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annotate sparse.xml @ 5:c3c110e8d1f8 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 35fa73d6e9ba8f0789ddfb743d893d950a68af02
author bgruening
date Tue, 10 Apr 2018 15:21:08 -0400
parents 58812a9f83ed
children bf3a5f8a66a2
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58812a9f83ed planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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1 <tool id="scipy_sparse" name="Sparse Matrix Functions" version="@VERSION@">
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2 <description>for manipulating 2-D Scipy sparse numeric data</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 "$sparse_script" '$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="sparse_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 numpy as np
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22 from scipy import sparse
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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
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26 input_json_path = sys.argv[1]
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27 params = json.load(open(input_json_path, "r"))
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28
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29 sparse_iter = []
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30 #for $i, $s in enumerate( $sparse_functions.sparse_inputs )
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31 sparse_index=$i
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32 sparse_path="${s.input.file_name}"
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33 sparse_iter.append(mmread(open(sparse_path, 'r')))
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34 #end for
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35
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36 my_function = getattr(sparse, params["sparse_functions"]["selected_function"])
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37 my_sparse = my_function(sparse_iter)
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38 mmwrite(open("$outfile", 'w+'), my_sparse)
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39 ]]>
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40 </configfile>
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41 </configfiles>
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42 <inputs>
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43 <conditional name="sparse_functions">
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44 <param name="selected_function" type="select" label="Select a task:">
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45 <option value="vstack" selected="true">Stack sparse matrices vertically (vstack)</option>
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46 <option value="hstack">Stack sparse matrices horizontally (hstack)</option>
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47 </param>
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48 <when value="vstack">
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49 <expand macro="multiple_input" name="sparse_inputs"/>
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50 </when>
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51 <when value="hstack">
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52 <expand macro="multiple_input" name="sparse_inputs"/>
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53 </when>
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54 </conditional>
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55 </inputs>
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56 <outputs>
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57 <data format="txt" name="outfile"/>
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58 </outputs>
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59 <tests>
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60 <test>
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61 <param name="selected_function" value="vstack"/>
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62 <param name="sparse_inputs_0|input" value="csr_sparse1.mtx" ftype="txt"/>
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63 <param name="sparse_inputs_1|input" value="csr_sparse2.mtx" ftype="txt"/>
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64 <output name="outfile" file="csr_stack_result01.mtx"/>
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65 </test>
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66 <test>
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67 <param name="selected_function" value="hstack"/>
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68 <param name="sparse_inputs_0|input" value="csc_sparse1.mtx" ftype="txt"/>
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69 <param name="sparse_inputs_1|input" value="csc_sparse2.mtx" ftype="txt"/>
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70 <output name="outfile" file="csc_stack_result01.mtx"/>
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71 </test>
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72 </tests>
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73 <help>
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74 <![CDATA[
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75 **What it does**
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76
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77 This tool stacks sparse matrices horizontally (column wise) or vertically (row wise).
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78 It can handle two different formats:
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79
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80 * Compressed Sparse Column matrix (csc_matrix)
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81
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82 * Compressed Sparse Row matrix (csr_matrix)
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83
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84 Sparse matrices in column format should be stacked horizontally (hstack) , while matrices in row format are stacked vertically (vstack). This tool outputs a single resulting sparse matrix which is compatible with the inputs in format.
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85
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86 **Parameters:** blocks sequence of sparse matrices with compatible shapes format.
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87
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88 For more information please refer to DOI:10.1109/MCSE.2011.37.
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89 ]]>
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90 </help>
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91 <expand macro="scipy_citation"/>
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92 </tool>