diff pca_cosine.xml @ 1:d18e7db42633 draft

"planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3b99f08f22b9e0c16c0a0adc82f8c16c1a25cedf"

--- a/pca_cosine.xml	Wed Apr 03 15:48:45 2019 -0400
+++ b/pca_cosine.xml	Mon Oct 07 12:50:44 2019 -0400
@@ -1,5 +1,5 @@
 <tool id="mdanalysis_cosine_analysis" name="Cosine Content" version="@VERSION@">
-    <description>Measure the cosine content of the PCA projection</description>
+    <description>- measure the cosine content of the PCA projection</description>
     <macros>
         <import>macros.xml</import>
     </macros>
@@ -7,8 +7,10 @@
     <command detect_errors="exit_code">
 <![CDATA[
      python '$__tool_directory__/pca_cosine.py' 
-        --idcd '$dcdin' 
-        --ipdb '$pdbin'
+        --itraj '$trajin' 
+        --istr '$strin'
+        --itrajext '$trajin.ext'
+        --istrext '$strin.ext'
         --icomponents '$components'
         --iindex '$index' 
         --output '$output' 
@@ -35,16 +37,25 @@
               </assert_contents>
             </output>
         </test>
+        <test>
+            <expand macro="tests_inputs_gmx"/>
+            <param name="components" value="3"/>
+            <param name="index" value="0"/>
+            <output name="cosout">
+              <assert_contents>
+                <has_text text="0.583" />
+              </assert_contents>
+            </output>
+        </test>
     </tests>
     <help><![CDATA[
 .. class:: infomark
 
 **What it does**
         
-The cosine content of the principal components is a good indicator for determine good or bad sampling and can be use to determine the convergence of the MD simulation.
-This tool can calculate the cosine content of a user define PCA projection.
-This tool use zero based indexes (0 is PC1).  
-    
+The cosine content of the principal components is a good indicator for determining the quality of the sampling and can be used to determine the convergence of the MD simulation.
+This tool can calculate the cosine content of a user-defined PCA projection. Note: it uses zero-based indexes (i.e. 0 is the first principal component).  
+
 _____
 
 
@@ -63,7 +74,7 @@
 **Output**
 
        - The cosine content value.
-       - Tab-separated file of raw data of first three principle component.
+       - Tab-separated file of raw data of the first three principal components.
 
     ]]></help>
       <expand macro="citations">