Mercurial > repos > bgruening > sklearn_sample_generator

annotate utils.py @ 25:86a086d2bbed draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 49522db5f2dc8a571af49e3f38e80c22571068f4
author bgruening
date Tue, 09 Jul 2019 19:28:42 -0400
parents 97b467e06354
children
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97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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1 import ast
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2 import json
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3 import imblearn
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4 import numpy as np
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5 import pandas
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6 import pickle
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7 import re
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8 import scipy
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9 import sklearn
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10 import skrebate
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11 import sys
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12 import warnings
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13 import xgboost
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14
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15 from collections import Counter
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16 from asteval import Interpreter, make_symbol_table
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17 from imblearn import under_sampling, over_sampling, combine
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18 from imblearn.pipeline import Pipeline as imbPipeline
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19 from mlxtend import regressor, classifier
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20 from scipy.io import mmread
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21 from sklearn import (
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22 cluster, compose, decomposition, ensemble, feature_extraction,
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23 feature_selection, gaussian_process, kernel_approximation, metrics,
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24 model_selection, naive_bayes, neighbors, pipeline, preprocessing,
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25 svm, linear_model, tree, discriminant_analysis)
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27 try:
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28 import iraps_classifier
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29 except ImportError:
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30 pass
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32 try:
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33 import model_validations
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34 except ImportError:
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35 pass
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37 try:
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38 import feature_selectors
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39 except ImportError:
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40 pass
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42 try:
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43 import preprocessors
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44 except ImportError:
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45 pass
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47 # handle pickle white list file
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48 WL_FILE = __import__('os').path.join(
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49 __import__('os').path.dirname(__file__), 'pk_whitelist.json')
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51 N_JOBS = int(__import__('os').environ.get('GALAXY_SLOTS', 1))
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54 class _SafePickler(pickle.Unpickler, object):
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55 """
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56 Used to safely deserialize scikit-learn model objects
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57 Usage:
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58 eg.: _SafePickler.load(pickled_file_object)
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59 """
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60 def __init__(self, file):
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61 super(_SafePickler, self).__init__(file)
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62 # load global white list
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63 with open(WL_FILE, 'r') as f:
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64 self.pk_whitelist = json.load(f)
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65
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66 self.bad_names = (
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67 'and', 'as', 'assert', 'break', 'class', 'continue',
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68 'def', 'del', 'elif', 'else', 'except', 'exec',
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69 'finally', 'for', 'from', 'global', 'if', 'import',
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70 'in', 'is', 'lambda', 'not', 'or', 'pass', 'print',
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71 'raise', 'return', 'try', 'system', 'while', 'with',
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72 'True', 'False', 'None', 'eval', 'execfile', '__import__',
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73 '__package__', '__subclasses__', '__bases__', '__globals__',
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74 '__code__', '__closure__', '__func__', '__self__', '__module__',
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75 '__dict__', '__class__', '__call__', '__get__',
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76 '__getattribute__', '__subclasshook__', '__new__',
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77 '__init__', 'func_globals', 'func_code', 'func_closure',
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78 'im_class', 'im_func', 'im_self', 'gi_code', 'gi_frame',
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79 '__asteval__', 'f_locals', '__mro__')
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80
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81 # unclassified good globals
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82 self.good_names = [
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83 'copy_reg._reconstructor', '__builtin__.object',
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84 '__builtin__.bytearray', 'builtins.object',
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85 'builtins.bytearray', 'keras.engine.sequential.Sequential',
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86 'keras.engine.sequential.Model']
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87
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88 # custom module in Galaxy-ML
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89 self.custom_modules = [
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90 '__main__', 'keras_galaxy_models', 'feature_selectors',
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91 'preprocessors', 'iraps_classifier', 'model_validations']
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92
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93 # override
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94 def find_class(self, module, name):
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95 # balack list first
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96 if name in self.bad_names:
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97 raise pickle.UnpicklingError("global '%s.%s' is forbidden"
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98 % (module, name))
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99
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100 # custom module in Galaxy-ML
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101 if module in self.custom_modules:
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102 cutom_module = sys.modules.get(module, None)
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103 if cutom_module:
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104 return getattr(cutom_module, name)
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105 else:
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106 raise pickle.UnpicklingError("Module %s' is not imported"
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107 % module)
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108
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109 # For objects from outside libraries, it's necessary to verify
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110 # both module and name. Currently only a blacklist checker
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111 # is working.
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112 # TODO: replace with a whitelist checker.
