# HG changeset patch
# User mheinzl
# Date 1557314478 14400
# Node ID 89ddbe5ae2aa292456fe04c700330de09654914a
# Parent  64f0362c974ebb1bf1890c4a8bbccc9ba9847914
planemo upload for repository https://github.com/monikaheinzl/duplexanalysis_galaxy/tree/master/tools/fsd commit b8a2f7b7615b2bcd3b602027af31f4e677da94f6-dirty

diff -r 64f0362c974e -r 89ddbe5ae2aa fsd.py
--- a/fsd.py	Wed May 08 07:14:49 2019 -0400
+++ b/fsd.py	Wed May 08 07:21:18 2019 -0400
@@ -78,8 +78,7 @@
     data_array_list = []
     list_to_plot_original = []
     colors = []
-    bins = numpy.arange(1, 22)
-    
+    bins = numpy.arange(1, 22)    
     with open(title_file, "w") as output_file, PdfPages(title_file2) as pdf:
         fig = plt.figure()
         fig.subplots_adjust(left=0.12, right=0.97, bottom=0.23, top=0.94, hspace=0)
@@ -283,9 +282,9 @@
                 ticks1[len(ticks1) - 1] = ">20"
 
             if to_plot[l] == "Relative frequencies":
-                counts_rel = ax.hist(list_to_plot2, bins=numpy.arange(minimumX, maximumX + 2), stacked=False, edgecolor="black", linewidth=1, label=label, align="left", alpha=1, rwidth=0.8, normed=True)
+                counts_rel = ax.hist(list_to_plot2, bins=numpy.arange(minimumX, maximumX + 2), stacked=False, edgecolor="black", linewidth=1, label=label, align="left", alpha=0.8, rwidth=0.8, normed=True)
             else:
-                counts = ax.hist(list_to_plot2, bins=numpy.arange(minimumX, maximumX + 2), stacked=False, edgecolor="black", linewidth=1, label=label, align="left", alpha=1, rwidth=0.8)
+                counts = ax.hist(list_to_plot2, bins=numpy.arange(minimumX, maximumX + 2), stacked=False, edgecolor="black", linewidth=1, label=label, align="left", alpha=0.8, rwidth=0.8)
                 ax.legend(loc='upper right', fontsize=14, frameon=True, bbox_to_anchor=(0.9, 1))
 
             ax.set_xticks(numpy.array(ticks))
@@ -316,17 +315,14 @@
                 unique, c = numpy.unique(list_to_plot2[i], return_counts=True)
                 new_c = []
                 new_unique = []
-                
                 for t in ticks:
                     if t not in unique:
-                        new_c.append(0) # add zero count of not occuring
+                        new_c.append(0)  # add zero count of not occuring
                         new_unique.append(t)
                     else:
                         c_idx = numpy.where(t == unique)[0]
                         new_c.append(c[c_idx])
                         new_unique.append(unique[c_idx])
-                print(new_unique)
-                print(new_c)
                 y = numpy.array(new_unique) * numpy.array(new_c)
                 if len([list_to_plot_original > 20]) > 0:
                     y[len(y) - 1] = sum(list_to_plot_original[i][list_to_plot_original[i] > 20])
@@ -338,10 +334,10 @@
 
                 if to_plot[l] == "Relative frequencies":
                     counts2_rel = ax.bar(x, list(numpy.float_(y)) / sum(y), align="edge", width=1./(len(list_to_plot) + 1),
-                                         edgecolor="black", label=label[i], alpha=1, linewidth=1, color=colors[i])
+                                         edgecolor="black", label=label[i], alpha=0.8, linewidth=1, color=colors[i])
                 else:
-                    counts2 = ax.bar(x, y, align="edge", width=1./len(list_to_plot), edgecolor="black", label=label[i],
-                                     alpha=1, linewidth=1, color=colors[i])
+                    counts2 = ax.bar(x, y, align="edge", width=1./(len(list_to_plot) + 1), edgecolor="black", label=label[i],
+                                     alpha=0.8, linewidth=1, color=colors[i])
                 if i == len(list_to_plot2):
                     barWidth += 1. / (len(list_to_plot) + 1) + 1. / (len(list_to_plot) + 1)
                 else: