diff simple_model_fit.xml @ 6:26decbf4bdb8 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"

--- a/simple_model_fit.xml	Thu Oct 01 20:31:44 2020 +0000
+++ b/simple_model_fit.xml	Tue Apr 13 17:56:21 2021 +0000
@@ -1,11 +1,11 @@
-<tool id="sklearn_model_fit" name="Fit a Pipeline, Ensemble" version="@VERSION@">
+<tool id="sklearn_model_fit" name="Fit a Pipeline, Ensemble" version="@VERSION@" profile="20.05">
     <description>or other models using a labeled dataset</description>
     <macros>
         <import>main_macros.xml</import>
         <import>keras_macros.xml</import>
     </macros>
-    <expand macro="python_requirements"/>
-    <expand macro="macro_stdio"/>
+    <expand macro="python_requirements" />
+    <expand macro="macro_stdio" />
     <version_command>echo "@VERSION@"</version_command>
     <command>
         <![CDATA[
@@ -25,46 +25,46 @@
         <inputs name="inputs" />
     </configfiles>
     <inputs>
-        <param name="infile_estimator" type="data" format="zip" label="Choose the dataset containing pipeline/estimator"/>
-        <param name="is_deep_learning" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Is the estimator a deep learning model?"/>
+        <param name="infile_estimator" type="data" format="zip" label="Choose the dataset containing pipeline/estimator" />
+        <param name="is_deep_learning" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Is the estimator a deep learning model?" />
         <conditional name="input_options">
-            <expand macro="data_input_options"/>
+            <expand macro="data_input_options" />
             <when value="tabular">
-                <expand macro="samples_tabular" label1="Choose the training dataset containing features" multiple1="true" multiple2="false"/>
+                <expand macro="samples_tabular" label1="Choose the training dataset containing features" multiple1="true" multiple2="false" />
             </when>
             <when value="sparse">
-                <expand macro="sparse_target"/>
+                <expand macro="sparse_target" />
             </when>
         </conditional>
     </inputs>
     <outputs>
-        <data format="zip" name="out_object" label="Fitted model (skeleton) on $(on_string)"/>
+        <data format="zip" name="out_object" label="Fitted model (skeleton) on $(on_string)" />
         <data format="h5" name="out_weights" label="Weights trained on ${on_string}">
             <filter>is_deep_learning</filter>
         </data>
     </outputs>
     <tests>
         <test>
-            <param name="infile_estimator" value="pipeline05" ftype="zip"/>
-            <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
+            <param name="infile_estimator" value="pipeline05" ftype="zip" />
+            <param name="infile1" value="regression_X.tabular" ftype="tabular" />
             <param name="header1" value="true" />
-            <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
-            <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
-            <param name="header2" value="true"/>
-            <param name="col2" value="1"/>
-            <output name="out_object" file="model_fit01" compare="sim_size" delta="50"/>
+            <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17" />
+            <param name="infile2" value="regression_y.tabular" ftype="tabular" />
+            <param name="header2" value="true" />
+            <param name="col2" value="1" />
+            <output name="out_object" file="model_fit01" compare="sim_size" delta="50" />
         </test>
         <test>
-            <param name="infile_estimator" value="keras_model04"/>
-            <param name="is_deep_learning" value="true"/>
-            <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
+            <param name="infile_estimator" value="keras_model04" />
+            <param name="is_deep_learning" value="true" />
+            <param name="infile1" value="regression_X.tabular" ftype="tabular" />
             <param name="header1" value="true" />
-            <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
-            <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
-            <param name="header2" value="true"/>
-            <param name="col2" value="1"/>
-            <output name="out_object" file="model_fit02" compare="sim_size" delta="10"/>
-            <output name="out_weights" file="model_fit02.h5" compare="sim_size" delta="10"/>
+            <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17" />
+            <param name="infile2" value="regression_y.tabular" ftype="tabular" />
+            <param name="header2" value="true" />
+            <param name="col2" value="1" />
+            <output name="out_object" file="model_fit02" compare="sim_size" delta="50" />
+            <output name="out_weights" file="model_fit02.h5" compare="sim_size" delta="50" />
         </test>
     </tests>
     <help>
@@ -88,7 +88,7 @@
         ]]>
     </help>
     <expand macro="sklearn_citation">
-        <expand macro="keras_citation"/>
-        <expand macro="selene_citation"/>
+        <expand macro="keras_citation" />
+        <expand macro="selene_citation" />
     </expand>
 </tool>