moran_coefficient() - Code Metrics - Inspection of "added autocorrelation descriptors" - richlewis42/scikit-chem - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( 5bdf16...98b503 )

by Rich

created 2016-08-30 21:25 UTC

moran_coefficient() B

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Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Importance

Changes	1
Bugs	0	Features	1

Metric	Value
cc	2
c	1
b	0
f	1
dl	0
loc	38
rs	8.8571

#! /usr/bin/env python
#
# Copyright (C) 2016 Rich Lewis <[email protected]>
# License: 3-clause BSD

"""
# skchem.features.descriptors.autocorrelation

Autocorrelation descriptors for scikit-chem.
"""

from functools import partial

from .caching import cache
# .scrutinizer.yml
before_commands:
    - sudo pip install abc # Python2
    - sudo pip3 install abc # Python3
from .fundamentals import adjacency_matrix, distance_matrix, atom_props
# .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


@cache.inject(distance_matrix, atom_props)
def moreau_broto_autocorrelation(mol, dist_mat, prop, prop_name='atomic_mass',

                                 c_scaled=False, centred=False,

                                 ks=range(1, 9)):

    """ The Moreau-Broto autocorrelation.


    $$ ATS_k = \frac{1}{2} \hdot \sum_{i=1}^A \sum_{j=1}^A $$

    With special case $$ ATS_0 = \sum_{i=1}^A w_i^2.

    Where $A$ is the number of atoms, and $w$ is an atomic property.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the descriptor.

        prop (str):
            The atomic property.

        c_scaled (bool):
            Whether the properties should be scaled against sp3 carbon.

        centred (bool):
            Whether the descriptor should be divided by the number of
            contributions (avoids dependence on molecular size).

        ks (iterable):
            The lags to calculate the descriptor over.

    Returns:
        float

    Examples:
        >>> import skchem
        >>> m = skchem.Mol.from_smiles('CC(O)CCO')
        >>> moreau_broto_autocorrelation(m, centred=False,
        ...                              prop_name='atomic_mass',
        ...                              ks=range(4))  # doctest: +ELLIPSIS
        array([ 1088.99...,   817.12...,   865.02...,   528.59...])
    """

    div = np.array([(dist_mat == k).sum() for k in ks]) if centred else 1
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param

    return np.array([(1 if k == 0 else 0.5) * prop.dot(dist_mat == k).dot(prop)
                     for k in ks]) / div


@cache.inject(distance_matrix, atom_props)
def moran_coefficient(mol, dist_mat, prop, prop_name='atomic_mass',

                      c_scaled=False, ks=range(1, 9)):


    """ Moran coefficient for lags ks.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the descriptor.

        prop (str):
            The atomic property.

        c_scaled (bool):
            Whether the properties should be scaled against sp3 carbon.

        centered (bool):
            Whether the descriptor should be divided by the number of
            contributions (avoids dependence on molecular size.

        ks (iterable):
            The lags to calculate the descriptor over.

    Returns:
        float
    """

    prop = prop - prop.mean()

    res = []

    for k in ks:
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        geodesic = dist_mat == k
        num = prop.dot(geodesic).dot(prop) / geodesic.sum()
        denom = (prop ** 2).sum() / len(prop)
        res.append(num / denom)

    return np.array(res)


@cache.inject(distance_matrix, atom_props)
def geary_coefficient(mol, dist_mat, prop, prop_name='atomic_mass',

                      c_scaled=False, ks=range(1, 9)):


    """ The geary coefficient for *ks* lags.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the descriptor.

        prop (str):
            The atomic property.

        c_scaled (bool):
            Whether the properties should be scaled against sp3 carbon.

        centered (bool):
            Whether the descriptor should be divided by the number of
            contributions (avoids dependence on molecular size.

        ks (iterable):
            The lags to calculate the descriptor over.

