Mercurial > repos > florianbegusch > qiime2_suite
comparison qiime2/qiime_sample-classifier_split-table.xml @ 0:370e0b6e9826 draft
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author | florianbegusch |
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date | Wed, 17 Jul 2019 03:05:17 -0400 |
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children | 914fa4daf16a |
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-1:000000000000 | 0:370e0b6e9826 |
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1 <?xml version="1.0" ?> | |
2 <tool id="qiime_sample-classifier_split-table" name="qiime sample-classifier split-table" version="2019.4"> | |
3 <description> - Split a feature table into training and testing sets.</description> | |
4 <requirements> | |
5 <requirement type="package" version="2019.4">qiime2</requirement> | |
6 </requirements> | |
7 <command><![CDATA[ | |
8 qiime sample-classifier split-table | |
9 | |
10 --i-table=$itable | |
11 --m-metadata-column="$mmetadatacolumn" | |
12 | |
13 | |
14 | |
15 #if $input_files_mmetadatafile: | |
16 #def list_dict_to_string(list_dict): | |
17 #set $file_list = list_dict[0]['additional_input'].__getattr__('file_name') | |
18 #for d in list_dict[1:]: | |
19 #set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name') | |
20 #end for | |
21 #return $file_list | |
22 #end def | |
23 | |
24 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile) | |
25 #end if | |
26 | |
27 | |
28 | |
29 #if $ptestsize: | |
30 --p-test-size=$ptestsize | |
31 #end if | |
32 | |
33 #if str($prandomstate): | |
34 --p-random-state="$prandomstate" | |
35 #end if | |
36 | |
37 #if $pnostratify: | |
38 --p-no-stratify | |
39 #end if | |
40 | |
41 #if str($pmissingsamples) != 'None': | |
42 --p-missing-samples=$pmissingsamples | |
43 #end if | |
44 | |
45 --o-training-table=otrainingtable | |
46 --o-test-table=otesttable | |
47 ; | |
48 cp otrainingtable.qza $otrainingtable; | |
49 cp otesttable.qza $otesttable; | |
50 cp mmetadatafile.qza $mmetadatafile | |
51 ]]></command> | |
52 <inputs> | |
53 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data"/> | |
54 <param label="--m-metadata-column: COLUMN MetadataColumn[Numeric | Categorical] Numeric metadata column to use as prediction target. [required]" name="mmetadatacolumn" optional="False" type="text"/> | |
55 <param label="--p-test-size: PROPORTION Range(0.0, 1.0, inclusive_start=False) Fraction of input samples to exclude from training set and use for classifier testing. [default: 0.2]" name="ptestsize" optional="True" type="float" value="0.2" min="0" max="1" exclusive_end="True"/> | |
56 <param label="--p-random-state: INTEGER Seed used by random number generator. [optional]" name="prandomstate" optional="True" type="integer"/> | |
57 <param label="--p-no-stratify: Evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples. [default: False]" name="pnostratify" selected="False" type="boolean"/> | |
58 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select"> | |
59 <option selected="True" value="None">Selection is Optional</option> | |
60 <option value="error">error</option> | |
61 <option value="ignore">ignore</option> | |
62 </param> | |
63 | |
64 <repeat name="input_files_mmetadatafile" optional="True" title="--m-metadata-file"> | |
65 <param label="--m-metadata-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [optional]" name="additional_input" type="data" format="tabular,qza,no_unzip.zip" /> | |
66 </repeat> | |
67 | |
68 </inputs> | |
69 <outputs> | |
70 <data format="qza" label="${tool.name} on ${on_string}: trainingtable.qza" name="otrainingtable"/> | |
71 <data format="qza" label="${tool.name} on ${on_string}: testtable.qza" name="otesttable"/> | |
72 </outputs> | |
73 <help><![CDATA[ | |
74 Split a feature table into training and testing sets. | |
75 ##################################################### | |
76 | |
77 Split a feature table into training and testing sets. By default stratifies | |
78 training and test sets on a metadata column, such that values in that | |
79 column are evenly represented across training and test sets. | |
80 | |
81 Parameters | |
82 ---------- | |
83 table : FeatureTable[Frequency] | |
84 Feature table containing all features that should be used for target | |
85 prediction. | |
86 metadata : MetadataColumn[Numeric | Categorical] | |
87 Numeric metadata column to use as prediction target. | |
88 test_size : Float % Range(0.0, 1.0, inclusive_start=False), optional | |
89 Fraction of input samples to exclude from training set and use for | |
90 classifier testing. | |
91 random_state : Int, optional | |
92 Seed used by random number generator. | |
93 stratify : Bool, optional | |
94 Evenly stratify training and test data among metadata categories. If | |
95 True, all values in column must match at least two samples. | |
96 missing_samples : Str % Choices('error', 'ignore'), optional | |
97 How to handle missing samples in metadata. "error" will fail if missing | |
98 samples are detected. "ignore" will cause the feature table and | |
99 metadata to be filtered, so that only samples found in both files are | |
100 retained. | |
101 | |
102 Returns | |
103 ------- | |
104 training_table : FeatureTable[Frequency] | |
105 Feature table containing training samples | |
106 test_table : FeatureTable[Frequency] | |
107 Feature table containing test samples | |
108 ]]></help> | |
109 <macros> | |
110 <import>qiime_citation.xml</import> | |
111 </macros> | |
112 <expand macro="qiime_citation"/> | |
113 </tool> |