83, "head_siz": 98, "heavi": 145, "help": [74, 76, 129, 144, 146, 147, 150, 152], "here": [104, 144, 146, 147, 149, 150, 152], "herebi": [14, 125], "hidden": [82, 83, 92, 94, 95, 99, 112], "hidden_dim": [98, 120], "hidden_featur": 83, "hidden_s": [112, 116, 117, 118, 147, 152], "high": [0, 147, 148, 151], "higher": 146, "highest_protocol": 145, "hint": 144, "hit": [8, 126, 146, 147, 150], "hitdata": 41, "hlc": 107, "hlc_name": 107, "hold": [104, 108, 145, 150, 152], "holder": [14, 125], "home": [87, 88, 89, 129, 145, 150], "homophili": 121, "hook": 144, "horizon": [0, 148, 151], "host": [5, 66, 150], "how": [5, 14, 100, 101, 106, 145, 147, 152], "howev": [45, 47, 50, 55, 146, 147], "html": [110, 118, 147], "http": [5, 14, 98, 99, 102, 110, 118, 120, 125, 144, 147, 149], "hull": 31, "human": 147, "hybrid": 24, "hyperparamet": [134, 147, 152], "i": [0, 1, 5, 9, 11, 13, 14, 16, 18, 19, 21, 23, 31, 34, 35, 36, 37, 39, 41, 43, 45, 47, 50, 55, 58, 59, 60, 63, 64, 69, 72, 74, 75, 76, 80, 82, 83, 84, 93, 94, 98, 99, 102, 104, 105, 107, 108, 110, 112, 114, 117, 118, 121, 123, 124, 125, 126, 127, 129, 131, 134, 135, 136, 138, 139, 140, 141, 144, 145, 146, 147, 148, 149, 150, 151, 152], "i3": [1, 21, 31, 35, 36, 37, 45, 47, 50, 55, 58, 69, 74, 76, 139, 147, 149], "i3_fil": [6, 21, 31], "i3_filt": [20, 33, 45, 47, 50, 55], "i3_list": [58, 139], "i3_shuffl": 58, "i3calibr": 35, "i3deploy": [6, 68, 72, 73], "i3extractor": [7, 17, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 45, 47, 49, 55], "i3featureextractor": [4, 17, 20, 74, 76], "i3featureextractoricecube86": [20, 22], "i3featureextractoricecubedeepcor": [20, 22], "i3featureextractoricecubeupgrad": [20, 22], "i3fileset": [3, 6, 49, 50], "i3filt": [33, 36, 45, 47, 50, 55], "i3filtermask": [33, 36], "i3fram": [20, 23, 35, 37, 74, 76], "i3galacticplanehybridrecoextractor": [20, 24], "i3genericextractor": [17, 20], "i3hybridrecoextractor": [17, 20], "i3inferencemodul": [72, 73, 74, 75, 76], "i3mctre": 31, "i3modul": [1, 68, 70, 72], "i3ntmuonlabelextractor": [20, 25], "i3ntmuonlabelsextractor": [17, 20], "i3particl": 26, "i3particleextractor": [17, 20], "i3pisaextractor": [17, 20], "i3pulsecleanermodul": [73, 74], "i3pulsenoisetruthflagicecubeupgrad": [20, 22], "i3quesoextractor": [17, 20], "i3read": [3, 45, 47, 48, 55], "i3retroextractor": [17, 20], "i3splinempeextractor": [17, 20], "i3splinempeicextractor": [20, 30], "i3toparquetconvert": [45, 46, 47], "i3tosqliteconvert": [46, 47, 55], "i3truthextractor": [4, 17, 20], "i3tumextractor": [17, 20], "ic": [96, 98, 107], "ice_arg": 107, "ice_transpar": [100, 108], "icecub": [1, 3, 14, 17, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 45, 47, 50, 55, 68, 71, 74, 75, 76, 79, 83, 85, 96, 98, 107, 108, 140, 147, 152], "icecube86": [4, 85, 87, 89], "icecube86prometheu": [85, 89], "icecube_deepcor": 89, "icecube_gen2": 89, "icecube_upgrad": [87, 89], "icecubedeepcor": [85, 87], "icecubedeepcore8": [85, 89], "icecubegen2": [85, 89], "icecubekaggl": [85, 87], "icecubeupgrad": [85, 87], "icecubeupgrade7": [85, 89], "icedemo81": [85, 89], "icemix": [79, 91], "icemixnod": [106, 107], "icetrai": [35, 37, 45, 47, 50, 55, 70, 71, 140, 149], "icetray_verbos": [45, 47, 50, 55], "id": [5, 7, 9, 13, 45, 47, 55, 64, 86, 104, 126, 145, 146, 147, 150], "id_column": 107, "ideal": 152, "ident": [84, 86, 87, 88, 89, 118], "identifi": [7, 11, 13, 16, 31, 107, 108, 121, 133, 134, 150], "identify_indic": [100, 108], "identitytask": [115, 116, 118], "ie": 92, "ignor": [11, 13, 16, 37, 63], "illustr": [0, 144, 145, 148, 151], "imag": [0, 1, 144, 147, 148, 151, 152], "impact": 98, "implement": [1, 5, 14, 19, 21, 49, 62, 70, 75, 83, 92, 93, 94, 95, 96, 98, 99, 102, 112, 120, 125, 144, 145, 147, 152], "impli": [14, 125], "import": [0, 1, 5, 59, 79, 128, 145, 146, 147, 148, 150, 151, 152], "impos": [11, 13, 90], "improv": [0, 1, 129, 147, 148, 151, 152], "in_featur": 83, "inaccur": 108, "inact": 104, "includ": [1, 5, 13, 14, 66, 67, 83, 90, 107, 125, 131, 144, 146, 147, 150, 152], "include_dynedg": 98, "incompat": 147, "incomplet": 14, "incorpor": 82, "increas": [0, 123, 148, 151], "indent": 109, "independ": [69, 72, 75, 145], "index": [1, 7, 11, 13, 16, 37, 59, 63, 84, 86, 92, 103, 108, 112, 123, 146, 147, 152], "index_column": [7, 11, 13, 16, 45, 47, 55, 59, 60, 63, 64, 126, 127, 133, 146, 147], "indic": [14, 60, 78, 84, 92, 103, 108, 112, 118, 123, 125, 129, 144, 147, 152], "indicesfor": 35, "indici": [11, 13, 16, 35, 60], "individu": [0, 11, 13, 16, 84, 94, 121, 146, 148, 151, 152], "industri": [0, 3, 148, 151], "inelast": [4, 117], "inelasticity_pr": 117, "inelasticityreconstruct": [115, 117], "inf": 121, "infer": [0, 1, 64, 68, 70, 71, 74, 76, 90, 118, 147, 148, 151], "inference_modul": [68, 73], "info": [141, 147], "inform": [5, 11, 13, 16, 18, 19, 21, 23, 31, 39, 41, 43, 66, 67, 104, 107, 108, 109, 145, 146, 147, 150, 152], "ingest": [0, 1, 3, 85, 148, 151], "inherit": [5, 19, 21, 37, 49, 62, 86, 107, 125, 141, 145, 146, 147, 152], "init_fn": [133, 134], "init_global_index": [3, 7], "init_predict_tqdm": 123, "init_test_tqdm": 123, "init_train_tqdm": 123, "init_validation_tqdm": 123, "init_valu": 83, "initi": [7, 36, 50, 64, 69, 72, 75, 83, 92, 98, 103, 108], "initial_st": 43, "initialis": [134, 147, 152], "injection_azimuth": [4, 146, 147], "injection_bjorkeni": [4, 146, 147], "injection_bjorkenx": [4, 146, 147], "injection_column_depth": [4, 146, 147], "injection_energi": [4, 146, 147], "injection_interaction_typ": [4, 146, 147], "injection_position_i": [4, 146, 147], "injection_position_x": [4, 146, 147], "injection_position_z": [4, 146, 147], "injection_typ": [4, 146, 147], "injection_zenith": [4, 146, 147, 152], "innov": [0, 148, 151], "inptut": 108, "input": [5, 7, 11, 13, 16, 45, 47, 49, 50, 55, 62, 66, 67, 69, 72, 74, 75, 76, 82, 83, 87, 92, 93, 94, 95, 96, 97, 98, 99, 104, 105, 107, 108, 110, 112, 116, 118, 120, 121, 131, 136, 138, 145, 146, 147, 150, 152], "input_dim": [83, 152], "input_dir": [145, 150], "input_featur": [86, 104], "input_feature_nam": [86, 104, 105, 107], "input_fil": [49, 69], "input_nam": 108, "ins": 86, "insert": 108, "insid": 146, "inspect": [147, 152], "inspir": 99, "instal": [144, 147], "instanc": [11, 19, 21, 31, 37, 39, 41, 43, 45, 47, 50, 55, 104, 109, 124, 126, 132, 134, 145, 146, 147, 152], "instanti": [7, 9, 134, 145, 146, 150], "instead": [21, 31, 45, 47, 50, 55, 72, 110, 125, 147, 152], "int": [5, 7, 8, 9, 11, 13, 14, 16, 25, 28, 36, 45, 47, 49, 50, 51, 52, 53, 55, 60, 62, 63, 64, 69, 72, 75, 82, 83, 84, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 125, 126, 127, 129, 133, 136, 141, 145, 152], "integ": [59, 92, 94, 95, 99, 125, 146, 147], "integer_primary_kei": 59, "integr": 152, "intend": [92, 112, 147], "interact": [117, 124, 146, 147], "interaction_kei": 124, "interaction_tim": [4, 117], "interaction_time_pr": 117, "interaction_typ": [4, 124], "interchang": [147, 152], "interfac": [0, 133, 134, 147, 148, 149, 150, 151], "interim": [7, 61, 62, 63, 64, 145], "intermedi": [0, 1, 3, 7, 11, 93, 147, 148, 151], "intern": [3, 17, 39, 47, 51], "internal_parquet_read": [3, 48], "interpol": [108, 123], "interpret": 116, "interv": [82, 147, 152], "intract": 146, "introduc": 147, "introduct": [110, 118], "intuit": [141, 152], "invers": 118, "invert": 118, "involv": 60, "io": [110, 118, 144, 147], "iop": 147, "iopscienc": 147, "is_boost_class": [33, 37], "is_boost_enum": [33, 37], "is_gcd_fil": [128, 139], "is_graphnet_class": [130, 135], "is_graphnet_modul": [130, 135], "is_i3_fil": [128, 139], "is_icecube_class": [33, 37], "is_method": [33, 37], "is_typ": [33, 37], "iseecub": [79, 119], "isinst": 145, "isn": 37, "isol": 105, "issu": [147, 152], "iter": 11, "its": [37, 112, 146, 147, 152], "itself": [37, 118, 145, 147, 152], "iv": 125, "jammy_flow": [110, 118, 140], "job": 150, "join": [145, 147], "json": [34, 133, 146, 147], "just": [5, 84, 145, 146, 147, 152], "k": [83, 92, 94, 96, 99, 102, 105, 112, 121, 125], "kaggl": [4, 82, 83, 87, 96, 98], "kappa": [117, 125], "kappa_switch": 125, "karg": [109, 113], "keep": [19, 21, 36, 39, 41, 43, 107, 145], "kei": [11, 23, 34, 35, 37, 59, 64, 83, 84, 107, 124, 133, 134, 145, 146, 147, 150], "kept": 36, "key_padding_mask": 83, "keyword": [123, 131, 136], "kind": [14, 125, 150], "km3net": [147, 152], "knn_graph_batch": [79, 121], "knnedg": [101, 102], "knngraph": [100, 105, 146, 147, 152], "know": 150, "known": 84, "kv": 83, "kwarg": [7, 8, 11, 13, 16, 36, 49, 51, 52, 53, 62, 80, 83, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 109, 110, 112, 113, 114, 116, 117, 118, 120, 123, 125, 127, 131, 133, 134, 141], "l": [108, 121], "label": [1, 11, 13, 16, 25, 28, 90, 93, 104, 114, 118, 122, 126, 133], "lai": 147, "lambda": [109, 147, 152], "land": 147, "larg": [0, 92, 125, 146, 148, 151], "larger": 145, "largest": 108, "last": [14, 94, 99, 112, 116, 117, 118, 123, 126, 152], "last_epoch": 123, "lastli": 150, "latent": [82, 92, 94, 96, 98, 99, 110, 112, 116, 117, 118, 120, 152], "latest": 147, "layer": [0, 79, 81, 84, 92, 93, 94, 95, 96, 98, 99, 110, 112, 116, 117, 118, 148, 151], "layer_s": 83, "layer_size_scal": 95, "layernorm": 83, "ldot": [80, 84], "lead": [146, 147], "learn": [0, 1, 5, 62, 64, 74, 76, 110, 114, 116, 118, 123, 145, 147, 148, 149, 150, 151, 152], "learnabl": [83, 91, 92, 93, 94, 95, 96, 97, 98, 99, 112, 118, 120, 152], "learnedtask": [115, 118], "least": [13, 144, 146, 147], "leav": 123, "len": [11, 13, 108, 145, 146], "length": [11, 13, 14, 37, 107, 108, 121, 123], "lenmatchbatchsampl": [10, 14], "less": [8, 126, 147, 152], "let": [147, 150, 152], "level": [0, 5, 11, 13, 16, 18, 31, 36, 43, 45, 47, 49, 50, 51, 52, 53, 55, 59, 62, 63, 66, 67, 80, 84, 98, 114, 141, 146, 147, 148, 150, 151], "leverag": 1, "lex_sort": [100, 108], "liabil": [14, 125], "liabl": [14, 125], "lib": [87, 88, 89, 129], "licens": [14, 125], "lift": 145, "light": 103, "lightn": [9, 123, 147, 152], "lightningdatamodul": 9, "lightningmodul": [82, 83, 109, 123, 141, 147, 152], "like": [14, 19, 37, 84, 103, 110, 118, 121, 125, 142, 144, 146, 147, 149, 152], "limit": [14, 107, 125], "line": [123, 129, 145, 146, 150], "linear": [94, 99, 108, 152], "linearli": 123, "liquid": 88, "liquido": [3, 4, 17, 41, 52, 79, 85, 145], "liquido_read": [3, 48], "liquido_v1": [85, 88], "liquidoread": [48, 52, 145], "list": [5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 23, 31, 34, 36, 37, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 80, 83, 84, 86, 87, 88, 89, 90, 92, 94, 96, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 118, 121, 123, 125, 126, 127, 133, 135, 136, 139, 141, 145, 146, 150], "list_all_submodul": [130, 135], "ljvmiranda921": 144, "load": [0, 8, 11, 58, 70, 109, 113, 131, 133, 146, 147, 148, 150, 151], "load_from_checkpoint": [147, 152], "load_modul": [10, 11, 109], "load_state_dict": [109, 113, 147, 152], "loaded_model": [147, 152], "local": [80, 87, 88, 89, 107, 129, 147, 149, 152], "locat": 108, "lock": 13, "log": [0, 1, 117, 122, 123, 125, 128, 146, 147, 148, 151, 152], "log10": [118, 127, 147, 152], "log_cmk": 125, "log_cmk_approx": 125, "log_cmk_exact": 125, "log_every_n_step": [90, 147, 152], "log_fold": [36, 49, 51, 