    Returns:
        float

    """

    res = []
    for k in ks:
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        geodesic = dist_mat == k
        num = 0.5 * ((prop - prop[:, np.newaxis]) ** 2 * geodesic).sum() / geodesic.sum()
        denom = ((prop - prop.mean()) ** 2).sum() / (len(prop) - 1)
        res.append(num / denom)

    return np.array(res)


@cache
@cache.inject(adjacency_matrix, distance_matrix)
def galvez_matrix(mol, dist_mat, adj_mat):

    """ The galvez matrix.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the matrix.

    Returns:
        np.array
    """

    temp = dist_mat ** -2
    np.fill_diagonal(temp, 0)
    galvez_mat = temp.dot(adj_mat) + np.diag(mol.atoms.valence_vertex_degree)
    return galvez_mat


@cache
@cache.inject(galvez_matrix)
def charge_matrix(mol, galvez_mat):

    """ The charge matrix.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the matrix.

    Returns:
        np.array

    """

    ct_mat = galvez_mat - galvez_mat.T
    ct_mat[np.diag_indices_from(ct_mat)] = mol.atoms.depleted_degree

    return ct_mat


@cache
@cache.inject(charge_matrix, distance_matrix)
def topological_charge_index(mol, c_mat, dist_mat, ks=range(11)):


    """ The Galvez tologogical charge index for lags ks.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the descriptor.

        ks (iterable):
            The lags for which to calculate the descriptor.

    Returns:
        np.array

    """
    return np.array([0.5 * np.abs(c_mat)[dist_mat == k].sum() for i in ks])



@cache.inject(topological_charge_index)
def mean_topological_charge_index(mol, tci, ks=range(11)):


    """ Mean topological charge index for lags ks.

    Args:
        mol (skchem.Mol):
            The molecule for which to calculate the descriptor.

        ks (iterable):
            The lags for which to calculate the descriptor.

    Returns:
        np.array
    """

    return tci / (len(mol.atoms) - 1)


@cache.inject(topological_charge_index)
def total_charge_index(mol, tci, ks=range(11)):
class SomeClass:
    def some_method(self):
        """Do x and return foo."""

    return tci.sum() / (len(mol.atoms) - 1)


PROPS = ['atomic_mass', 'van_der_waals_volume', 'sanderson_electronegativity',
         'polarisability', 'ionisation_energy', 'intrinsic_state']

KS = range(1, 9)

DESCRIPTORS = [partial(moreau_broto_autocorrelation, k=k, prop=p, centered=c)
               for k in KS for c in (False, True) for p in PROPS]

FS = (moran_coefficient, geary_coefficient)

DESCRIPTORS += [partial(f, k=k, prop=p) for f in FS for k in KS for p in PROPS]

__all__ = ['moreau_broto_autocorrelation', 'moran_coefficient',
           'geary_coefficient', 'topological_charge_index',
           'mean_topological_charge_index', 'total_charge_index']


Push — master ( 5bdf16...98b503 )

