changeset 0:edcf58ab7552 draft

planemo upload for repository https://github.com/eteriSokhoyan/galaxytools/tree/master/tools/GraphClust/Plotting commit 057c2fd398055dc86eb2c00d8a74f301d5c231d9-dirty

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MotifFinderPlot.py	Wed Feb 22 16:53:29 2017 -0500
@@ -0,0 +1,60 @@
+#!/usr/bin/env python
+
+import matplotlib
+matplotlib.use('Agg')
+from matplotlib import pyplot as plt
+import matplotlib.patches as mpatches
+from collections import defaultdict
+import glob
+import pandas as pd
+import itertools
+import seaborn as sns
+
+
+def plot_bar(ranges, colors, orig_names, cluster_nums):
+    fig, ax = plt.subplots()
+    for i, k in enumerate(sorted(ranges.keys())):
+        ax.broken_barh(ranges[k], (i-0.25, 0.5), facecolors=colors[k])
+
+    ax.set_xlim(0)
+    ax.set_xlabel('position in sequence')
+    ax.set_yticklabels(['']+[k+'-'+orig_names[k] for k in sorted(ranges.keys())])
+    ax.grid(True)
+    fig.suptitle('Structure motif prediction\nRegions with same color are prediticted to have similar structures')
+    # Add the legend
+    patches = [mpatches.Patch(color=cluster_nums[lab], label=lab) for lab in sorted(cluster_nums)]
+    ax.legend(handles=patches, loc='best')  # , bbox_to_anchor=(1, 0.5), loc='center left')
+    plt.savefig("motif_plot.png", bbox_inches='tight')
+
+
+def parse_clusters():
+    currentdir_files = sorted(list(glob.glob('*')))
+    print ("currentdir_files are: ", currentdir_files)
+    print ("RESULTS_files are: ", sorted(list(glob.glob('RESULTS/*'))))
+    
+    cluster_files = sorted(list(glob.glob('RESULTS/*.cluster.all')))
+    if len(cluster_files) == 0:
+        raise RuntimeError('Expected cluster.all search path is empty:{}'.format(cluster_files))
+    palette = itertools.cycle(sns.color_palette("Set2", len(cluster_files)))
+
+
+    ranges = defaultdict(list)
+    colors = defaultdict(list)
+    orig_names = defaultdict(list)
+    cluster_nums = defaultdict(list)
+    for cluster_file in cluster_files:
+        cluster_color = next(palette)
+        df_cluster = pd.read_csv(cluster_file, sep='\s+', header=None)
+        for irow, row in df_cluster.iterrows():
+            seq, start, end, strand = row[0].split("#")
+            ranges[seq].append((int(start), int(end)-int(start)+1))
+            colors[seq].append(cluster_color)
+            assert row[1] == 'RESULT'
+            cluster_nums['cluster-{}'.format(row[2])] = cluster_color
+            assert row[9] == 'ORIGHEAD'
+            orig_names[seq] = row[10]
+    return ranges, colors, orig_names, cluster_nums
+
+
+my_ranges, my_colors, my_orig_names, my_cluster_nums = parse_clusters()
+plot_bar(my_ranges, my_colors, my_orig_names, my_cluster_nums)

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MotifFinderPlot.xml	Wed Feb 22 16:53:29 2017 -0500
@@ -0,0 +1,35 @@
+<tool id="motifFinderPlot" name="Motif_Finder_Plot" version="0.1">
+  <requirements>
+    <!-- <requirement type="package" version="2.0.0">matplotlib</requirement> -->
+    <!-- <requirement type="package" version='0.19.2'>pandas</requirement> -->
+    <requirement type="package" version='0.7.1'>seaborn</requirement>
+  </requirements>
+  <stdio>
+    <exit_code range="1:" />
+  </stdio>
+  <command>
+    <![CDATA[
+        unzip $RESULTS -d "RESULTS"  &> /dev/null &&
+        python '$__tool_directory__/MotifFinderPlot.py'
+]]>
+  </command>
+  <inputs>
+    <param type="data" name="RESULTS" format="zip" />
+  </inputs>
+  <outputs>
+    <data name="motif_plot" format="png" from_work_dir="motif_plot.png" label="motif_plot"  />
+  </outputs>
+  <tests>
+    <test>
+      <param name="RESULTS" value="RESULTS.zip" ftype="searchgui_archive"/>
+      <output name="motif_plot" file="motif_plot.png" ftype="png" compare="sim_size" />
+    </test>
+  </tests>
+  <help>
+    <![CDATA[
+
+    ]]>
+  </help>
+  <citations>
+  </citations>
+</tool>

Binary file test-data/RESULTS.zip has changed

Binary file test-data/motif_plot.png has changed