230 basic linting rule i2

alphadia/calibration/models.py

@@ -1,7 +1,6 @@
 import numpy as np
-
-from sklearn.preprocessing import PolynomialFeatures
 from sklearn.base import BaseEstimator, RegressorMixin
+from sklearn.preprocessing import PolynomialFeatures
 
 
 class LOESSRegression(BaseEstimator, RegressorMixin):

alphadia/calibration/property.py

@@ -2,19 +2,20 @@
 import logging
 import pickle
 
-# alphadia imports
-from alphadia.plotting.utils import density_scatter
-from alphadia.calibration.models import LOESSRegression
+import numpy as np
 
 # third party imports
 import pandas as pd
-import numpy as np
-from matplotlib import pyplot as plt
-
 import sklearn.base
+from matplotlib import pyplot as plt
 from sklearn.linear_model import LinearRegression
-from sklearn.preprocessing import PolynomialFeatures
 from sklearn.pipeline import Pipeline
+from sklearn.preprocessing import PolynomialFeatures
+
+from alphadia.calibration.models import LOESSRegression
+
+# alphadia imports
+from alphadia.plotting.utils import density_scatter
 
 
 class Calibration:

alphadia/cli.py

@@ -1,25 +1,21 @@
 #!python
 
 # native imports
+# alpha family imports
+# third party imports
+import argparse
+import json
 import logging
+import os
+import re
 import sys
 
 import yaml
-import os
-import re
-import json
 
 # alphadia imports
 import alphadia
-from alphadia.workflow import reporting
 from alphadia import utils
-
-
-# alpha family imports
-
-# third party imports
-import argparse
-
+from alphadia.workflow import reporting
 
 logger = logging.getLogger()
 

alphadia/consensus/utils.py

@@ -1,5 +1,6 @@
 import logging
 import os
+
 import pandas as pd
 
 logger = logging.getLogger()

alphadia/data/alpharaw.py

@@ -1,24 +1,26 @@
 # native imports
+import logging
 import math
 import os
-import logging
 
-# alphadia imports
-from alphadia import utils
+import numba as nb
 
-from alphadia.data.stats import log_stats
+# third party imports
+import numpy as np
+import pandas as pd
+from alpharaw import mzml as alpharawmzml
+
+# TODO fix: "import resolves to its containing file"
+from alpharaw import sciex as alpharawsciex
 
 # alpha family imports
 from alpharaw import (
     thermo as alpharawthermo,
-)  # TODO fix: "import resolves to its containing file"
-from alpharaw import sciex as alpharawsciex
-from alpharaw import mzml as alpharawmzml
+)
 
-# third party imports
-import numpy as np
-import numba as nb
-import pandas as pd
+# alphadia imports
+from alphadia import utils
+from alphadia.data.stats import log_stats
 
 logger = logging.getLogger()
 

alphadia/data/bruker.py

@@ -1,23 +1,24 @@
 # native imports
+import logging
 import math
 import os
-import logging
 
-# alphadia imports
-from alphadia import utils
-from alphadia.data.stats import log_stats
+import alphatims.bruker
+import alphatims.tempmmap as tm
 
 # alpha family imports
 import alphatims.utils
-import alphatims.bruker
-import alphatims.tempmmap as tm
+import numba as nb
 
 # third party imports
 import numpy as np
-import numba as nb
 from numba.core import types
 from numba.experimental import jitclass
 
+# alphadia imports
+from alphadia import utils
+from alphadia.data.stats import log_stats
+
 logger = logging.getLogger()
 
 

alphadia/data/stats.py

@@ -1,6 +1,7 @@
-import numpy as np
 import logging
 
+import numpy as np
+
 logger = logging.getLogger()
 
 

alphadia/fdr.py

@@ -1,19 +1,18 @@
 # native imports
-import os
 import logging
+import os
 
-# alphadia imports
-
-# alpha family imports
-from alphadia import fragcomp
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
 
 # third party imports
 import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import matplotlib as mpl
 import sklearn
 
+# alphadia imports
+# alpha family imports
+from alphadia import fragcomp
 
 logger = logging.getLogger()
 

alphadia/fdrexperimental.py

@@ -1,20 +1,18 @@
 # native imports
-from abc import ABC, abstractmethod
 import warnings
+from abc import ABC, abstractmethod
 from copy import deepcopy
 
 # alphadia imports
-
 # alpha family imports
-
 # third party imports
 import numpy as np
 import torch
 import torch.nn as nn
 import torch.optim as optim
 from sklearn import model_selection
-from tqdm import tqdm
 from torchmetrics.classification import BinaryAUROC
+from tqdm import tqdm
 
 
 class Classifier(ABC):

alphadia/fdrx/base.py

@@ -2,18 +2,19 @@
 It is flexible with regards to the features, type of classifier and type of identifications (precursors, peptides, proteins).
 """
 