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113 good_names = self.good_names
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114 pk_whitelist = self.pk_whitelist
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115 if re.match(r'^[a-zA-Z_][a-zA-Z0-9_]*$', name):
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116 fullname = module + '.' + name
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117 if (fullname in good_names)\
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118 or (module.startswith(('sklearn.', 'xgboost.', 'skrebate.',
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119 'imblearn.', 'mlxtend.', 'numpy.'))
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120 or module == 'numpy'):
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121 if fullname not in (pk_whitelist['SK_NAMES'] +
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122 pk_whitelist['SKR_NAMES'] +
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123 pk_whitelist['XGB_NAMES'] +
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124 pk_whitelist['NUMPY_NAMES'] +
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125 pk_whitelist['IMBLEARN_NAMES'] +
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126 pk_whitelist['MLXTEND_NAMES'] +
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127 good_names):
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128 # raise pickle.UnpicklingError
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129 print("Warning: global %s is not in pickler whitelist "
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130 "yet and will loss support soon. Contact tool "
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131 "author or leave a message at github.com" % fullname)
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132 mod = sys.modules[module]
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133 return getattr(mod, name)
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134
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135 raise pickle.UnpicklingError("global '%s' is forbidden" % fullname)
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136
21
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137
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138 def load_model(file):
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139 """Load pickled object with `_SafePicker`
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140 """
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141 return _SafePickler(file).load()
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142
20
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143
24
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144 def read_columns(f, c=None, c_option='by_index_number',
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145 return_df=False, **args):
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146 """Return array from a tabular dataset by various columns selection
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147 """
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148 data = pandas.read_csv(f, **args)
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149 if c_option == 'by_index_number':
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150 cols = list(map(lambda x: x - 1, c))
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151 data = data.iloc[:, cols]
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152 if c_option == 'all_but_by_index_number':
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153 cols = list(map(lambda x: x - 1, c))
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154 data.drop(data.columns[cols], axis=1, inplace=True)
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155 if c_option == 'by_header_name':
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156 cols = [e.strip() for e in c.split(',')]
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157 data = data[cols]
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158 if c_option == 'all_but_by_header_name':
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159 cols = [e.strip() for e in c.split(',')]
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160 data.drop(cols, axis=1, inplace=True)
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161 y = data.values
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162 if return_df:
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163 return y, data
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164 else:
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165 return y
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166
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167
24
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168 def feature_selector(inputs, X=None, y=None):
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169 """generate an instance of sklearn.feature_selection classes
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170
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171 Parameters
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172 ----------
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173 inputs : dict
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174 From galaxy tool parameters.
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175 X : array
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176 Containing training features.
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177 y : array or list
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178 Target values.
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179 """
23
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180 selector = inputs['selected_algorithm']
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181 if selector != 'DyRFECV':
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182 selector = getattr(sklearn.feature_selection, selector)
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183 options = inputs['options']
19
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184
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185 if inputs['selected_algorithm'] == 'SelectFromModel':
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
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diff changeset
186 if not options['threshold'] or options['threshold'] == 'None':
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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187 options['threshold'] = None
23
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188 else:
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diff changeset
189 try:
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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190 options['threshold'] = float(options['threshold'])
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191 except ValueError:
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192 pass
19
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193 if inputs['model_inputter']['input_mode'] == 'prefitted':
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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194 model_file = inputs['model_inputter']['fitted_estimator']
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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195 with open(model_file, 'rb') as model_handler:
21
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196 fitted_estimator = load_model(model_handler)
19
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197 new_selector = selector(fitted_estimator, prefit=True, **options)
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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198 else:
23
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199 estimator_json = inputs['model_inputter']['estimator_selector']
19
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200 estimator = get_estimator(estimator_json)
24
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201 check_feature_importances = try_get_attr(
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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202 'feature_selectors', 'check_feature_importances')
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203 estimator = check_feature_importances(estimator)
19
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204 new_selector = selector(estimator, **options)
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205
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206 elif inputs['selected_algorithm'] == 'RFE':
23
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207 step = options.get('step', None)
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208 if step and step >= 1.0:
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209 options['step'] = int(step)
24
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210 estimator = get_estimator(inputs["estimator_selector"])
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211 check_feature_importances = try_get_attr(
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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212 'feature_selectors', 'check_feature_importances')
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213 estimator = check_feature_importances(estimator)
19
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214 new_selector = selector(estimator, **options)
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215
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216 elif inputs['selected_algorithm'] == 'RFECV':
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217 options['scoring'] = get_scoring(options['scoring'])
