Formatcode for linting

Makefile

@@ -36,7 +36,7 @@ fmt:              ## Format code using black & isort.
 lint:             ## Run pep8, black, mypy linters.
 	@echo "Run scMusketeers linting"
 	$(ENV_PREFIX)poetry run flake8 scmusketeers/
-	$(ENV_PREFIX)poetry run black -l 79 --check scmusketeers/ tests/
+	$(ENV_PREFIX)poetry run black -l 100 --check scmusketeers/ tests/
 	$(ENV_PREFIX)poetry run mypy --ignore-missing-imports scmusketeers/ tests/
 
 .PHONY: test

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "sc-musketeers"
-version = "0.3.3"
+version = "0.3.4"
 description = "A tri-partite modular autoencoder for addressing imbalanced cell type annotation and batch effect reduction"
 license = "MIT"
 authors = ["AntoineCollin","Christophe Becavin"]

scmusketeers/__init__.py

@@ -1 +1 @@
-from . import tools, arguments, transfer
+from . import arguments, tools, transfer

scmusketeers/__main__.py

@@ -1,7 +1,6 @@
+from scmusketeers.arguments.runfile import get_runfile
 from scmusketeers.run_musk import run_sc_musketeers
-from scmusketeers.arguments.runfile import (
-    get_runfile,
-)
+
 
 def main_entry_point():
     # Get all arguments

scmusketeers/arguments/class_param.py

@@ -1,5 +1,6 @@
 from scmusketeers.tools.utils import str2bool
 
+
 class CLASS_PARAM:
 
     class_hidden_size = [64]

scmusketeers/run_musk.py

@@ -3,16 +3,10 @@
 
 from ax.service.ax_client import AxClient, ObjectiveProperties
 
-from scmusketeers.arguments.neptune_log import (
-    start_neptune_log,
-    stop_neptune_log,
-)
-from scmusketeers.arguments.runfile import (
-    PROCESS_TYPE,
-    create_argparser,
-    get_runfile,
-    get_default_param
-)
+from scmusketeers.arguments.neptune_log import (start_neptune_log,
+                                                stop_neptune_log)
+from scmusketeers.arguments.runfile import (PROCESS_TYPE, create_argparser,
+                                            get_default_param, get_runfile)
 from scmusketeers.transfer.experiment import MakeExperiment
 from scmusketeers.transfer.optimize_model import Workflow
 

scmusketeers/tools/clust_compute.py

@@ -5,7 +5,6 @@
 import pandas as pd
 from anndata import AnnData
 from sklearn.metrics import *
-
 # from sklearn.metrics import confusion_matrix, balanced_accuracy_score, accuracy_score,silhouette_samples,f1_score,matthews_corrcoef,cohen_kappa_score
 from sklearn.neighbors import NearestNeighbors
 from sklearn.preprocessing import LabelEncoder

scmusketeers/tools/layers.py

@@ -6,7 +6,6 @@
 # from keras.engine.base_layer import InputSpec
 import keras.backend as K
 import tensorflow as tf
-
 # from keras.engine.topology import Layer
 from keras.layers import Dense, Lambda
 

scmusketeers/transfer/experiment.py

@@ -1,11 +1,8 @@
 import neptune
 import pandas as pd
 
-from ..arguments.neptune_log import (
-    add_custom_log,
-    start_neptune_log,
-    stop_neptune_log,
-)
+from ..arguments.neptune_log import (add_custom_log, start_neptune_log,
+                                     stop_neptune_log)
 from ..arguments.runfile import set_hyperparameters
 from . import dataset_tf
 from .optimize_model import Workflow

scmusketeers/transfer/optimize_model.py

@@ -24,18 +24,11 @@
     from . import freeze
 
 import keras
-from sklearn.metrics import (
-    accuracy_score,
-    adjusted_mutual_info_score,
-    adjusted_rand_score,
-    balanced_accuracy_score,
-    cohen_kappa_score,
-    confusion_matrix,
-    davies_bouldin_score,
-    f1_score,
-    matthews_corrcoef,
-    normalized_mutual_info_score,
-)
+from sklearn.metrics import (accuracy_score, adjusted_mutual_info_score,
+                             adjusted_rand_score, balanced_accuracy_score,
+                             cohen_kappa_score, confusion_matrix,
+                             davies_bouldin_score, f1_score, matthews_corrcoef,
+                             normalized_mutual_info_score)
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.utils import compute_class_weight
 
