Fingerprinter.fit() - Code Metrics - Inspection of "updated pylintrc" - richlewis42/scikit-chem - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( 2bc047...202252 )

by Rich

created 2016-04-14 16:47 UTC

Fingerprinter.fit() A

↳ Parent: Fingerprinter

Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Metric	Value
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loc	2
rs	10

#! /usr/bin/env python
#
# Copyright (C) 2007-2009 Rich Lewis <[email protected]>
# License: 3-clause BSD

"""
skchem.descriptors.fingerprints

Fingerprinting classes and associated functions are defined.

"""

from functools import wraps

import pandas as pd
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3
from rdkit.Chem import DataStructs
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3
from rdkit.Chem.rdMolDescriptors import (GetMorganFingerprint,
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3
                                         GetHashedMorganFingerprint,
                                         GetAtomPairFingerprint,
                                         GetHashedAtomPairFingerprint,
                                         GetTopologicalTorsionFingerprint,
                                         GetHashedTopologicalTorsionFingerprint,
                                         GetMACCSKeysFingerprint,
                                         GetFeatureInvariants,
                                         GetConnectivityInvariants)
from rdkit.Chem.rdReducedGraphs import GetErGFingerprint
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3
from rdkit.Chem.rdmolops import RDKFingerprint
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3

import numpy as np
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3
import skchem

def skchemize(func, columns=None, *args, **kwargs):
    """

    transform an RDKit fingerprinting function to work well with pandas

    >>> from rdkit import Chem
    >>> import skchem
    >>> from skchem.descriptors import skchemize
    >>> from skchem.core import Mol
    >>> f = skchemize(Chem.RDKFingerprint)
    >>> m = Mol.from_smiles('c1ccccc1')
    >>> f(m)
    0       0
    1       0
    2       0
    3       0
    4       0
    5       0
    6       0
    7       0
    8       0
    9       0
    10      0
    11      0
    12      0
    13      0
    14      0
    15      0
    16      0
    17      0
    18      0
    19      0
    20      0
    21      0
    22      0
    23      0
    24      0
    25      0
    26      0
    27      0
    28      0
    29      0
           ..
    2018    0
    2019    0
    2020    0
    2021    0
    2022    0
    2023    0
    2024    0
    2025    0
    2026    0
    2027    0
    2028    0
    2029    0
    2030    0
    2031    0
    2032    0
    2033    0
    2034    0
    2035    0
    2036    0
    2037    0
    2038    0
    2039    0
    2040    0
    2041    0
    2042    0
    2043    0
    2044    0
    2045    0
    2046    0
    2047    0
    dtype: int64
    >>> from skchem.data import resource
    >>> df = skchem.read_sdf(resource('test_sdf', 'multi_molecule-simple.sdf'))
    >>> df.structure.apply(f)
          0     1     2     3     4     5     6     7     8     9     ...   2038  \\
    name                                                              ...
    297      0     0     0     0     0     0     0     0     0     0  ...      0
    6324     0     0     0     0     0     0     0     0     0     0  ...      0
    6334     0     0     0     0     0     0     0     0     0     0  ...      0
    <BLANKLINE>
          2039  2040  2041  2042  2043  2044  2045  2046  2047
    name
    297      0     0     0     0     0     0     0     0     0
    6324     0     0     0     0     0     0     0     0     0
    6334     0     0     0     0     0     0     0     0     0
    <BLANKLINE>
    [3 rows x 2048 columns]

    """
    @wraps(func)
    def func_wrapper(m):


        """ Function that wraps an rdkit function allowing it to produce dataframes. """

        arr = np.array(0)
        DataStructs.ConvertToNumpyArray(func(m, *args, **kwargs), arr)


        return pd.Series(arr, index=columns)

    return func_wrapper


class Fingerprinter(object):

    """ Fingerprinter Base class. """

    def __init__(self, name, func):
        self.NAME = name

        self.func = func

    def __call__(self, obj):
        return self.transform(obj)

    def __add__(self, other):
        fpers = []
        for fper in (self, other):
            if isinstance(fper, FusionFingerprinter):
                fpers += fper.fingerprinters

            else:
                fpers.append(fper)

        return FusionFingerprinter(fpers)

    def fit(self, X, y):
class SomeClass:
    def some_method(self):
        """Do x and return foo."""
        return self

    def transform(self, obj):