moran_coefficient() B

Complexity

Size

Duplication

Importance

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) 2016 Rich Lewis <[email protected]>
4			# License: 3-clause BSD
5
6			"""
7			# skchem.features.descriptors.autocorrelation
8
9			Autocorrelation descriptors for scikit-chem.
10			"""
11
12			from functools import partial
13
14			from .caching import cache
			0 ignored issues – show Configuration introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report Unable to import 'caching' (invalid syntax (<string>, line 109)) 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...
15			from .fundamentals import adjacency_matrix, distance_matrix, atom_props
			0 ignored issues – show Configuration introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The import `fundamentals` 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
17			import numpy as np
			0 ignored issues – show Configuration introduced 2016-08-30 21:55 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...
18
19
20			@cache.inject(distance_matrix, atom_props)
21			def moreau_broto_autocorrelation(mol, dist_mat, prop, prop_name='atomic_mass',
			0 ignored issues – show Coding Style Naming introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The name `ks` does not conform to the argument naming conventions (`[a-z_][a-z0-9_]{2,30}$`). This check looks for invalid names for a range of different identifiers. You can set regular expressions to which the identifiers must conform if the defaults do not match your requirements. If your project includes a Pylint configuration file, the settings contained in that file take precedence. To find out more about Pylint, please refer to their site. Loading history... best-practice introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report Too many arguments (7/5) Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `prop_name` seems to be unused. Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `mol` seems to be unused. Loading history...
22			c_scaled=False, centred=False,
			0 ignored issues – show Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `c_scaled` seems to be unused. Loading history...
23			ks=range(1, 9)):
24
25			""" The Moreau-Broto autocorrelation.
			0 ignored issues – show Bug introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report A suspicious escape sequence `\h` was found. Did you maybe forget to add an `r` prefix? Escape sequences in Python are generally interpreted according to rules similar to standard C. Only if strings are prefixed with `r` or `R` are they interpreted as regular expressions. The escape sequence that was used indicates that you might have intended to write a regular expression. Learn more about the available escape sequences. in the Python documentation. Loading history... Bug introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report A suspicious escape sequence `\s` was found. Did you maybe forget to add an `r` prefix? Escape sequences in Python are generally interpreted according to rules similar to standard C. Only if strings are prefixed with `r` or `R` are they interpreted as regular expressions. The escape sequence that was used indicates that you might have intended to write a regular expression. Learn more about the available escape sequences. in the Python documentation. Loading history...
26
27			$$ ATS_k = \frac{1}{2} \hdot \sum_{i=1}^A \sum_{j=1}^A $$
28
29			With special case $$ ATS_0 = \sum_{i=1}^A w_i^2.
30
31			Where $A$ is the number of atoms, and $w$ is an atomic property.
32
33			Args:
34			mol (skchem.Mol):
35			The molecule for which to calculate the descriptor.
36
37			prop (str):
38			The atomic property.
39
40			c_scaled (bool):
41			Whether the properties should be scaled against sp3 carbon.
42
43			centred (bool):
44			Whether the descriptor should be divided by the number of
45			contributions (avoids dependence on molecular size).
46
47			ks (iterable):
48			The lags to calculate the descriptor over.
49
50			Returns:
51			float
52
53			Examples:
54			>>> import skchem
55			>>> m = skchem.Mol.from_smiles('CC(O)CCO')
56			>>> moreau_broto_autocorrelation(m, centred=False,
57			... prop_name='atomic_mass',
58			... ks=range(4)) # doctest: +ELLIPSIS
59			array([ 1088.99..., 817.12..., 865.02..., 528.59...])
60			"""
61
62			div = np.array([(dist_mat == k).sum() for k in ks]) if centred else 1
			0 ignored issues – show Comprehensibility Bug introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report `k` is re-defining a name which is already available in the outer-scope (previously defined on line `238`). It is generally a bad practice to shadow variables from the outer-scope. In most cases, this is done unintentionally and might lead to unexpected behavior: param = 5 class Foo: def __init__(self, param): # "param" would be flagged here self.param = param Loading history...
63
64			return np.array([(1 if k == 0 else 0.5) * prop.dot(dist_mat == k).dot(prop)
65			for k in ks]) / div
66
67
68			@cache.inject(distance_matrix, atom_props)
69			def moran_coefficient(mol, dist_mat, prop, prop_name='atomic_mass',
