diff svm.xml @ 19:d67dcd63f6cb draft

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

--- a/svm.xml	Thu Oct 01 20:06:56 2020 +0000
+++ b/svm.xml	Tue Apr 13 17:32:55 2021 +0000
@@ -1,20 +1,20 @@
-<tool id="sklearn_svm_classifier" name="Support vector machines (SVMs)" version="@VERSION@">
+<tool id="sklearn_svm_classifier" name="Support vector machines (SVMs)" version="@VERSION@" profile="20.05">
     <description>for classification</description>
     <macros>
         <import>main_macros.xml</import>
         <!-- macro name="class_weight" argument="class_weight"-->
     </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[
     python '$svc_script' '$inputs'
 ]]>
     </command>
     <configfiles>
-        <inputs name="inputs"/>
+        <inputs name="inputs" />
         <configfile name="svc_script">
-<![CDATA[
+            <![CDATA[
 import sys
 import json
 import sklearn.svm
@@ -72,110 +72,110 @@
                 <option value="LinearSVC">Linear Support Vector Classification</option>
             </param>
             <when value="SVC">
-                <expand macro="sl_mixed_input"/>
+                <expand macro="sl_mixed_input" />
                 <expand macro="svc_advanced_options">
-                    <expand macro="C"/>
+                    <expand macro="C" />
                 </expand>
             </when>
             <when value="NuSVC">
-                <expand macro="sl_mixed_input"/>
+                <expand macro="sl_mixed_input" />
                 <expand macro="svc_advanced_options">
-                    <param argument="nu" type="float" optional="true" value="0.5" label="Nu control parameter" help="Controls the number of support vectors. Should be in the interval (0, 1]. "/>
+                    <param argument="nu" type="float" optional="true" value="0.5" label="Nu control parameter" help="Controls the number of support vectors. Should be in the interval (0, 1]. " />
                 </expand>
             </when>
             <when value="LinearSVC">
-                <expand macro="sl_mixed_input"/>
+                <expand macro="sl_mixed_input" />
                 <section name="options" title="Advanced Options" expanded="False">
-                    <expand macro="C"/>
-                    <expand macro="tol" default_value="0.001" help_text="Tolerance for stopping criterion. "/>
-                    <expand macro="random_state" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data for probability estimation. A fixed seed allows reproducible results."/>
+                    <expand macro="C" />
+                    <expand macro="tol" default_value="0.001" help_text="Tolerance for stopping criterion. " />
+                    <expand macro="random_state" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data for probability estimation. A fixed seed allows reproducible results." />
                     <!--expand macro="class_weight"/-->
-                    <param argument="max_iter" type="integer" optional="true" value="1000" label="Maximum number of iterations" help="The maximum number of iterations to be run."/>
+                    <param argument="max_iter" type="integer" optional="true" value="1000" label="Maximum number of iterations" help="The maximum number of iterations to be run." />
                     <param argument="loss" type="select" label="Loss function" help="Specifies the loss function. ''squared_hinge'' is the square of the hinge loss.">
                         <option value="squared_hinge" selected="true">Squared hinge</option>
                         <option value="hinge">Hinge</option>
                     </param>
                     <param argument="penalty" type="select" label="Penalization norm" help=" ">
-                        <option value="l1" >l1</option>
+                        <option value="l1">l1</option>
                         <option value="l2" selected="true">l2</option>
                     </param>
-                    <param argument="dual" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use the shrinking heuristic" help="Select the algorithm to either solve the dual or primal optimization problem. Prefer dual=False when n_samples > n_features."/>
+                    <param argument="dual" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use the shrinking heuristic" help="Select the algorithm to either solve the dual or primal optimization problem. Prefer dual=False when n_samples > n_features." />
                     <param argument="multi_class" type="select" label="Multi-class strategy" help="Determines the multi-class strategy if y contains more than two classes.">
                         <option value="ovr" selected="true">ovr</option>
-                        <option value="crammer_singer" >crammer_singer</option>
+                        <option value="crammer_singer">crammer_singer</option>
                     </param>
-                    <param argument="fit_intercept" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Calculate the intercept for this model" help="If set to false, data is expected to be already centered."/>
-                    <param argument="intercept_scaling" type="float" optional="true" value="1" label="Add synthetic feature to the instance vector" help=" "/>
+                    <param argument="fit_intercept" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Calculate the intercept for this model" help="If set to false, data is expected to be already centered." />
+                    <param argument="intercept_scaling" type="float" optional="true" value="1" label="Add synthetic feature to the instance vector" help=" " />
                 </section>
             </when>
         </expand>
     </inputs>
-    <expand macro="output"/>
+    <expand macro="output" />
     <tests>
         <test>
-            <param name="infile1" value="train_set.tabular" ftype="tabular"/>
-            <param name="infile2" value="train_set.tabular" ftype="tabular"/>
-            <param name="header1" value="True"/>
-            <param name="header2" value="True"/>
-            <param name="col1" value="1,2,3,4"/>
-            <param name="col2" value="5"/>
-            <param name="selected_task" value="train"/>
