| Previous changeset 1:00816d9855fc (2020-04-02) Next changeset 3:77f068ba47dd (2020-04-14) |
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Commit message:
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/pyprophet commit d1c34e31a93761cf7cfd4068bcdb70495d4d90bb" |
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modified:
pyprophet_score.xml |
| b |
| diff -r 00816d9855fc -r 8b30c8ffa687 pyprophet_score.xml --- a/pyprophet_score.xml Thu Apr 02 01:34:49 2020 -0400 +++ b/pyprophet_score.xml Tue Apr 14 10:53:02 2020 -0400 |
| [ |
| @@ -1,4 +1,4 @@ -<tool id="pyprophet_score" name="PyProphet score" version="@VERSION@.1"> +<tool id="pyprophet_score" name="PyProphet score" version="@VERSION@.2"> <description> Error-rate estimation for MS1, MS2 and transition-level data </description> @@ -10,13 +10,13 @@ <![CDATA[ pyprophet score --in='$input' + --classifier=$conditional_classifier.classifier + #if str($conditional_classifier.classifier)=='XGBoost': - --classifier=$conditional_classifier.classifier $conditional_classifier.xgb_autotune - #elif str($conditional_classifier.classifier)=='LDA': - --classifier=$conditional_classifier.classifier - #elif str($conditional_classifier.classifier)=='prev_weights': - --apply_weights=$conditional_classifier.apply_weights + #end if + #if $apply_weights: + --apply_weights='$apply_weights' #end if --xeval_fraction=$xeval_fraction --xeval_num_iter=$xeval_num_iter @@ -50,19 +50,16 @@ <inputs> <param name="input" type="data" format="osw" label="Input file" help="This file needs to be in OSW format (--in)" /> <conditional name="conditional_classifier"> - <param name="classifier" type="select" label="Either a 'LDA' or 'XGBoost' classifier is used for semi-supervised learning or previously calculated Pyprophet score weights can be loaded" help="(--classifier)"> + <param argument="--classifier" type="select" label="Either a 'LDA' or 'XGBoost' classifier is used for semi-supervised learning" > <option value="LDA" selected="True" >LDA</option> <option value="XGBoost">XGBoost</option> - <option value="prev_weights">Apply previously calculated weights</option> </param> <when value="LDA"/> <when value="XGBoost"> <param name="xgb_autotune" type="boolean" truevalue="--xgb_autotune" falsevalue="--no-xgb_autotune" label="XGBoost: Autotune hyperparameters" help="(--xgb_autotune / --no-xgb_autotune)"/> </when> - <when value="prev_weights"> - <param name="apply_weights" type="data" format="osw" label="Apply PyProphet score weights file instead of semi-supervised learning." help="(--apply_weights)" /> - </when> </conditional> + <param argument="apply_weights" type="data" format="osw" optional="True" label="Apply PyProphet score weights file (osw format) instead of semi-supervised learning." /> <param argument="--level" type="select" display="radio" label="The data level selected for scoring. 'ms1ms2' integrates both MS1- and MS2-level scores and can be used instead of 'ms2'-level results" > <option value="ms1" >MS1</option> <option value="ms2" >MS2</option> @@ -121,10 +118,7 @@ </test> <test> <param name="input" value="merged.osw" ftype="osw"/> - <conditional name="conditional_classifier"> - <param name="classifier" value="prev_weights"/> - <param name="apply_weights" value="score.osw" ftype="osw"/> - </conditional> + <param name="apply_weights" value="score.osw" ftype="osw"/> <param name="level" value="ms2"/> <param name="xeval_num_iter" value="2" /> <param name="ss_num_iter" value="2" /> @@ -152,3 +146,4 @@ </help> <expand macro="citations"/> </tool> + |