			0 ignored issues – show Coding Style Naming introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The name `ks` does not conform to the argument naming conventions (`[a-z_][a-z0-9_]{2,30}$`). This check looks for invalid names for a range of different identifiers. You can set regular expressions to which the identifiers must conform if the defaults do not match your requirements. If your project includes a Pylint configuration file, the settings contained in that file take precedence. To find out more about Pylint, please refer to their site. Loading history... best-practice introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report Too many arguments (6/5) Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `prop_name` seems to be unused. Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `mol` seems to be unused. Loading history...
70			c_scaled=False, ks=range(1, 9)):
			0 ignored issues – show Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `c_scaled` seems to be unused. Loading history...
71
72			""" Moran coefficient for lags ks.
73
74			Args:
75			mol (skchem.Mol):
76			The molecule for which to calculate the descriptor.
77
78			prop (str):
79			The atomic property.
80
81			c_scaled (bool):
82			Whether the properties should be scaled against sp3 carbon.
83
84			centered (bool):
85			Whether the descriptor should be divided by the number of
86			contributions (avoids dependence on molecular size.
87
88			ks (iterable):
89			The lags to calculate the descriptor over.
90
91			Returns:
92			float
93			"""
94
95			prop = prop - prop.mean()
96
97			res = []
98
99			for k in ks:
			0 ignored issues – show Comprehensibility Bug introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report `k` is re-defining a name which is already available in the outer-scope (previously defined on line `238`). It is generally a bad practice to shadow variables from the outer-scope. In most cases, this is done unintentionally and might lead to unexpected behavior: param = 5 class Foo: def __init__(self, param): # "param" would be flagged here self.param = param Loading history...
100			geodesic = dist_mat == k
101			num = prop.dot(geodesic).dot(prop) / geodesic.sum()
102			denom = (prop ** 2).sum() / len(prop)
103			res.append(num / denom)
104
105			return np.array(res)
106
107
108			@cache.inject(distance_matrix, atom_props)
109			def geary_coefficient(mol, dist_mat, prop, prop_name='atomic_mass',
			0 ignored issues – show Coding Style Naming introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The name `ks` does not conform to the argument naming conventions (`[a-z_][a-z0-9_]{2,30}$`). This check looks for invalid names for a range of different identifiers. You can set regular expressions to which the identifiers must conform if the defaults do not match your requirements. If your project includes a Pylint configuration file, the settings contained in that file take precedence. To find out more about Pylint, please refer to their site. Loading history... best-practice introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report Too many arguments (6/5) Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `prop_name` seems to be unused. Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `mol` seems to be unused. Loading history...
110			c_scaled=False, ks=range(1, 9)):
			0 ignored issues – show Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `c_scaled` seems to be unused. Loading history...
111
112			""" The geary coefficient for ks lags.
113
114			Args:
115			mol (skchem.Mol):
116			The molecule for which to calculate the descriptor.
117
118			prop (str):
119			The atomic property.
120
121			c_scaled (bool):
122			Whether the properties should be scaled against sp3 carbon.
123
124			centered (bool):
125			Whether the descriptor should be divided by the number of
126			contributions (avoids dependence on molecular size.
127
128			ks (iterable):
129			The lags to calculate the descriptor over.
130
131			Returns:
132			float
133
134			"""
135
136			res = []
137			for k in ks:
			0 ignored issues – show Comprehensibility Bug introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report `k` is re-defining a name which is already available in the outer-scope (previously defined on line `238`). It is generally a bad practice to shadow variables from the outer-scope. In most cases, this is done unintentionally and might lead to unexpected behavior: param = 5 class Foo: def __init__(self, param): # "param" would be flagged here self.param = param Loading history...
138			geodesic = dist_mat == k
139			num = 0.5 * ((prop - prop[:, np.newaxis]) ** 2 * geodesic).sum() / geodesic.sum()
140			denom = ((prop - prop.mean()) ** 2).sum() / (len(prop) - 1)
141			res.append(num / denom)
142
143			return np.array(res)
144
145
146			@cache
147			@cache.inject(adjacency_matrix, distance_matrix)
148			def galvez_matrix(mol, dist_mat, adj_mat):
149
150			""" The galvez matrix.
151
152			Args:
153			mol (skchem.Mol):
154			The molecule for which to calculate the matrix.
155
156			Returns:
157			np.array
158			"""
159
160			temp = dist_mat ** -2