52, 53, 62, 141], "log_model": [147, 152], "logcmk": [122, 125], "logcoshloss": [122, 125, 147, 152], "logger": [7, 9, 11, 14, 19, 36, 49, 51, 52, 53, 60, 62, 69, 70, 90, 102, 109, 124, 127, 128, 141, 147, 152], "loggeradapt": 141, "logic": 146, "logit": [116, 125, 152], "logrecord": 141, "long": 146, "longer": 107, "longev": [0, 148, 151], "longtensor": [80, 84, 121], "look": [23, 146, 147], "lookup": 135, "loop": [147, 152], "loss": [11, 13, 16, 90, 104, 110, 114, 118, 123, 125, 129, 147, 152], "loss_factor": 125, "loss_funct": [1, 118, 122, 147, 152], "loss_weight": [104, 118, 147, 152], "loss_weight_column": [11, 13, 16, 104, 126, 133], "loss_weight_default_valu": [11, 13, 16, 104, 133], "loss_weight_t": [11, 13, 16, 126, 133], "lossfunct": [118, 122, 125, 147], "lot": 144, "lower": [0, 147, 148, 151], "lr": [147, 152], "m": [103, 108, 125], "machin": 1, "made": [147, 152], "maeloss": [122, 125], "magnitud": [0, 148, 151], "mai": [49, 60, 70, 107, 118, 146, 147, 149, 152], "main": [1, 14, 91, 144, 147], "mainli": 37, "major": [114, 118], "make": [0, 7, 107, 127, 133, 134, 144, 145, 146, 147, 148, 150, 151, 152], "make_dataload": [122, 126], "make_train_validation_dataload": [122, 126], "makedir": [147, 152], "manag": [0, 122, 145, 147, 148, 151], "mandatori": 82, "mangl": 37, "mani": [64, 145, 147, 152], "manipul": [34, 100, 101, 106], "map": [7, 11, 13, 16, 22, 23, 59, 87, 88, 89, 104, 105, 118, 147, 150, 152], "mari": [0, 148, 151], "martin": 93, "mask": [14, 104, 121], "masked_entri": 121, "master": 125, "match": [14, 49, 104, 127, 139, 142, 145], "math": [1, 83, 128], "mathbb": 84, "mathbf": [80, 84], "matic": 118, "matric": 83, "matrix": [84, 102, 103, 108, 121, 125, 146], "max": [80, 83, 94, 96, 99, 125, 127, 129, 147, 152], "max_activ": 107, "max_epoch": [90, 147, 152], "max_length": 107, "max_pool": [80, 84], "max_pool_x": [80, 84], "max_puls": 107, "max_rel_po": 120, "max_table_s": 64, "max_weight": 127, "maximum": [64, 84, 107, 108, 118, 120, 129], "mc": [23, 59], "mc_truth": [19, 43, 146, 147], "mctree": [31, 35], "md": 147, "mean": [0, 11, 13, 16, 79, 94, 96, 99, 108, 125, 134, 145, 146, 147, 148, 151, 152], "meaning": 82, "meant": [145, 147, 152], "measur": [107, 108, 121, 147, 150], "mechan": 83, "meet": 118, "member": [21, 23, 31, 37, 49, 107, 133, 134, 141, 145, 150], "memori": [13, 146], "mention": 147, "merchant": [14, 125], "merg": [7, 14, 62, 63, 64, 125, 145, 146, 150], "merge_fil": [7, 62, 63, 64, 145, 150], "merged_database_nam": 64, "messag": [83, 123, 141, 147], "messagepass": 83, "metaclass": [133, 134], "metaproject": 149, "meter": 147, "meth": 147, "method": [5, 7, 9, 11, 13, 14, 16, 19, 21, 31, 33, 34, 35, 37, 44, 45, 49, 54, 55, 62, 63, 64, 66, 67, 70, 72, 83, 84, 86, 98, 108, 117, 125, 127, 145, 147, 152], "metric": [92, 94, 96, 99, 103, 112, 123, 147, 152], "might": [146, 147, 152], "mileston": [123, 147, 152], "million": [64, 66], "min": [80, 84, 94, 96, 99, 127, 147, 152], "min_pool": [80, 81, 84], "min_pool_x": [80, 81, 84], "mind": 147, "minh": 93, "mini": 126, "minim": [90, 110, 146, 147, 150, 152], "minimum": [107, 118], "minkowski": [100, 101], "minkowskiknnedg": [101, 103], "minu": 125, "mise": 125, "miss": 78, "mit": [14, 125], "mix": 18, "ml": [0, 1, 148, 151], "mlp": [81, 82, 83, 94, 98, 99, 120, 152], "mlp_dim": [82, 120], "mlp_ratio": [83, 98], "mode": [90, 118], "model": [0, 1, 5, 68, 70, 71, 74, 76, 80, 81, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 110, 112, 113, 114, 115, 116, 117, 118, 120, 121, 122, 123, 125, 126, 129, 131, 133, 134, 136, 143, 145, 146, 148, 149, 150, 151], "model_config": [70, 74, 76, 128, 130, 131, 133, 136, 147, 152], "model_config_path": [147, 152], "model_nam": [74, 76], "modelconfig": [70, 74, 76, 109, 130, 133, 134], "modelconfigsav": 134, "modelconfigsaverabc": [130, 134], "modelconfigsavermeta": [130, 134], "modif": [147, 152], "modifi": [14, 125, 147, 152], "modul": [0, 3, 6, 7, 11, 17, 18, 37, 38, 40, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 61, 62, 64, 68, 69, 71, 72, 73, 74, 75, 78, 79, 82, 83, 85, 91, 100, 101, 103, 104, 105, 106, 109, 111, 115, 119, 122, 128, 130, 133, 134, 135, 136, 140, 145, 147, 148, 151, 152], "modular": [0, 79, 145, 147, 148, 151, 152], "moduletyp": 135, "mont": 35, "more": [1, 11, 13, 14, 58, 59, 92, 109, 133, 134, 141, 146, 147, 152], "most": [0, 1, 60, 103, 118, 145, 148, 150, 151, 152], "mryab": 125, "mseloss": [122, 125], "msg": 141, "mulitpli": 125, "multi": [83, 94, 99, 114], "multiclassclassificationtask": [115, 116, 147], "multiheadattent": [14, 83], "multiindex": 150, "multipl": [11, 13, 16, 18, 82, 108, 123, 125, 133, 141, 152], "multipli": [83, 123], "multiprocess": [7, 14, 45, 47, 55, 145], "multiprocessing_context": [13, 14], "muon": [25, 146, 152], "must": [13, 18, 49, 50, 59, 62, 80, 123, 125, 127, 144, 145, 146, 147, 150], "my": [146, 147, 150], "my_custom_label": [146, 147], "my_databas": 64, "my_fil": [145, 150], "my_geometry_t": 150, "my_outdir": [145, 150], "my_tabl": 150, "mycustomlabel": [146, 147], "mydetector": 150, "myexperi": 150, "myextractor": 150, "mygraphnetmodel": 152, "mymodel": 152, "mypi": 144, "mypicklewrit": 145, "myread": 150, "n": [14, 19, 80, 84, 103, 121, 125, 146, 147, 150], "n_1": 84, "n_b": 84, "n_cluster": 108, "n_event": [145, 150], "n_featur": [82, 98, 120], "n_freq": 82, "n_head": [83, 92, 96], "n_pmt": 108, "n_puls": [107, 150], "n_rel": 98, "n_worker": [69, 72, 75], "name": [4, 5, 7, 8, 11, 13, 16, 18, 19, 21, 22, 24, 25, 27, 28, 29, 30, 31, 32, 34, 36, 37, 39, 41, 43, 45, 47, 49, 51, 52, 53, 55, 59, 62, 63, 64, 70, 74, 76, 86, 87, 88, 89, 104, 105, 107, 108, 110, 112, 118, 121, 124, 127, 129, 131, 133, 134, 135, 136, 141, 144, 145, 146, 147, 150, 152], "namespac": [4, 109, 133, 134], "nan": 108, "narg": 129, "nb_dom": 121, "nb_file": 7, "nb_input": [92, 93, 94, 95, 96, 97, 99, 112, 116, 117, 118, 147, 152], "nb_intermedi": 93, "nb_nearest_neighbour": [102, 103, 105, 146, 147, 152], "nb_neighbor": 83, "nb_neighbour": [92, 94, 96, 99, 112, 147, 152], "nb_output": [93, 95, 97, 107, 116, 117, 118, 147, 152], "nb_repeats_allow": 141, "ndarrai": [11, 13, 31, 104, 108, 127, 145], "nearest": [92, 94, 96, 99, 102, 103, 105, 112, 121, 147, 152], "nearli": 152, "necessari": [0, 9, 34, 144, 148, 151], "need": [0, 5, 9, 34, 64, 79, 82, 109, 112, 125, 138, 145, 146, 147, 148, 149, 150, 151, 152], "negat": 84, "neighbour": [83, 92, 94, 96, 99, 102, 103, 105, 112, 121, 147, 152], "nest": 34, "nester": 34, "network": [1, 83, 93, 111, 152], "neural": [1, 111, 152], "neutrino": [0, 1, 21, 43, 50, 83, 96, 98, 108, 120, 146, 147, 148, 150, 151, 152], "new": [0, 1, 18, 83, 107, 131, 136, 144, 145, 147, 148, 151, 152], "new_features_nam": 107, "new_phras": 138, "nfdi": [0, 148, 151], "nn": [0, 79, 83, 102, 105, 148, 151, 152], "no_weight_decai": 98, "node": [11, 13, 16, 79, 80, 84, 92, 93, 94, 96, 99, 100, 101, 102, 104, 105, 112, 121, 146, 147, 152], "node_definit": [104, 105, 146, 147, 152], "node_feature_nam": [107, 146, 147, 152], "node_level": 126, "node_rnn": [79, 92, 111], "node_truth": [11, 13, 16, 126, 133], "node_truth_t": [11, 13, 16, 126, 133, 147], "nodeasdomtimeseri": [106, 107], "nodedefinit": [104, 105, 106, 107, 147, 152], "nodesaspuls": [104, 106, 107, 146, 147, 152], "nodetimernn": 112, "nois": [22, 35, 74, 147], "non": [9, 34, 37, 59, 92, 118, 125, 147], "none": [5, 7, 8, 9, 11, 13, 14, 16, 21, 23, 31, 35, 36, 37, 45, 47, 49, 50, 51, 52, 53, 55, 59, 60, 62, 63, 64, 66, 67, 69, 70, 76, 83, 84, 86, 87, 88, 89, 90, 92, 94, 96, 98, 99, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 118, 123, 125, 126, 127, 129, 131, 132, 133, 135, 139, 141, 145, 146, 147, 150, 152], "noninfring": [14, 125], "norm_lay": 83, "normal": [83, 94, 99, 108, 110, 118, 150], "normalizing_flow": [1, 79], "normalizingflow": [79, 110, 118], "northeren": 25, "note": [11, 13, 16, 50, 63, 64, 108, 134, 147], "notebook": 144, "notic": [14, 64, 121, 125], "notimplementederror": 145, "now": [147, 150, 152], "np": [127, 145], "null": [36, 59, 146, 147, 152], "nullspliti3filt": [33, 36, 45, 47, 50, 55], "num": 129, "num_class": 125, "num_edg": 146, "num_edge_featur": 146, "num_featur": 146, "num_head": [83, 120], "num_lay": [112, 120], "num_nod": 146, "num_puls": 107, "num_register_token": 120, "num_row": [104, 146], "num_sampl": 14, "num_work": [7, 8, 9, 14, 47, 63, 126, 145, 146, 147, 150, 152], "number": [0, 5, 7, 11, 13, 14, 16, 19, 45, 47, 55, 60, 63, 64, 69, 72, 75, 82, 83, 84, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 112, 116, 117, 118, 120, 121, 123, 126, 127, 129, 145, 146, 147, 148, 150, 151], "numer": [118, 150], "numpi": 108, "numu": 124, "numucc": 124, "o": [0, 88, 118, 145, 147, 148, 149, 151, 152], "obj": [34, 37, 135], "object": [4, 6, 11, 13, 14, 16, 23, 34, 37, 80, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 125, 126, 129, 141, 146, 147, 152], "observ": 150, "observatori": [21, 50], "obtain": [14, 84, 125], "occur": [8, 126], "oerso": 95, "offer": 146, "offset": [107, 108], "ofintern": 38, "often": 146, "old_phras": 138, "om": [35, 37], "omit": 152, "on_fit_end": 123, "on_train_end": 113, "on_train_epoch_end": 123, "on_train_epoch_start": 123, "on_validation_end": 123, "onc": [141, 147, 149], "one": [11, 13, 21, 31, 59, 74, 84, 133, 134, 139, 144, 145, 146, 147, 150, 152], "ones": [108, 113], "onli": [0, 1, 11, 13, 16, 36, 64, 79, 84, 92, 107, 108, 118, 127, 131, 134, 136, 140, 145, 146, 147, 148, 150, 151, 152], "open": [0, 49, 144, 145, 146, 147, 148, 149, 150, 151], "opensciencegrid": 149, "oper": [14, 80, 83, 91, 94], "oppos": 146, "optic": [37, 108], "optim": [90, 110, 113, 123, 147, 152], "optimis": [0, 1, 147, 148, 151, 152], "optimizer_class": [110, 147, 152], "optimizer_closur": 113, "optimizer_kwarg": [110, 147, 152], "optimizer_step": 113, "optimzi": 110, "option": [5, 7, 9, 11, 13, 14, 16, 21, 31, 59, 64, 66, 67, 70, 76, 82, 83, 84, 86, 87, 88, 89, 92, 94, 96, 98, 99, 103, 104, 105, 107, 108, 109, 110, 112, 118, 123, 125, 127, 128, 129, 131, 133, 139, 145, 146, 147, 150, 152], "orca": 89, "orca150": [85, 89, 152], "orca150superdens": [85, 89], "orca_150": 89, "order": [0, 34, 49, 69, 72, 75, 80, 107, 121, 125, 147, 148, 151], "ordinari": 152, "ordinarili": 150, "org": [99, 102, 125, 147, 149], "orient": [0, 79, 148, 151], "origin": [14, 98, 146, 152], "ot": 125, "other": [14, 26, 59, 102, 125, 144, 146, 147, 152], "otherwis": [14, 37, 125], "our": [147, 150], "out": [5, 11, 13, 14, 94, 115, 125, 141, 144, 145, 146, 147, 150, 152], "out_featur": 83, "outdir": [7, 45, 47, 55, 145, 147, 150, 152], "outer": 34, "outlin": [150, 152], "output": [19, 64, 69, 70, 82, 83, 90, 92, 93, 94, 95, 97, 99, 104, 107, 108, 112, 116, 117, 118, 127, 133, 134, 145, 150, 152], "output_dim": [82, 152], "output_dir": [62, 63, 64, 145], "output_fil": 7, "output_file_path": 145, "output_fold": [6, 69], "outsid": [67, 144], "over": [103, 107, 145, 146], "overal": 125, "overhead": 150, "overrid": [9, 123], "overridden": 107, "overview": [0, 148, 151], "overwrit": [70, 123], "overwritten": [49, 129, 131], "own": [144, 147], "ownership": 144, "p": [35, 66, 125, 145], "p11003": 147, "packag": [0, 1, 58, 118, 135, 139, 140, 