Mercurial > repos > bgruening > sklearn_feature_selection

annotate feature_selection.xml @ 17:2bbbac61e48d draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
author bgruening
date Sun, 30 Dec 2018 01:57:11 -0500
parents 026667802750
children ec25331946b8
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2eb90e73f0d5 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 79fe42239dcf077b13f85cbcd6c6e30d7e1e4832
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1 <tool id="sklearn_feature_selection" name="Feature Selection" version="@VERSION@.1">
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2 <description>module, including univariate filter selection methods and recursive feature elimination algorithm</description>
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3 <macros>
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4 <import>main_macros.xml</import>
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5 </macros>
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6 <expand macro="python_requirements"/>
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7 <expand macro="macro_stdio"/>
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8 <version_command>echo "@VERSION@"</version_command>
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9 <command>
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10 <![CDATA[
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11 python "$feature_selection_script" '$inputs'
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12 ]]>
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13 </command>
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14 <configfiles>
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15 <inputs name="inputs" />
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16 <configfile name="feature_selection_script">
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17 <![CDATA[
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18 import json
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19 import sklearn.feature_selection
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20
17
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21 with open('$__tool_directory__/sk_whitelist.json', 'r') as f:
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22 sk_whitelist = json.load(f)
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23 exec(open('$__tool_directory__/utils.py').read(), globals())
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25 warnings.simplefilter('ignore')
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27 safe_eval = SafeEval()
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28
0
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29 input_json_path = sys.argv[1]
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30 with open(input_json_path, 'r') as param_handler:
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31 params = json.load(param_handler)
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33 #handle cheetah
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34 #if $fs_algorithm_selector.selected_algorithm == 'SelectFromModel'\
2bbbac61e48d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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35 and $fs_algorithm_selector.model_inputter.input_mode == 'prefitted':
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36 params['fs_algorithm_selector']['model_inputter']['fitted_estimator'] =\
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37 '$fs_algorithm_selector.model_inputter.fitted_estimator'
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38 #end if
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39
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40 #if $fs_algorithm_selector.selected_algorithm == 'SelectFromModel'\
2bbbac61e48d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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41 and $fs_algorithm_selector.model_inputter.input_mode == 'new'\
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42 and $fs_algorithm_selector.model_inputter.estimator_selector.selected_module == 'customer_estimator':
2bbbac61e48d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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43 params['fs_algorithm_selector']['model_inputter']['estimator_selector']['c_estimator'] =\
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44 '$fs_algorithm_selector.model_inputter.estimator_selector.c_estimator'
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45 #end if
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46
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47 #if $fs_algorithm_selector.selected_algorithm in ['RFE', 'RFECV']\
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48 and $fs_algorithm_selector.estimator_selector.selected_module == 'customer_estimator':
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49 params['fs_algorithm_selector']['estimator_selector']['c_estimator'] =\
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50 '$fs_algorithm_selector.estimator_selector.c_estimator'
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51 #end if
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52
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53 # Read features
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54 features_has_header = params['input_options']['header1']
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55 input_type = params['input_options']['selected_input']
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56 if input_type == 'tabular':
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57 header = 'infer' if features_has_header else None
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58 column_option = params['input_options']['column_selector_options_1']['selected_column_selector_option']
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59 if column_option in ['by_index_number', 'all_but_by_index_number', 'by_header_name', 'all_but_by_header_name']:
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60 c = params['input_options']['column_selector_options_1']['col1']
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61 else:
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62 c = None
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63 X, input_df = read_columns(
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64 '$input_options.infile1',
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65 c = c,
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66 c_option = column_option,
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67 return_df = True,
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68 sep='\t',
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69 header=header,
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70 parse_dates=True
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71 )
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72 else:
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73 X = mmread('$input_options.infile1')
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74
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75 # Read labels
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76 header = 'infer' if params['input_options']['header2'] else None
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77 column_option = params['input_options']['column_selector_options_2']['selected_column_selector_option2']
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78 if column_option in ['by_index_number', 'all_but_by_index_number', 'by_header_name', 'all_but_by_header_name']:
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79 c = params['input_options']['column_selector_options_2']['col2']
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80 else:
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81 c = None
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82 y = read_columns(
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83 '$input_options.infile2',
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84 c = c,
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85 c_option = column_option,
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86 sep='\t',
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87 header=header,
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88 parse_dates=True
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89 )
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90 y=y.ravel()
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91
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92 # Create feature selector
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93 new_selector = feature_selector(params['fs_algorithm_selector'])
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94 if params['fs_algorithm_selector']['selected_algorithm'] != 'SelectFromModel'\
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95 or params['fs_algorithm_selector']['model_inputter']['input_mode'] != 'prefitted' :
2
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96 new_selector.fit(X, y)
0
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97
2
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98 ## Transform to select features
