isort import linting

ms2deepscore/MS2DeepScore.py

@@ -1,12 +1,12 @@
 from typing import List
+
 import numpy as np
 from matchms import Spectrum
 from matchms.similarity.BaseSimilarity import BaseSimilarity
 from tqdm import tqdm
 
-from .vector_operations import cosine_similarity
-from .vector_operations import cosine_similarity_matrix
 from .typing import BinnedSpectrumType
+from .vector_operations import cosine_similarity, cosine_similarity_matrix
 
 
 class MS2DeepScore(BaseSimilarity):

ms2deepscore/MS2DeepScoreMonteCarlo.py

@@ -1,13 +1,13 @@
 from typing import List, Tuple
+
 import numpy as np
 from matchms import Spectrum
 from matchms.similarity.BaseSimilarity import BaseSimilarity
 from tqdm import tqdm
 
-from .vector_operations import cosine_similarity_matrix
-from .vector_operations import mean_pooling, median_pooling
-from .vector_operations import std_pooling, iqr_pooling
 from .typing import BinnedSpectrumType
+from .vector_operations import (cosine_similarity_matrix, iqr_pooling,
+                                mean_pooling, median_pooling, std_pooling)
 
 
 class MS2DeepScoreMonteCarlo(BaseSimilarity):

ms2deepscore/MetadataFeatureGenerator.py

@@ -1,7 +1,8 @@
-from typing import List, Union
-from matchms import Metadata
 import json
 from importlib import import_module
+from typing import List, Union
+
+from matchms import Metadata
 
 
 class MetadataFeatureGenerator:

ms2deepscore/SpectrumBinner.py

@@ -1,15 +1,17 @@
 import json
 from typing import List, Tuple
-from tqdm import tqdm
+
 from matchms.typing import SpectrumType
+from tqdm import tqdm
+
+from ms2deepscore.MetadataFeatureGenerator import (MetadataFeatureGenerator,
+                                                   load_from_json)
 
 from .BinnedSpectrum import BinnedSpectrum
+from .spectrum_binning_fixed import (create_peak_list_fixed, set_d_bins_fixed,
+                                     unique_peaks_fixed)
 from .typing import BinnedSpectrumType
-from .spectrum_binning_fixed import create_peak_list_fixed
-from .spectrum_binning_fixed import set_d_bins_fixed
-from .spectrum_binning_fixed import unique_peaks_fixed
 from .utils import create_peak_dict
-from ms2deepscore.MetadataFeatureGenerator import MetadataFeatureGenerator, load_from_json
 
 
 class SpectrumBinner:

ms2deepscore/__init__.py

@@ -1,12 +1,12 @@
 import logging
+
 from . import models
 from .__version__ import __version__
 from .BinnedSpectrum import BinnedSpectrum
 from .MS2DeepScore import MS2DeepScore
 from .MS2DeepScoreMonteCarlo import MS2DeepScoreMonteCarlo
 from .SpectrumBinner import SpectrumBinner
 
-
 logging.getLogger(__name__).addHandler(logging.NullHandler())
 
 __author__ = "Netherlands eScience Center"

ms2deepscore/data_generators.py

@@ -1,13 +1,14 @@
 """ Data generators for training/inference with siamese Keras model.
 """
 import warnings
-from typing import List, Iterator, NamedTuple, Optional
+from typing import Iterator, List, NamedTuple, Optional
 
 import numpy as np
 import pandas as pd
 from tensorflow.keras.utils import Sequence  # pylint: disable=import-error
 
 from ms2deepscore.SpectrumBinner import SpectrumBinner
+
 from .typing import BinnedSpectrumType
 
 

ms2deepscore/models/SiameseModel.py

@@ -1,8 +1,10 @@
 from pathlib import Path
 from typing import Tuple, Union
+
 import h5py
 from tensorflow import keras
-from tensorflow.keras.layers import BatchNormalization, Dense, Dropout, Input, concatenate  # pylint: disable=import-error
+from tensorflow.keras.layers import (  # pylint: disable=import-error
+    BatchNormalization, Dense, Dropout, Input, concatenate)
 
 from ms2deepscore import SpectrumBinner
 

ms2deepscore/models/load_model.py

@@ -1,9 +1,11 @@
 from pathlib import Path
 from typing import Union
+
 import h5py
 from tensorflow import keras
 
 from ms2deepscore.SpectrumBinner import SpectrumBinner
+
 from .SiameseModel import SiameseModel
 
