# HG changeset patch
# User iuc
# Date 1649842436 0
# Node ID 0a2a2e19bf2d1c68ed1b0574a0a3e279edb709d9
# Parent  f4899d509faad1ec4206395a06853366ea510b12
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/heatmap2 commit 4f9970932fa3521656d5618582ba5df4173ca66c"

diff -r f4899d509faa -r 0a2a2e19bf2d heatmap2.xml
--- a/heatmap2.xml	Tue Apr 12 15:53:08 2022 +0000
+++ b/heatmap2.xml	Wed Apr 13 09:33:56 2022 +0000
@@ -1,9 +1,10 @@
-<tool id="ggplot2_heatmap2" name="heatmap2" version="@VERSION@">
+<tool id="ggplot2_heatmap2" name="heatmap2" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@">
     <macros>
-        <token name="@VERSION@">3.1.1</token>
+        <token name="@TOOL_VERSION@">3.1.1</token>
+        <token name="@VERSION_SUFFIX@">1</token>
     </macros>
     <requirements>
-        <requirement type="package" version="@VERSION@">r-gplots</requirement>
+        <requirement type="package" version="@TOOL_VERSION@">r-gplots</requirement>
         <requirement type="package" version="1.1_3">r-rcolorbrewer</requirement>
     </requirements>
     <command detect_errors="exit_code"><![CDATA[
@@ -41,7 +42,7 @@
 
 #if $zscore_cond.zscore == "rows":
     linput <- t(apply(linput, 1, scale))
-    colnames(linput) <- colnames(input)
+    colnames(linput) <- colnames(input)[2:ncol(input)]
     rownames(linput) <- input[,1]
     scale <- "none"
 #elif $zscore_cond.zscore == "cols":
@@ -278,6 +279,31 @@
             <param name="type" value="two"/>
             <output name="output1" file="result1pearson.pdf" compare="sim_size"/>
         </test>
+        <test>
+            <param name="input1" value="mtcars.txt"/>
+            <param name="zscore" value="rows"/>
+            <param name="type" value="three"/>
+            <param name="image_file_format" value="png"/>
+            <output name="output1" file="result4.png" compare="sim_size"/>
+        </test>
+        <test>
+            <param name="input1" value="mtcars.txt"/>
+            <param name="cluster" value="yes"/>
+            <param name="distance" value="pearson_correlation"/>
+            <param name="scale" value="row"/>
+            <param name="type" value="three"/>
+            <param name="image_file_format" value="png"/>
+            <output name="output1" file="result5.png" compare="sim_size"/>
+        </test>
+        <test>
+            <param name="input1" value="mtcars.txt"/>
+            <param name="cluster" value="yes"/>
+            <param name="distance" value="spearmann_correlation"/>
+            <param name="scale" value="column"/>
+            <param name="type" value="three"/>
+            <param name="image_file_format" value="png"/>
+            <output name="output1" file="result6.png" compare="sim_size"/>
+        </test>
     </tests>
     <help><![CDATA[
 This tool employs the heatmap.2 function from the R gplots package and will generate a heatmap of your data. If clustering is enabled, the heatmap uses the Euclidean distance method and the Complete hierarchical clustering method by default.
diff -r f4899d509faa -r 0a2a2e19bf2d test-data/result4.png
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diff -r f4899d509faa -r 0a2a2e19bf2d test-data/result5.png
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diff -r f4899d509faa -r 0a2a2e19bf2d test-data/result6.png
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