Mercurial > repos > florianbegusch > qiime2_suite

comparison qiime2/qiime_sample-classifier_predict-classification.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-classification" name="qiime sample-classifier predict-classification" version="2019.7"> 2 <tool id="qiime_sample-classifier_predict-classification" name="qiime sample-classifier predict-classification"
3 <description> - Use trained classifier to predict target values for new samples.</description> 3 version="2020.8">
4 <requirements> 4 <description>Use trained classifier 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-classification 9 qiime sample-classifier predict-classification
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="$pnjobs" 18
19 --o-probabilities=oprobabilities
20
21 #if str($examples) != 'None':
22 --examples=$examples
17 #end if 23 #end if
18 24
19 --o-predictions=opredictions
20 ; 25 ;
21 cp opredictions.qza $opredictions 26 cp oprobabilities.qza $oprobabilities
22 ]]></command> 27
23 <inputs> 28 ]]></command>
24 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data"/> 29 <inputs>
25 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data"/> 30 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data" />
26 </inputs> 31 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data" />
27 <outputs> 32 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
28 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions"/> 33
29 </outputs> 34 </inputs>
30 <help><![CDATA[ 35
36 <outputs>
37 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" />
38 <data format="qza" label="${tool.name} on ${on_string}: probabilities.qza" name="oprobabilities" />
39
40 </outputs>
41
42 <help><![CDATA[
31 Use trained classifier to predict target values for new samples. 43 Use trained classifier to predict target values for new samples.
32 ################################################################ 44 ###############################################################
33 45
34 Use trained estimator to predict target values for new samples. These will 46 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 47 typically be unseen samples, e.g., test data (derived manually or from
36 split_table) or samples with unknown values, but can theoretically be any 48 split_table) or samples with unknown values, but can theoretically be any
37 samples present in a feature table that contain overlapping features with 49 samples present in a feature table that contain overlapping features with
42 table : FeatureTable[Frequency] 54 table : FeatureTable[Frequency]
43 Feature table containing all features that should be used for target 55 Feature table containing all features that should be used for target
44 prediction. 56 prediction.
45 sample_estimator : SampleEstimator[Classifier] 57 sample_estimator : SampleEstimator[Classifier]
46 Sample classifier trained with fit_classifier. 58 Sample classifier trained with fit_classifier.
59 n_jobs : Int, optional
60 Number of jobs to run in parallel.
47 61
48 Returns 62 Returns
49 ------- 63 -------
50 predictions : SampleData[ClassifierPredictions] 64 predictions : SampleData[ClassifierPredictions]
51 Predicted target values for each input sample. 65 Predicted target values for each input sample.
52 ]]></help> 66 probabilities : SampleData[Probabilities]
53 <macros> 67 Predicted class probabilities for each input sample.
68 ]]></help>
69 <macros>
54 <import>qiime_citation.xml</import> 70 <import>qiime_citation.xml</import>
55 </macros> 71 </macros>
56 <expand macro="qiime_citation"/> 72 <expand macro="qiime_citation"/>
57 </tool> 73 </tool>