Mercurial > repos > bgruening > sklearn_data_preprocess

annotate pre_process.xml @ 31:eb79bde99328 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author bgruening
date Mon, 16 Dec 2019 05:15:58 -0500
parents 685046e0381a
children 0e5fcf7ddc75
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1 <tool id="sklearn_data_preprocess" name="Preprocess" version="@VERSION@">
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2 <description>raw feature vectors into standardized datasets</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 "$pre_processor_script" '$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="pre_processor_script">
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17 <![CDATA[
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18 import sys
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19 import json
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20 import pandas
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21 import pickle
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23 from scipy.io import mmread
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24 from scipy.io import mmwrite
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25 from sklearn import preprocessing
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26 from galaxy_ml.utils import read_columns, SafeEval
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29 safe_eval = SafeEval()
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31 input_json_path = sys.argv[1]
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32 with open(input_json_path, "r") as param_handler:
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33 params = json.load(param_handler)
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34
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35 #if $input_type.selected_input_type == "sparse":
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36 X = mmread("$infile")
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37 #else:
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38 header = 'infer' if params["input_type"]["header1"] else None
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39 column_option = params["input_type"]["column_selector_options_1"]["selected_column_selector_option"]
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40 if column_option in ["by_index_number", "all_but_by_index_number", "by_header_name", "all_but_by_header_name"]:
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41 c = params["input_type"]["column_selector_options_1"]["col1"]
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42 else:
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43 c = None
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44 X, input_df = read_columns(
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45 "$input_type.infile",
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46 c=c,
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47 c_option=column_option,
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48 return_df=True,
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49 sep='\t',
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50 header=header,
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51 parse_dates=True,
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52 encoding=None,
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eb79bde99328 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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53 index_col=None)
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54 X = X.astype(float)
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55 #end if
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56
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57 preprocessor = params["input_type"]["pre_processors"]["selected_pre_processor"]
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58 options = params["input_type"]["pre_processors"]["options"]
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59 if 'feature_range' in options:
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60 feature_range = safe_eval(options['feature_range'].strip())
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61 if not feature_range:
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62 feature_range = (0, 1)
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63 options['feature_range'] = feature_range
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64
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65 my_class = getattr(preprocessing, preprocessor)
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66 estimator = my_class(**options)
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67 estimator.fit(X)
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68 result = estimator.transform(X)
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69
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70 #if $input_type.selected_input_type == "sparse":
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71 with open("$outfile_transform", "wb") as transform_handler:
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72 mmwrite(transform_handler, result)
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73 #else:
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74 columns = input_df.columns
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75 if preprocessor == 'PolynomialFeatures':
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76 columns = None
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77 header = False
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78 res = pandas.DataFrame(result, columns=columns)
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79 res.to_csv(path_or_buf = "$outfile_transform", sep="\t",
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80 index=False, header=True if header else False)
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81 #end if
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82
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83 #if $save:
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84 with open("$outfile_fit", 'wb') as out_handler:
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85 pickle.dump(estimator, out_handler, pickle.HIGHEST_PROTOCOL)
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86 #end if
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87 ]]>
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88 </configfile>
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89 </configfiles>
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90 <inputs>
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91 <conditional name="input_type">
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92 <param name="selected_input_type" type="select" label="Select the type of your input data:">
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93 <option value="tabular" selected="true">Tabular</option>
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94 <option value="sparse">Sparse</option>
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95 </param>
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96 <when value="tabular">
15
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97 <param name="infile" type="data" format="tabular" label="Select a tabular file you want to train your preprocessor on its data:" />
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98 <param name="header1" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Does the dataset contain header:" />
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99 <conditional name="column_selector_options_1">
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100 <expand macro="samples_column_selector_options" multiple="true" column_option="selected_column_selector_option" col_name="col1" infile="infile"/>
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101 </conditional>
0
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102 <conditional name="pre_processors">
15
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103 <expand macro="sparse_preprocessors_ext" />
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104 <expand macro="sparse_preprocessor_options_ext" />
0
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105 </conditional>
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106 </when>
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107 <when value="sparse">
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108 <param name="infile" type="data" format="txt" label="Select a sparse representation you want to train your preprocessor on its data:"/>
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109 <conditional name="pre_processors">
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110 <expand macro="sparse_preprocessors"/>
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111 <expand macro="sparse_preprocessor_options"/>
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112 </conditional>
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113 </when>
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114 </conditional>
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115 <param name="save" type="boolean" truevalue="booltrue" falsevalue="boolflase" checked="false"
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116 label="Save the preprocessor"
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117 help="Saves the preprocessor after fitting to the data. The preprocessor can then be passed to other tools and used in later operations."/>
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118 </inputs>
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119 <outputs>
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120 <data format="tabular" name="outfile_transform" from_work_dir="./output"/>
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121 <data format="zip" name="outfile_fit">
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122 <filter>save</filter>
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123 </data>
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124 </outputs>
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125 <tests>
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126 <test>
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127 <param name="infile" value="train.tabular" ftype="tabular"/>
15