-import sklearn.base
-import pandas as pd
+import logging
+
 import numpy as np
-from alphadia.fragcomp import FragmentCompetition
-from alphadia.fdrx.stats import get_pep, add_q_values, keep_best
+import pandas as pd
+import sklearn.base
+
 from alphadia.fdrx.plotting import (
     _plot_fdr_curve,
     _plot_roc_curve,
     _plot_score_distribution,
 )
-
-import logging
+from alphadia.fdrx.stats import add_q_values, get_pep, keep_best
+from alphadia.fragcomp import FragmentCompetition
 
 logger = logging.getLogger()
 

alphadia/fdrx/plotting.py

@@ -1,5 +1,5 @@
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 import sklearn.metrics
 
 

alphadia/features.py

@@ -1,14 +1,14 @@
 # native imports
 
 # alphadia imports
-from alphadia import utils
-from alphadia.numba import numeric
+import numba as nb
 
 # alpha family imports
-
 # third party imports
 import numpy as np
-import numba as nb
+
+from alphadia import utils
+from alphadia.numba import numeric
 
 
 @nb.njit

alphadia/fragcomp.py

@@ -1,10 +1,11 @@
-from alphadia import utils
-from alphatims import utils as timsutils
 import logging
+
+import numba as nb
 import numpy as np
 import pandas as pd
+from alphatims import utils as timsutils
 
-import numba as nb
+from alphadia import utils
 
 logger = logging.getLogger(__name__)
 

alphadia/grouping.py

@@ -5,9 +5,10 @@
 # alpha family imports
 
 # third party imports
+from typing import Any
+
 import numpy as np
 import pandas as pd
-from typing import Any
 from numpy.typing import NDArray
 
 

alphadia/libtransform.py

@@ -1,29 +1,27 @@
 # native imports
-from pathlib import Path
 import logging
-
 import os
 import typing
+from pathlib import Path
 
-# alphadia imports
-from alphadia import utils, validate
+# third party imports
+import numpy as np
+import pandas as pd
 
 # alpha family imports
 from alphabase.peptide import fragment
+from alphabase.peptide.fragment import get_charged_frag_types
 from alphabase.protein import fasta
-from alphabase.spectral_library.flat import SpecLibFlat
+from alphabase.protein.fasta import protease_dict
 from alphabase.spectral_library.base import SpecLibBase
-from alphabase.spectral_library.reader import LibraryReaderBase
 from alphabase.spectral_library.decoy import decoy_lib_provider
-from alphabase.peptide.fragment import get_charged_frag_types
-from alphabase.protein.fasta import protease_dict
-
-from peptdeep.protein.fasta import PredictSpecLibFasta
+from alphabase.spectral_library.flat import SpecLibFlat
+from alphabase.spectral_library.reader import LibraryReaderBase
 from peptdeep.pretrained_models import ModelManager
+from peptdeep.protein.fasta import PredictSpecLibFasta
 
-# third party imports
-import numpy as np
-import pandas as pd
+# alphadia imports
+from alphadia import utils, validate
 
 logger = logging.getLogger()
 

alphadia/numba/config.py

@@ -1,13 +1,12 @@
 # native imports
 
 # alphadia imports
-from alphadia.workflow import reporting
-
 # alpha family imports
-
 # third party imports
 import numpy as np
 
+from alphadia.workflow import reporting
+
 
 class JITConfig:
     """

alphadia/numba/fft.py

@@ -1,16 +1,15 @@
-import numpy as np
 import numba as nb
+import numpy as np
+from numba.extending import overload
+from rocket_fft import pocketfft
 from rocket_fft.overloads import (
-    ndshape_and_axes,
-    zeropad_or_crop,
-    increase_shape,
-    get_fct,
     decrease_shape,
+    get_fct,
+    increase_shape,
+    ndshape_and_axes,
     resize,
+    zeropad_or_crop,
 )
-from rocket_fft import pocketfft
-
-from numba.extending import overload
 
 
 class NumbaContextOnly(Exception):

alphadia/numba/fragments.py

@@ -6,8 +6,8 @@
 
 # third party imports
 import numba as nb
-from numba.extending import overload_method
 import numpy as np
+from numba.extending import overload_method
 
 
 @nb.experimental.jitclass()

alphadia/numba/numeric.py

@@ -5,8 +5,8 @@
 # alpha family imports
 
 # third party imports
-import numpy as np
 import numba as nb
+import numpy as np
 
 
 @nb.njit(parallel=False, fastmath=True)