cleanup is_run_from_ipython()

examples/python/gate_scheduling_sat.py

@@ -23,6 +23,7 @@ The objective is to minimize the max end time of all jobs.
 """
 
 from ortools.sat.python import cp_model
+from ortools.sat.python import visualization
 
 
 def main():
@@ -115,17 +116,36 @@ def main():
 
 
   # Output solution.
-  print('Solution')
-  print('  - makespan = %i' % solver.ObjectiveValue())
-  for i in all_jobs:
-    performed_machine = 1 - solver.Value(performed[i])
-    start = solver.Value(starts[i])
-    print('  - Job %i starts at %i on machine %i' %
-          (i, start, performed_machine))
-  print('Statistics')
-  print('  - conflicts : %i' % solver.NumConflicts())
-  print('  - branches  : %i' % solver.NumBranches())
-  print('  - wall time : %f ms' % solver.WallTime())
+  if visualization.run_from_ipython():
+    output = visualization.SvgWrapper(solver.ObjectiveValue(), max_length, 40.0)
+    output.AddTitle('Makespan = %i' % solver.ObjectiveValue())
+    color_manager = visualization.ColorManager()
+    color_manager.SeedRandomColor(0)
+
+    for i in all_jobs:
+      performed_machine = 1 - solver.Value(performed[i])
+      start = solver.Value(starts[i])
+      dx = jobs[i][0]
+      dy = jobs[i][1]
+      sy = performed_machine * (max_length - dy)
+      output.AddRectangle(start, sy, dx, dy, color_manager.RandomColor(),
+                          'black', 'j%i' % i)
+
+    output.AddXScale()
+    output.AddYScale()
+    output.Display()
+  else:
+    print('Solution')
+    print('  - makespan = %i' % solver.ObjectiveValue())
+    for i in all_jobs:
+      performed_machine = 1 - solver.Value(performed[i])
+      start = solver.Value(starts[i])
+      print('  - Job %i starts at %i on machine %i' %
+            (i, start, performed_machine))
+    print('Statistics')
+    print('  - conflicts : %i' % solver.NumConflicts())
+    print('  - branches  : %i' % solver.NumBranches())
+    print('  - wall time : %f ms' % solver.WallTime())
 
 
 if __name__ == '__main__':

examples/python/hidato_sat.py

@@ -12,6 +12,7 @@
 # limitations under the License.
 
 from ortools.sat.python import cp_model
+from ortools.sat.python import visualization
 
 
 def BuildPairs(rows, cols):
@@ -130,12 +131,12 @@ def SolveHidato(puzzle, index):
 
   r = len(puzzle)
   c = len(puzzle[0])
-
-  print('')
-  print('----- Solving problem %i -----' % index)
-  print('')
-  print(('Initial game (%i x %i)' % (r, c)))
-  PrintMatrix(puzzle)
+  if not visualization.run_from_ipython():
+    print('')
+    print('----- Solving problem %i -----' % index)
+    print('')
+    print(('Initial game (%i x %i)' % (r, c)))
+    PrintMatrix(puzzle)
 
   #
   # declare variables
@@ -170,11 +171,24 @@ def SolveHidato(puzzle, index):
   status = solver.Solve(model)
 
   if status == cp_model.MODEL_SAT:
-    PrintSolution([solver.Value(x) for x in positions], r, c,)
-    print('Statistics')
-    print('  - conflicts : %i' % solver.NumConflicts())
-    print('  - branches  : %i' % solver.NumBranches())
-    print('  - wall time : %f ms' % solver.WallTime())
+    if visualization.run_from_ipython():
+      output = visualization.SvgWrapper(10, r, 40.0)
+      for i in range(len(positions)):
+        val = solver.Value(positions[i])
+        x = val % c
+        y = val // c
+        color = 'white' if puzzle[y][x] == 0 else 'lightgreen'
+        value = solver.Value(positions[i])
+        output.AddRectangle(x, r - y - 1, 1, 1, color, 'black', str(i + 1))
+
+      output.AddTitle('Puzzle %i solved in %f s' % (index, solver.WallTime()))
+      output.Display()
+    else:
+      PrintSolution([solver.Value(x) for x in positions], r, c,)
+      print('Statistics')
+      print('  - conflicts : %i' % solver.NumConflicts())
+      print('  - branches  : %i' % solver.NumBranches())
+      print('  - wall time : %f ms' % solver.WallTime())
 
 
 def main():

examples/python/jobshop_ft06_sat.py

@@ -83,8 +83,13 @@ def main():
   solver = cp_model.CpSolver()
   response = solver.Solve(model)
 
-  # Print out makespan.
-  print('Optimal makespan: %i' % solver.ObjectiveValue())
+  # Output solution.
+  if visualization.run_from_ipython():
+    starts = [[solver.Value(all_tasks[(i, j)][0]) for j in all_machines]
+              for i in all_jobs]
+    visualization.DisplayJobshop(starts, durations, machines, 'FT06')
+  else:
+    print('Optimal makespan: %i' % solver.ObjectiveValue())
 
 
 if __name__ == '__main__':