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1 <?xml version="1.0" ?>
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2 <tool id="qiime_sample-classifier_split-table" name="qiime sample-classifier split-table" version="2019.4">
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3 <description> - Split a feature table into training and testing sets.</description>
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4 <requirements>
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5 <requirement type="package" version="2019.4">qiime2</requirement>
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6 </requirements>
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7 <command><![CDATA[
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8 qiime sample-classifier split-table
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9
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10 --i-table=$itable
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11 --m-metadata-column="$mmetadatacolumn"
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12
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13
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14
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15 #if $input_files_mmetadatafile:
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16 #def list_dict_to_string(list_dict):
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17 #set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
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18 #for d in list_dict[1:]:
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19 #set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name')
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20 #end for
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21 #return $file_list
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22 #end def
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23
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24 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile)
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25 #end if
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26
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27
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28
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29 #if $ptestsize:
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30 --p-test-size=$ptestsize
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31 #end if
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32
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33 #if str($prandomstate):
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34 --p-random-state="$prandomstate"
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35 #end if
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36
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37 #if $pnostratify:
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38 --p-no-stratify
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39 #end if
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40
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41 #if str($pmissingsamples) != 'None':
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42 --p-missing-samples=$pmissingsamples
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43 #end if
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44
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45 --o-training-table=otrainingtable
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46 --o-test-table=otesttable
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47 ;
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48 cp otrainingtable.qza $otrainingtable;
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49 cp otesttable.qza $otesttable;
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50 ]]></command>
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51 <inputs>
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52 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data"/>
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53 <param label="--m-metadata-column: COLUMN MetadataColumn[Numeric | Categorical] Numeric metadata column to use as prediction target. [required]" name="mmetadatacolumn" optional="False" type="text"/>
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54 <param label="--p-test-size: PROPORTION Range(0.0, 1.0, inclusive_start=False) Fraction of input samples to exclude from training set and use for classifier testing. [default: 0.2]" name="ptestsize" optional="True" type="float" value="0.2" min="0" max="1" exclusive_end="True"/>
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55 <param label="--p-random-state: INTEGER Seed used by random number generator. [optional]" name="prandomstate" optional="True" type="integer"/>
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56 <param label="--p-no-stratify: Evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples. [default: False]" name="pnostratify" selected="False" type="boolean"/>
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57 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
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58 <option selected="True" value="None">Selection is Optional</option>
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59 <option value="error">error</option>
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60 <option value="ignore">ignore</option>
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61 </param>
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62
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63 <repeat name="input_files_mmetadatafile" optional="True" title="--m-metadata-file">
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64 <param label="--m-metadata-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [optional]" name="additional_input" type="data" format="tabular,qza,no_unzip.zip" />
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65 </repeat>
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66
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67 </inputs>
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68 <outputs>
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69 <data format="qza" label="${tool.name} on ${on_string}: trainingtable.qza" name="otrainingtable"/>
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70 <data format="qza" label="${tool.name} on ${on_string}: testtable.qza" name="otesttable"/>
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71 </outputs>
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72 <help><![CDATA[
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73 Split a feature table into training and testing sets.
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74 #####################################################
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75
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76 Split a feature table into training and testing sets. By default stratifies
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77 training and test sets on a metadata column, such that values in that
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78 column are evenly represented across training and test sets.
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79
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80 Parameters
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81 ----------
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82 table : FeatureTable[Frequency]
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83 Feature table containing all features that should be used for target
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84 prediction.
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85 metadata : MetadataColumn[Numeric | Categorical]
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86 Numeric metadata column to use as prediction target.
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87 test_size : Float % Range(0.0, 1.0, inclusive_start=False), optional
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88 Fraction of input samples to exclude from training set and use for
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89 classifier testing.
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90 random_state : Int, optional
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91 Seed used by random number generator.
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92 stratify : Bool, optional
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93 Evenly stratify training and test data among metadata categories. If
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94 True, all values in column must match at least two samples.
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95 missing_samples : Str % Choices('error', 'ignore'), optional
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96 How to handle missing samples in metadata. "error" will fail if missing
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97 samples are detected. "ignore" will cause the feature table and
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98 metadata to be filtered, so that only samples found in both files are
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99 retained.
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100
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101 Returns
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102 -------
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103 training_table : FeatureTable[Frequency]
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104 Feature table containing training samples
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105 test_table : FeatureTable[Frequency]
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106 Feature table containing test samples
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107 ]]></help>
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108 <macros>
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109 <import>qiime_citation.xml</import>
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110 </macros>
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111 <expand macro="qiime_citation"/>
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112 </tool>
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