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99 selected_names = None
0
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100
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101 res = new_selector.transform(X)
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102 if features_has_header:
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103 selected_names = input_df.columns[new_selector.get_support(indices=True)]
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104 res = pandas.DataFrame(res, columns = selected_names)
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105 res.to_csv(path_or_buf='$outfile', sep='\t', index=False)
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106
17
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107 #if $save:
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108 with open('$outfile_selector', 'wb') as output_handler:
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109 pickle.dump(new_selector, output_handler, pickle.HIGHEST_PROTOCOL)
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110 #end if
0
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111
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112 ]]>
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113 </configfile>
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114 </configfiles>
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115 <inputs>
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116 <expand macro="feature_selection_fs"/>
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117 <param name="save" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Save the fitted selector?"/>
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118 <expand macro="sl_mixed_input"/>
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119 </inputs>
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120 <outputs>
17
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121 <data format="tabular" name="outfile" />
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122 <data format="zip" name="outfile_selector" label="${fs_algorithm_selector.selected_algorithm}">
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123 <filter>save</filter>
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124 </data>
0
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125 </outputs>
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126 <tests>
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127 <test>
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128 <param name="selected_algorithm" value="SelectFromModel"/>
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129 <param name="input_mode" value="new"/>
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130 <param name="selected_module" value="ensemble"/>
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131 <param name="selected_estimator" value="RandomForestRegressor"/>
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132 <param name="text_params" value="n_estimators=10, random_state=10"/>
10
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133 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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134 <param name="header1" value="false"/>
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135 <param name="col1" value="1,2,3,4,5"/>
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136 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
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137 <param name="col2" value="6"/>
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138 <param name="header2" value="false"/>
0
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139 <output name="outfile" file="feature_selection_result01"/>
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140 </test>
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141 <test>
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142 <param name="selected_algorithm" value="GenericUnivariateSelect"/>
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143 <param name="param" value="20"/>
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144 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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145 <param name="header1" value="True"/>
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146 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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147 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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148 <param name="col2" value="1"/>
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149 <param name="header2" value="True"/>
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150 <output name="outfile" file="feature_selection_result02"/>
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151 </test>
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152 <test>
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153 <param name="selected_algorithm" value="SelectPercentile"/>
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154 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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155 <param name="header1" value="True"/>
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156 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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157 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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158 <param name="col2" value="1"/>
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159 <param name="header2" value="True"/>
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160 <output name="outfile" file="feature_selection_result03"/>
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161 </test>
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162 <test>
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163 <param name="selected_algorithm" value="SelectKBest"/>
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164 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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165 <param name="header1" value="True"/>
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166 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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167 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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168 <param name="col2" value="1"/>
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169 <param name="header2" value="True"/>
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170 <output name="outfile" file="feature_selection_result04"/>
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171 </test>
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172 <test>
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173 <param name="selected_algorithm" value="SelectFpr"/>
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174 <param name="alpha" value="0.05"/>
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175 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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176 <param name="header1" value="True"/>
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177 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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178 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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179 <param name="col2" value="1"/>
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180 <param name="header2" value="True"/>
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181 <output name="outfile" file="feature_selection_result05"/>
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182 </test>
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183 <test>
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184 <param name="selected_algorithm" value="SelectFdr"/>
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185 <param name="alpha" value="0.05"/>
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186 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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187 <param name="header1" value="True"/>
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188 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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189 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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190 <param name="col2" value="1"/>
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191 <param name="header2" value="True"/>
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192 <output name="outfile" file="feature_selection_result06"/>
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193 </test>
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194 <test>
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195 <param name="selected_algorithm" value="SelectFwe"/>
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196 <param name="alpha" value="0.05"/>
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197 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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198 <param name="header1" value="True"/>
