0.0.26

examples/ipython/campsite.ipynb

@@ -42,7 +42,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install docplex==0.0.24"
+    "!pip install docplex"
    ]
   },
   {
@@ -287,7 +287,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "version": "2.7.8"
   }
  },
  "nbformat": 4,

examples/ipython/kmedian.ipynb

@@ -103,7 +103,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install docplex==0.0.24"
+    "!pip install docplex"
    ]
   },
   {
@@ -469,7 +469,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "version": "2.7.8"
   }
  },
  "nbformat": 4,

examples/ipython/matchmaker.ipynb

@@ -51,7 +51,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install docplex==0.0.24"
+    "!pip install docplex"
    ]
   },
   {
@@ -243,7 +243,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "version": "2.7.8"
   }
  },
  "nbformat": 4,

examples/ipython/n_c.ipynb

@@ -24,7 +24,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install docplex==0.0.24"
+    "!pip install docplex"
    ]
   },
   {
@@ -351,7 +351,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "version": "2.7.8"
   }
  },
  "nbformat": 4,

examples/ipython/warehouse.ipynb

@@ -163,7 +163,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install docplex>=0.0.24"
+    "!pip install docplex"
    ]
   },
   {
@@ -642,7 +642,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "version": "2.7.8"
   }
  },
  "nbformat": 4,

examples/ipython/whiskas.ipynb

@@ -79,7 +79,7 @@
     }
    ],
    "source": [
-    "!pip install docplex>=0.0.24"
+    "!pip install docplex"
    ]
   },
   {
@@ -419,21 +419,21 @@
  "metadata": {
   "celltoolbar": "Dashboard",
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "python3"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3
+    "version": 2
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "pygments_lexer": "ipython2",
+   "version": "2.7.8"
   }
  },
  "nbformat": 4,

examples/modeling/nurses.py

@@ -251,7 +251,7 @@ def print_solution(model):
     print("*************************** Solution ***************************")
     print("Allocation By Department:")
     for d in model.departments:
-        print ("\t{}: {}".format(d, sum(
+        print("\t{}: {}".format(d, sum(
             model.nurse_assignment_vars[n, s].solution_value for n in model.nurses for s in model.shifts if
             s.department == d)))
     print("Cost By Department:")
@@ -267,7 +267,7 @@ def print_solution(model):
         print("\t{}: total hours:{}".format(n.name, total_hours))
         for s in model.shifts:
             if model.nurse_assignment_vars[n, s].solution_value == 1:
-                print ("\t\t{}: {} {}-{}".format(s.day.name, s.department, s.start_time, s.end_time))
+                print("\t\t{}: {} {}-{}".format(s.day.name, s.department, s.start_time, s.end_time))
 
 
 SKILLS = ["Anaesthesiology",

examples/modeling/sport_scheduling.py

@@ -92,7 +92,6 @@ def build_sports(docloud_context=None):
 def solve_sports(docloud_context=None):
     model = build_sports(docloud_context=docloud_context)
     model.print_information()
-    model.export_as_lp()
     model.solve()
     model.report()
     TSolution = namedtuple("TSolution", ["week", "is_divisional", "team1", "team2"])
@@ -126,7 +125,7 @@ def solve_sports(docloud_context=None):
        url = "https://docloud.service.com/job_manager/rest/v1"
        api_key = "example api_key"
     """
-    print("This example hits the limits of CPLEX Optimization Studio and will work only the DOcloud solve.")
+    print("This example hits the limits of CPLEX Optimization Studio Community Edition and will work only with the DOcloud solve or a commercial edition of CPLEX.")
     url = "YOUR_URL_HERE"
     api_key = None
     ctx = DOcloudContext.make_default_context(url, api_key)

examples/workflow/cutstock.py

@@ -78,7 +78,7 @@ def setup_objective(self):
         self.minimize(1 - self.scal_prod(self.use_vars, self.duals))
 
     def get_use_values(self):
-        assert self.has_solution()
+        assert self.solution
 
         return [use_var.solution_value for use_var in self.use_vars]
 
@@ -202,7 +202,7 @@ def run(self, context=None):
         curr = self.infinity
         status = False
         while loop_count < 100 and abs(best - curr) >= obj_eps:
-            print('\n#items={},#patterns={},#vars={}'.format(len(self.items), len(self.patterns), self.variable_stats))
+            print('\n#items={},#patterns={}'.format(len(self.items), len(self.patterns)))
             if loop_count > 0:
                 self.refresh_model()
             status = master_model.solve()
@@ -212,7 +212,7 @@ def run(self, context=None):
                 print('{}> master model fails, stop'.format(loop_count))
                 break
             else:
-                assert master_model.has_solution()
+                assert master_model.solution
                 curr = self.objective_value
                 print('{}> new column generation iteration, best={:g}, curr={:g}'.format(loop_count, best, curr))
                 duals = self.get_fill_dual_values()

examples/workflow/lagrangian_relaxation.py

@@ -81,7 +81,7 @@ def run_GAP_model_with_Lagrangian_relaxation(As, Bs, Cs, max_iters=101, docloud_
             print("*** solve fails, stopping at iteration: %d" % loop_count)
             break
         best = mdl.objective_value
-        penalties = [pv.get_value() for pv in p_vars]
+        penalties = [pv.solution_value for pv in p_vars]
         print('%d> new lagrangian iteration, obj=%g, m=%s, p=%s' % (loop_count, best, str(multipliers), str(penalties)))
 
         do_stop = True
@@ -95,7 +95,7 @@ def run_GAP_model_with_Lagrangian_relaxation(As, Bs, Cs, max_iters=101, docloud_
 
         if do_stop:
             print("* Lagrangian relaxation succeeds, best={:g}, penalty={:g}, #iterations={}"
-                  .format(best, total_penalty.get_value(), loop_count))
+                  .format(best, total_penalty.solution_value, loop_count))
             break
         else:
             # update multipliers and start loop again.

examples/workflow/load_balancing.py

@@ -135,15 +135,15 @@ def run(self, docloud_context=None):
     def print_solution(self, do_filter_zeros=True):
         m = self
         active_servers = sorted([s for s in m.servers if m.active_var_by_server[s].solution_value == 1])
-        print ("Active Servers: {}".format(active_servers))
-        print ("*** User assignment ***")
+        print("Active Servers: {}".format(active_servers))
+        print("*** User assignment ***")
         for (u, s) in sorted(m.assign_user_to_server_vars):
             if m.assign_user_to_server_vars[(u, s)].solution_value == 1:
-                print ("{} uses {}, migration: {}".format(u, s, "yes" if m._is_migration(u, s) else "no"))
-        print ("*** Servers sleeping processes ***")
+                print("{} uses {}, migration: {}".format(u, s, "yes" if m._is_migration(u, s) else "no"))
+        print("*** Servers sleeping processes ***")
         for s in active_servers:
             sleeping = sum(self.assign_user_to_server_vars[u, s].solution_value * u.sleeping for u in self.users)
-            print ("Server: {} #sleeping={}".format(s, sleeping))
+            print("Server: {} #sleeping={}".format(s, sleeping))
 
 
 SERVERS = ["server002", "server003", "server001", "server006", "server007", "server004", "server005"]