Mercurial > repos > florianbegusch > qiime2_suite
comparison qiime2/qiime_sample-classifier_split-table.xml @ 29:3ba9833030c1 draft
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author | florianbegusch |
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date | Fri, 04 Sep 2020 13:12:49 +0000 |
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28:c28331a63dfd | 29:3ba9833030c1 |
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1 <?xml version="1.0" ?> | |
2 <tool id="qiime_sample-classifier_split-table" name="qiime sample-classifier split-table" | |
3 version="2020.8"> | |
4 <description>Split a feature table into training and testing sets.</description> | |
5 <requirements> | |
6 <requirement type="package" version="2020.8">qiime2</requirement> | |
7 </requirements> | |
8 <command><![CDATA[ | |
9 qiime sample-classifier split-table | |
10 | |
11 --i-table=$itable | |
12 # if $input_files_mmetadatafile: | |
13 # def list_dict_to_string(list_dict): | |
14 # set $file_list = list_dict[0]['additional_input'].__getattr__('file_name') | |
15 # for d in list_dict[1:]: | |
16 # set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name') | |
17 # end for | |
18 # return $file_list | |
19 # end def | |
20 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile) | |
21 # end if | |
22 | |
23 #if '__ob__' in str($mmetadatacolumn): | |
24 #set $mmetadatacolumn_temp = $mmetadatacolumn.replace('__ob__', '[') | |
25 #set $mmetadatacolumn = $mmetadatacolumn_temp | |
26 #end if | |
27 #if '__cb__' in str($mmetadatacolumn): | |
28 #set $mmetadatacolumn_temp = $mmetadatacolumn.replace('__cb__', ']') | |
29 #set $mmetadatacolumn = $mmetadatacolumn_temp | |
30 #end if | |
31 #if 'X' in str($mmetadatacolumn): | |
32 #set $mmetadatacolumn_temp = $mmetadatacolumn.replace('X', '\\') | |
33 #set $mmetadatacolumn = $mmetadatacolumn_temp | |
34 #end if | |
35 #if '__sq__' in str($mmetadatacolumn): | |
36 #set $mmetadatacolumn_temp = $mmetadatacolumn.replace('__sq__', "'") | |
37 #set $mmetadatacolumn = $mmetadatacolumn_temp | |
38 #end if | |
39 #if '__db__' in str($mmetadatacolumn): | |
40 #set $mmetadatacolumn_temp = $mmetadatacolumn.replace('__db__', '"') | |
41 #set $mmetadatacolumn = $mmetadatacolumn_temp | |
42 #end if | |
43 | |
44 --m-metadata-column=$mmetadatacolumn | |
45 | |
46 | |
47 --p-test-size=$ptestsize | |
48 | |
49 #if str($prandomstate): | |
50 --p-random-state=$prandomstate | |
51 #end if | |
52 #if $pnostratify: | |
53 --p-no-stratify | |
54 #end if | |
55 | |
56 #if str($pmissingsamples) != 'None': | |
57 --p-missing-samples=$pmissingsamples | |
58 #end if | |
59 | |
60 --o-training-table=otrainingtable | |
61 | |
62 --o-test-table=otesttable | |
63 | |
64 #if str($examples) != 'None': | |
65 --examples=$examples | |
66 #end if | |
67 | |
68 ; | |
69 cp otesttable.qza $otesttable | |
70 | |
71 ]]></command> | |
72 <inputs> | |
73 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Balance⁴ | PercentileNormalized⁵ | Design⁶] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data" /> | |
74 <repeat name="input_files_mmetadatafile" optional="True" title="--m-metadata-file"> | |
75 <param format="tabular,qza,no_unzip.zip" label="--m-metadata-file: METADATA" name="additional_input" optional="True" type="data" /> | |
76 </repeat> | |
77 <param label="--m-metadata-column: COLUMN MetadataColumn[Numeric | Categorical] Numeric metadata column to use as prediction target. [required]" name="mmetadatacolumn" optional="False" type="text" /> | |
78 <param exclude_min="True" label="--p-test-size: PROPORTION Range(0.0, 1.0, inclusive_start=False) Fraction of input samples to exclude from training set and use for classifier testing. [default: 0.2]" max="1.0" min="0.0" name="ptestsize" optional="True" type="float" value="0.2" /> | |
79 <param label="--p-random-state: INTEGER Seed used by random number generator. [optional]" name="prandomstate" optional="False" type="text" /> | |
80 <param label="--p-no-stratify: Do not evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples. [default: True]" name="pnostratify" selected="False" type="boolean" /> | |
81 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select"> | |
82 <option selected="True" value="None">Selection is Optional</option> | |
83 <option value="error">error</option> | |
84 <option value="ignore">ignore</option> | |
85 </param> | |
86 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" /> | |
87 | |
88 </inputs> | |
89 | |
90 <outputs> | |
91 <data format="qza" label="${tool.name} on ${on_string}: trainingtable.qza" name="otrainingtable" /> | |
92 <data format="qza" label="${tool.name} on ${on_string}: testtable.qza" name="otesttable" /> | |
93 | |
94 </outputs> | |
95 | |
96 <help><![CDATA[ | |
97 Split a feature table into training and testing sets. | |
98 ############################################################### | |
99 | |
100 Split a feature table into training and testing sets. By default stratifies | |
101 training and test sets on a metadata column, such that values in that | |
102 column are evenly represented across training and test sets. | |
103 | |
104 Parameters | |
105 ---------- | |
106 table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Balance⁴ | PercentileNormalized⁵ | Design⁶] | |
107 Feature table containing all features that should be used for target | |
108 prediction. | |
109 metadata : MetadataColumn[Numeric | Categorical] | |
110 Numeric metadata column to use as prediction target. | |
111 test_size : Float % Range(0.0, 1.0, inclusive_start=False), optional | |
112 Fraction of input samples to exclude from training set and use for | |
113 classifier testing. | |
114 random_state : Int, optional | |
115 Seed used by random number generator. | |
116 stratify : Bool, optional | |
117 Evenly stratify training and test data among metadata categories. If | |
118 True, all values in column must match at least two samples. | |
119 missing_samples : Str % Choices('error', 'ignore'), optional | |
120 How to handle missing samples in metadata. "error" will fail if missing | |
121 samples are detected. "ignore" will cause the feature table and | |
122 metadata to be filtered, so that only samples found in both files are | |
123 retained. | |
124 | |
125 Returns | |
126 ------- | |
127 training_table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Balance⁴ | PercentileNormalized⁵ | Design⁶] | |
128 Feature table containing training samples | |
129 test_table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Balance⁴ | PercentileNormalized⁵ | Design⁶] | |
130 Feature table containing test samples | |
131 ]]></help> | |
132 <macros> | |
133 <import>qiime_citation.xml</import> | |
134 </macros> | |
135 <expand macro="qiime_citation"/> | |
136 </tool> |