 

ms2deepscore/spectrum_binning_fixed.py

@@ -1,9 +1,10 @@
 """ Functions to create binned vector from spectrum using fixed width bins.
 """
 from typing import List
+
 import numpy as np
-from tqdm import tqdm
 from matchms import Spectrum
+from tqdm import tqdm
 
 
 def create_peak_list_fixed(spectrums, peaks_vocab, d_bins,

ms2deepscore/spectrum_pair_selection.py

@@ -1,7 +1,7 @@
 import numba
 import numpy as np
-from scipy.sparse import lil_array, coo_array
 from matchms.similarity.vector_similarity_functions import jaccard_index
+from scipy.sparse import coo_array, lil_array
 
 
 def jaccard_similarity_matrix_cherrypicking(

ms2deepscore/train_new_model/calculate_tanimoto_matrix.py

@@ -5,11 +5,11 @@
 from collections import Counter
 from typing import List
 
+import numpy as np
 import pandas as pd
 from matchms import Spectrum
-import numpy as np
-
-from matchms.similarity.vector_similarity_functions import jaccard_similarity_matrix
+from matchms.similarity.vector_similarity_functions import \
+    jaccard_similarity_matrix
 from rdkit import Chem
 from tqdm import tqdm
 

ms2deepscore/train_new_model/train_ms2deepscore.py

@@ -4,22 +4,21 @@
 
 import os
 from os import PathLike
-from typing import List, Dict, Optional, Union
+from typing import Dict, List, Optional, Union
+
 import numpy as np
 import tensorflow as tf
-from matplotlib import pyplot as plt
 from matchms import Spectrum
+from matplotlib import pyplot as plt
+
 from ms2deepscore import SpectrumBinner
 from ms2deepscore.data_generators import DataGeneratorAllInchikeys
 from ms2deepscore.models import SiameseModel
-from ms2deepscore.train_new_model.calculate_tanimoto_matrix import (
-    calculate_tanimoto_scores_unique_inchikey,
-)
-from ms2deepscore.utils import (
-    save_pickled_file,
-    return_non_existing_file_name,
-    load_pickled_file,
-)
+from ms2deepscore.train_new_model.calculate_tanimoto_matrix import \
+    calculate_tanimoto_scores_unique_inchikey
+from ms2deepscore.utils import (load_pickled_file,
+                                return_non_existing_file_name,
+                                save_pickled_file)
 
 
 def bin_spectra(

ms2deepscore/train_new_model/validation_and_test_split.py

@@ -1,9 +1,11 @@
 import os
+import random
 from typing import List, Tuple
+
 from matchms import Spectrum
-import random
 from tqdm import tqdm
-from ms2deepscore.utils import save_pickled_file, load_pickled_file
+
+from ms2deepscore.utils import load_pickled_file, save_pickled_file
 
 
 def select_unique_inchikeys(spectra):

ms2deepscore/train_new_model/visualize_results.py

@@ -1,10 +1,12 @@
 import os
+
 import numpy as np
 from matplotlib import pyplot as plt
-from ms2deepscore.models import load_model
-from ms2deepscore.utils import load_pickled_file, save_pickled_file
+
 from ms2deepscore import MS2DeepScore
+from ms2deepscore.models import load_model
 from ms2deepscore.plotting import create_histograms_plot
+from ms2deepscore.utils import load_pickled_file, save_pickled_file
 
 
 def get_tanimoto_indexes(tanimoto_df, spectra):

ms2deepscore/typing.py

@@ -1,4 +1,5 @@
 from typing import Optional
+
 from .BinnedSpectrum import BinnedSpectrum
 
 BinnedSpectrumType = Optional[BinnedSpectrum]

setup.py

@@ -1,8 +1,7 @@
 #!/usr/bin/env python
 import os
 
-from setuptools import setup
-from setuptools import find_packages
+from setuptools import find_packages, setup
 
 here = os.path.abspath(os.path.dirname(__file__))
 

tests/test_MetadataFeatureGenerator.py

@@ -1,12 +1,10 @@
 import pytest
 from matchms import Metadata
-from ms2deepscore.MetadataFeatureGenerator import (
-    MetadataFeatureGenerator,
-    StandardScaler,
-    OneHotEncoder,
-    CategoricalToBinary,
-    )
 
+from ms2deepscore.MetadataFeatureGenerator import (CategoricalToBinary,
+                                                   MetadataFeatureGenerator,
+                                                   OneHotEncoder,
+                                                   StandardScaler)
 
 
 @pytest.fixture

tests/test_SpectrumBinner.py

@@ -1,8 +1,11 @@
 import numpy as np
 import pytest
 from matchms import Spectrum
+
 from ms2deepscore import SpectrumBinner
-from ms2deepscore.MetadataFeatureGenerator import CategoricalToBinary, StandardScaler
+from ms2deepscore.MetadataFeatureGenerator import (CategoricalToBinary,
+                                                   StandardScaler)
+
 
 def test_SpectrumBinner():
     """Test if default initalization works"""

tests/test_data_generators.py

@@ -1,16 +1,19 @@
+import string
+
 import numpy as np
 import pandas as pd
 import pytest
-import string
 from matchms import Spectrum
 