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218 options['n_jobs'] = N_JOBS
23
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219 splitter, groups = get_cv(options.pop('cv_selector'))
24
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220 if groups is None:
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221 options['cv'] = splitter
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222 else:
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223 options['cv'] = list(splitter.split(X, y, groups=groups))
23
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224 step = options.get('step', None)
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225 if step and step >= 1.0:
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226 options['step'] = int(step)
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227 estimator = get_estimator(inputs['estimator_selector'])
24
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228 check_feature_importances = try_get_attr(
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229 'feature_selectors', 'check_feature_importances')
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230 estimator = check_feature_importances(estimator)
19
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231 new_selector = selector(estimator, **options)
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232
24
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233 elif inputs['selected_algorithm'] == 'DyRFECV':
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234 options['scoring'] = get_scoring(options['scoring'])
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235 options['n_jobs'] = N_JOBS
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diff changeset
236 splitter, groups = get_cv(options.pop('cv_selector'))
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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237 if groups is None:
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238 options['cv'] = splitter
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239 else:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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240 options['cv'] = list(splitter.split(X, y, groups=groups))
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241 step = options.get('step')
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242 if not step or step == 'None':
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243 step = None
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244 else:
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245 step = ast.literal_eval(step)
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246 options['step'] = step
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247 estimator = get_estimator(inputs["estimator_selector"])
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248 check_feature_importances = try_get_attr(
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249 'feature_selectors', 'check_feature_importances')
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250 estimator = check_feature_importances(estimator)
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251 DyRFECV = try_get_attr('feature_selectors', 'DyRFECV')
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252
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253 new_selector = DyRFECV(estimator, **options)
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254
23
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255 elif inputs['selected_algorithm'] == 'VarianceThreshold':
19
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256 new_selector = selector(**options)
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257
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258 else:
23
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259 score_func = inputs['score_func']
19
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260 score_func = getattr(sklearn.feature_selection, score_func)
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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261 new_selector = selector(score_func, **options)
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262
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263 return new_selector
21
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diff changeset
264
19
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265
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266 def get_X_y(params, file1, file2):
24
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267 """Return machine learning inputs X, y from tabluar inputs
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268 """
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269 input_type = (params['selected_tasks']['selected_algorithms']
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270 ['input_options']['selected_input'])
23
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271 if input_type == 'tabular':
24
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272 header = 'infer' if (params['selected_tasks']['selected_algorithms']
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273 ['input_options']['header1']) else None
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274 column_option = (params['selected_tasks']['selected_algorithms']
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275 ['input_options']['column_selector_options_1']
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276 ['selected_column_selector_option'])
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277 if column_option in ['by_index_number', 'all_but_by_index_number',
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278 'by_header_name', 'all_but_by_header_name']:
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279 c = (params['selected_tasks']['selected_algorithms']
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280 ['input_options']['column_selector_options_1']['col1'])
19
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281 else:
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282 c = None
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283 X = read_columns(
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284 file1,
21
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285 c=c,
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286 c_option=column_option,
19
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287 sep='\t',
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288 header=header,
24
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289 parse_dates=True).astype(float)
19
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290 else:
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291 X = mmread(file1)
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292
24
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293 header = 'infer' if (params['selected_tasks']['selected_algorithms']
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294 ['input_options']['header2']) else None
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295 column_option = (params['selected_tasks']['selected_algorithms']
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296 ['input_options']['column_selector_options_2']
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297 ['selected_column_selector_option2'])
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298 if column_option in ['by_index_number', 'all_but_by_index_number',
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299 'by_header_name', 'all_but_by_header_name']:
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300 c = (params['selected_tasks']['selected_algorithms']
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301 ['input_options']['column_selector_options_2']['col2'])
19
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302 else:
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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303 c = None
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304 y = read_columns(
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305 file2,
21
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306 c=c,
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307 c_option=column_option,
19
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308 sep='\t',
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309 header=header,
24
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diff changeset
310 parse_dates=True)
21
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311 y = y.ravel()
24
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312
19
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313 return X, y
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314
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315
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316 class SafeEval(Interpreter):
24
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317 """Customized symbol table for safely literal eval
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318 """
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319 def __init__(self, load_scipy=False, load_numpy=False,
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320 load_estimators=False):
19
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321
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322 # File opening and other unneeded functions could be dropped
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323 unwanted = ['open', 'type', 'dir', 'id', 'str', 'repr']
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324
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325 # Allowed symbol table. Add more if needed.