144, 147, 148, 151, 152], "pad": [104, 108, 121], "padding_valu": [25, 28, 121], "pair": [21, 31, 45, 47, 50, 55, 82], "pairwis": [103, 121], "pairwise_shuffl": [56, 58], "panda": [60, 127, 145, 147, 150, 152], "paper": 125, "paradigm": [147, 152], "parallel": [7, 45, 47, 55, 145, 150], "param": [14, 39, 41, 43], "paramet": [5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142], "parent": [34, 147], "parent_kei": 34, "parquet": [1, 3, 5, 10, 13, 39, 42, 43, 45, 47, 51, 53, 55, 57, 63, 66, 67, 87, 88, 89, 145, 146, 147, 150], "parquet_dataset": [10, 12, 146], "parquet_extractor": [17, 38], "parquet_to_sqlit": [3, 56], "parquet_writ": [3, 61], "parquetdataconvert": [44, 45], "parquetdataset": [9, 12, 13, 145, 147], "parquetextractor": [7, 38, 39, 41, 47, 49], "parquetread": [48, 51], "parquettosqliteconvert": [46, 47], "parquetwrit": [13, 39, 47, 61, 63, 145, 146, 150], "pars": [23, 128, 129, 130, 131, 136, 145], "parse_graph_definit": [10, 11], "parse_label": [10, 11], "part": [71, 145, 147, 149, 150], "particl": [31, 59, 124, 146, 147, 150], "particlenet": [79, 91], "particular": [14, 125, 144], "particularli": [146, 147, 152], "partit": 64, "partli": [0, 148, 151], "pass": [11, 16, 82, 83, 90, 92, 93, 94, 95, 96, 97, 98, 99, 104, 110, 112, 114, 118, 120, 123, 125, 127, 144, 145, 146, 147, 150, 152], "path": [5, 11, 13, 16, 21, 31, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 64, 69, 72, 74, 75, 76, 83, 104, 109, 113, 123, 126, 129, 131, 132, 133, 139, 145, 146, 147, 150, 152], "path_to_arrai": 150, "path_to_geometry_t": 150, "patienc": 129, "pd": [145, 147, 150], "pdf": [102, 110], "pdg": 124, "penal": 125, "peopl": [147, 152], "pep257": 144, "pep8": 144, "per": [11, 13, 16, 23, 59, 83, 84, 92, 112, 118, 125, 127, 146, 147], "percentil": [107, 108], "percentileclust": [106, 107], "perceptron": [83, 94, 99], "perform": [0, 9, 80, 82, 83, 84, 90, 91, 92, 94, 96, 99, 107, 110, 112, 113, 114, 116, 118, 126, 147, 148, 151, 152], "permiss": [14, 125], "permit": [14, 125], "persistent_work": [8, 126], "person": [5, 14, 125], "perturb": [104, 105], "perturbation_dict": [104, 105], "pframe": [45, 47, 50, 55], "philosophi": [147, 152], "photon": [43, 146, 147], "phrase": 138, "phyic": 1, "physic": [0, 1, 21, 35, 37, 68, 74, 76, 79, 115, 118, 146, 147, 148, 151, 152], "physicist": [0, 1, 147, 148, 151], "physicst": 1, "pick": 146, "pickl": [145, 147, 150, 152], "pid": [4, 60, 124, 133, 146], "pid_kei": 124, "piecewiselinearlr": [122, 123, 147, 152], "pip": [144, 149], "pisa": 27, "place": [14, 82, 98, 138, 144], "plai": 1, "plane": [24, 125], "pleas": [72, 145, 146, 147, 150], "plot": 146, "plug": 1, "pmt": [84, 108, 146, 147], "pmt_area": 4, "pmt_dir_i": 4, "pmt_dir_x": 4, "pmt_dir_z": 4, "pmt_number": 4, "point": [5, 30, 110, 124, 125, 126, 147, 150, 152], "pole": 96, "pone": 89, "pone_triangl": 89, "ponesmal": [65, 66], "ponetriangl": [85, 89], "pool": [7, 79, 80, 81, 92, 94, 96, 99], "pop_default": 129, "popular": 152, "port": 147, "portabl": [0, 147, 148, 151, 152], "portion": [14, 125], "pos_x": 147, "posit": [74, 82, 83, 84, 98, 108, 117, 120, 131, 136, 146, 150], "position_i": 4, "position_x": 4, "position_x_pr": 117, "position_y_pr": 117, "position_z": 4, "position_z_pr": 117, "positionreconstruct": [115, 117], "possibl": [0, 34, 64, 144, 148, 150, 151], "post": [92, 94, 96, 99], "post_processing_layer_s": [92, 94, 96, 147, 152], "posterior": 110, "pow": [147, 152], "power": [145, 147, 152], "pr": 112, "practic": [0, 144, 148, 151], "pre": [0, 5, 46, 47, 65, 86, 104, 124, 144, 146, 147, 148, 151, 152], "pre_configur": [1, 3, 47], "precis": 125, "precommit": 144, "preconfigur": 47, "pred": [90, 114, 118], "predict": [0, 9, 26, 30, 32, 74, 76, 90, 93, 98, 110, 114, 116, 118, 125, 126, 147, 148, 151, 152], "predict_as_datafram": [90, 147, 152], "prediction_column": [70, 76, 90, 126], "prediction_kei": 125, "prediction_label": [90, 118, 147, 152], "prefer": 103, "prefetch_factor": 8, "prepar": [0, 5, 9, 125, 146, 148, 151], "prepare_data": [5, 9], "preprocess": 147, "present": [11, 13, 21, 31, 36, 121, 129, 139, 140, 146, 152], "previou": [123, 147, 152], "primari": [59, 64, 146, 147], "primary_hadron_1_direction_phi": [4, 146, 147], "primary_hadron_1_direction_theta": [4, 146, 147], "primary_hadron_1_energi": [4, 146, 147], "primary_hadron_1_position_i": [4, 146, 147], "primary_hadron_1_position_x": [4, 146, 147], "primary_hadron_1_position_z": [4, 146, 147], "primary_hadron_1_typ": [4, 146, 147], "primary_key_rescu": 64, "primary_lepton_1_direction_phi": [4, 146, 147], "primary_lepton_1_direction_theta": [4, 146, 147], "primary_lepton_1_energi": [4, 146, 147], "primary_lepton_1_position_i": [4, 146, 147], "primary_lepton_1_position_x": [4, 146, 147], "primary_lepton_1_position_z": [4, 146, 147], "primary_lepton_1_typ": [4, 146, 147], "principl": [1, 147], "print": [5, 109, 123, 141], "prior": 146, "prioriti": 144, "privat": 127, "pro": [147, 152], "probabl": [83, 125, 152], "problem": [0, 102, 144, 146, 147, 148, 151, 152], "procedur": 9, "proceedur": 64, "process": [1, 7, 14, 45, 47, 55, 74, 82, 86, 92, 94, 96, 99, 144, 145, 147, 152], "process_posit": 123, "produc": [5, 49, 82, 110, 114, 124, 127, 146, 147], "product": [8, 83, 126], "programm": [0, 148, 151], "progress": 123, "progressbar": [122, 123, 147, 152], "proj_drop": 83, "project": [0, 53, 83, 144, 147, 148, 151, 152], "prometheu": [3, 4, 17, 43, 53, 66, 79, 85, 146, 147, 152], "prometheus_dataset": [1, 65], "prometheus_extractor": [17, 42], "prometheus_read": [3, 48], "prometheusextractor": [7, 42, 43, 49], "prometheusfeatureextractor": [42, 43], "prometheusread": [48, 53], "prometheustruthextractor": [42, 43], "prompt": 147, "prone": 147, "proof": [147, 152], "properti": [5, 9, 11, 13, 14, 19, 26, 37, 49, 62, 84, 86, 90, 97, 107, 108, 118, 124, 132, 141, 145], "protocol": 145, "prototyp": 88, "proven": [19, 21, 39, 41, 43, 145], "provid": [0, 1, 7, 11, 13, 14, 16, 74, 79, 98, 104, 109, 110, 125, 144, 145, 146, 147, 148, 151, 152], "pth": [147, 152], "public": [66, 86, 127], "publicprometheusdataset": [65, 66], "publish": [14, 125, 147, 152], "puls": [5, 11, 13, 16, 18, 22, 23, 35, 37, 43, 59, 74, 80, 84, 98, 104, 107, 108, 114, 120, 121, 146, 147, 150, 152], "pulse_truth": 5, "pulsemap": [5, 11, 13, 16, 22, 66, 67, 74, 76, 126, 133, 146, 147], "pulsemap_extractor": [74, 76], "pulseseri": 35, "pulsmap": [74, 76], "punch4nfdi": [0, 148, 151], "pure": [7, 19, 20, 23, 37], "purpos": [0, 14, 79, 125, 148, 150, 151], "put": [64, 147, 152], "py": [14, 125, 147], "py3": 149, "pydant": [131, 133, 134, 136], "pydantic_cor": [131, 136], "pydocstyl": 144, "pyg": [146, 147, 152], "pylint": 144, "python": [0, 1, 7, 19, 20, 23, 34, 37, 144, 147, 148, 149, 151, 152], "python3": [87, 88, 89, 129], "pytorch": [16, 123, 147, 149, 152], "pytorch_lightn": [90, 123, 141, 147, 152], "pytorchlightn": 147, "q": 83, "qk_scale": 83, "qkv_bia": 83, "qualiti": [0, 147, 148, 151], "quantiti": [27, 118, 121, 147], "queri": [11, 13, 16, 59, 60, 64, 83, 146, 147], "query_databas": [56, 59], "query_t": [11, 13, 16, 146], "queso": 28, "question": 147, "quick": [108, 147], "r": [84, 102, 145, 147, 149, 150], "radial": 102, "radialedg": [101, 102], "radiat": [107, 108, 147, 152], "radiu": [102, 147], "rais": [11, 13, 21, 23, 31, 109, 110, 131, 136, 145], "random": [3, 11, 13, 16, 56, 60, 63, 107, 133, 146, 147], "randomchunksampl": [10, 14], "randomli": [14, 60, 104, 105, 134, 147, 152], "rang": [14, 118, 148, 150, 151, 152], "rare": 145, "rasmu": [0, 95, 148, 151], "rate": [110, 123], "rather": [118, 141, 147, 152], "ratio": [9, 83, 98], "raw": [0, 107, 108, 146, 147, 148, 150, 151, 152], "rde": 4, "re": [132, 146, 147, 150, 152], "reach": [146, 150], "read": [0, 3, 7, 11, 13, 16, 34, 48, 50, 51, 52, 53, 86, 94, 115, 145, 146, 147, 148, 150, 151], "read_csv": 150, "read_sql": 147, "readabl": 147, "reader": [1, 3, 47, 49, 50, 51, 52, 53, 150], "readi": [65, 150, 152], "readm": 147, "readout": [92, 94, 96, 99], "readout_layer_s": [92, 94, 96, 99, 147, 152], "readthedoc": 147, "receiv": [0, 148, 151, 152], "reciev": [62, 145, 150, 152], "recommend": [147, 149, 150, 152], "reconstruct": [0, 1, 22, 24, 25, 29, 30, 32, 68, 71, 79, 96, 112, 115, 118, 146, 147, 148, 151], "record": 141, "recov": 118, "recreat": [146, 147, 152], "recurr": 111, "recurs": [23, 37, 45, 47, 49, 50, 55, 109, 135, 139], "reduc": [147, 152], "reduce_opt": 80, "refer": [9, 89, 110, 133, 146, 147, 150, 152], "refresh_r": 123, "regardless": [146, 147, 152], "regist": 120, "regress": 114, "regular": [37, 83, 147, 152], "rel": [83, 98, 120], "rel_pos_bia": 83, "rel_pos_bucket": 120, "relat": [58, 139, 150], "relev": [1, 37, 58, 139, 144], "reli": [50, 110], "reload": 152, "relu": 99, "remain": 146, "remaining_batch": 14, "remov": [8, 45, 55, 104, 126, 129, 150], "renam": [72, 138], "rename_state_dict_entri": [128, 138], "repeat": [104, 141], "repeat_label": 104, "repeatfilt": [128, 141], "replac": [86, 87, 88, 89, 138], "replace_with_ident": [86, 87, 88, 89], "repo": 144, "repositori": 144, "repres": [84, 92, 104, 105, 107, 108, 121, 131, 133, 134, 145, 146, 147, 150, 152], "represent": [5, 11, 13, 16, 37, 66, 67, 82, 83, 84, 105, 109, 110, 112, 146, 147, 150, 152], "reproduc": [133, 134, 152], "repurpos": 152, "requir": [0, 21, 27, 39, 43, 59, 107, 116, 118, 125, 144, 145, 146, 147, 148, 149, 150, 151, 152], "requires_icecub": [128, 140], "research": [0, 147, 148, 151], "reset": 83, "reset_paramet": 83, "resolv": [11, 13, 16, 60], "respect": [126, 147, 150], "respons": [146, 147], "restrict": [14, 118, 125, 152], "result": [14, 59, 63, 84, 105, 108, 123, 125, 126, 135, 147, 150, 152], "retriev": [86, 145, 146], "retro": 29, "return": [5, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 31, 34, 35, 37, 49, 50, 51, 52, 53, 58, 59, 60, 62, 63, 64, 69, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 138, 139, 140, 141, 142, 145, 146, 147, 150, 152], "return_discard": 37, "return_el": 125, "reusabl": [0, 148, 151], "reuseabl": [147, 152], "review": 144, "rhel_7_x86_64": 149, "right": [14, 125, 147], "rmse": 125, "rmseloss": [122, 125], "rmsevonmisesfisher3dloss": [122, 125], "rng": 58, "rnn": [1, 79, 92, 112], "rnn_dropout": 92, "rnn_dynedg": 92, "rnn_hidden_s": 92, "rnn_layer": 92, "rnn_tito": [79, 91], "role": 152, "root": 125, "roughli": 146, "row": [59, 64, 104, 108, 121, 146, 147, 150, 152], "run": [1, 14, 50, 69, 71, 72, 75, 145, 147, 149, 150, 152], "run_sql_cod": [56, 59], "runner": [87, 88, 89, 129], "runtim": [124, 149], "runtimeerror": [21, 31], "ryabinin": 125, "sai": [147, 152], "same": [18, 37, 59, 80, 84, 108, 116, 121, 123, 135, 141, 146, 147, 152], "sampl": [14, 60, 83, 104, 105, 107, 147, 152], "sample_puls": 107, "sampler": [3, 10], "satisfi": [0, 145, 148, 151], "save": [7, 19, 21, 34, 39, 41, 43, 45, 47, 55, 59, 61, 62, 64, 109, 123, 125, 126, 127, 131, 132, 133, 134, 145, 147, 150], "save_config": [132, 147, 152], "save_dataset_config": [130, 133], "save_dir": [123, 147, 152], "save_fil": [62, 145], "save_method": [7, 145, 150], "save_model_config": [130, 134], "save_result": [122, 126], "save_select": [122, 126], "save_state_dict": [109, 147, 152], "save_to_sql": [56, 