Legendary Output, v1.1

src/Generator/generator.py

@@ -38,7 +38,8 @@ def accept(solution):
     Maybe skip this during the first step to generate a more
     random solution.
     """
-    return tighten(solution)
+    #return tighten(solution)
+    return solution
 
 
 def tighten(solution):

src/Output/output.py

@@ -1,7 +1,9 @@
 import matplotlib.pyplot as plt
 from matplotlib import colors
+from matplotlib import patches
 import numpy as np
 from SchedulingAlgorithms.simanneal import rate
+import random
 
 def create_plot(problem, solution):
     
@@ -9,14 +11,20 @@ def create_plot(problem, solution):
 
     with plt.xkcd():
         fig,ax = plt.subplots()
+        colorlist = list(colors.XKCD_COLORS.values())
+        random.shuffle(colorlist)
         for m in range(0, problem.machines):
             mach_ops = [ x for x in solution if problem.problem_data[x[1][0]][x[1][1]][1] == m ]
             xranges = [ (x[0], problem.problem_data[x[1][0]][x[1][1]][0]) for x in mach_ops ]
             ax.broken_barh(xranges, ((problem.machines - m)*10, 9), 
-                    facecolors=[list(colors.XKCD_COLORS.values())[x[1][0]] for x in mach_ops])
+                    facecolors=[colorlist[x[1][0]] for x in mach_ops])
         ax.set_ylim(5, 5 + (problem.machines+1)*10)
         ax.set_xlim(0, 1.25 * end)
         ax.set_yticks([15 + m * 10 for m in range(0, problem.machines)])
         ax.set_yticklabels([ problem.machines - 1 - m for m in range(0, problem.machines)] )
+        handlecolors = colorlist[0:problem.jobs]
+        handles = [ patches.Patch(color = handlecolors[j], label = "Job "+str(j)) for j in range(0,problem.jobs) ]
+        labels = ["Job "+str(j) for j in range(0,problem.jobs)]
+        ax.legend(handles, labels)
 
     plt.show()

src/example.py

@@ -1,9 +1,10 @@
-from Generator import generator as g
+#import Parser.js1_style as p
+import Parser.js2_style as p
 from SchedulingAlgorithms import simanneal as sim
 from Output import output as o
 
-g.mock()
-problem = g.problem
+#problem = p.parse_file("../inputdata/jobshop1.txt")[0]
+problem = p.parse_file("../inputdata/sample")
 sim.init(problem)
 solution = sim.anneal()
 o.create_plot(problem, solution)