@@ -53,32 +46,22 @@
     from transfer.dataset_tf import Dataset, load_dataset
 
 try:
-    from ..tools.clust_compute import (
-        balanced_cohen_kappa_score,
-        balanced_f1_score,
-        balanced_matthews_corrcoef,
-        batch_entropy_mixing_score,
-        lisi_avg,
-        nn_overlap,
-    )
+    from ..tools.clust_compute import (balanced_cohen_kappa_score,
+                                       balanced_f1_score,
+                                       balanced_matthews_corrcoef,
+                                       batch_entropy_mixing_score, lisi_avg,
+                                       nn_overlap)
     from ..tools.models import DANN_AE
     from ..tools.permutation import batch_generator_training_permuted
-    from ..tools.utils import (
-        default_value,
-        nan_to_0,
-        scanpy_to_input,
-        str2bool,
-    )
+    from ..tools.utils import (default_value, nan_to_0, scanpy_to_input,
+                               str2bool)
 
 except ImportError:
-    from tools.clust_compute import (
-        balanced_cohen_kappa_score,
-        balanced_f1_score,
-        balanced_matthews_corrcoef,
-        batch_entropy_mixing_score,
-        lisi_avg,
-        nn_overlap,
-    )
+    from tools.clust_compute import (balanced_cohen_kappa_score,
+                                     balanced_f1_score,
+                                     balanced_matthews_corrcoef,
+                                     batch_entropy_mixing_score, lisi_avg,
+                                     nn_overlap)
     from tools.models import DANN_AE
     from tools.permutation import batch_generator_training_permuted
     from tools.utils import default_value, nan_to_0, scanpy_to_input, str2bool
@@ -100,7 +83,6 @@
 import seaborn as sns
 import tensorflow as tf
 from ax.service.managed_loop import optimize
-
 # from numba import cuda
 from neptune.utils import stringify_unsupported
 

scmusketeers/workflow/__init__.py

@@ -1 +1 @@
-from . import benchmark_models, benchmark, dataset, hyperparameters
+from . import benchmark, benchmark_models, dataset, hyperparameters

scmusketeers/workflow/benchmark.py

@@ -18,40 +18,22 @@
 sys.path.insert(1, os.path.join(sys.path[0], ".."))
 
 try:
-    from .benchmark_models import (
-        celltypist_model,
-        harmony_svm,
-        pca_knn,
-        pca_svm,
-        scanvi,
-        scBalance_model,
-        scmap_cells,
-        scmap_cluster,
-        uce,
-    )
+    from .benchmark_models import (celltypist_model, harmony_svm, pca_knn,
+                                   pca_svm, scanvi, scBalance_model,
+                                   scmap_cells, scmap_cluster, uce)
     from .dataset import Dataset, load_dataset
 except ImportError:
-    from workflow.benchmark_models import (
-        celltypist_model,
-        harmony_svm,
-        pca_svm,
-        scanvi,
-        scBalance_model,
-        scmap_cells,
-        scmap_cluster,
-        uce,
-    )
+    from workflow.benchmark_models import (celltypist_model, harmony_svm,
+                                           pca_svm, scanvi, scBalance_model,
+                                           scmap_cells, scmap_cluster, uce)
     from workflow.dataset import Dataset, load_dataset
 
 try:
-    from ..tools.clust_compute import (
-        balanced_cohen_kappa_score,
-        balanced_f1_score,
-        balanced_matthews_corrcoef,
-        batch_entropy_mixing_score,
-        lisi_avg,
-        nn_overlap,
-    )
+    from ..tools.clust_compute import (balanced_cohen_kappa_score,
+                                       balanced_f1_score,
+                                       balanced_matthews_corrcoef,
+                                       batch_entropy_mixing_score, lisi_avg,
+                                       nn_overlap)
     from ..tools.utils import nan_to_0, str2bool
 except ImportError:
     from tools.utils import str2bool
@@ -64,18 +46,11 @@
         balanced_cohen_kappa_score,
     )
 