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128 <param name="selected_column_selector_option" value="all_columns"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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129 <param name="selected_input_type" value="tabular"/>
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130 <param name="selected_pre_processor" value="KernelCenterer"/>
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131 <param name="save" value="true"/>
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132 <output name="outfile_transform" file="prp_result01" ftype="tabular"/>
23
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133 <output name="outfile_fit" file="prp_model01" ftype="zip" compare="sim_size" delta="5"/>
0
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134 </test>
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135 <test>
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136 <param name="infile" value="train.tabular" ftype="tabular"/>
15
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137 <param name="selected_column_selector_option" value="all_columns"/>
0
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138 <param name="selected_input_type" value="tabular"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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139 <param name="selected_pre_processor" value="MinMaxScaler"/>
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140 <param name="save" value="true"/>
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141 <output name="outfile_transform" file="prp_result02" ftype="tabular"/>
23
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142 <output name="outfile_fit" file="prp_model02" ftype="zip" compare="sim_size" delta="5"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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143 </test>
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144 <test>
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145 <param name="infile" value="train.tabular" ftype="tabular"/>
15
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146 <param name="selected_column_selector_option" value="all_columns"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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147 <param name="selected_input_type" value="tabular"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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148 <param name="selected_pre_processor" value="PolynomialFeatures"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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149 <param name="save" value="true"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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150 <output name="outfile_transform" file="prp_result03" ftype="tabular"/>
23
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151 <output name="outfile_fit" file="prp_model03" ftype="zip" compare="sim_size" delta="5"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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152 </test>
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153 <test>
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154 <param name="infile" value="train.tabular" ftype="tabular"/>
15
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155 <param name="selected_column_selector_option" value="all_columns"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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156 <param name="selected_input_type" value="tabular"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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157 <param name="selected_pre_processor" value="RobustScaler"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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158 <param name="save" value="true"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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159 <output name="outfile_transform" file="prp_result04" ftype="tabular"/>
23
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160 <output name="outfile_fit" file="prp_model04" ftype="zip" compare="sim_size" delta="5"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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161 </test>
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162 <test>
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163 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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164 <param name="selected_input_type" value="sparse"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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165 <param name="selected_pre_processor" value="Binarizer"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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166 <param name="save" value="true"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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167 <output name="outfile_transform" file="prp_result05" ftype="tabular"/>
23
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168 <output name="outfile_fit" file="prp_model05" ftype="zip" compare="sim_size" delta="5"/>
0
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169 </test>
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170 <test>
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171 <param name="infile" value="train.tabular" ftype="tabular"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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172 <param name="selected_input_type" value="tabular"/>
15
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173 <param name="selected_column_selector_option" value="all_columns"/>
0
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174 <param name="selected_pre_processor" value="StandardScaler"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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175 <param name="save" value="true"/>
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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176 <output name="outfile_transform" file="prp_result07" ftype="tabular"/>
23
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177 <output name="outfile_fit" file="prp_model07" ftype="zip" compare="sim_size" delta="5"/>
0
29899feb4d44 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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178 </test>
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179 <test>
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180 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
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181 <param name="selected_input_type" value="sparse"/>
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182 <param name="selected_pre_processor" value="MaxAbsScaler"/>
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183 <param name="save" value="true"/>
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184 <output name="outfile_transform" file="prp_result08" ftype="tabular"/>
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185 <output name="outfile_fit" file="prp_model08" ftype="zip" compare="sim_size" delta="5"/>
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186 </test>
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187 <test>
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188 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
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189 <param name="selected_input_type" value="sparse"/>
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190 <param name="selected_pre_processor" value="Normalizer"/>
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191 <param name="save" value="true"/>
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192 <output name="outfile_transform" file="prp_result09" ftype="tabular"/>
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193 <output name="outfile_fit" file="prp_model09" ftype="zip" compare="sim_size" delta="5"/>
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194 </test>
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195 <test>
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196 <param name="infile" value="regression_X.tabular" ftype="tabular"/>
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197 <param name="header1" value="true"/>
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198 <param name="selected_column_selector_option" value="all_columns"/>
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199 <param name="selected_input_type" value="tabular"/>
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200 <param name="selected_pre_processor" value="MinMaxScaler"/>
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201 <param name="feature_range" value="(-1, 1)"/>
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202 <param name="save" value="false"/>
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203 <output name="outfile_transform" file="prp_result10" ftype="tabular"/>
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204 </test>
0
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205 </tests>
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206 <help>
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207 <![CDATA[
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208 **What it does**
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209
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210 This tool provides several transformer classes to change raw feature vectors into a representation that is more suitable for the downstream estimators. The library is provided by sklearn.preprocessing package.
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211
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212 For information about preprocessing classes and parameter settings please refer to `Scikit-learn preprocessing`_.
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213
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214 .. _`Scikit-learn preprocessing`: http://scikit-learn.org/stable/modules/preprocessing.html
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215 ]]>
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216 </help>
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217 <expand macro="sklearn_citation"/>
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218 </tool>