59], "scalabl": 146, "scalar": [11, 13, 19, 121, 125], "scale": [82, 83, 95, 98, 103, 104, 107, 108, 118, 120, 125, 146, 152], "scaled_emb": [98, 120], "scatter": [107, 108], "schedul": 110, "scheduler_class": [110, 147, 152], "scheduler_config": [110, 147, 152], "scheduler_kwarg": [110, 147, 152], "schema": 147, "scheme": [92, 94, 96, 99, 145], "scientif": [0, 1, 148, 151], "scope": 144, "script": [147, 152], "search": [45, 47, 49, 50, 51, 52, 53, 55, 139, 145], "sec": 125, "second": 103, "section": 147, "see": [82, 92, 102, 104, 110, 118, 123, 144, 146, 147, 149], "seed": [9, 11, 13, 16, 60, 104, 105, 126, 133, 146, 147], "seen": 82, "select": [5, 8, 9, 11, 13, 14, 16, 28, 36, 60, 107, 126, 127, 133, 144, 147, 150], "selection_nam": 8, "self": [11, 13, 90, 104, 110, 114, 131, 136, 145, 146, 147, 150, 152], "sell": [14, 125], "send": 118, "sensor": [86, 104, 108, 146, 147, 150, 152], "sensor_i": 150, "sensor_id": [87, 89, 150], "sensor_id_column": [87, 88, 89, 150], "sensor_index_nam": 86, "sensor_mask": 104, "sensor_pos_i": [4, 89, 146, 147, 152], "sensor_pos_x": [4, 89, 146, 147, 152], "sensor_pos_z": [4, 89, 146, 147, 152], "sensor_position_nam": 86, "sensor_string_id": 89, "sensor_tim": 150, "sensor_x": [146, 150], "sensor_z": 150, "separ": [34, 103, 123, 147, 149], "seper": [112, 146], "seq_length": [82, 98, 120, 121], "sequenc": [14, 69, 72, 75, 82, 83, 108, 121, 126, 147, 152], "sequenti": [11, 13], "sequential_index": [11, 13, 16], "seri": [11, 13, 16, 22, 23, 35, 37, 59, 74, 92, 107, 112, 146, 147, 152], "serial": [145, 146], "serialis": [33, 34, 147, 152], "serv": 146, "session": [133, 134, 146, 147, 152], "set": [3, 6, 9, 13, 21, 23, 31, 45, 47, 49, 50, 55, 62, 82, 83, 98, 107, 108, 109, 118, 124, 126, 144, 145, 147, 150, 152], "set_extractor": 49, "set_gcd": [21, 31], "set_index": 150, "set_number_of_input": 107, "set_output_feature_nam": 107, "set_verbose_print_recurs": 109, "setlevel": 141, "setup": [9, 123, 149], "setuptool": 149, "sever": [147, 152], "sh": 149, "shall": [14, 125], "shape": [19, 103, 104, 107, 121, 125, 145, 146], "share": [90, 110, 114, 147, 152], "share_redirect": 5, "shared_step": [90, 110, 114], "sharelink": 5, "shell": 149, "should": [8, 11, 13, 16, 19, 21, 34, 60, 67, 70, 83, 84, 86, 87, 88, 89, 92, 98, 104, 105, 112, 121, 125, 126, 131, 133, 134, 136, 144, 145, 146, 147, 149, 150, 152], "show": [60, 123, 147], "shown": 147, "shuffl": [8, 9, 58, 63, 126, 146], "shutdown": 9, "sid": 5, "sigmoid": 152, "sign": 125, "signal": [74, 152], "signatur": [23, 37], "signific": 146, "significantli": 146, "signup": 147, "similar": [14, 23, 37, 107, 147, 152], "similarli": [37, 145, 146, 147, 152], "simpl": [0, 79, 90, 147, 148, 151, 152], "simplecoarsen": 80, "simplest": [147, 152], "simpli": [147, 152], "simul": [35, 43, 53, 66, 74, 147, 150], "sinc": [14, 74, 125, 147], "singl": [5, 11, 18, 62, 64, 84, 94, 99, 108, 124, 127, 133, 134, 145, 146, 147, 150, 152], "single_event_as_arrai": 108, "sinusoid": [82, 98, 120], "sinusoidalposemb": [81, 82], "sipm_i": [4, 88], "sipm_id": 88, "sipm_x": [4, 88], "sipm_z": [4, 88], "situat": 144, "size": [13, 14, 64, 82, 83, 84, 92, 94, 95, 96, 98, 99, 121, 129, 146], "skip": [36, 94, 99, 147], "skip_readout": [94, 99], "sklearn": [147, 152], "sk\u0142odowska": [0, 148, 151], "slack": 147, "slice": [83, 94, 99], "slower": 64, "small": [125, 146, 147, 152], "smaller": [62, 145], "smooth": 144, "snippet": [147, 152], "so": [14, 125, 146, 147, 149, 150, 152], "soft": 82, "softmax": 125, "softwar": [0, 14, 50, 125, 148, 151], "solut": [82, 83, 96, 98, 144], "solv": [1, 144, 152], "some": [11, 13, 14, 16, 45, 47, 50, 55, 104, 108, 146, 147], "someth": [147, 152], "somewhat": 147, "sort": [104, 108], "sort_bi": 104, "sota": 5, "sourc": [0, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 78, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142, 144, 146, 147, 148, 151], "south": 96, "space": [82, 102, 103, 118, 127], "space_coord": 103, "spacetim": 82, "spacetimeencod": [81, 82], "sparsetensor": 83, "spatial": 108, "spawn": [13, 14], "special": [23, 74, 112, 121], "specialis": [147, 152], "specif": [0, 1, 3, 5, 6, 7, 11, 13, 16, 17, 19, 22, 37, 48, 49, 50, 59, 64, 68, 70, 73, 75, 78, 80, 84, 85, 86, 87, 88, 89, 91, 92, 97, 102, 104, 107, 111, 115, 116, 117, 118, 119, 125, 144, 145, 146, 147, 148, 150, 151, 152], "specifi": [11, 13, 14, 16, 60, 80, 108, 110, 118, 123, 146, 147, 150, 152], "speed": [74, 103, 146], "sphere": 102, "spite": 125, "splinemp": 30, "split": [0, 9, 36, 64, 80, 148, 151], "split_se": 9, "splitinicepuls": 59, "sql": 127, "sqlite": [1, 3, 5, 9, 10, 16, 47, 55, 57, 59, 64, 66, 67, 146, 147], "sqlite3": 147, "sqlite_dataset": [10, 15, 146], "sqlite_util": [3, 56], "sqlite_writ": [3, 61], "sqlitedataconvert": [54, 55], "sqlitedatas": 146, "sqlitedataset": [9, 15, 16, 145], "sqlitewrit": [61, 64, 145, 146], "squar": 125, "src": [14, 147], "stabl": [117, 118], "stage": [9, 123], "standalon": 112, "standard": [0, 3, 4, 36, 60, 70, 87, 88, 89, 92, 104, 105, 107, 108, 110, 113, 114, 118, 129, 144, 147, 148, 150, 151, 152], "standard_argu": 129, "standard_averaged_model": [1, 79], "standard_model": [1, 79, 147], "standardaveragedmodel": [79, 113], "standardaveragemodel": 113, "standardflowtask": [115, 118], "standardis": 85, "standardlearnedtask": [115, 116, 117, 118, 152], "standardmodel": [79, 90, 113, 114], "start": [14, 31, 144, 147, 150, 152], "state": [0, 70, 92, 112, 138, 148, 151], "state_dict": [70, 74, 76, 109, 113, 138, 147], "static": [125, 144], "statist": 108, "std": 84, "std_pool": [81, 84], "std_pool_x": [81, 84], "stdout": 123, "step": [90, 110, 113, 114, 121, 123, 147, 150, 152], "still": 133, "stochast": 83, "stop": [31, 123, 129], "stopped_muon": 4, "store": [11, 13, 16, 59, 62, 63, 64, 124, 145, 146, 147, 150, 152], "str": [5, 6, 7, 8, 9, 11, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 39, 41, 43, 45, 47, 49, 50, 51, 52, 53, 55, 58, 59, 60, 62, 63, 64, 66, 67, 69, 70, 72, 74, 75, 76, 83, 84, 86, 87, 88, 89, 90, 92, 94, 96, 98, 99, 104, 105, 107, 108, 109, 110, 113, 118, 121, 123, 124, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 139, 141, 145, 150], "straightforward": 146, "strategi": [147, 152], "stream": 36, "stream_handl": 141, "streamhandl": 141, "streamlin": 1, "string": [4, 5, 11, 13, 16, 34, 60, 84, 86, 87, 104, 109, 110, 118, 131, 147, 150, 152], "string_id": 150, "string_id_column": [87, 88, 89, 150], "string_index_nam": 86, "string_mask": 104, "string_select": [11, 13, 16, 126, 133], "string_selection_resolv": [3, 56], "stringselectionresolv": [56, 60], "strongli": [147, 152], "structur": [90, 135, 145, 146, 147, 152], "style": 144, "sub": 147, "subclass": [0, 5, 79, 90, 145, 146, 147, 148, 151, 152], "subev": 36, "subeventstreami3filt": [33, 36], "subfold": [45, 47, 50, 55], "subject": [14, 98, 125], "sublicens": [14, 125], "submit": 98, "submodul": [1, 3, 10, 12, 15, 17, 20, 33, 38, 40, 42, 44, 46, 48, 54, 56, 61, 65, 68, 71, 73, 77, 79, 81, 85, 91, 100, 101, 106, 111, 115, 119, 122, 128, 130, 135], "subpackag": [1, 3, 10, 17, 20, 68, 79, 100, 128], "subsampl": [63, 146], "subsequ": 147, "subset": [11, 13, 16, 83, 92, 94, 96, 99, 112, 147], "substanti": [14, 125], "suggest": [90, 125, 147], "suit": [0, 110, 118, 147, 148, 151], "suitabl": [1, 150], "sum": [80, 84, 90, 94, 96, 99, 108, 114, 127, 147, 152], "sum_pool": [80, 81, 84], "sum_pool_and_distribut": [81, 84], "sum_pool_x": [80, 81, 84], "summar": [74, 76, 107, 108], "summari": [107, 108], "summaris": [147, 152], "summariz": 152, "summarization_indic": 108, "super": [145, 146, 147, 152], "supervis": [114, 118, 152], "support": [0, 7, 37, 118, 144, 145, 146, 147, 148, 151], "suppos": [5, 108, 146, 150], "sure": [144, 145], "swa": 113, "swapabl": 147, "switch": [125, 147, 152], "synchron": 7, "syntax": [60, 90, 125, 146, 147], "system": [139, 147, 152], "t": [4, 37, 59, 123, 125, 145, 146, 147, 150, 152], "t_co": 8, "tabl": [5, 11, 13, 16, 18, 19, 21, 39, 41, 43, 49, 59, 63, 64, 86, 104, 127, 145, 146, 147], "table_nam": [43, 59], "table_without_index": 150, "tackl": 152, "tag": [126, 144], "take": [37, 84, 108, 112, 144, 146], "talk": 147, "tar": 5, "target": [90, 110, 116, 118, 125, 136, 147, 152], "target_label": [90, 110, 118, 147, 152], "target_norm": 118, "target_pr": [116, 152], "task": [0, 1, 9, 79, 90, 114, 116, 117, 125, 144, 147, 148, 151], "team": [144, 146, 147, 149, 150, 152], "teardown": 9, "technic": [0, 148, 150, 151], "techniqu": [0, 148, 151, 152], "telescop": [0, 1, 147, 148, 150, 151, 152], "tend": 64, "tensor": [11, 13, 16, 70, 80, 82, 83, 84, 86, 90, 92, 93, 94, 95, 96, 97, 98, 99, 103, 107, 108, 110, 112, 113, 114, 118, 120, 121, 125, 138, 142, 146, 147, 150, 152], "term": [83, 125, 152], "termin": 147, "test": [5, 9, 60, 66, 67, 118, 126, 133, 140, 144, 146, 147, 152], "test_dataload": 9, "test_dataloader_kwarg": [5, 9, 66, 67], "test_dataset": [1, 65], "test_funct": 140, "test_select": [9, 133, 146, 147], "test_siz": 126, "testdataset": [65, 67], "tev": 66, "than": [0, 8, 107, 118, 126, 141, 146, 147, 148, 151, 152], "thei": [69, 72, 75, 107, 145, 146, 147, 152], "them": [0, 1, 34, 70, 79, 94, 118, 146, 147, 148, 150, 151, 152], "themselv": [1, 133, 134, 147, 152], "therebi": [1, 133, 134, 147, 152], "therefor": [34, 50, 145, 146, 147, 150, 152], "thi": [0, 3, 5, 7, 9, 11, 13, 14, 16, 18, 19, 21, 23, 37, 39, 41, 43, 45, 47, 49, 50, 55, 58, 59, 63, 64, 67, 71, 74, 79, 82, 84, 90, 92, 94, 98, 99, 103, 104, 105, 107, 108, 110, 112, 114, 116, 117, 118, 121, 123, 125, 126, 127, 131, 133, 134, 141, 144, 145, 146, 147, 148, 149, 150, 151, 152], "thing": 147, "thoglu": [110, 118], "those": [21, 31, 146, 147], "thread": 13, "three": [99, 108, 125, 152], "threshold": [0, 74, 148, 151], "through": [0, 108, 116, 117, 118, 125, 145, 147, 148, 151, 152], "throw": 145, "thu": [134, 152], "ti": 146, "time": [0, 4, 59, 80, 82, 84, 92, 103, 107, 108, 112, 117, 121, 127, 141, 146, 147, 148, 150, 151], "time_column": 107, "time_coord": 103, "time_lik": 103, "time_like_weight": 103, "time_series_column": [92, 112], "time_window": 80, "timereconstruct": [115, 117], "tini": 147, "tito": [83, 92, 96], "to_config": 152, "to_csv": [147, 152], "to_parquet": 150, "todo": 147, "togeth": [0, 14, 79, 102, 125, 148, 151], "token": 120, "too": [147, 152], "tool": [0, 1, 148, 151], "top": 152, "torch": [0, 11, 13, 16, 79, 83, 104, 105, 109, 110, 140, 146, 147, 148, 149, 150, 151, 152], "torch_cpu": 149, "torch_geometr": [84, 121, 146, 147, 152], "torch_lightn": 152, "tort": [14, 125], "total": [108, 121, 126, 127, 146, 147, 150], "total_energi": [4, 146, 147, 152], "tqdmprogressbar": 123, "track": [0, 19, 21, 25, 39, 41, 43, 66, 117, 122, 124, 144, 145, 147, 148, 151], "tradit": [0, 148, 151], "train": [0, 1, 5, 7, 9, 10, 60, 65, 66, 67, 68, 74, 83, 90, 98, 104, 110, 113, 114, 121, 123, 124, 125, 126, 127, 129, 133, 134, 136, 143, 145, 146, 147, 148, 150, 151], "train_batch": [90, 113], "train_dataload": [9, 90, 147, 152], "train_dataloader_kwarg": [5, 9, 66, 67], "train_ev": 118, "train_select": [133, 146, 147], "train_val_split": 9, "trainabl": 134, "trainer": [90, 123, 126, 147, 152], "trainer_kwarg": 