comparison pairwise_metrics.xml @ 4:1573e8255a34 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
author bgruening
date Fri, 16 Feb 2018 09:13:01 -0500
parents 18afd0c1cc56
children 49e5ce162e0e
comparison
equal deleted inserted replaced
3:f8cd85c496c9 4:1573e8255a34
50 metric_res = pairwise_distances_argmin(X,Y,**options) 50 metric_res = pairwise_distances_argmin(X,Y,**options)
51 else: 51 else:
52 my_function = getattr(pairwise, metric_function) 52 my_function = getattr(pairwise, metric_function)
53 metric_res = my_function(X,Y,**options) 53 metric_res = my_function(X,Y,**options)
54 54
55 pandas.DataFrame(metric_res).to_csv(path_or_buf = "$outfile", sep="\t", index=False, header=False) 55 pandas.DataFrame(metric_res).to_csv(path_or_buf = "$outfile", sep="\t", index=False, header=False)
56 ]]> 56 ]]>
57 </configfile> 57 </configfile>
58 </configfiles> 58 </configfiles>
59 <inputs> 59 <inputs>
60 <conditional name="input_type"> 60 <conditional name="input_type">
74 <section name="options" title="Advanced Options" expanded="False"> 74 <section name="options" title="Advanced Options" expanded="False">
75 <expand macro="gamma" help_text="Floating point scaling parameter of the chi2 kernel. "/> 75 <expand macro="gamma" help_text="Floating point scaling parameter of the chi2 kernel. "/>
76 </section> 76 </section>
77 </when> 77 </when>
78 <when value="linear_kernel"> 78 <when value="linear_kernel">
79 </when> 79 </when>
80 <when value="manhattan_distances"> 80 <when value="manhattan_distances">
81 <section name="options" title="Advanced Options" expanded="False"> 81 <section name="options" title="Advanced Options" expanded="False">
82 <param argument="sum_over_features" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Sum over features" help="If True, return the pairwise distance matrix, else return the componentwise L1 pairwise-distances. "/> 82 <param argument="sum_over_features" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Sum over features" help="If True, return the pairwise distance matrix, else return the componentwise L1 pairwise-distances. "/>
83 </section> 83 </section>
84 </when> 84 </when>
117 <conditional name="metric_functions"> 117 <conditional name="metric_functions">
118 <expand macro="sparse_pairwise_metric_functions"/> 118 <expand macro="sparse_pairwise_metric_functions"/>
119 <expand macro="sparse_pairwise_condition"/> 119 <expand macro="sparse_pairwise_condition"/>
120 <expand macro="argmin_distance_condition"/> 120 <expand macro="argmin_distance_condition"/>
121 </conditional> 121 </conditional>
122 </when> 122 </when>
123 </conditional> 123 </conditional>
124 </inputs> 124 </inputs>
125 <outputs> 125 <outputs>
126 <data format="tabular" name="outfile"/> 126 <data format="tabular" name="outfile"/>
127 </outputs> 127 </outputs>
130 <param name="selected_input_type" value="tabular"/> 130 <param name="selected_input_type" value="tabular"/>
131 <param name="selected_metric_function" value="rbf_kernel"/> 131 <param name="selected_metric_function" value="rbf_kernel"/>
132 <param name="input_files_0|input" value="test.tabular" ftype="tabular"/> 132 <param name="input_files_0|input" value="test.tabular" ftype="tabular"/>
133 <param name="input_files_1|input" value="test2.tabular" ftype="tabular"/> 133 <param name="input_files_1|input" value="test2.tabular" ftype="tabular"/>
134 <param name="gamma" value="0.5"/> 134 <param name="gamma" value="0.5"/>
135 <output name="outfile" file="pw_metric01.tabular"/> 135 <output name="outfile" file="pw_metric01.tabular" compare="sim_size" />
136 </test> 136 </test>
137 <test> 137 <test>
138 <param name="selected_input_type" value="tabular"/> 138 <param name="selected_input_type" value="tabular"/>
139 <param name="selected_metric_function" value="pairwise_distances"/> 139 <param name="selected_metric_function" value="pairwise_distances"/>
140 <param name="metric" value="manhattan"/> 140 <param name="metric" value="manhattan"/>
154 **What it does** 154 **What it does**
155 155
156 This tool consists of utilities to evaluate pairwise distances or affinity of sets of samples. 156 This tool consists of utilities to evaluate pairwise distances or affinity of sets of samples.
157 The base utilities are contained in Scikit-learn python library in sklearn.metrics package. 157 The base utilities are contained in Scikit-learn python library in sklearn.metrics package.
158 This module contains both distance metrics and kernels. For a brief summary, please refer to: 158 This module contains both distance metrics and kernels. For a brief summary, please refer to:
159 http://scikit-learn.org/stable/modules/metrics.html#metrics 159 http://scikit-learn.org/stable/modules/metrics.html#metrics
160 ]]> 160 ]]>
161 </help> 161 </help>
162 <expand macro="sklearn_citation"/> 162 <expand macro="sklearn_citation"/>
163 </tool> 163 </tool>