161			np.fill_diagonal(temp, 0)
162			galvez_mat = temp.dot(adj_mat) + np.diag(mol.atoms.valence_vertex_degree)
163			return galvez_mat
164
165
166			@cache
167			@cache.inject(galvez_matrix)
168			def charge_matrix(mol, galvez_mat):
169
170			""" The charge matrix.
171
172			Args:
173			mol (skchem.Mol):
174			The molecule for which to calculate the matrix.
175
176			Returns:
177			np.array
178
179			"""
180
181			ct_mat = galvez_mat - galvez_mat.T
182			ct_mat[np.diag_indices_from(ct_mat)] = mol.atoms.depleted_degree
183
184			return ct_mat
185
186
187			@cache
188			@cache.inject(charge_matrix, distance_matrix)
189			def topological_charge_index(mol, c_mat, dist_mat, ks=range(11)):
			0 ignored issues – show Coding Style Naming introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The name `ks` does not conform to the argument naming conventions (`[a-z_][a-z0-9_]{2,30}$`). This check looks for invalid names for a range of different identifiers. You can set regular expressions to which the identifiers must conform if the defaults do not match your requirements. If your project includes a Pylint configuration file, the settings contained in that file take precedence. To find out more about Pylint, please refer to their site. Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `mol` seems to be unused. Loading history...
190
191			""" The Galvez tologogical charge index for lags ks.
192
193			Args:
194			mol (skchem.Mol):
195			The molecule for which to calculate the descriptor.
196
197			ks (iterable):
198			The lags for which to calculate the descriptor.
199
200			Returns:
201			np.array
202
203			"""
204			return np.array([0.5 * np.abs(c_mat)[dist_mat == k].sum() for i in ks])
			0 ignored issues – show Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The variable `i` seems to be unused. Loading history...
205
206
207			@cache.inject(topological_charge_index)
208			def mean_topological_charge_index(mol, tci, ks=range(11)):
			0 ignored issues – show Coding Style Naming introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The name `ks` does not conform to the argument naming conventions (`[a-z_][a-z0-9_]{2,30}$`). This check looks for invalid names for a range of different identifiers. You can set regular expressions to which the identifiers must conform if the defaults do not match your requirements. If your project includes a Pylint configuration file, the settings contained in that file take precedence. To find out more about Pylint, please refer to their site. Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `ks` seems to be unused. Loading history...
209
210			""" Mean topological charge index for lags ks.
211
212			Args:
213			mol (skchem.Mol):
214			The molecule for which to calculate the descriptor.
215
216			ks (iterable):
217			The lags for which to calculate the descriptor.
218
219			Returns:
220			np.array
221			"""
222
223			return tci / (len(mol.atoms) - 1)
224
225
226			@cache.inject(topological_charge_index)
227			def total_charge_index(mol, tci, ks=range(11)):
			0 ignored issues – show Coding Style Naming introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The name `ks` does not conform to the argument naming conventions (`[a-z_][a-z0-9_]{2,30}$`). This check looks for invalid names for a range of different identifiers. You can set regular expressions to which the identifiers must conform if the defaults do not match your requirements. If your project includes a Pylint configuration file, the settings contained in that file take precedence. To find out more about Pylint, please refer to their site. Loading history... Coding Style introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report This function should have a docstring. The coding style of this project requires that you add a docstring to this code element. Below, you find an example for methods: class SomeClass: def some_method(self): """Do x and return foo.""" If you would like to know more about docstrings, we recommend to read PEP-257: Docstring Conventions. Loading history... Unused Code introduced 2016-08-30 21:55 UTC by Report Bug Copy Issue Report The argument `ks` seems to be unused. Loading history...
228
229			return tci.sum() / (len(mol.atoms) - 1)
230
231
232			PROPS = ['atomic_mass', 'van_der_waals_volume', 'sanderson_electronegativity',
233			'polarisability', 'ionisation_energy', 'intrinsic_state']
234
235			KS = range(1, 9)
236
237			DESCRIPTORS = [partial(moreau_broto_autocorrelation, k=k, prop=p, centered=c)
238			for k in KS for c in (False, True) for p in PROPS]
239
240			FS = (moran_coefficient, geary_coefficient)
241
242			DESCRIPTORS += [partial(f, k=k, prop=p) for f in FS for k in KS for p in PROPS]
243
244			__all__ = ['moreau_broto_autocorrelation', 'moran_coefficient',
245			'geary_coefficient', 'topological_charge_index',
246			'mean_topological_charge_index', 'total_charge_index']
247

richlewis42 / scikit-chem

Push — master ( 5bdf16...98b503 )

moran_coefficient() B

Complexity

Size

Duplication

Importance

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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