Mercurial > repos > bgruening > sklearn_pairwise_metrics
annotate pairwise_metrics.xml @ 12:75c2920010b1 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit cd4a8b019168acd5a513c57a1b1f380622f230f6
author | bgruening |
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date | Sun, 01 Jul 2018 03:19:17 -0400 |
parents | dd1ed289bba1 |
children | 0dfaead1d284 |
rev | line source |
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0
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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1 <tool id="sklearn_pairwise_metrics" name="Evaluate pairwise distances" version="@VERSION@"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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2 <description>or compute affinity or kernel for sets of samples</description> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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3 <macros> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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4 <import>main_macros.xml</import> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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5 </macros> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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6 <expand macro="python_requirements"/> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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7 <expand macro="macro_stdio"/> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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8 <version_command>echo "@VERSION@"</version_command> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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9 <command> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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10 <![CDATA[ |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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11 python "$pairwise_script" '$inputs' |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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12 ]]> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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13 </command> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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14 <configfiles> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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15 <inputs name="inputs" /> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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16 <configfile name="pairwise_script"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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17 <![CDATA[ |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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18 import sys |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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19 import json |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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20 import pandas |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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21 import numpy as np |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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22 from sklearn.metrics import pairwise |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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23 from sklearn.metrics import pairwise_distances_argmin |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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24 from scipy.io import mmread |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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25 from scipy.io import mmwrite |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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26 |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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27 input_json_path = sys.argv[1] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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28 params = json.load(open(input_json_path, "r")) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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29 |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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30 options = params["input_type"]["metric_functions"]["options"] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
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31 metric_function = params["input_type"]["metric_functions"]["selected_metric_function"] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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32 |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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33 input_iter = [] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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34 #for $i, $s in enumerate( $input_type.input_files ) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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35 input_index=$i |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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36 input_path="${s.input.file_name}" |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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37 #if $input_type.selected_input_type == "sparse": |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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38 input_iter.append(mmread(open(input_path, 'r'))) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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39 #else: |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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40 input_iter.append(pandas.read_csv(input_path, sep='\t', header=0, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False ).values) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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41 #end if |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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42 #end for |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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43 |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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44 if len(input_iter)>1: |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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45 X = input_iter[0] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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46 Y = input_iter[1] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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47 else: X = Y = input_iter[0] |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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48 |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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49 if metric_function=="pairwise_distances_argmin": |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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50 metric_res = pairwise_distances_argmin(X,Y,**options) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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51 else: |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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52 my_function = getattr(pairwise, metric_function) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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53 metric_res = my_function(X,Y,**options) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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54 |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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55 pandas.DataFrame(metric_res).to_csv(path_or_buf = "$outfile", sep="\t", index=False, header=False) |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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56 ]]> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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57 </configfile> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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58 </configfiles> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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59 <inputs> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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60 <conditional name="input_type"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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61 <param name="selected_input_type" type="select" label="Select the type of your input data:"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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62 <option value="tabular" selected="true">Tabular data (.tabular, .txt)</option> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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63 <option value="sparse">Sparse matrix (.mtx)</option> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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64 </param> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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65 <when value="tabular"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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66 <expand macro="multiple_input" max_num="2" format="tabular"/> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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67 <conditional name="metric_functions"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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68 <expand macro="sparse_pairwise_metric_functions"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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69 <expand macro="pairwise_metric_functions"/> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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70 </expand> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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71 <when value="additive_chi2_kernel"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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72 </when> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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73 <when value="chi2_kernel"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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74 <section name="options" title="Advanced Options" expanded="False"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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75 <expand macro="gamma" help_text="Floating point scaling parameter of the chi2 kernel. "/> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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76 </section> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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77 </when> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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78 <when value="linear_kernel"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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79 </when> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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80 <when value="manhattan_distances"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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81 <section name="options" title="Advanced Options" expanded="False"> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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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. "/> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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83 </section> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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84 </when> |
dd1ed289bba1
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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85 <when value="polynomial_kernel"> |
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86 <section name="options" title="Advanced Options" expanded="False"> |
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87 <expand macro="gamma" default_value=""/> |
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88 <expand macro="degree"/> |
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89 <expand macro="coef0"/> |
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90 </section> |
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91 </when> |
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92 <when value="rbf_kernel"> |
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93 <section name="options" title="Advanced Options" expanded="False"> |
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94 <expand macro="gamma" default_value=""/> |
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95 </section> |
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96 </when> |
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97 <when value="laplacian_kernel"> |
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98 <section name="options" title="Advanced Options" expanded="False"> |
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99 <expand macro="gamma" default_value=""/> |
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100 </section> |
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101 </when> |
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102 <when value="pairwise_kernels"> |
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103 <section name="options" title="Advanced Options" expanded="False"> |
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104 <expand macro="pairwise_kernel_metrics"/> |
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105 </section> |
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106 </when> |
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107 <expand macro="sparse_pairwise_condition"> |
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108 <expand macro="distance_nonsparse_metrics"/> |
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109 </expand> |
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110 <expand macro="argmin_distance_condition"> |
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111 <expand macro="distance_nonsparse_metrics"/> |
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112 </expand> |
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113 </conditional> |
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114 </when> |
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115 <when value="sparse"> |
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116 <expand macro="multiple_input" max_num="2"/> |
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117 <conditional name="metric_functions"> |
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118 <expand macro="sparse_pairwise_metric_functions"/> |
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119 <expand macro="sparse_pairwise_condition"/> |
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120 <expand macro="argmin_distance_condition"/> |
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121 </conditional> |
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122 </when> |
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123 </conditional> |
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124 </inputs> |
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125 <outputs> |
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126 <data format="tabular" name="outfile"/> |
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127 </outputs> |
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128 <tests> |
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129 <test> |
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130 <param name="selected_input_type" value="tabular"/> |
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131 <param name="selected_metric_function" value="rbf_kernel"/> |
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132 <param name="input_files_0|input" value="test.tabular" ftype="tabular"/> |
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133 <param name="input_files_1|input" value="test2.tabular" ftype="tabular"/> |
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134 <param name="gamma" value="0.5"/> |
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135 <output name="outfile" file="pw_metric01.tabular" compare="sim_size" /> |
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136 </test> |
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137 <test> |
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138 <param name="selected_input_type" value="tabular"/> |
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139 <param name="selected_metric_function" value="pairwise_distances"/> |
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140 <param name="metric" value="manhattan"/> |
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141 <param name="input_files_0|input" value="test.tabular" ftype="tabular"/> |
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142 <output name="outfile" file="pw_metric02.tabular"/> |
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143 </test> |
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144 <test> |
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145 <param name="selected_input_type" value="sparse"/> |
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146 <param name="selected_metric_function" value="pairwise_distances"/> |
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147 <param name="metric" value="cosine"/> |
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148 <param name="input_files_0|input" value="sparse.mtx" ftype="txt"/> |
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149 <output name="outfile" file="pw_metric03.tabular"/> |
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150 </test> |
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151 </tests> |
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152 <help> |
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153 <![CDATA[ |
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154 **What it does** |
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155 |
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156 This tool consists of utilities to evaluate pairwise distances or affinity of sets of samples. |
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157 The base utilities are contained in Scikit-learn python library in sklearn.metrics package. |
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158 This module contains both distance metrics and kernels. For a brief summary, please refer to: |
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159 http://scikit-learn.org/stable/modules/metrics.html#metrics |
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160 ]]> |
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161 </help> |
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162 <expand macro="sklearn_citation"/> |
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163 </tool> |