90, "training_config": [128, 130, 147, 152], "training_example_data_sqlit": [129, 146, 147, 152], "training_step": [90, 113], "trainingconfig": [130, 136, 147, 152], "transform": [1, 79, 83, 84, 96, 98, 112, 118, 120, 127, 147, 152], "transform_infer": [118, 147, 152], "transform_prediction_and_target": [118, 147, 152], "transform_support": [118, 147, 152], "transform_target": [118, 147, 152], "transit": 138, "transpar": [133, 134, 144, 147, 152], "transpos": 34, "transpose_list_of_dict": [33, 34], "traverse_and_appli": [130, 135], "treat": [92, 112], "tree": [23, 147], "tri": [23, 37], "triangl": 89, "trident": [66, 89], "trident1211": [85, 89], "tridentsmal": [65, 66], "trigger": [23, 146, 147, 152], "trivial": [37, 118], "true": [36, 59, 74, 92, 94, 96, 98, 99, 104, 107, 109, 123, 125, 127, 139, 145, 146, 147, 152], "trust": [109, 147, 152], "truth": [3, 4, 5, 11, 13, 16, 22, 31, 43, 59, 63, 66, 67, 104, 118, 126, 127, 133, 146, 150, 152], "truth_dict": 104, "truth_label": 146, "truth_tabl": [5, 11, 13, 16, 63, 126, 127, 133, 146, 147], "truthdata": 41, "try": [37, 145], "tum": [25, 32], "tupl": [7, 11, 13, 14, 16, 35, 37, 59, 83, 92, 94, 96, 99, 108, 118, 121, 126, 129, 138], "turn": [108, 144], "tutorial_output": [147, 152], "two": [8, 94, 123, 125, 126, 145, 146, 147, 150], "txt": 149, "type": [0, 5, 7, 8, 9, 11, 13, 14, 16, 20, 21, 31, 33, 34, 35, 41, 43, 49, 50, 51, 52, 53, 58, 59, 60, 62, 63, 64, 69, 80, 82, 83, 84, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 107, 108, 109, 110, 112, 113, 114, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 129, 131, 132, 133, 134, 135, 138, 139, 140, 141, 142, 144, 145, 146, 147, 148, 150, 151], "typic": [0, 34, 112, 146, 148, 150, 151], "u": [146, 150], "ultra": 146, "unaccur": 125, "unambigu": [133, 134], "unbatch_edge_index": [79, 80], "uncertainti": [117, 147, 152], "uncompress": 146, "under": [0, 147, 148, 150, 151, 152], "unfamiliar": 152, "uniform": [122, 127], "uniformweightfitt": 127, "union": [0, 7, 8, 9, 11, 13, 16, 23, 34, 37, 45, 47, 49, 50, 51, 52, 53, 55, 69, 70, 72, 74, 75, 76, 80, 83, 84, 90, 92, 94, 99, 104, 105, 108, 110, 114, 118, 133, 136, 139, 145, 148, 150, 151], "uniqu": [11, 13, 16, 59, 107, 108, 121, 133, 147, 150, 152], "unit": [0, 7, 67, 103, 140, 144, 148, 151], "univers": 96, "unlik": 146, "unscal": 152, "untransform": 116, "up": [0, 74, 144, 148, 151], "updat": [99, 112, 113, 121, 123, 147, 149, 152], "upgrad": [4, 22, 87, 147, 149], "upon": [110, 152], "us": [0, 1, 2, 4, 5, 7, 8, 9, 11, 12, 13, 14, 15, 16, 18, 19, 21, 26, 31, 33, 34, 39, 41, 43, 45, 47, 49, 50, 54, 55, 56, 59, 60, 62, 63, 64, 66, 67, 68, 70, 72, 74, 76, 79, 82, 83, 84, 86, 90, 92, 94, 95, 96, 98, 99, 102, 104, 105, 107, 108, 109, 110, 112, 115, 116, 117, 118, 120, 121, 123, 124, 125, 127, 128, 129, 130, 133, 134, 135, 140, 141, 144, 145, 148, 149, 150, 151], "usabl": [0, 148, 151], "usag": [110, 118, 129], "use_cach": 60, "use_global_featur": [92, 96], "use_post_processing_lay": [92, 96], "user": [0, 5, 79, 90, 123, 146, 147, 148, 149, 151, 152], "usual": 146, "util": [1, 3, 17, 20, 34, 35, 36, 37, 57, 58, 59, 60, 79, 100, 122, 129, 131, 132, 133, 134, 135, 136, 138, 139, 140, 141, 142, 143, 146, 147, 149, 152], "v": 83, "v1": 149, "v4": 149, "val_batch": [90, 113], "val_dataload": [9, 90], "valid": [5, 9, 37, 60, 66, 67, 90, 110, 113, 114, 118, 123, 125, 129, 131, 136, 146, 147, 152], "validate_fil": 49, "validate_task": [90, 110, 114], "validation_dataloader_kwarg": [5, 9, 66, 67], "validation_step": [90, 113], "validationerror": [131, 136], "valu": [11, 13, 16, 31, 34, 59, 83, 84, 99, 103, 104, 105, 108, 118, 121, 124, 125, 129, 131, 152], "valueerror": [23, 109, 110], "var": 117, "var1": 19, "var_n": 19, "variabl": [19, 21, 23, 31, 37, 49, 94, 107, 108, 121, 127, 141, 145, 150, 152], "varieti": 147, "variou": [1, 61, 71, 147], "vast": [114, 118], "vector": [80, 83, 84, 125, 145, 152], "verbos": [45, 47, 50, 55, 90, 114, 123], "verbose_print": 109, "veri": [60, 146, 147, 152], "verifi": [90, 110, 114], "versa": 123, "version": [84, 108, 118, 123, 144, 147, 152], "vertex": [117, 147], "vertex_i": 4, "vertex_x": 4, "vertex_z": 4, "vertexreconstruct": [115, 117], "viabl": 150, "vice": 123, "virtual": 149, "visibl": 117, "visible_energi": 4, "visible_inelast": [4, 117], "visible_inelasticity_pr": 117, "visibleinelasticityreconstruct": [115, 117], "visit": 150, "vmf": 117, "vmf_loss": 125, "vmfs_factor": 125, "volum": 31, "von": 125, "vonmisesfisher2dloss": [122, 125, 147, 152], "vonmisesfisher3dloss": [122, 125], "vonmisesfisherloss": [122, 125], "w": [147, 152], "wa": [0, 7, 98, 146, 147, 148, 150, 151, 152], "wai": [14, 37, 60, 114, 144, 147, 150, 152], "wandb": [147, 152], "wandb_dir": [147, 152], "wandb_logg": [147, 152], "wandblogg": [147, 152], "want": [146, 147, 149, 150, 152], "warn": [141, 147], "warning_onc": [141, 147], "warranti": [14, 125], "waterdemo81": [85, 89], "wb": 145, "we": [34, 37, 60, 108, 110, 144, 147, 149, 150, 152], "weight": [11, 13, 16, 74, 76, 83, 98, 104, 108, 118, 125, 127, 134, 147, 152], "weight_fit": [1, 122], "weight_nam": 127, "weightfitt": [122, 127], "well": [144, 147, 152], "wether": 99, "what": [1, 82, 104, 144, 147, 152], "whatev": 147, "wheel": 149, "when": [0, 11, 13, 14, 16, 34, 36, 59, 74, 83, 92, 94, 96, 99, 112, 124, 141, 144, 145, 146, 147, 148, 149, 150, 151, 152], "whenev": 149, "where": [19, 45, 47, 50, 55, 104, 105, 107, 108, 112, 121, 124, 145, 146, 147, 150, 152], "wherea": [127, 146], "whether": [8, 14, 35, 37, 59, 82, 83, 92, 94, 96, 98, 99, 109, 120, 125, 135, 139, 140, 147], "which": [0, 5, 11, 13, 16, 19, 21, 22, 31, 35, 39, 41, 43, 60, 62, 64, 69, 71, 72, 75, 80, 84, 94, 99, 104, 105, 108, 109, 110, 116, 118, 121, 125, 126, 129, 145, 146, 147, 148, 151, 152], "while": [0, 23, 90, 123, 144, 146, 148, 151], "who": [5, 138, 147, 152], "whom": [14, 125], "whose": 74, "wide": [14, 110, 152], "width": 14, "willing": [146, 150], "window": [80, 146, 147], "wise": 84, "wish": [0, 69, 144, 148, 151], "with_standard_argu": 129, "within": [31, 80, 83, 84, 94, 99, 102, 147, 152], "without": [1, 14, 102, 105, 107, 125, 146, 149], "work": [0, 4, 35, 92, 144, 145, 146, 147, 148, 151, 152], "worker": [6, 7, 14, 45, 55, 58, 63, 69, 72, 75, 129, 141], "workflow": [0, 148, 151], "would": [144, 146, 147, 150, 152], "wrap": [123, 133, 134], "write": [63, 74, 76, 145, 147, 152], "writer": [1, 3, 47, 62, 63, 64, 150], "written": [47, 69, 145], "wrt": 118, "www": 147, "x": [4, 31, 82, 83, 84, 87, 103, 107, 108, 112, 118, 121, 125, 127, 146, 147, 150, 152], "x8": 146, "x_i": 83, "x_j": 83, "x_low": 127, "xyz": [86, 87, 88, 89, 107, 108, 146, 150], "xyz_coord": 121, "xyzt": 121, "y": [4, 31, 82, 87, 103, 121], "yaml": [131, 132, 147], "yet": 108, "yield": [0, 94, 99, 125, 148, 151], "yml": [60, 129, 133, 134, 146, 147, 152], "you": [64, 69, 82, 110, 133, 134, 144, 146, 147, 149, 150, 152], "your": [105, 110, 144, 145, 146, 147, 149], "yourself": 144, "z": [4, 31, 82, 87, 103, 107, 108, 121], "z_name": 107, "z_offset": [107, 108], "z_scale": [107, 108], "zenith": [4, 117, 124, 147, 152], "zenith_kappa": 117, "zenith_kei": 124, "zenith_pr": 117, "zenithreconstruct": [115, 117], "zenithreconstructionwithkappa": [115, 117, 147, 152], "\u00f8rs\u00f8e": [0, 148, 151]}, "titles": ["Usage", "API", "constants", "data", "constants", "curated_datamodule", "dataclasses", "dataconverter", "dataloader", "datamodule", "dataset", "dataset", "parquet", "parquet_dataset", "samplers", "sqlite", "sqlite_dataset", "extractors", "combine_extractors", "extractor", "icecube", "i3extractor", "i3featureextractor", "i3genericextractor", "i3hybridrecoextractor", "i3ntmuonlabelsextractor", "i3particleextractor", "i3pisaextractor", "i3quesoextractor", "i3retroextractor", "i3splinempeextractor", "i3truthextractor", "i3tumextractor", "utilities", "collections", "frames", "i3_filters", "types", "internal", "parquet_extractor", "liquido", "h5_extractor", "prometheus", "prometheus_extractor", "parquet", "deprecated_methods", "pre_configured", "dataconverters", "readers", "graphnet_file_reader", "i3reader", "internal_parquet_reader", "liquido_reader", "prometheus_reader", "sqlite", "deprecated_methods", "utilities", "parquet_to_sqlite", "random", "sqlite_utilities", "string_selection_resolver", "writers", "graphnet_writer", "parquet_writer", "sqlite_writer", "datasets", "prometheus_datasets", "test_dataset", "deployment", "deployer", "deployment_module", "i3modules", "deprecated_methods", "icecube", "cleaning_module", "i3deployer", "inference_module", "exceptions", "exceptions", "models", "coarsening", "components", "embedding", "layers", "pool", "detector", "detector", "icecube", "liquido", "prometheus", "easy_model", "gnn", "RNN_tito", "convnet", "dynedge", "dynedge_jinst", "dynedge_kaggle_tito", "gnn", "icemix", "particlenet", "graphs", "edges", "edges", "minkowski", "graph_definition", "graphs", "nodes", "nodes", "utils", "model", "normalizing_flow", "rnn", "node_rnn", "standard_averaged_model", "standard_model", "task", "classification", "reconstruction", "task", "transformer", "iseecube", "utils", "training", "callbacks", "labels", "loss_functions", "utils", "weight_fitting", "utilities", "argparse", "config", "base_config", "configurable", "dataset_config", "model_config", "parsing", "training_config", "decorators", "deprecation_tools", "filesys", "imports", "logging", "maths", "src", "Contributing To GraphNeT", "Data Conversion in GraphNeT", "Datasets In GraphNeT", "GraphNeT tutorial", "GraphNeT", "Installation", "Integrating New Experiments into GraphNeT", "GraphNeT", "Models In GraphNeT", "<no title>"], "titleterms": {"1": 150, "2": 150, "In": [146, 152], "The": [147, 152], "To": 144, "acknowledg": 0, "ad": [146, 147, 150, 152], "advanc": 147, "api": 1, "appendix": 147, "appli": 150, "argpars": 129, "backbon": 152, "base_config": 131, "befor": 150, "callback": 123, "checkpoint": 152, "choos": 146, "class": [147, 150, 152], "classif": 116, "cleaning_modul": 74, "coarsen": 80, "code": 144, "collect": 34, "combin": [146, 147], "combine_extractor": 18, "compon": 81, "config": 130, "configur": 132, "constant": [2, 4], "content": 147, "contribut": 144, "convent": 144, "convers": 145, "convnet": 93, "creat": 147, "curated_datamodul": 5, "custom": [146, 147], "cvmf": 149, "data": [3, 145, 150], "dataclass": 6, "dataconfig": 147, "dataconvert": [7, 47, 145], "dataload": 8, "datamodul": 9, "dataset": [10, 11, 65, 146, 147], "dataset_config": 133, "datasetconfig": 147, "decor": 137, "deploy": [68, 69], "deployment_modul": 70, "deprecated_method": [45, 55, 72], "deprecation_tool": 138, "detector": [85, 86, 150], "dynedg": 94, "dynedge_jinst": 95, "dynedge_kaggle_tito": 96, "easy_model": 90, "edg": [101, 102], "embed": 82, "energi": 152, "event": 146, "exampl": [147, 150, 152], "except": [77, 78], "experi": [150, 152], "extractor": [17, 19, 145, 150], "filesi": 139, "frame": 35, "function": 147, "geometri": 150, "github": 144, "gnn": [91, 97], "graph": [100, 105], "graph_definit": 104, "graphdefinit": 152, "graphnet": 147, "graphnet_file_read": 49, "graphnet_writ": 62, "graphnetfileread": 150, "graphnetgraphnet": [144, 145, 146, 148, 