-from sklearn.metrics import (
-    accuracy_score,
-    adjusted_mutual_info_score,
-    adjusted_rand_score,
-    balanced_accuracy_score,
-    cohen_kappa_score,
-    confusion_matrix,
-    davies_bouldin_score,
-    f1_score,
-    matthews_corrcoef,
-    normalized_mutual_info_score,
-)
+from sklearn.metrics import (accuracy_score, adjusted_mutual_info_score,
+                             adjusted_rand_score, balanced_accuracy_score,
+                             cohen_kappa_score, confusion_matrix,
+                             davies_bouldin_score, f1_score, matthews_corrcoef,
+                             normalized_mutual_info_score)
 from sklearn.model_selection import GroupKFold
 
 f1_score = functools.partial(f1_score, average="macro")
@@ -90,7 +65,6 @@
 import pandas as pd
 import scanpy as sc
 import seaborn as sns
-
 # from numba import cuda
 from neptune.utils import stringify_unsupported
 

scmusketeers/workflow/benchmark_models.py

@@ -6,12 +6,12 @@
 from sklearn.neighbors import KNeighborsClassifier
 
 try:
+    import celltypist
     import scanpy.external as sce
-    from scmappy import common_genes, scmap_annotate
     import scBalance as sb
     import scBalance.scbalance_IO as ss
-    import celltypist
     import scvi
+    from scmappy import common_genes, scmap_annotate
 except:
     pass
 import numpy as np

scmusketeers/workflow/hyperparameters.py

@@ -9,18 +9,11 @@
 import sys
 
 import keras
-from sklearn.metrics import (
-    accuracy_score,
-    adjusted_mutual_info_score,
-    adjusted_rand_score,
-    balanced_accuracy_score,
-    cohen_kappa_score,
-    confusion_matrix,
-    davies_bouldin_score,
-    f1_score,
-    matthews_corrcoef,
-    normalized_mutual_info_score,
-)
+from sklearn.metrics import (accuracy_score, adjusted_mutual_info_score,
+                             adjusted_rand_score, balanced_accuracy_score,
+                             cohen_kappa_score, confusion_matrix,
+                             davies_bouldin_score, f1_score, matthews_corrcoef,
+                             normalized_mutual_info_score)
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.utils import compute_class_weight
 
@@ -38,42 +31,26 @@
     from workflow.dataset import Dataset, load_dataset
 
 try:
-    from ..tools.clust_compute import (
-        balanced_cohen_kappa_score,
-        balanced_f1_score,
-        balanced_matthews_corrcoef,
-        batch_entropy_mixing_score,
-        lisi_avg,
-        nn_overlap,
-    )
+    from ..tools.clust_compute import (balanced_cohen_kappa_score,
+                                       balanced_f1_score,
+                                       balanced_matthews_corrcoef,
+                                       batch_entropy_mixing_score, lisi_avg,
+                                       nn_overlap)
     from ..tools.models import DANN_AE
     from ..tools.permutation import batch_generator_training_permuted
-    from ..tools.utils import (
-        check_dir,
-        default_value,
-        nan_to_0,
-        scanpy_to_input,
-        str2bool,
-    )
+    from ..tools.utils import (check_dir, default_value, nan_to_0,
+                               scanpy_to_input, str2bool)
 
 except ImportError:
-    from tools.clust_compute import (
-        balanced_cohen_kappa_score,
-        balanced_f1_score,
-        balanced_matthews_corrcoef,
-        batch_entropy_mixing_score,
-        lisi_avg,
-        nn_overlap,
-    )
+    from tools.clust_compute import (balanced_cohen_kappa_score,
+                                     balanced_f1_score,
+                                     balanced_matthews_corrcoef,
+                                     batch_entropy_mixing_score, lisi_avg,
+                                     nn_overlap)
     from tools.models import DANN_AE
     from tools.permutation import batch_generator_training_permuted
-    from tools.utils import (
-        check_dir,
-        default_value,
-        nan_to_0,
-        scanpy_to_input,
-        str2bool,
-    )
+    from tools.utils import (check_dir, default_value, nan_to_0,
+                             scanpy_to_input, str2bool)
 
 
 f1_score = functools.partial(f1_score, average="macro")
@@ -92,7 +69,6 @@
 import seaborn as sns
 import tensorflow as tf
 from ax.service.managed_loop import optimize
-
 # from numba import cuda
 from neptune.utils import stringify_unsupported