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src/obnb/__init__.py

@@ -1,4 +1,5 @@
 """Collection of network learning evaluation utilities."""
+
 from obnb import graph, label, model_trainer
 from obnb.dataset import Dataset, OpenBiomedNetBench
 from obnb.util.checkers import checkVersion

src/obnb/config/__init__.py

@@ -1,4 +1,5 @@
 """Configurations used by obnb."""
+
 from obnb.typing import Dict
 
 __all__ = [

src/obnb/data/__init__.py

@@ -1,4 +1,5 @@
 """Interface with various databases to retrieve data."""
+
 from obnb.data import annotated_ontology, annotation, network, ontology
 from obnb.data.annotated_ontology import (
     DISEASES,

src/obnb/data/annotated_ontology/__init__.py

@@ -1,4 +1,5 @@
 """Annotated ontology data."""
+
 from obnb.data.annotated_ontology.diseases import (
     DISEASES,
     DISEASES_ExperimentsFiltered,

src/obnb/data/annotation/__init__.py

@@ -1,4 +1,5 @@
 """Annotation data."""
+
 from obnb.data.annotation.diseases import DISEASESAnnotation
 from obnb.data.annotation.disgenet import DisGeNETAnnotation
 from obnb.data.annotation.gene_ontology import GeneOntologyAnnotation

src/obnb/data/experimental/__init__.py

@@ -8,6 +8,7 @@
     versions of the package.
 
 """
+
 from obnb.data.experimental.alevinfry import AlevinFry
 
 __all__ = [

src/obnb/data/network/__init__.py

@@ -1,4 +1,5 @@
 """Network data."""
+
 from obnb.data.network.biogrid import BioGRID
 from obnb.data.network.bioplex import BioPlex
 from obnb.data.network.comppi import ComPPIHumanInt

src/obnb/data/ontology/__init__.py

@@ -1,4 +1,5 @@
 """Ontology data."""
+
 from obnb.data.ontology.gene_ontology import GeneOntology
 from obnb.data.ontology.mondo import MondoDiseaseOntology
 

src/obnb/dataset/__init__.py

@@ -1,4 +1,5 @@
 """Dataset objects."""
+
 from obnb.dataset.base import Dataset
 from obnb.dataset.dataset import OpenBiomedNetBench
 from obnb.dataset.dataset_dgl import OpenBiomedNetBenchDGL

src/obnb/dataset/base.py

@@ -1,4 +1,5 @@
 """Dataset object."""
+
 import numpy as np
 from sklearn.preprocessing import KBinsDiscretizer
 

src/obnb/dataset/dataset.py

@@ -1,4 +1,5 @@
 """Helper functions to construct processed datasets."""
+
 import obnb.data
 import obnb.label.split
 from obnb.dataset.base import Dataset

src/obnb/dataset/dataset_dgl.py

@@ -1,4 +1,5 @@
 """DGL dataset object."""
+
 import os.path as osp
 
 try:

src/obnb/dataset/dataset_pyg.py

@@ -1,4 +1,5 @@
 """PyTorch Geometric dataset object."""
+
 import os.path as osp
 
 try:

src/obnb/ext/attnwalk.py

@@ -11,6 +11,7 @@
 }
 
 """
+
 from typing import Union
 
 import networkx as nx

src/obnb/ext/orbital_features.py

@@ -1,4 +1,5 @@
 """Grpahlet orbital feature extraction."""
+
 import itertools
 import multiprocessing
 from functools import partial

src/obnb/feature/__init__.py

@@ -1,4 +1,5 @@
 """Feature objects."""
+
 from obnb.feature.multifeat import MultiFeatureVec
 from obnb.feature.singlefeat import FeatureVec
 

src/obnb/feature/multifeat.py

@@ -1,4 +1,5 @@
 """Multi modality feature objects."""
+
 from itertools import chain
 
 import numpy as np

src/obnb/feature/singlefeat.py

@@ -1,4 +1,5 @@
 """Single modality feature objects."""
+
 import numpy as np
 
 from obnb.feature.base import BaseFeature

src/obnb/graph/__init__.py

@@ -1,4 +1,5 @@
 """Graph and feature vector objects."""
+
 from obnb.graph.dense import DenseGraph
 from obnb.graph.ontology import OntologyGraph
 from obnb.graph.sparse import DirectedSparseGraph, SparseGraph

src/obnb/label/__init__.py

@@ -1,4 +1,5 @@
 """Labelset collection with splitting and filtering utilities."""
+
 from obnb.label import filters, split
 from obnb.label.collection import LabelsetCollection
 

