--- a/PTModel.xml	Fri Nov 06 20:17:18 2020 +0000
+++ b/PTModel.xml	Thu Dec 01 19:05:16 2022 +0000
@@ -1,13 +1,11 @@
 <?xml version='1.0' encoding='UTF-8'?>
 <!--This is a configuration file for the integration of a tools into Galaxy (https://galaxyproject.org/). This file was automatically generated using CTDConverter.-->
 <!--Proposed Tool Section: [Peptide property prediction]-->
-<tool id="PTModel" name="PTModel" version="@TOOL_VERSION@+galaxy@GALAXY_VERSION@" profile="20.05">
+<tool id="PTModel" name="PTModel" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
   <description>Trains a model for the prediction of proteotypic peptides from a training set.</description>
   <macros>
     <token name="@EXECUTABLE@">PTModel</token>
     <import>macros.xml</import>
-    <import>macros_autotest.xml</import>
-    <import>macros_test.xml</import>
   </macros>
   <expand macro="requirements"/>
   <expand macro="stdio"/>
@@ -68,30 +66,30 @@
     <configfile name="hardcoded_json"><![CDATA[{"log": "log.txt", "threads": "\${GALAXY_SLOTS:-1}", "no_progress": true}]]></configfile>
   </configfiles>
   <inputs>
-    <param name="in_positive" argument="-in_positive" type="data" format="idxml" optional="false" label="input file with positive examples" help=" select idxml data sets(s)"/>
-    <param name="in_negative" argument="-in_negative" type="data" format="idxml" optional="false" label="input file with negative examples" help=" select idxml data sets(s)"/>
-    <param name="c" argument="-c" type="float" optional="true" value="1.0" label="the penalty parameter of the svm" help=""/>
-    <param name="svm_type" argument="-svm_type" display="radio" type="select" optional="false" label="the type of the svm (NU_SVC or C_SVC)" help="">
+    <param argument="-in_positive" type="data" format="idxml" optional="false" label="input file with positive examples" help=" select idxml data sets(s)"/>
+    <param argument="-in_negative" type="data" format="idxml" optional="false" label="input file with negative examples" help=" select idxml data sets(s)"/>
+    <param argument="-c" type="float" optional="true" value="1.0" label="the penalty parameter of the svm" help=""/>
+    <param argument="-svm_type" type="select" optional="true" label="the type of the svm (NU_SVC or C_SVC)" help="">
       <option value="NU_SVC">NU_SVC</option>
       <option value="C_SVC" selected="true">C_SVC</option>
-      <expand macro="list_string_san"/>
+      <expand macro="list_string_san" name="svm_type"/>
     </param>
-    <param name="nu" argument="-nu" type="float" optional="true" min="0.0" max="1.0" value="0.5" label="the nu parameter [0..1] of the svm (for nu-SVR)" help=""/>
-    <param name="kernel_type" argument="-kernel_type" display="radio" type="select" optional="false" label="the kernel type of the svm" help="">
+    <param argument="-nu" type="float" optional="true" min="0.0" max="1.0" value="0.5" label="the nu parameter [0..1] of the svm (for nu-SVR)" help=""/>
+    <param argument="-kernel_type" type="select" optional="true" label="the kernel type of the svm" help="">
       <option value="LINEAR">LINEAR</option>
       <option value="RBF">RBF</option>
       <option value="POLY">POLY</option>
       <option value="OLIGO" selected="true">OLIGO</option>
-      <expand macro="list_string_san"/>
+      <expand macro="list_string_san" name="kernel_type"/>
     </param>
-    <param name="degree" argument="-degree" type="integer" optional="true" min="1" value="1" label="the degree parameter of the kernel function of the svm (POLY kernel)" help=""/>
-    <param name="border_length" argument="-border_length" type="integer" optional="true" min="1" value="22" label="length of the POBK" help=""/>
-    <param name="k_mer_length" argument="-k_mer_length" type="integer" optional="true" min="1" value="1" label="k_mer length of the POBK" help=""/>
-    <param name="sigma" argument="-sigma" type="float" optional="true" value="5.0" label="sigma of the POBK" help=""/>
-    <param name="max_positive_count" argument="-max_positive_count" type="integer" optional="true" min="1" value="1000" label="quantity of positive samples for training (randomly chosen if smaller than available quantity)" help=""/>
-    <param name="max_negative_count" argument="-max_negative_count" type="integer" optional="true" min="1" value="1000" label="quantity of positive samples for training (randomly chosen if smaller than available quantity)" help=""/>
-    <param name="redundant" argument="-redundant" type="boolean" truevalue="true" falsevalue="false" checked="false" label="if the input sets are redundant and the redundant peptides should occur more than once in the training set, this flag has to be set" help=""/>
-    <param name="additive_cv" argument="-additive_cv" type="boolean" truevalue="true" falsevalue="false" checked="false" label="if the step sizes should be interpreted additively (otherwise the actual value is multiplied with the step size to get the new value" help=""/>
+    <param argument="-degree" type="integer" optional="true" min="1" value="1" label="the degree parameter of the kernel function of the svm (POLY kernel)" help=""/>
+    <param argument="-border_length" type="integer" optional="true" min="1" value="22" label="length of the POBK" help=""/>
