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"sha256:16187aa2317c731170a88ef35e8937ae0f533c402872c1ee5e6d079fcf320801"}, ] [metadata] diff --git a/pyproject.toml b/pyproject.toml index 151b5eb..d4551a0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,8 @@ name = "eeg_research" version = "0.1.0" description = "All tools and pipelines developed for eeg research" -authors = ["Samuel Louviot "] +authors = ["Dr. Samuel Louviot ", +"Dr. Alp Erkent "] license = "LGPL-3.0" readme = "README.md" packages = [{include = "eeg_research", from = "src"}] diff --git a/src/eeg_research/io/__init__.py b/src/eeg_research/io/__init__.py new file mode 100644 index 0000000..0074603 --- /dev/null +++ b/src/eeg_research/io/__init__.py @@ -0,0 +1,2 @@ +from .xdf import read_raw_xdf, RawXDF +__all__ = ['read_raw_xdf', 'RawXDF'] \ No newline at end of file diff --git a/src/eeg_research/io/xdf.py b/src/eeg_research/io/xdf.py new file mode 100644 index 0000000..ecbebb2 --- /dev/null +++ b/src/eeg_research/io/xdf.py @@ -0,0 +1,78 @@ +from pathlib import Path +import numpy as np +import mne +import pyxdf + +def _parse_channel_names(eeg_stream: dict) -> dict: + chan_dict = eeg_stream['info']['desc'][0]['channels'][0]['channel'] + ch_names = list() + ch_types = list() + for chan in chan_dict: + ch_names.append(chan['label'][0]) + if chan['type'][0].lower() == 'marker': + ch_types.append('stim') + else: + ch_types.append(chan['type'][0].lower()) + + parsed_chan_info = { + "ch_names": ch_names, + "ch_types": ch_types, + } + + return parsed_chan_info + +#def _convert_signal(eeg_stream:dict) -> np.ndarray: +# units = { +# "microvolts": 10e-6, +# "millivolts": 10e-3, +# "volts": 1, +# } +# unit_matrix = list() +# chan_dict = eeg_stream['info']['desc'][0]['channels'][0]['channel'] +# signals = eeg_stream['time_series'].T +# unit_matrix = np.array([[units.get(chan['unit'][0].lower(),1) +# for chan in chan_dict]]).T +# return np.multiply(signals,unit_matrix) + +class RawXDF(mne.io.BaseRaw): + """Raw object from XDF file.""" + + def __init__(self, + input_fname, + preload=False, + *, + verbose=None, + ): + + eeg, _= pyxdf.load_xdf(input_fname, select_streams=5) + sfreq = float(eeg[0]['info']['nominal_srate'][0]) + info = mne.create_info(**_parse_channel_names(eeg[0]), sfreq=sfreq) + last_samps = int(eeg[0]['footer']['info']['sample_count'][0])-1 + chan_dict = eeg[0]['info']['desc'][0]['channels'][0]['channel'] + orig_units = {chan['label'][0]: "uv" if chan['unit'][0] == "microvolts" + else "n/a" for chan in chan_dict} + super().__init__( + info, + preload, + filenames=[input_fname], + last_samps=last_samps, + orig_format="int", + orig_units=orig_units, + verbose=verbose, + ) + self._data = eeg[0]['time_series'].T + +def read_raw_xdf(filename, **kwargs): + """Read XDF file. + + Args: + filename : str | Path + Path to XDF file. + **kwargs : dict + Additional keyword arguments passed to RawXDF. + + Returns + raw : RawXDF + Raw object containing XDF data. + """ + return RawXDF(filename, **kwargs) \ No newline at end of file diff --git a/src/eeg_research/system/bids_selector.py b/src/eeg_research/system/bids_selector.py index aa9a01f..384ca70 100644 --- a/src/eeg_research/system/bids_selector.py +++ b/src/eeg_research/system/bids_selector.py @@ -7,195 +7,527 @@ as individual modality. The workaround is to either do a monkey patching to the packages by forcing it to allow such datatype or write from scratch a separate class that would be less strict. -The monkey patching is not very pythonic and is not recommended in the dev community -Because of the side effect that can induce. Therefore I am on the road to -write another 'bids-like' data handler (also simplier) from scratch. -This will be useful for everybody dealing with pseudo BIDS layout with the -possibility to customize the queries. +The monkey patching is not very pythonic and it is usually a bad practice +because of the side effect that can induce. Therefore here is a 'bids-like' data +handler (also simplier) which will be useful for everybody dealing with pseudo +BIDS layout with the possibility to customize the queries. + +The main class to use is `BidsArchitecture` which give the architecture +(the layout, the structure) of the desired dataset for a specific query. """ +import copy import os from dataclasses import dataclass -from functools import reduce +from functools import cached_property, reduce from pathlib import Path +from typing import Any, Dict, Iterator, List, Optional, Union from warnings import warn -from functools import cached_property +import re import pandas as pd -@dataclass -class BasePath: - root: Path | None = None - subject: str | None = None - session: str | None = None - datatype: str | None = None - task: str | None = None - acquisition: str | None = None - run: str | None = None - description: str | None = None - suffix: str | None = None - extension: str | None = None - - def __post_init__(self): - if self.extension and "." not in self.extension: - self.extension = "." + self.extension - def __str__(self): - string_list = [] - for attribute, value in self.