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326 new_syms = {
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327 'np_arange': getattr(np, 'arange'),
24
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328 'ensemble_ExtraTreesClassifier':
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329 getattr(ensemble, 'ExtraTreesClassifier')
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330 }
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331
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332 syms = make_symbol_table(use_numpy=False, **new_syms)
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333
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334 if load_scipy:
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335 scipy_distributions = scipy.stats.distributions.__dict__
20
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diff changeset
336 for k, v in scipy_distributions.items():
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diff changeset
337 if isinstance(v, (scipy.stats.rv_continuous,
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338 scipy.stats.rv_discrete)):
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diff changeset
339 syms['scipy_stats_' + k] = v
19
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340
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341 if load_numpy:
24
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342 from_numpy_random = [
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343 'beta', 'binomial', 'bytes', 'chisquare', 'choice',
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344 'dirichlet', 'division', 'exponential', 'f', 'gamma',
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345 'geometric', 'gumbel', 'hypergeometric', 'laplace',
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346 'logistic', 'lognormal', 'logseries', 'mtrand',
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347 'multinomial', 'multivariate_normal', 'negative_binomial',
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348 'noncentral_chisquare', 'noncentral_f', 'normal', 'pareto',
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349 'permutation', 'poisson', 'power', 'rand', 'randint',
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350 'randn', 'random', 'random_integers', 'random_sample',
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351 'ranf', 'rayleigh', 'sample', 'seed', 'set_state',
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352 'shuffle', 'standard_cauchy', 'standard_exponential',
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353 'standard_gamma', 'standard_normal', 'standard_t',
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354 'triangular', 'uniform', 'vonmises', 'wald', 'weibull', 'zipf']
19
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355 for f in from_numpy_random:
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356 syms['np_random_' + f] = getattr(np.random, f)
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357
23
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358 if load_estimators:
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diff changeset
359 estimator_table = {
24
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360 'sklearn_svm': getattr(sklearn, 'svm'),
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361 'sklearn_tree': getattr(sklearn, 'tree'),
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362 'sklearn_ensemble': getattr(sklearn, 'ensemble'),
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363 'sklearn_neighbors': getattr(sklearn, 'neighbors'),
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364 'sklearn_naive_bayes': getattr(sklearn, 'naive_bayes'),
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365 'sklearn_linear_model': getattr(sklearn, 'linear_model'),
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366 'sklearn_cluster': getattr(sklearn, 'cluster'),
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367 'sklearn_decomposition': getattr(sklearn, 'decomposition'),
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368 'sklearn_preprocessing': getattr(sklearn, 'preprocessing'),
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369 'sklearn_feature_selection':
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370 getattr(sklearn, 'feature_selection'),
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diff changeset
371 'sklearn_kernel_approximation':
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372 getattr(sklearn, 'kernel_approximation'),
23
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373 'skrebate_ReliefF': getattr(skrebate, 'ReliefF'),
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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374 'skrebate_SURF': getattr(skrebate, 'SURF'),
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375 'skrebate_SURFstar': getattr(skrebate, 'SURFstar'),
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376 'skrebate_MultiSURF': getattr(skrebate, 'MultiSURF'),
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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377 'skrebate_MultiSURFstar': getattr(skrebate, 'MultiSURFstar'),
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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378 'skrebate_TuRF': getattr(skrebate, 'TuRF'),
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379 'xgboost_XGBClassifier': getattr(xgboost, 'XGBClassifier'),
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380 'xgboost_XGBRegressor': getattr(xgboost, 'XGBRegressor'),
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381 'imblearn_over_sampling': getattr(imblearn, 'over_sampling'),
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382 'imblearn_combine': getattr(imblearn, 'combine')
23
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383 }
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diff changeset
384 syms.update(estimator_table)
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385
19
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diff changeset
386 for key in unwanted:
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387 syms.pop(key, None)
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388
24
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diff changeset
389 super(SafeEval, self).__init__(
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diff changeset
390 symtable=syms, use_numpy=False, minimal=False,
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391 no_if=True, no_for=True, no_while=True, no_try=True,
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392 no_functiondef=True, no_ifexp=True, no_listcomp=False,
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393 no_augassign=False, no_assert=True, no_delete=True,
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394 no_raise=True, no_print=True)
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395
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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diff changeset
396
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397 def get_estimator(estimator_json):
24
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398 """Return a sklearn or compatible estimator from Galaxy tool inputs
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399 """
19
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400 estimator_module = estimator_json['selected_module']
23
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401
24
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402 if estimator_module == 'custom_estimator':
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403 c_estimator = estimator_json['c_estimator']
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404 with open(c_estimator, 'rb') as model_handler:
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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405 new_model = load_model(model_handler)
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diff changeset
406 return new_model
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diff changeset
407
24
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diff changeset
408 if estimator_module == "binarize_target":
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409 wrapped_estimator = estimator_json['wrapped_estimator']
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diff changeset
410 with open(wrapped_estimator, 'rb') as model_handler:
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411 wrapped_estimator = load_model(model_handler)
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diff changeset
412 options = {}
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diff changeset
413 if estimator_json['z_score'] is not None:
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414 options['z_score'] = estimator_json['z_score']
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415 if estimator_json['value'] is not None:
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416 options['value'] = estimator_json['value']
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417 options['less_is_positive'] = estimator_json['less_is_positive']