 from ms2deepscore import SpectrumBinner
-from ms2deepscore.MetadataFeatureGenerator import StandardScaler, CategoricalToBinary
 from ms2deepscore.data_generators import (DataGeneratorAllInchikeys,
                                           DataGeneratorAllSpectrums,
                                           _exclude_nans_from_labels,
                                           _validate_labels)
-from tests.test_user_worfklow import load_processed_spectrums, get_reference_scores
+from ms2deepscore.MetadataFeatureGenerator import (CategoricalToBinary,
+                                                   StandardScaler)
+from tests.test_user_worfklow import (get_reference_scores,
+                                      load_processed_spectrums)
 
 
 def create_dummy_data():

tests/test_models.py

@@ -1,18 +1,22 @@
 import os
 from pathlib import Path
-from packaging import version
+
 import numpy as np
 import tensorflow as tf
+from packaging import version
 from tensorflow import keras
+
 if version.parse(tf.__version__) >= version.parse("2.11"):
     AdamOptimizer = keras.optimizers.legacy.Adam
 else:
     AdamOptimizer = keras.optimizers.Adam
 from ms2deepscore import SpectrumBinner
-from ms2deepscore.data_generators import DataGeneratorAllInchikeys, DataGeneratorAllSpectrums
-from ms2deepscore.models import SiameseModel, load_model
+from ms2deepscore.data_generators import (DataGeneratorAllInchikeys,
+                                          DataGeneratorAllSpectrums)
 from ms2deepscore.MetadataFeatureGenerator import StandardScaler
-from tests.test_user_worfklow import load_processed_spectrums, get_reference_scores
+from ms2deepscore.models import SiameseModel, load_model
+from tests.test_user_worfklow import (get_reference_scores,
+                                      load_processed_spectrums)
 
 TEST_RESOURCES_PATH = Path(__file__).parent / 'resources'
 

tests/test_models_duplicate_inchikeys.py

@@ -1,12 +1,14 @@
 import os
 from pathlib import Path
 
-from ms2deepscore import SpectrumBinner
-from ms2deepscore.data_generators import DataGeneratorAllSpectrums, DataGeneratorAllInchikeys
-from tests.test_user_worfklow import load_processed_spectrums, get_reference_scores
-
 import pytest
 
+from ms2deepscore import SpectrumBinner
+from ms2deepscore.data_generators import (DataGeneratorAllInchikeys,
+                                          DataGeneratorAllSpectrums)
+from tests.test_user_worfklow import (get_reference_scores,
+                                      load_processed_spectrums)
+
 
 def test_error_duplicate_inchikeys():
     """Test an expected error when duplicate inchikeys are given to DataGenerator"""

tests/test_ms2deepscore.py

@@ -1,4 +1,5 @@
 from pathlib import Path
+
 import numpy as np
 import pytest
 

tests/test_ms2deepscoremontecarlo.py

@@ -1,4 +1,5 @@
 from pathlib import Path
+
 import numpy as np
 import pytest
 

tests/test_plotting.py

@@ -1,11 +1,8 @@
 import numpy as np
-from ms2deepscore.plotting import (
-    create_confusion_matrix_plot,
-    create_histograms_plot,
-    plot_histograms,
-    calculate_histograms
-)
 
+from ms2deepscore.plotting import (calculate_histograms,
+                                   create_confusion_matrix_plot,
+                                   create_histograms_plot, plot_histograms)
 
 mock_reference_scores = np.random.random((100, 100))
 mock_comparison_scores = np.random.random((100, 100))

tests/test_spectrum_binning_fixed.py

@@ -1,10 +1,11 @@
 import numpy as np
 import pytest
 from matchms import Spectrum
-from ms2deepscore.spectrum_binning_fixed import bin_number_array_fixed
-from ms2deepscore.spectrum_binning_fixed import create_peak_list_fixed
-from ms2deepscore.spectrum_binning_fixed import set_d_bins_fixed
-from ms2deepscore.spectrum_binning_fixed import unique_peaks_fixed
+
+from ms2deepscore.spectrum_binning_fixed import (bin_number_array_fixed,
+                                                 create_peak_list_fixed,
+                                                 set_d_bins_fixed,
+                                                 unique_peaks_fixed)
 
 
 def test_create_peak_list_fixed():

tests/test_spectrum_binning_linear.py

@@ -1,11 +1,13 @@
 import os
+
 import numpy as np
 import pytest
 from matchms import Spectrum
-from ms2deepscore.spectrum_binning_linear import bin_number_array_linear
-from ms2deepscore.spectrum_binning_linear import create_peak_list_linear
-from ms2deepscore.spectrum_binning_linear import set_d_bins_linear
-from ms2deepscore.spectrum_binning_linear import unique_peaks_linear
+
+from ms2deepscore.spectrum_binning_linear import (bin_number_array_linear,
+                                                  create_peak_list_linear,
+                                                  set_d_bins_linear,
+                                                  unique_peaks_linear)
 
 
 def test_create_peak_list_linear():