150, 151, 152], "h5_extractor": 41, "i3_filt": 36, "i3deploy": 75, "i3extractor": 21, "i3featureextractor": 22, "i3genericextractor": 23, "i3hybridrecoextractor": 24, "i3modul": 71, "i3ntmuonlabelsextractor": 25, "i3particleextractor": 26, "i3pisaextractor": 27, "i3quesoextractor": 28, "i3read": 50, "i3retroextractor": 29, "i3splinempeextractor": 30, "i3truthextractor": 31, "i3tumextractor": 32, "icecub": [20, 73, 87, 149], "icemix": 98, "implement": [146, 150], "import": 140, "index": 150, "inference_modul": 76, "instal": 149, "instanti": 152, "integr": 150, "intern": 38, "internal_parquet_read": 51, "introduct": 147, "iseecub": 120, "issu": 144, "label": [124, 146, 147], "layer": 83, "liquido": [40, 88], "liquido_read": 52, "load": 152, "log": 141, "loss_funct": 125, "math": 142, "minkowski": 103, "model": [79, 109, 147, 152], "model_config": 134, "modelconfig": [147, 152], "multi": 150, "multipl": [146, 147], "new": [146, 150], "node": [106, 107], "node_rnn": 112, "normalizing_flow": 110, "overview": 147, "own": [150, 152], "parquet": [12, 44], "parquet_dataset": 13, "parquet_extractor": 39, "parquet_to_sqlit": 57, "parquet_writ": 63, "parquetdataset": 146, "pars": 135, "particlenet": 99, "pool": 84, "pre_configur": 46, "prometheu": [42, 89], "prometheus_dataset": 66, "prometheus_extractor": 43, "prometheus_read": 53, "pull": 144, "qualiti": 144, "quick": 149, "random": 58, "reader": [48, 145], "reconstruct": [117, 152], "reproduc": 147, "request": 144, "rnn": 111, "rnn_tito": 92, "sampler": 14, "save": 152, "select": 146, "sqlite": [15, 54], "sqlite_dataset": 16, "sqlite_util": 59, "sqlite_writ": 64, "sqlitedataset": [146, 147], "src": 143, "standard_averaged_model": 113, "standard_model": 114, "standardmodel": [147, 152], "start": 149, "state_dict": 152, "string_selection_resolv": 60, "subset": 146, "support": 150, "syntax": 152, "tabl": 150, "task": [115, 118, 152], "test_dataset": 67, "track": 152, "train": [122, 152], "training_config": 136, "transform": 119, "truth": 147, "tutori": 147, "type": 37, "us": [146, 147, 152], "usag": 0, "util": [33, 56, 108, 121, 126, 128], "v": 146, "weight_fit": 127, "write": 150, "writer": [61, 145], "your": [150, 152]}}) \ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml index 65a16b1c4..865cd4448 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1 +1 @@ -https://graphnet-team.github.io/graphnetabout/about.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.constants.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.constants.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.curated_datamodule.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataclasses.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataconverter.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataloader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.datamodule.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.parquet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.parquet.parquet_dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.samplers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.sqlite.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.sqlite.sqlite_dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.combine_extractors.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3featureextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3genericextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3hybridrecoextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3ntmuonlabelsextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3particleextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3pisaextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3quesoextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3retroextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3splinempeextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3truthextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3tumextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.collections.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.frames.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.i3_filters.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.types.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.internal.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.internal.parquet_extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.liquido.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.liquido.h5_extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.prometheus.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.prometheus.prometheus_extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.parquet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.parquet.deprecated_methods.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.pre_configured.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.pre_configured.dataconverters.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.graphnet_file_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.i3reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.internal_parquet_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.liquido_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.prometheus_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.sqlite.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.sqlite.deprecated_methods.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.parquet_to_sqlite.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.random.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.sqlite_utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.string_selection_resolver.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.graphnet_writer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.parquet_writer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.sqlite_writer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.datasets.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.datasets.prometheus_datasets.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.datasets.test_dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.deployer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.deployment_module.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.i3modules.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.i3modules.deprecated_methods.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.cleaning_module.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.i3deployer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.inference_module.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.exceptions.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.exceptions.exceptions.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.coarsening.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.embedding.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.layers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.pool.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.detector.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.icecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.liquido.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.prometheus.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.easy_model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.RNN_tito.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.convnet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.dynedge.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.dynedge_jinst.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.dynedge_kaggle_tito.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.gnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.icemix.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.particlenet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.edges.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.edges.edges.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.edges.minkowski.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.graph_definition.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.graphs.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.nodes.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.nodes.nodes.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.utils.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.normalizing_flow.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.rnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.rnn.node_rnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.standard_averaged_model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.standard_model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.classification.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.reconstruction.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.task.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.transformer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.transformer.iseecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.utils.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.callbacks.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.labels.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.loss_functions.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.utils.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.weight_fitting.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.argparse.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.base_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.configurable.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.dataset_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.model_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.parsing.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.training_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.decorators.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.deprecation_tools.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.filesys.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.imports.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.logging.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.maths.htmlhttps://graphnet-team.github.io/graphnetapi/modules.htmlhttps://graphnet-team.github.io/graphnetcontribute/contribute.htmlhttps://graphnet-team.github.io/graphnetdata_conversion/data_conversion.htmlhttps://graphnet-team.github.io/graphnetdatasets/datasets.htmlhttps://graphnet-team.github.io/graphnetgetting_started/getting_started.htmlhttps://graphnet-team.github.io/graphnetindex.htmlhttps://graphnet-team.github.io/graphnetinstallation/install.htmlhttps://graphnet-team.github.io/graphnetintegration/integration.htmlhttps://graphnet-team.github.io/graphnetintro/intro.htmlhttps://graphnet-team.github.io/graphnetmodels/models.htmlhttps://graphnet-team.github.io/graphnetsubstitutions.htmlhttps://graphnet-team.github.io/graphnetgenindex.htmlhttps://graphnet-team.github.io/graphnetpy-modindex.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/constants.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/curated_datamodule.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataclasses.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataconverter.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataloader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/datamodule.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/parquet/parquet_dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/samplers.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/sqlite/sqlite_dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/combine_extractors.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3featureextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3genericextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3hybridrecoextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3ntmuonlabelsextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3particleextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3pisaextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3quesoextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3retroextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3splinempeextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3truthextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3tumextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/collections.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/frames.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/i3_filters.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/types.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/internal/parquet_extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/liquido/h5_extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/prometheus/prometheus_extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/parquet/deprecated_methods.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/pre_configured/dataconverters.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/graphnet_file_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/i3reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/internal_parquet_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/liquido_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/prometheus_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/sqlite/deprecated_methods.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/utilities/random.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/utilities/sqlite_utilities.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/utilities/string_selection_resolver.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/writers/graphnet_writer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/writers/parquet_writer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/writers/sqlite_writer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/datasets/prometheus_datasets.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/datasets/test_dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/deployer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/deployment_module.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/icecube/cleaning_module.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/icecube/inference_module.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/exceptions/exceptions.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/coarsening.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/components/embedding.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/components/layers.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/components/pool.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/detector.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/icecube.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/liquido.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/prometheus.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/easy_model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/RNN_tito.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/convnet.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/dynedge.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/dynedge_jinst.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/dynedge_kaggle_tito.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/gnn.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/icemix.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/particlenet.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/edges/edges.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/edges/minkowski.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/graph_definition.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/graphs.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/nodes/nodes.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/utils.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/normalizing_flow.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/rnn/node_rnn.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/standard_averaged_model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/standard_model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/task/classification.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/task/reconstruction.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/task/task.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/transformer/iseecube.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/utils.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/callbacks.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/labels.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/loss_functions.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/utils.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/weight_fitting.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/argparse.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/base_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/configurable.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/dataset_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/model_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/parsing.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/training_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/deprecation_tools.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/filesys.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/imports.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/logging.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/maths.htmlhttps://graphnet-team.github.io/graphnet_modules/index.htmlhttps://graphnet-team.github.io/graphnetsearch.html \ No newline at end of file +https://graphnet-team.github.io/graphnetabout/about.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.constants.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.constants.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.curated_datamodule.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataclasses.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataconverter.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataloader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.datamodule.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.parquet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.parquet.parquet_dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.samplers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.sqlite.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.dataset.sqlite.sqlite_dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.combine_extractors.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3featureextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3genericextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3hybridrecoextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3ntmuonlabelsextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3particleextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3pisaextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3quesoextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3retroextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3splinempeextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3truthextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.i3tumextractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.collections.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.frames.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.i3_filters.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.icecube.utilities.types.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.internal.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.internal.parquet_extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.liquido.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.liquido.h5_extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.prometheus.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.extractors.prometheus.prometheus_extractor.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.parquet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.parquet.deprecated_methods.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.pre_configured.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.pre_configured.dataconverters.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.graphnet_file_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.i3reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.internal_parquet_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.liquido_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.readers.prometheus_reader.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.sqlite.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.sqlite.deprecated_methods.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.parquet_to_sqlite.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.random.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.sqlite_utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.utilities.string_selection_resolver.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.graphnet_writer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.parquet_writer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.data.writers.sqlite_writer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.datasets.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.datasets.prometheus_datasets.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.datasets.test_dataset.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.deployer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.deployment_module.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.i3modules.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.i3modules.deprecated_methods.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.cleaning_module.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.i3deployer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.deployment.icecube.inference_module.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.exceptions.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.exceptions.exceptions.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.coarsening.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.embedding.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.layers.