-            <param name="selected_algorithm" value="SVC"/>
-            <param name="random_state" value="5"/>
-            <output name="outfile_fit" file="svc_model01" compare="sim_size"/>
+            <param name="infile1" value="train_set.tabular" ftype="tabular" />
+            <param name="infile2" value="train_set.tabular" ftype="tabular" />
+            <param name="header1" value="True" />
+            <param name="header2" value="True" />
+            <param name="col1" value="1,2,3,4" />
+            <param name="col2" value="5" />
+            <param name="selected_task" value="train" />
+            <param name="selected_algorithm" value="SVC" />
+            <param name="random_state" value="5" />
+            <output name="outfile_fit" file="svc_model01" compare="sim_size" />
         </test>
         <test>
-            <param name="infile1" value="train_set.tabular" ftype="tabular"/>
-            <param name="infile2" value="train_set.tabular" ftype="tabular"/>
-            <param name="header1" value="True"/>
-            <param name="header2" value="True"/>
-            <param name="col1" value="1,2,3,4"/>
-            <param name="col2" value="5"/>
-            <param name="selected_task" value="train"/>
-            <param name="selected_algorithm" value="NuSVC"/>
-            <param name="random_state" value="5"/>
-            <output name="outfile_fit" file="svc_model02" compare="sim_size"/>
+            <param name="infile1" value="train_set.tabular" ftype="tabular" />
+            <param name="infile2" value="train_set.tabular" ftype="tabular" />
+            <param name="header1" value="True" />
+            <param name="header2" value="True" />
+            <param name="col1" value="1,2,3,4" />
+            <param name="col2" value="5" />
+            <param name="selected_task" value="train" />
+            <param name="selected_algorithm" value="NuSVC" />
+            <param name="random_state" value="5" />
+            <output name="outfile_fit" file="svc_model02" compare="sim_size" />
         </test>
         <test>
-            <param name="infile1" value="train_set.tabular" ftype="tabular"/>
-            <param name="infile2" value="train_set.tabular" ftype="tabular"/>
-            <param name="header1" value="True"/>
-            <param name="header2" value="True"/>
-            <param name="col1" value="1,2,3,4"/>
-            <param name="col2" value="5"/>
-            <param name="selected_task" value="train"/>
-            <param name="selected_algorithm" value="LinearSVC"/>
-            <param name="random_state" value="5"/>
-            <output name="outfile_fit" file="svc_model03" compare="sim_size"/>
+            <param name="infile1" value="train_set.tabular" ftype="tabular" />
+            <param name="infile2" value="train_set.tabular" ftype="tabular" />
+            <param name="header1" value="True" />
+            <param name="header2" value="True" />
+            <param name="col1" value="1,2,3,4" />
+            <param name="col2" value="5" />
+            <param name="selected_task" value="train" />
+            <param name="selected_algorithm" value="LinearSVC" />
+            <param name="random_state" value="5" />
+            <output name="outfile_fit" file="svc_model03" compare="sim_size" />
         </test>
         <test>
-            <param name="infile_model" value="svc_model01" ftype="zip"/>
-            <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
-            <param name="header" value="True"/>
-            <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="svc_prediction_result01.tabular"/>
+            <param name="infile_model" value="svc_model01" ftype="zip" />
+            <param name="infile_data" value="test_set.tabular" ftype="tabular" />
+            <param name="header" value="True" />
+            <param name="selected_task" value="load" />
+            <output name="outfile_predict" file="svc_prediction_result01.tabular" />
         </test>
         <test>
-            <param name="infile_model" value="svc_model02" ftype="zip"/>
-            <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
-            <param name="header" value="True"/>
-            <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="svc_prediction_result02.tabular"/>
+            <param name="infile_model" value="svc_model02" ftype="zip" />
+            <param name="infile_data" value="test_set.tabular" ftype="tabular" />
+            <param name="header" value="True" />
+            <param name="selected_task" value="load" />
+            <output name="outfile_predict" file="svc_prediction_result02.tabular" />
         </test>
         <test>
-            <param name="infile_model" value="svc_model03" ftype="zip"/>
-            <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
-            <param name="header" value="True"/>
-            <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="svc_prediction_result03.tabular"/>
+            <param name="infile_model" value="svc_model03" ftype="zip" />
+            <param name="infile_data" value="test_set.tabular" ftype="tabular" />
+            <param name="header" value="True" />
+            <param name="selected_task" value="load" />
+            <output name="outfile_predict" file="svc_prediction_result03.tabular" />
         </test>
         <!-- The following test is expected to fail, it is testing the whitelist/blacklist filtering.
         It loads a pickle with malicious content that we do not accept. -->
         <test expect_failure="true">
-            <param name="infile_model" value="pickle_blacklist" ftype="zip"/>
-            <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
-            <param name="header" value="True"/>
-            <param name="selected_task" value="load"/>
+            <param name="infile_model" value="pickle_blacklist" ftype="zip" />
+            <param name="infile_data" value="test_set.tabular" ftype="tabular" />
+            <param name="header" value="True" />
+            <param name="selected_task" value="load" />
         </test>
     </tests>
     <help><![CDATA[
@@ -203,5 +203,5 @@
 
     ]]>
     </help>
-    <expand macro="sklearn_citation"/>
+    <expand macro="sklearn_citation" />
 </tool>