+    <param argument="-k_mer_length" type="integer" optional="true" min="1" value="1" label="k_mer length of the POBK" help=""/>
+    <param argument="-sigma" type="float" optional="true" value="5.0" label="sigma of the POBK" help=""/>
+    <param argument="-max_positive_count" type="integer" optional="true" min="1" value="1000" label="quantity of positive samples for training (randomly chosen if smaller than available quantity)" help=""/>
+    <param argument="-max_negative_count" type="integer" optional="true" min="1" value="1000" label="quantity of positive samples for training (randomly chosen if smaller than available quantity)" help=""/>
+    <param argument="-redundant" type="boolean" truevalue="true" falsevalue="false" checked="false" label="if the input sets are redundant and the redundant peptides should occur more than once in the training set, this flag has to be set" help=""/>
+    <param argument="-additive_cv" type="boolean" truevalue="true" falsevalue="false" checked="false" label="if the step sizes should be interpreted additively (otherwise the actual value is multiplied with the step size to get the new value" help=""/>
     <section name="cv" title="Parameters for the grid search / cross validation:" help="" expanded="false">
       <param name="skip_cv" argument="-cv:skip_cv" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Has to be set if the cv should be skipped and the model should just be trained with the specified parameters" help=""/>
       <param name="number_of_runs" argument="-cv:number_of_runs" type="integer" optional="true" min="1" value="10" label="number of runs for the CV" help=""/>
@@ -110,9 +108,9 @@
       <param name="sigma_stop" argument="-cv:sigma_stop" type="float" optional="true" value="15.0" label="stopping point of sigma" help=""/>
     </section>
     <expand macro="adv_opts_macro">
-      <param name="force" argument="-force" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Overrides tool-specific checks" help=""/>
-      <param name="test" argument="-test" type="hidden" optional="true" value="False" label="Enables the test mode (needed for internal use only)" help="">
-        <expand macro="list_string_san"/>
+      <param argument="-force" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Overrides tool-specific checks" help=""/>
+      <param argument="-test" type="hidden" optional="true" value="False" label="Enables the test mode (needed for internal use only)" help="">
+        <expand macro="list_string_san" name="test"/>
       </param>
     </expand>
     <param name="OPTIONAL_OUTPUTS" type="select" optional="true" multiple="true" label="Optional outputs">
@@ -133,13 +131,55 @@
       <filter>OPTIONAL_OUTPUTS is not None and "ctd_out_FLAG" in OPTIONAL_OUTPUTS</filter>
     </data>
   </outputs>
-  <tests>
-    <expand macro="autotest_PTModel"/>
-    <expand macro="manutest_PTModel"/>
+  <tests><!-- TOPP_PTModel_1 -->
+    <test expect_num_outputs="2">
+      <section name="adv_opts">
+        <param name="force" value="false"/>
+        <param name="test" value="true"/>
+      </section>
+      <param name="in_positive" value="PTModel_1_input_positive.idXML"/>
+      <param name="in_negative" value="PTModel_1_input_negative.idXML"/>
+      <output name="out" file="PTModel_1_output.tmp" compare="sim_size" delta_frac="0.7" ftype="txt"/>
+      <param name="c" value="0.5"/>
+      <param name="svm_type" value="C_SVC"/>
+      <param name="nu" value="0.5"/>
+      <param name="kernel_type" value="OLIGO"/>
+      <param name="degree" value="1"/>
+      <param name="border_length" value="22"/>
+      <param name="k_mer_length" value="1"/>
+      <param name="sigma" value="5.0"/>
+      <param name="max_positive_count" value="1000"/>
+      <param name="max_negative_count" value="1000"/>
+      <param name="redundant" value="false"/>
+      <param name="additive_cv" value="false"/>
+      <section name="cv">
+        <param name="skip_cv" value="true"/>
+        <param name="number_of_runs" value="10"/>
+        <param name="number_of_partitions" value="10"/>
+        <param name="degree_start" value="1"/>
+        <param name="degree_step_size" value="2"/>
+        <param name="degree_stop" value="4"/>
+        <param name="c_start" value="1.0"/>
+        <param name="c_step_size" value="100.0"/>
+        <param name="c_stop" value="1000.0"/>
+        <param name="nu_start" value="0.1"/>
+        <param name="nu_step_size" value="1.3"/>
+        <param name="nu_stop" value="0.9"/>
+        <param name="sigma_start" value="1.0"/>
+        <param name="sigma_step_size" value="1.3"/>
+        <param name="sigma_stop" value="15.0"/>
+      </section>
+      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
+      <output name="ctd_out" ftype="xml">
+        <assert_contents>
+          <is_valid_xml/>
+        </assert_contents>
+      </output>
+    </test>
   </tests>
   <help><![CDATA[Trains a model for the prediction of proteotypic peptides from a training set.
 
 
-For more information, visit http://www.openms.de/doxygen/release/2.6.0/html/TOPP_PTModel.html]]></help>
+For more information, visit http://www.openms.de/doxygen/release/2.8.0/html/TOPP_PTModel.html]]></help>
   <expand macro="references"/>
 </tool>