__dict__.items(): - if not "_" in attribute: - string_list.append(f"{attribute}: {value}") - - return "\n".join(string_list) - - def _make_path(self, absolute=True): - relative_path = Path( - os.path.join( - f"sub-{self.subject}", - f"ses-{self.session}", - self.datatype, - ) - ) - if absolute and getattr(self,"root", False): - return self.root / relative_path - else: - return relative_path - - def _make_basename(self): - fname_elem = [ - f"sub-{self.subject}", - f"ses-{self.session}", - f"task-{self.task}", - self.suffix, - ] - if self.description: - fname_elem.insert(3, f"desc-{self.description}") - if self.run: - fname_elem.insert(3, f"run-{self.run}") - if self.acquisition: - fname_elem.insert(3, f"acq-{self.acquisition}") +class BidsValidationError(Exception): + pass + +def set_errors(object, value: pd.DataFrame): + if hasattr(object, 'errors'): + delattr(object, 'errors') + if hasattr(object, '_errors'): + delattr(object, '_errors') + + setattr(object, '_errors', value) + +def set_database(object, value: pd.DataFrame): + if hasattr(object, 'database'): + delattr(object, 'database') + if hasattr(object, '_database'): + delattr(object, '_database') + + setattr(object, '_database', value) + +def merge_error_logs(self, other): + """Merge error logs efficiently.""" + if self._errors.empty and other._errors.empty: + return self._errors + + return pd.concat([ + self._errors, + other._errors.loc[~other._errors.index.isin(self._errors.index)] + ], copy=False) + +def is_all_columns_valid(database: pd.DataFrame) -> bool: + valid_columns = { + 'root', + 'subject', + 'session', + 'datatype', + 'task', + 'run', + 'acquisition', + 'description', + 'suffix', + 'extension', + 'atime', + 'mtime', + 'ctime', + 'filename' + } + database_columns = set(database.columns) + return valid_columns.issubset(database_columns) + +def has_all_filenames_valid(database: pd.DataFrame) -> bool: + return database['filename'].apply(validate_bids_file).all() + +def purify_database(database: pd.DataFrame) -> pd.DataFrame: + return database[database['filename'].apply(validate_bids_file)] + +def get_invalid_columns(database: pd.DataFrame) -> List[str]: + valid_columns = { + 'root', + 'subject', + 'session', + 'datatype', + 'task', + 'run', + 'acquisition', + 'description', + 'suffix', + 'extension', + 'atime', + 'mtime', + 'ctime', + 'filename' + } + database_columns = set(database.columns) + return list(database_columns - valid_columns) + +def get_invalid_filenames(database: pd.DataFrame) -> List[str]: + return database[~database['filename'].apply(validate_bids_file)] + + +def prepare_for_operations(object1, object2): + """Prepare objects for set operations and validate them.""" + conditions = ( + isinstance(object1, BidsArchitecture), + isinstance(object1, pd.DataFrame), + isinstance(object1, set), + isinstance(object2, BidsArchitecture), + isinstance(object2, pd.DataFrame), + isinstance(object2, set), + ) + if not any(conditions): + raise ValueError(f"Can't perform with {object1.__class__.__name__} and" + f" {object2.__class__.__name__}") + + if isinstance(object2, pd.DataFrame): + return object2.index + elif isinstance(object2, BidsArchitecture): + if not is_all_columns_valid(object2._database): + raise ValueError(f"{object2.__class__.__name__} has invalid columns: " + f"{get_invalid_columns(object2._database)}") - fname_elem = [elem for elem in fname_elem if elem is not None] + if not has_all_filenames_valid(object2._database): + raise ValueError(f"{object2.__class__.__name__} has invalid filenames: " + f"{get_invalid_filenames(object2._database)}") + + return object2._database.index + return object2 # If it's already a set - return "_".join(fname_elem) +def validate_bids_file(file: Path) -> bool: + """Validate the BIDS filename and pathname. + + Args: + file: Path to validate + + Returns: + bool: True if validation passes + + Raises: + BidsValidationError: If validation fails + """ + valid_keys = {"sub", + "ses", + "task", + "acq", + "run", + "recording", + "desc", + "space"} + + valid_datatype_pattern = re.compile(r"^[a-z0-9]+$") + key_value_pattern = re.compile(r"(?P[a-zA-Z0-9]+)-(?P[a-zA-Z0-9]+)") + path_pattern = re.compile(r"(sub|ses)-[\w\d]+") + + errors = [] + + filename = os.fspath(file.name) if file.suffix else None + if filename: + bids_path_parts = file.parent.parts[-3:] + + conditions = ( + bids_path_parts[0].startswith("sub"), + bids_path_parts[2].startswith("ses"), + "-" in bids_path_parts[0], + "-" in bids_path_parts[2], + ) + if not any(conditions): + raise BidsValidationError( + "Path does not contain valid BIDS elements (e.g., 'sub-*')." + "Should be in the form of" + "'root/sub-