Mercurial > repos > florianbegusch > qiime2_suite

comparison qiime2/qiime_sample-classifier_predict-regression.xml @ 14:a0a8d77a991c draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
Uploaded
author florianbegusch
date Thu, 03 Sep 2020 09:51:29 +0000
parents f190567fe3f6
children
comparison
equal deleted inserted replaced
13:887cd4ad8e16 14:a0a8d77a991c
1 <?xml version="1.0" ?> 1 <?xml version="1.0" ?>
2 <tool id="qiime_sample-classifier_predict-regression" name="qiime sample-classifier predict-regression" version="2019.7"> 2 <tool id="qiime_sample-classifier_predict-regression" name="qiime sample-classifier predict-regression"
3 <description> - Use trained regressor to predict target values for new samples.</description> 3 version="2020.8">
4 <requirements> 4 <description>Use trained regressor to predict target values for new samples.</description>
5 <requirement type="package" version="2019.7">qiime2</requirement> 5 <requirements>
6 </requirements> 6 <requirement type="package" version="2020.8">qiime2</requirement>
7 <command><![CDATA[ 7 </requirements>
8 <command><![CDATA[
8 qiime sample-classifier predict-regression 9 qiime sample-classifier predict-regression
9 10
10 --i-table=$itable 11 --i-table=$itable
12
11 --i-sample-estimator=$isampleestimator 13 --i-sample-estimator=$isampleestimator
12 14
13 #set $pnjobs = '${GALAXY_SLOTS:-4}' 15 --p-n-jobs=$pnjobs
14 16
15 #if str($pnjobs): 17 --o-predictions=opredictions
16 --p-n-jobs="$pnjobs" 18
19 #if str($examples) != 'None':
20 --examples=$examples
17 #end if 21 #end if
18 22
19 --o-predictions=opredictions
20 ; 23 ;
21 cp opredictions.qza $opredictions 24 cp opredictions.qza $opredictions
22 ]]></command> 25
23 <inputs> 26 ]]></command>
24 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data"/> 27 <inputs>
25 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Regressor] Sample regressor trained with fit_regressor. [required]" name="isampleestimator" optional="False" type="data"/> 28 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data" />
26 </inputs> 29 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Regressor] Sample regressor trained with fit_regressor. [required]" name="isampleestimator" optional="False" type="data" />
27 <outputs> 30 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
28 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions"/> 31
29 </outputs> 32 </inputs>
30 <help><![CDATA[ 33
34 <outputs>
35 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" />
36
37 </outputs>
38
39 <help><![CDATA[
31 Use trained regressor to predict target values for new samples. 40 Use trained regressor to predict target values for new samples.
32 ############################################################### 41 ###############################################################
33 42
34 Use trained estimator to predict target values for new samples. These will 43 Use trained estimator to predict target values for new samples. These will
35 typically be unseen samples, e.g., test data (derived manually or from 44 typically be unseen samples, e.g., test data (derived manually or from
42 table : FeatureTable[Frequency] 51 table : FeatureTable[Frequency]
43 Feature table containing all features that should be used for target 52 Feature table containing all features that should be used for target
44 prediction. 53 prediction.
45 sample_estimator : SampleEstimator[Regressor] 54 sample_estimator : SampleEstimator[Regressor]
46 Sample regressor trained with fit_regressor. 55 Sample regressor trained with fit_regressor.
56 n_jobs : Int, optional
57 Number of jobs to run in parallel.
47 58
48 Returns 59 Returns
49 ------- 60 -------
50 predictions : SampleData[RegressorPredictions] 61 predictions : SampleData[RegressorPredictions]
51 Predicted target values for each input sample. 62 Predicted target values for each input sample.
52 ]]></help> 63 ]]></help>
53 <macros> 64 <macros>
54 <import>qiime_citation.xml</import> 65 <import>qiime_citation.xml</import>
55 </macros> 66 </macros>
56 <expand macro="qiime_citation"/> 67 <expand macro="qiime_citation"/>
57 </tool> 68 </tool>