        """ calculate the fingerprint for the given object. """

        if isinstance(obj, skchem.Mol):
            return self._transform(obj)

        elif isinstance(obj, pd.DataFrame):
            return obj.structure.apply(self.transform)

        elif isinstance(obj, pd.Series):
            return obj.apply(self.transform)

        else:
            raise NotImplementedError

    def _transform(self, mol):

        """ Calculate the fingerprint on a molecule. """

        return pd.Series(list(self.func(mol)), name=mol.name)


class FusionFingerprinter(Fingerprinter):
class SomeClass:
    def some_method(self):
        """Do x and return foo."""

    def __init__(self, fingerprinters):
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)

        self.fingerprinters = fingerprinters

    def transform(self, obj):

        if isinstance(obj, skchem.Mol):
            return pd.concat([fp.transform(obj) for fp in self.fingerprinters],  keys=[fp.NAME for fp in self.fingerprinters])


        elif isinstance(obj, pd.DataFrame):
            return pd.concat([fp.transform(obj) for fp in self.fingerprinters], keys=[fp.NAME for fp in self.fingerprinters], axis=1)


        elif isinstance(obj, pd.Series):
            return pd.concat([fp.transform(obj.structure) for fp in self.fingerprinters],  keys=[fp.NAME for fp in self.fingerprinters], axis=1)


        else:
            raise NotImplementedError

    def _transform(self, mol):

        return pd.concat([fp.transform(mol) for fp in self.fingerprinters])

class MorganFingerprinter(Fingerprinter):


    """ Morgan Fingerprint Transformer. """

    NAME = 'morgan'

    def __init__(self, radius=2, n_feats=2048, as_bits=True,
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
                 use_features=False, use_bond_types=True, use_chirality=False):

        """
        @param radius
        @param n_feats
        @param as_bits
        @param use_features
        @param use_bond_types
        @param use_chirality
        """
        self.radius = radius
        self.n_feats = n_feats
        self.as_bits = as_bits
        self.use_features = use_features
        self.use_bond_types = use_bond_types
        self.use_chirality = use_chirality

    def _transform(self, mol):

        """
        @param mol

        @returns pd.Series
        """
        if self.n_feats == -1:

            res = GetMorganFingerprint(mol, self.radius,
                                       useFeatures=self.use_features,
                                       useBondTypes=self.use_bond_types,
                                       useChirality=self.use_chirality)
        else:
            res = list(GetHashedMorganFingerprint(mol, self.radius,
                                        nBits=self.n_feats,

                                        useFeatures=self.use_features,

                                        useBondTypes=self.use_bond_types,

                                        useChirality=self.use_chirality))


        res = pd.Series(res, name=mol.name)

        if self.as_bits:
            return (res > 0).astype(int)
        else:
            return res


class AtomPairFingerprinter(Fingerprinter):


    """ Atom Pair Tranformer. """

    NAME = 'atom_pair'

    def __init__(self, min_length=1, max_length=30, n_feats=2048, as_bits=False, use_chirality=False):
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
        self.min_length = min_length
        self.max_length = max_length
        self.n_feats = n_feats
        self.as_bits = as_bits
        self.use_chirality = use_chirality

    def _transform(self, mol):

        """
        @param molecules

        @return pd.Series
        """

        if self.n_feats == -1:

            res = GetAtomPairFingerprint(mol, minLength=self.min_length,
                                         maxLength=self.max_length,
                                         includeChirality=self.use_chirality)
        else:
            res = list(GetHashedAtomPairFingerprint(mol, minLength=self.min_length,
                                         maxLength=self.max_length,

                                         nBits=self.n_feats,

                                         includeChirality=self.use_chirality))


        res = pd.Series(res, name=mol.name)

        if self.as_bits:
            return (res > 0).astype(int)
        else:
            return res

class TopologicalTorsionFingerprinter(Fingerprinter):
class SomeClass:
    def some_method(self):
        """Do x and return foo."""

