--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mds_plot.xml	Thu Aug 15 03:39:14 2013 -0400
@@ -0,0 +1,52 @@
+<tool id="ctb_mds_plot" name="MDS Scatter Plot" version="0.1">
+    <description>of molecule similarity</description>
+    <requirements>
+        <requirement type="package" version="0.13.1">scikit_learn</requirement>
+        <requirement type="package" version="1.2.1">matplotlib</requirement>
+    </requirements>
+    <command interpreter='python'>
+        mds_plot.py
+            -i $infile
+            --oformat $oformat
+            -o $outfile
+    </command>
+    <inputs>
+        <param name="infile" type="data" format="binary" label="Similarity Matrix"/>
+        <param name='oformat' type='select' format='text' label="Format of the resulting picture">
+            <option value='png'>PNG</option>
+            <option value='svg'>SVG</option>
+        </param>
+    </inputs>
+    <outputs>
+        <data type="data" format="png" name="outfile" label="${tool.name} on ${on_string}"></data>
+    </outputs>
+    <tests>
+        <test>
+            <param name="infile" ftype="tabular" value="sm.dat" />
+            <output ftype="png" name="outfile" file='mds_plot_on_sm_dat.png' />
+        </test>
+    </tests>
+    <help>
+
+**Note**. You need an NxN similarity matrix as input. Use the NxN Clustering tool to generate one.
+
+**What it does**
+
+Scatter plot of similarity matrix after embeding in 2D coordinates using Multidimensional Scaling (MDS).
+
+-----
+
+**Example**
+
+* input::
+    Similarity Matrix
+
+* output::
+
+	Scatter plot
+
+.. image:: $PATH_TO_IMAGES/mds_plot.png
+
+    </help>
+
+</tool>