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comparison qiime2/qiime_sample-classifier_regress-samples.xml @ 14:a0a8d77a991c draft

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author florianbegusch
date Thu, 03 Sep 2020 09:51:29 +0000
parents f190567fe3f6
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13:887cd4ad8e16 14:a0a8d77a991c
1 <?xml version="1.0" ?> 1 <?xml version="1.0" ?>
2 <tool id="qiime_sample-classifier_regress-samples" name="qiime sample-classifier regress-samples" version="2019.7"> 2 <tool id="qiime_sample-classifier_regress-samples" name="qiime sample-classifier regress-samples"
3 <description> - Train and test a cross-validated supervised learning regressor.</description> 3 version="2020.8">
4 <requirements> 4 <description>Train and test a cross-validated supervised learning regressor.</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 regress-samples 9 qiime sample-classifier regress-samples
9 10
10 --i-table=$itable 11 --i-table=$itable
11 --m-metadata-column="$mmetadatacolumn" 12 # if $input_files_mmetadatafile:
12 13 # def list_dict_to_string(list_dict):
13 #if str($ptestsize): 14 # set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
14 --p-test-size=$ptestsize 15 # for d in list_dict[1:]:
15 #end if 16 # set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name')
16 17 # end for
17 #if str($pstep): 18 # return $file_list
18 --p-step=$pstep 19 # end def
19 #end if 20 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile)
20 21 # end if
21 #if str($pcv): 22
22 --p-cv=$pcv 23 #if '__ob__' in str($mmetadatacolumn):
23 #end if 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=$ptestsize
48
49 --p-step=$pstep
50
51 --p-cv=$pcv
24 52
25 #if str($prandomstate): 53 #if str($prandomstate):
26 --p-random-state="$prandomstate" 54 --p-random-state=$prandomstate
27 #end if 55 #end if
28 56 --p-n-jobs=$pnjobs
29 #set $pnjobs = '${GALAXY_SLOTS:-4}' 57
30 58 --p-n-estimators=$pnestimators
31 #if str($pnjobs):
32 --p-n-jobs="$pnjobs"
33 #end if
34
35
36 #if str($pnestimators):
37 --p-n-estimators=$pnestimators
38 #end if
39 59
40 #if str($pestimator) != 'None': 60 #if str($pestimator) != 'None':
41 --p-estimator=$pestimator 61 --p-estimator=$pestimator
42 #end if 62 #end if
43 63
44 #if $poptimizefeatureselection: 64 #if $poptimizefeatureselection:
45 --p-optimize-feature-selection 65 --p-optimize-feature-selection
46 #end if 66 #end if
52 #if $pparametertuning: 72 #if $pparametertuning:
53 --p-parameter-tuning 73 --p-parameter-tuning
54 #end if 74 #end if
55 75
56 #if str($pmissingsamples) != 'None': 76 #if str($pmissingsamples) != 'None':
57 --p-missing-samples=$pmissingsamples 77 --p-missing-samples=$pmissingsamples
58 #end if 78 #end if
59
60
61
62
63 #if $metadatafile:
64 --m-metadata-file=$metadatafile
65 #end if
66
67
68
69 79
70 --o-sample-estimator=osampleestimator 80 --o-sample-estimator=osampleestimator
81
71 --o-feature-importance=ofeatureimportance 82 --o-feature-importance=ofeatureimportance
83
72 --o-predictions=opredictions 84 --o-predictions=opredictions
85
73 --o-model-summary=omodelsummary 86 --o-model-summary=omodelsummary
87
74 --o-accuracy-results=oaccuracyresults 88 --o-accuracy-results=oaccuracyresults
89
90 #if str($examples) != 'None':
91 --examples=$examples
92 #end if
93
75 ; 94 ;
76 cp osampleestimator.qza $osampleestimator; 95 cp opredictions.qza $opredictions
77 cp ofeatureimportance.qza $ofeatureimportance; 96
78 cp opredictions.qza $opredictions; 97 ;
79 qiime tools export --input-path omodelsummary.qzv --output-path out && mkdir -p '$omodelsummary.files_path' 98 qiime tools export omodelsummary.qzv --output-path out
99 && mkdir -p '$omodelsummary.files_path'
80 && cp -r out/* '$omodelsummary.files_path' 100 && cp -r out/* '$omodelsummary.files_path'
81 && mv '$omodelsummary.files_path/index.html' '$omodelsummary'; 101 && mv '$omodelsummary.files_path/index.html' '$omodelsummary'
82 qiime tools export --input-path oaccuracyresults.qzv --output-path out && mkdir -p '$oaccuracyresults.files_path' 102
103 ;
104 qiime tools export oaccuracyresults.qzv --output-path out
105 && mkdir -p '$oaccuracyresults.files_path'
83 && cp -r out/* '$oaccuracyresults.files_path' 106 && cp -r out/* '$oaccuracyresults.files_path'
84 && mv '$oaccuracyresults.files_path/index.html' '$oaccuracyresults' 107 && mv '$oaccuracyresults.files_path/index.html' '$oaccuracyresults'
85 ]]></command> 108
86 <inputs> 109 ]]></command>
87 <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"/> 110 <inputs>