    NAME = 'topological_torsion'

    def __init__(self, target_size=4, n_feats=2048, as_bits=False,
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
                 use_chirality=False):
                 self.target_size = target_size

                 self.n_feats = n_feats

                 self.as_bits = as_bits

                 self.use_chirality = use_chirality


    def _transform(self, mol):

        if self.n_feats == -1:

            res = GetTopologicalTorsionFingerprint(mol, targetSize=self.targetSize,

                                        includeChirality=self.use_chirality)


        else:
            res = list(GetHashedTopologicalTorsionFingerprint(mol,
                                        targetSize=self.targetSize,

                                        nBits=self.n_feats))


        res = pd.Series(res, name=mol.name)

        if self.as_bits:
            return (res > 0).astype(int)
        else:
            return res


class MACCSKeysFingerprinter(Fingerprinter):

    """ MACCS Keys Fingerprints """

    NAME = 'maccs'

    def __init__(self):
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
        pass

    def _transform(self, mol):

        return pd.Series(list(GetMACCSKeysFingerprint(mol)))

class ErGFingerprinter(Fingerprinter):

    """ ErG Fingerprints """

    NAME = 'erg'

    def __init__(self):
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
        pass

    def _transform(self, mol):

        return pd.Series(GetErGFingerprint(mol))

class FeatureInvariantsFingerprinter(Fingerprinter):

    """ Feature invariant fingerprints. """

    NAME = 'feat_inv'

    def __init__(self):
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
        pass

    def _transform(self, mol):

        return pd.Series(GetFeatureInvariants(mol))

class ConnectivityInvariantsFingerprinter(Fingerprinter):

    """ Connectiity invariant fingerprints """
    

    NAME = 'conn_inv'

    def __init__(self):
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
        pass

    def _transform(self, mol):

        return pd.Series(GetConnectivityInvariants(mol))

class RDKFingerprinter(Fingerprinter):


    """ RDKit fingerprint """

    NAME = 'rdk'

    def __init__(self, min_path=1, max_path=7, n_feats=2048, n_bits_per_hash=2,
class SomeParent:
    def __init__(self):
        self.x = 1

class SomeChild(SomeParent):
    def __init__(self):
        # Initialize the super class
        SomeParent.__init__(self)
                 use_hs=True, target_density=0.0, min_size=128,

                 branched_paths=True, use_bond_types=True):

                 self.min_path = 1

                 self.max_path = 7

                 self.n_feats = 2048

                 self.n_bits_per_hash = 2

                 self.use_hs = True

                 self.target_density = 0.0

                 self.min_size = 128

                 self.branched_paths = True

                 self.use_bond_types = True


    def _transform(self, mol):

        return pd.Series(list(RDKFingerprint(mol, minPath=self.min_path,
                                             maxPath=self.max_path,
                                             fpSize=self.n_feats,
                                             nBitsPerHash=self.n_bits_per_hash,
                                             useHs=self.use_hs,
                                             tgtDensity=self.target_density,
                                             minSize=self.min_size,
                                             branchedPaths=self.branched_paths,
                                             useBondOrder=self.use_bond_types)),
                        name=mol.name)



Push — master ( 2bc047...202252 )