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418 if estimator_json['clf_or_regr'] == 'BinarizeTargetClassifier':
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419 klass = try_get_attr('iraps_classifier',
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420 'BinarizeTargetClassifier')
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diff changeset
421 else:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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422 klass = try_get_attr('iraps_classifier',
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diff changeset
423 'BinarizeTargetRegressor')
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424 return klass(wrapped_estimator, **options)
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diff changeset
425
19
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426 estimator_cls = estimator_json['selected_estimator']
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diff changeset
427
23
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diff changeset
428 if estimator_module == 'xgboost':
24
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diff changeset
429 klass = getattr(xgboost, estimator_cls)
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430 else:
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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431 module = getattr(sklearn, estimator_module)
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diff changeset
432 klass = getattr(module, estimator_cls)
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diff changeset
433
24
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diff changeset
434 estimator = klass()
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diff changeset
435
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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436 estimator_params = estimator_json['text_params'].strip()
23
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diff changeset
437 if estimator_params != '':
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diff changeset
438 try:
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diff changeset
439 safe_eval = SafeEval()
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diff changeset
440 params = safe_eval('dict(' + estimator_params + ')')
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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441 except ValueError:
21
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diff changeset
442 sys.exit("Unsupported parameter input: `%s`" % estimator_params)
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diff changeset
443 estimator.set_params(**params)
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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444 if 'n_jobs' in estimator.get_params():
21
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diff changeset
445 estimator.set_params(n_jobs=N_JOBS)
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diff changeset
446
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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diff changeset
447 return estimator
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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diff changeset
448
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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diff changeset
449
23
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diff changeset
450 def get_cv(cv_json):
24
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diff changeset
451 """ Return CV splitter from Galaxy tool inputs
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diff changeset
452
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diff changeset
453 Parameters
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diff changeset
454 ----------
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
455 cv_json : dict
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
456 From Galaxy tool inputs.
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
457 e.g.:
23
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
458 {
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
459 'selected_cv': 'StratifiedKFold',
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
460 'n_splits': 3,
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
461 'shuffle': True,
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
462 'random_state': 0
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
463 }
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
464 """
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
465 cv = cv_json.pop('selected_cv')
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
466 if cv == 'default':
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
467 return cv_json['n_splits'], None
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
468
24
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
469 groups = cv_json.pop('groups_selector', None)
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
470 if groups is not None:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
471 infile_g = groups['infile_g']
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
472 header = 'infer' if groups['header_g'] else None
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
473 column_option = (groups['column_selector_options_g']
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
474 ['selected_column_selector_option_g'])
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
475 if column_option in ['by_index_number', 'all_but_by_index_number',
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
476 'by_header_name', 'all_but_by_header_name']:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
477 c = groups['column_selector_options_g']['col_g']
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
478 else:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
479 c = None
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
480 groups = read_columns(
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
481 infile_g,
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
482 c=c,
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
483 c_option=column_option,
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
484 sep='\t',
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
485 header=header,
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
486 parse_dates=True)
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
487 groups = groups.ravel()
23
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
488
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
489 for k, v in cv_json.items():
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
490 if v == '':
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
491 cv_json[k] = None
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
492
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
493 test_fold = cv_json.get('test_fold', None)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
494 if test_fold:
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
495 if test_fold.startswith('__ob__'):
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
496 test_fold = test_fold[6:]
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
497 if test_fold.endswith('__cb__'):
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
498 test_fold = test_fold[:-6]
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
499 cv_json['test_fold'] = [int(x.strip()) for x in test_fold.split(',')]
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
500
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
501 test_size = cv_json.get('test_size', None)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
502 if test_size and test_size > 1.0:
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
503 cv_json['test_size'] = int(test_size)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
504
24
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
505 if cv == 'OrderedKFold':
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
506 cv_class = try_get_attr('model_validations', 'OrderedKFold')
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
507 elif cv == 'RepeatedOrderedKFold':
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
508 cv_class = try_get_attr('model_validations', 'RepeatedOrderedKFold')
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
509 else:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
510 cv_class = getattr(model_selection, cv)
23
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
511 splitter = cv_class(**cv_json)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
512
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
513 return splitter, groups
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
514
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
515
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
516 # needed when sklearn < v0.20
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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diff changeset
517 def balanced_accuracy_score(y_true, y_pred):
24
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
518 """Compute balanced accuracy score, which is now available in
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
519 scikit-learn from v0.20.0.