src/obnb/label/filters/__init__.py

@@ -1,4 +1,5 @@
 """Filter objecst for preprocessing the labelset collection."""
+
 from obnb.label.filters.base import Compose
 from obnb.label.filters.existence_filter import (
     EntityExistenceFilter,

src/obnb/label/filters/range_filter.py

@@ -164,7 +164,7 @@ def get_val_getter(self, lsc):
         def val_getter(label_id):
             y_all, masks = lsc.split(self.splitter, **self.kwargs)
             neg_idx = lsc.entity[lsc.get_negative(label_id)]
-            self.logger.debug(f"{label_id = } {neg_idx = }")
+            self.logger.debug(f"{label_id =} {neg_idx =}")
             # TODO: make label_ids to index mapping?
             y = y_all[:, lsc.label_ids.index(label_id)]
             min_num_pos = min_num_neg = np.inf
@@ -175,7 +175,7 @@ def val_getter(label_id):
                     min_num_pos = min(min_num_pos, num_pos)
                     if self.count_negatives:
                         num_neg = np.intersect1d(neg_idx, masked_idx).size
-                        self.logger.debug(f"{num_neg = }, {masked_idx = }")
+                        self.logger.debug(f"{num_neg =}, {masked_idx =}")
                         min_num_neg = min(min_num_neg, num_neg)
             self.logger.info(f"{label_id}, {min_num_pos=}, {min_num_neg=}")
             return min(min_num_pos, min_num_neg)

src/obnb/label/split/__init__.py

@@ -1,4 +1,5 @@
 """Genearting data splits from the labelset collection."""
+
 from obnb.label.split.holdout import (
     AllHoldout,
     RandomRatioHoldout,

src/obnb/metric/__init__.py

@@ -1,4 +1,5 @@
 """Metric functions used for evaluation."""
+
 from obnb.metric.standard import auroc, log2_auprc_prior, precision_at_topk
 
 __all__ = [

src/obnb/metric/graphgym_metric.py

@@ -1,4 +1,5 @@
 """Custom metrics compatible with GraphGym logger."""
+
 from functools import wraps
 
 import torch

src/obnb/metric/standard.py

@@ -1,4 +1,5 @@
 """Standard metric extending those available in sklearn."""
+
 from functools import wraps
 
 try:

src/obnb/model_trainer/__init__.py

@@ -1,4 +1,5 @@
 """Unified framework for training different types of models."""
+
 from obnb.model_trainer.label_propagation import LabelPropagationTrainer
 from obnb.model_trainer.supervised_learning import (
     MultiSupervisedLearningTrainer,

src/obnb/registry.py

@@ -3,6 +3,7 @@
 Helps interface with user defined modules for OBNB pipelines.
 
 """
+
 from obnb.typing import Any
 from obnb.util.misc import DotDict
 

src/obnb/transform/base.py

@@ -33,5 +33,4 @@ def fullname(self) -> str:
 
 class BaseDatasetTransform(BaseTransform, ABC):
     @abstractmethod
-    def __call__(self, dataset):
-        ...
+    def __call__(self, dataset): ...

src/obnb/transform/node_feature.py

@@ -1,4 +1,5 @@
 """Node feature transformation module."""
+
 import warnings
 from abc import ABC, abstractmethod
 
@@ -50,8 +51,7 @@ def __call__(self, dataset):
             dataset.feature = FeatureVec.from_mat(feat, node_ids)
 
     @abstractmethod
-    def _prepare_feat(self, dataset) -> np.ndarray:
-        ...
+    def _prepare_feat(self, dataset) -> np.ndarray: ...
 
 
 @register_nodefeat

src/obnb/typing.py

@@ -1,4 +1,5 @@
 """Collection of types used in obnb."""
+
 from typing import (
     Any,
     Callable,

src/obnb/util/checkers.py

@@ -4,6 +4,7 @@
 a function call is valid.
 
 """
+
 import os
 import warnings
 from typing import get_args

src/obnb/util/cx_explorer.py

@@ -1,4 +1,5 @@
 """Utility for exploring NDEx CX data."""
+
 import itertools
 import json
 from collections import defaultdict

src/obnb/util/logger.py

@@ -1,4 +1,5 @@
 """Logger utils."""
+
 import logging
 import logging.config
 import os

src/obnb/util/path.py

@@ -1,4 +1,5 @@
 """Path utilities."""
+
 import hashlib
 import os.path as osp
 

src/obnb/util/version.py

@@ -1,4 +1,5 @@
 """Version utility module for obnb."""
+
 from obnb import config
 from obnb.typing import List