Fingerprinter.fit() A

Complexity

Size

Duplication

1. Missing Dependencies

2. Missing init.py files

1. Missing Dependencies

2. Missing init.py files

1. Missing Dependencies

2. Missing init.py files

1. Missing Dependencies

2. Missing init.py files

1. Missing Dependencies

2. Missing init.py files

1. Missing Dependencies

2. Missing init.py files

1			#! /usr/bin/env python
2			#
3			# Copyright (C) 2007-2009 Rich Lewis <[email protected]>
4			# License: 3-clause BSD
5
6			"""
7			skchem.descriptors.fingerprints
8
9			Fingerprinting classes and associated functions are defined.
10
11			"""
12
13			from functools import wraps
14
15			import pandas as pd
			0 ignored issues – show Configuration introduced 2016-01-19 16:21 UTC by Report Bug Copy Issue Report The import `pandas` could not be resolved. This can be caused by one of the following: 1. Missing Dependencies This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands. # .scrutinizer.yml before_commands: - sudo pip install abc # Python2 - sudo pip3 install abc # Python3 Tip: We are currently not using virtualenv to run pylint, when installing your modules make sure to use the command for the correct version. 2. Missing __init__.py files This error could also result from missing `__init__.py` files in your module folders. Make sure that you place one file in each sub-folder. Loading history...
16			from rdkit.Chem import DataStructs
			0 ignored issues – show Configuration introduced 2016-01-19 16:21 UTC by Report Bug Copy Issue Report The import `rdkit.Chem` could not be resolved. This can be caused by one of the following: 1. Missing Dependencies This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands. # .scrutinizer.yml before_commands: - sudo pip install abc # Python2 - sudo pip3 install abc # Python3 Tip: We are currently not using virtualenv to run pylint, when installing your modules make sure to use the command for the correct version. 2. Missing __init__.py files This error could also result from missing `__init__.py` files in your module folders. Make sure that you place one file in each sub-folder. Loading history...
17			from rdkit.Chem.rdMolDescriptors import (GetMorganFingerprint,
			0 ignored issues – show Configuration introduced 2016-04-14 16:48 UTC by Report Bug Copy Issue Report The import `rdkit.Chem.rdMolDescriptors` could not be resolved. This can be caused by one of the following: 1. Missing Dependencies This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands. # .scrutinizer.yml before_commands: - sudo pip install abc # Python2 - sudo pip3 install abc # Python3 Tip: We are currently not using virtualenv to run pylint, when installing your modules make sure to use the command for the correct version. 2. Missing __init__.py files This error could also result from missing `__init__.py` files in your module folders. Make sure that you place one file in each sub-folder. Loading history...
18			GetHashedMorganFingerprint,
19			GetAtomPairFingerprint,
20			GetHashedAtomPairFingerprint,
21			GetTopologicalTorsionFingerprint,
22			GetHashedTopologicalTorsionFingerprint,
23			GetMACCSKeysFingerprint,
24			GetFeatureInvariants,
25			GetConnectivityInvariants)
26			from rdkit.Chem.rdReducedGraphs import GetErGFingerprint
			0 ignored issues – show Configuration introduced 2016-04-14 16:48 UTC by Report Bug Copy Issue Report The import `rdkit.Chem.rdReducedGraphs` could not be resolved. This can be caused by one of the following: 1. Missing Dependencies This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands. # .scrutinizer.yml before_commands: - sudo pip install abc # Python2 - sudo pip3 install abc # Python3 Tip: We are currently not using virtualenv to run pylint, when installing your modules make sure to use the command for the correct version. 2. Missing __init__.py files This error could also result from missing `__init__.py` files in your module folders. Make sure that you place one file in each sub-folder. Loading history...
27			from rdkit.Chem.rdmolops import RDKFingerprint
			0 ignored issues – show Configuration introduced 2016-04-14 16:48 UTC by Report Bug Copy Issue Report The import `rdkit.Chem.rdmolops` could not be resolved. This can be caused by one of the following: 1. Missing Dependencies This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands. # .scrutinizer.yml before_commands: - sudo pip install abc # Python2 - sudo pip3 install abc # Python3 Tip: We are currently not using virtualenv to run pylint, when installing your modules make sure to use the command for the correct version. 2. Missing __init__.py files This error could also result from missing `__init__.py` files in your module folders. Make sure that you place one file in each sub-folder. Loading history...
28
29			import numpy as np
			0 ignored issues – show Configuration introduced 2016-01-19 16:21 UTC by Report Bug Copy Issue Report The import `numpy` could not be resolved. This can be caused by one of the following: 1. Missing Dependencies This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands. # .scrutinizer.yml before_commands: - sudo pip install abc # Python2 - sudo pip3 install abc # Python3 Tip: We are currently not using virtualenv to run pylint, when installing your modules make sure to use the command for the correct version. 2. Missing __init__.py files This error could also result from missing `__init__.py` files in your module folders. Make sure that you place one file in each sub-folder. Loading history...
30			import skchem
31
32			def skchemize(func, columns=None, args, *kwargs):
33			"""
34

richlewis42 / scikit-chem

Push — master ( 2bc047...202252 )

Fingerprinter.fit() A

Complexity

Size

Duplication

1. Missing Dependencies

2. Missing __init__.py files

1. Missing Dependencies

2. Missing __init__.py files

1. Missing Dependencies

2. Missing __init__.py files

1. Missing Dependencies

2. Missing __init__.py files

1. Missing Dependencies

2. Missing __init__.py files

1. Missing Dependencies

2. Missing __init__.py files

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