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
520 """
23
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
521 C = metrics.confusion_matrix(y_true, y_pred)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
522 with np.errstate(divide='ignore', invalid='ignore'):
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
523 per_class = np.diag(C) / C.sum(axis=1)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
524 if np.any(np.isnan(per_class)):
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
525 warnings.warn('y_pred contains classes not in y_true')
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
526 per_class = per_class[~np.isnan(per_class)]
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff changeset
527 score = np.mean(per_class)
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
528 return score
19
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
529
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
530
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
531 def get_scoring(scoring_json):
24
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
532 """Return single sklearn scorer class
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
533 or multiple scoers in dictionary
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
534 """
23
4ba68dd788b3 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
parents: 21
diff changeset
535 if scoring_json['primary_scoring'] == 'default':
19
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
536 return None
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
537
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
538 my_scorers = metrics.SCORERS
24
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
539 my_scorers['binarize_auc_scorer'] =\
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
540 try_get_attr('iraps_classifier', 'binarize_auc_scorer')
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
541 my_scorers['binarize_average_precision_scorer'] =\
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
542 try_get_attr('iraps_classifier', 'binarize_average_precision_scorer')
19
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
bgruening
parents:
diff changeset
543 if 'balanced_accuracy' not in my_scorers:
24
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
544 my_scorers['balanced_accuracy'] =\
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
parents: 23
diff changeset
545 metrics.make_scorer(balanced_accuracy_score)
19
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546
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547 if scoring_json['secondary_scoring'] != 'None'\
24
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548 and scoring_json['secondary_scoring'] !=\
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549 scoring_json['primary_scoring']:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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550 return_scoring = {}
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551 primary_scoring = scoring_json['primary_scoring']
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552 return_scoring[primary_scoring] = my_scorers[primary_scoring]
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addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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553 for scorer in scoring_json['secondary_scoring'].split(','):
addf8e0f2654 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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554 if scorer != scoring_json['primary_scoring']:
24
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555 return_scoring[scorer] = my_scorers[scorer]
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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556 return return_scoring
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557
21
d4d2c915adb8 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1
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558 return my_scorers[scoring_json['primary_scoring']]
24
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559
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560
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561 def get_search_params(estimator):
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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562 """Format the output of `estimator.get_params()`
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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563 """
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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564 params = estimator.get_params()
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565 results = []
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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566 for k, v in params.items():
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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567 # params below won't be shown for search in the searchcv tool
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568 keywords = ('n_jobs', 'pre_dispatch', 'memory', 'steps',
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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569 'nthread', 'verbose')
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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570 if k.endswith(keywords):
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571 results.append(['*', k, k+": "+repr(v)])
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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572 else:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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573 results.append(['@', k, k+": "+repr(v)])
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574 results.append(
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575 ["", "Note:",
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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576 "@, params eligible for search in searchcv tool."])
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
577
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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578 return results
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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579
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580
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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581 def try_get_attr(module, name):
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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diff changeset
582 """try to get attribute from a custom module
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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diff changeset
583
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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diff changeset
584 Parameters
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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585 ----------
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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586 module : str
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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587 Module name
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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diff changeset
588 name : str
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
589 Attribute (class/function) name.
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bgruening
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diff changeset
590
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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diff changeset
591 Returns
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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592 -------
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
bgruening
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diff changeset
593 class or function
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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594 """
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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595 mod = sys.modules.get(module, None)
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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596 if mod:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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597 return getattr(mod, name)
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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598 else:
97b467e06354 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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599 raise Exception("No module named %s." % module)