88 <param label="--m-metadata-column: COLUMN MetadataColumn[Numeric] Numeric metadata column to use as prediction target. [required]" name="mmetadatacolumn" optional="False" type="text"/> 111 <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" />
89 <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" /> 112 <repeat name="input_files_mmetadatafile" optional="True" title="--m-metadata-file">
90 <param label="--p-step: PROPORTION Range(0.0, 1.0, inclusive_start=False) If optimize-feature-selection is True, step is the percentage of features to remove at each iteration. [default: 0.05]" name="pstep" optional="True" type="float" value="0.05" min="0" max="1" /> 113 <param format="tabular,qza,no_unzip.zip" label="--m-metadata-file: METADATA" name="additional_input" optional="True" type="data" />
91 <param label="--p-cv: INTEGER Number of k-fold cross-validations to perform. Range(1, None) [default: 5]" name="pcv" optional="True" type="integer" value="5" min="1"/> 114 </repeat>
92 <param label="--p-random-state: INTEGER Seed used by random number generator. [optional]" name="prandomstate" optional="True" type="integer"/> 115 <param label="--m-metadata-column: COLUMN MetadataColumn[Numeric] Numeric metadata column to use as prediction target. [required]" name="mmetadatacolumn" optional="False" type="text" />
93 <param label="--p-n-estimators: INTEGER Range(1, None) Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting. [default: 100]" name="pnestimators" optional="True" type="integer" value="100" min="1"/> 116 <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" />
94 <param label="--p-estimator: " name="pestimator" optional="True" type="select"> 117 <param exclude_min="True" label="--p-step: PROPORTION Range(0.0, 1.0, inclusive_start=False) If optimize-feature-selection is True, step is the percentage of features to remove at each iteration. [default: 0.05]" max="1.0" min="0.0" name="pstep" optional="True" type="float" value="0.05" />
95 <option selected="True" value="None">Selection is Optional</option> 118 <param label="--p-cv: INTEGER Number of k-fold cross-validations to perform. Range(1, None) [default: 5]" min="1" name="pcv" optional="True" type="integer" value="5" />
96 <option value="RandomForestRegressor">RandomForestRegressor</option> 119 <param label="--p-random-state: INTEGER Seed used by random number generator. [optional]" name="prandomstate" optional="False" type="text" />
97 <option value="ExtraTreesRegressor">ExtraTreesRegressor</option> 120 <param label="--p-n-estimators: INTEGER Range(1, None) Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting. [default: 100]" min="1" name="pnestimators" optional="True" type="integer" value="100" />
98 <option value="GradientBoostingRegressor">GradientBoostingRegressor</option> 121 <param label="--p-estimator: " name="pestimator" optional="True" type="select">
99 <option value="AdaBoostRegressor">AdaBoostRegressor</option> 122 <option selected="True" value="None">Selection is Optional</option>
100 <option value="ElasticNet">ElasticNet</option> 123 <option value="RandomForestRegressor">RandomForestRegressor</option>
101 <option value="Ridge">Ridge</option> 124 <option value="ExtraTreesRegressor">ExtraTreesRegressor</option>
102 <option value="Lasso">Lasso</option> 125 <option value="GradientBoostingRegressor">GradientBoostingRegressor</option>
103 <option value="KNeighborsRegressor">KNeighborsRegressor</option> 126 <option value="AdaBoostRegressor">AdaBoostRegressor</option>
104 <option value="LinearSVR">LinearSVR</option> 127 <option value="ElasticNet">ElasticNet</option>
105 <option value="SVR">SVR</option> 128 <option value="Ridge">Ridge</option>
106 </param> 129 <option value="Lasso">Lasso</option>
107 <param label="--p-optimize-feature-selection: --p-no-optimize-feature-selection Automatically optimize input feature selection using recursive feature elimination. [default: False]" name="poptimizefeatureselection" selected="False" type="boolean"/> 130 <option value="KNeighborsRegressor">KNeighborsRegressor</option>
108 <param label="--p-stratify: --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="pstratify" selected="False" type="boolean"/> 131 <option value="LinearSVR">LinearSVR</option>
109 <param label="--p-parameter-tuning: --p-no-parameter-tuning Automatically tune hyperparameters using random grid search. [default: False]" name="pparametertuning" selected="False" type="boolean"/> 132 <option value="SVR">SVR</option>
110 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select"> 133 </param>
111 <option selected="True" value="None">Selection is Optional</option> 134 <param label="--p-optimize-feature-selection: --p-optimize-feature-selection: / --p-no-optimize-feature-selection Automatically optimize input feature selection using recursive feature elimination. [default: False]" name="poptimizefeatureselection" selected="False" type="boolean" />
112 <option value="error">error</option> 135 <param label="--p-stratify: --p-stratify: / --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="pstratify" selected="False" type="boolean" />
113 <option value="ignore">ignore</option> 136 <param label="--p-parameter-tuning: --p-parameter-tuning: / --p-no-parameter-tuning Automatically tune hyperparameters using random grid search. [default: False]" name="pparametertuning" selected="False" type="boolean" />
114 </param> 137 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
115 138 <option selected="True" value="None">Selection is Optional</option>
116 139 <option value="error">error</option>
117 <param label="--m-metadata-file METADATA" name="metadatafile" type="data" format="tabular,qza,no_unzip.zip" /> 140 <option value="ignore">ignore</option>
118 141 </param>
119 142 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
120 </inputs> 143
121 <outputs> 144 </inputs>
122 <data format="qza" label="${tool.name} on ${on_string}: sampleestimator.qza" name="osampleestimator"/> 145
123 <data format="qza" label="${tool.name} on ${on_string}: featureimportance.qza" name="ofeatureimportance"/> 146 <outputs>
124 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions"/> 147 <data format="qza" label="${tool.name} on ${on_string}: sampleestimator.qza" name="osampleestimator" />
125 <data format="html" label="${tool.name} on ${on_string}: modelsummary.qzv" name="omodelsummary"/> 148 <data format="qza" label="${tool.name} on ${on_string}: featureimportance.qza" name="ofeatureimportance" />
126 <data format="html" label="${tool.name} on ${on_string}: accuracyresults.qzv" name="oaccuracyresults"/> 149 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" />
127 </outputs> 150 <data format="html" label="${tool.name} on ${on_string}: modelsummary.html" name="omodelsummary" />
128 <help><![CDATA[ 151 <data format="html" label="${tool.name} on ${on_string}: accuracyresults.html" name="oaccuracyresults" />
152
153 </outputs>
154
155 <help><![CDATA[
129 Train and test a cross-validated supervised learning regressor. 156 Train and test a cross-validated supervised learning regressor.
130 ############################################################### 157 ###############################################################
131 158
132 Predicts a continuous sample metadata column using a supervised learning 159 Predicts a continuous sample metadata column using a supervised learning
133 regressor. Splits input data into training and test sets. The training set 160 regressor. Splits input data into training and test sets. The training set
153 features to remove at each iteration. 180 features to remove at each iteration.
154 cv : Int % Range(1, None), optional 181 cv : Int % Range(1, None), optional
155 Number of k-fold cross-validations to perform. 182 Number of k-fold cross-validations to perform.
156 random_state : Int, optional 183 random_state : Int, optional
157 Seed used by random number generator. 184 Seed used by random number generator.
185 n_jobs : Int, optional
186 Number of jobs to run in parallel.
158 n_estimators : Int % Range(1, None), optional 187 n_estimators : Int % Range(1, None), optional
159 Number of trees to grow for estimation. More trees will improve 188 Number of trees to grow for estimation. More trees will improve
160 predictive accuracy up to a threshold level, but will also increase 189 predictive accuracy up to a threshold level, but will also increase
161 time and memory requirements. This parameter only affects ensemble 190 time and memory requirements. This parameter only affects ensemble
162 estimators, such as Random Forest, AdaBoost, ExtraTrees, and 191 estimators, such as Random Forest, AdaBoost, ExtraTrees, and
188 model_summary : Visualization 217 model_summary : Visualization
189 Summarized parameter and (if enabled) feature selection information for 218 Summarized parameter and (if enabled) feature selection information for
190 the trained estimator. 219 the trained estimator.
191 accuracy_results : Visualization 220 accuracy_results : Visualization
192 Accuracy results visualization. 221 Accuracy results visualization.
193 ]]></help> 222 ]]></help>
194 <macros> 223 <macros>
195 <import>qiime_citation.xml</import> 224 <import>qiime_citation.xml</import>
196 </macros> 225 </macros>
197 <expand macro="qiime_citation"/> 226 <expand macro="qiime_citation"/>
198 </tool> 227 </tool>