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.components.pool.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.detector.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.icecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.liquido.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.detector.prometheus.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.easy_model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.RNN_tito.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.convnet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.dynedge.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.dynedge_jinst.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.dynedge_kaggle_tito.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.gnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.icemix.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.gnn.particlenet.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.edges.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.edges.edges.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.edges.minkowski.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.graph_definition.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.graphs.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.nodes.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.nodes.nodes.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.graphs.utils.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.normalizing_flow.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.rnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.rnn.node_rnn.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.standard_averaged_model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.standard_model.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.classification.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.reconstruction.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.task.task.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.transformer.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.transformer.iseecube.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.models.utils.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.callbacks.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.labels.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.loss_functions.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.utils.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.training.weight_fitting.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.argparse.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.base_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.configurable.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.dataset_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.model_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.parsing.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.config.training_config.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.decorators.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.deprecation_tools.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.filesys.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.imports.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.logging.htmlhttps://graphnet-team.github.io/graphnetapi/graphnet.utilities.maths.htmlhttps://graphnet-team.github.io/graphnetapi/modules.htmlhttps://graphnet-team.github.io/graphnetcontribute/contribute.htmlhttps://graphnet-team.github.io/graphnetdata_conversion/data_conversion.htmlhttps://graphnet-team.github.io/graphnetdatasets/datasets.htmlhttps://graphnet-team.github.io/graphnetgetting_started/getting_started.htmlhttps://graphnet-team.github.io/graphnetindex.htmlhttps://graphnet-team.github.io/graphnetinstallation/install.htmlhttps://graphnet-team.github.io/graphnetintegration/integration.htmlhttps://graphnet-team.github.io/graphnetintro/intro.htmlhttps://graphnet-team.github.io/graphnetmodels/models.htmlhttps://graphnet-team.github.io/graphnetsubstitutions.htmlhttps://graphnet-team.github.io/graphnetgenindex.htmlhttps://graphnet-team.github.io/graphnetpy-modindex.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/constants.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/curated_datamodule.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataclasses.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataconverter.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataloader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/datamodule.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/parquet/parquet_dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/samplers.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/dataset/sqlite/sqlite_dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/combine_extractors.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3featureextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3genericextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3hybridrecoextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3ntmuonlabelsextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3particleextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3pisaextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3quesoextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3retroextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3splinempeextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3truthextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/i3tumextractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/collections.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/frames.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/i3_filters.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/icecube/utilities/types.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/internal/parquet_extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/liquido/h5_extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/extractors/prometheus/prometheus_extractor.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/parquet/deprecated_methods.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/pre_configured/dataconverters.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/graphnet_file_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/i3reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/internal_parquet_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/liquido_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/readers/prometheus_reader.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/sqlite/deprecated_methods.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/utilities/random.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/utilities/sqlite_utilities.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/utilities/string_selection_resolver.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/writers/graphnet_writer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/writers/parquet_writer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/data/writers/sqlite_writer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/datasets/prometheus_datasets.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/datasets/test_dataset.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/deployer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/deployment_module.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/i3modules/deprecated_methods.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/icecube/cleaning_module.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/icecube/i3deployer.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/deployment/icecube/inference_module.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/exceptions/exceptions.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/coarsening.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/components/embedding.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/components/layers.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/components/pool.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/detector.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/icecube.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/liquido.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/detector/prometheus.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/easy_model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/RNN_tito.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/convnet.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/dynedge.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/dynedge_jinst.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/dynedge_kaggle_tito.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/gnn.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/icemix.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/gnn/particlenet.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/edges/edges.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/edges/minkowski.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/graph_definition.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/graphs.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/nodes/nodes.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/graphs/utils.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/normalizing_flow.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/rnn/node_rnn.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/standard_averaged_model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/standard_model.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/task/classification.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/task/reconstruction.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/task/task.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/transformer/iseecube.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/models/utils.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/callbacks.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/labels.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/loss_functions.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/utils.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/training/weight_fitting.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/argparse.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/base_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/configurable.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/dataset_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/model_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/parsing.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/config/training_config.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/deprecation_tools.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/filesys.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/imports.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/logging.htmlhttps://graphnet-team.github.io/graphnet_modules/graphnet/utilities/maths.htmlhttps://graphnet-team.github.io/graphnet_modules/index.htmlhttps://graphnet-team.github.io/graphnetsearch.html \ No newline at end of file