diff model_prediction.xml @ 15:3bb1b688b0e4 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb

--- a/model_prediction.xml	Thu Aug 11 08:55:45 2022 +0000
+++ b/model_prediction.xml	Wed Aug 09 13:06:25 2023 +0000
@@ -1,4 +1,4 @@
-<tool id="model_prediction" name="Model Prediction" version="@VERSION@" profile="20.05">
+<tool id="model_prediction" name="Model Prediction" version="@VERSION@" profile="@PROFILE@">
     <description>predicts on new data using a preffited model</description>
     <macros>
         <import>main_macros.xml</import>
@@ -14,7 +14,6 @@
             --inputs '$inputs'
             --infile_estimator '$infile_estimator'
             --outfile_predict '$outfile_predict'
-            --infile_weights '$infile_weights'
             #if $input_options.selected_input == 'seq_fasta'
             --fasta_path '$input_options.fasta_path'
             #elif $input_options.selected_input == 'variant_effect'
@@ -29,8 +28,7 @@
         <inputs name="inputs" />
     </configfiles>
     <inputs>
-        <param name="infile_estimator" type="data" format="zip" label="Choose the dataset containing pipeline/estimator object" />
-        <param name="infile_weights" type="data" format="h5" optional="true" label="Choose the dataset containing weights for the estimator above" help="Optional. For deep learning only." />
+        <param name="infile_estimator" type="data" format="h5mlm" label="Choose the dataset containing pipeline/estimator object" />
         <param argument="method" type="select" label="Select invocation method">
             <option value="predict" selected="true">predict</option>
             <option value="predict_proba">predict_proba</option>
@@ -78,7 +76,7 @@
     </outputs>
     <tests>
         <test>
-            <param name="infile_estimator" value="best_estimator_.zip" ftype="zip" />
+            <param name="infile_estimator" value="best_estimator_.h5mlm" ftype="h5mlm" />
             <param name="method" value="predict" />
             <param name="infile1" value="regression_X.tabular" ftype="tabular" />
             <param name="header1" value="true" />
@@ -86,20 +84,19 @@
             <output name="outfile_predict" file="model_pred01.tabular" />
         </test>
         <test>
-            <param name="infile_estimator" value="keras_model04" ftype="zip" />
-            <param name="infile_weights" value="train_test_eval_weights02.h5" ftype="h5" />
+            <param name="infile_estimator" value="train_test_eval_model01" ftype="h5mlm" />
             <param name="method" value="predict" />
             <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" />
-            <output name="outfile_predict">
+            <output name="outfile_predict" >
                 <assert_contents>
                     <has_n_columns n="1" />
-                    <has_text text="70.2" />
-                    <has_text text="61.2" />
-                    <has_text text="74.2" />
-                    <has_text text="65.9" />
-                    <has_text text="52.9" />
+                    <has_text text="71.0" />
+                    <has_text text="61.3" />
+                    <has_text text="83.7" />
+                    <has_text text="69.2" />
+                    <has_text text="51.8" />
                 </assert_contents>
             </output>
         </test>
@@ -110,7 +107,7 @@
 
 Given a fitted estimator and new data sets, this tool outpus the prediction results on the data sets via invoking the estimator's `predict` or `predict_proba` method.
 
-For estimator, this tool supports fitted sklearn estimators (pickled) and trained deep learning models (model skeleton + weights). It predicts on three different dataset inputs,
+For estimator, this tool supports fitted sklearn estimators and trained deep learning models. It predicts on three different dataset inputs,
 
 - tabular