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199 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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200 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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201 <param name="col2" value="1"/>
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202 <param name="header2" value="True"/>
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203 <output name="outfile" file="feature_selection_result07"/>
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204 </test>
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205 <test>
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206 <param name="selected_algorithm" value="RFE"/>
10
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207 <param name="input_mode" value="new"/>
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208 <param name="selected_module" value="ensemble"/>
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209 <param name="selected_estimator" value="RandomForestRegressor"/>
13
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210 <param name="text_params" value="n_estimators=10, random_state=10"/>
10
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211 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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212 <param name="header1" value="false"/>
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213 <param name="col1" value="1,2,3,4,5"/>
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214 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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215 <param name="col2" value="6"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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216 <param name="header2" value="false"/>
0
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217 <output name="outfile" file="feature_selection_result08"/>
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218 </test>
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219 <test>
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220 <param name="selected_algorithm" value="RFECV"/>
10
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221 <param name="input_mode" value="new"/>
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222 <param name="selected_module" value="ensemble"/>
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223 <param name="selected_estimator" value="RandomForestRegressor"/>
13
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224 <param name="text_params" value="n_estimators=10, random_state=10"/>
10
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225 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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226 <param name="header1" value="false"/>
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227 <param name="col1" value="1,2,3,4,5"/>
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228 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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229 <param name="col2" value="6"/>
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230 <param name="header2" value="false"/>
0
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231 <output name="outfile" file="feature_selection_result09"/>
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232 </test>
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233 <test>
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234 <param name="selected_algorithm" value="VarianceThreshold"/>
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235 <param name="threshold" value="0.1"/>
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236 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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237 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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238 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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239 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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240 <param name="col2" value="1"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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241 <param name="header2" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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242 <output name="outfile" file="feature_selection_result10"/>
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243 </test>
6
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244 <test>
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245 <param name="selected_algorithm" value="SelectKBest"/>
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246 <param name="k" value="3"/>
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247 <param name="infile1" value="test3.tabular" ftype="tabular"/>
b0d554b38770 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit cd4a8b019168acd5a513c57a1b1f380622f230f6
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248 <param name="header1" value="True"/>
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249 <param name="selected_column_selector_option" value="all_but_by_header_name"/>
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250 <param name="col1" value="target"/>
b0d554b38770 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit cd4a8b019168acd5a513c57a1b1f380622f230f6
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251 <param name="infile2" value="test3.tabular" ftype="tabular"/>
b0d554b38770 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit cd4a8b019168acd5a513c57a1b1f380622f230f6
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252 <param name="header2" value="True"/>
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253 <param name="selected_column_selector_option2" value="by_header_name"/>
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254 <param name="col2" value="target"/>
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255 <output name="outfile" file="feature_selection_result11"/>
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256 </test>
10
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257 <test>
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258 <param name="selected_algorithm" value="SelectFromModel"/>
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259 <param name="input_mode" value="prefitted"/>
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260 <param name="fitted_estimator" value="rfr_model01" ftype="zip"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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261 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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262 <param name="header1" value="false"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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263 <param name="col1" value="1,2,3,4,5"/>
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264 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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265 <param name="col2" value="1"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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266 <param name="header2" value="false"/>
96f9b73327f2 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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267 <output name="outfile" file="feature_selection_result12"/>
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268 </test>
0
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269 </tests>
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270 <help>
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271 <![CDATA[
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272 **What it does**
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273 This tool provides several loss, score, and utility functions to measure classification performance. Some metrics might require probability estimates of the positive class, confidence values, or binary decisions values. This tool is based on
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274 sklearn.metrics package.
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275 For information about classification metric functions and their parameter settings please refer to `Scikit-learn classification metrics`_.
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276
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277 .. _`Scikit-learn classification metrics`: http://scikit-learn.org/stable/modules/model_evaluation.html#classification-metrics
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278 ]]>
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279 </help>
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280 <expand macro="sklearn_citation">
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281 <expand macro="skrebate_citation"/>
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282 <expand macro="xgboost_citation"/>
dc411a215138 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cf3d813ec755166ee0bd517b4ecbbd4f84d4df1
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283 </expand>
0
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284 </tool>