Update examples

examples/asyncexample.py

@@ -1,13 +1,12 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
-    from amplpy import AMPL, DataFrame
+    # You can install amplpy with "python -m pip install amplpy"
+    from amplpy import AMPL
     import amplpy
     from time import time
 

examples/dataframeexample.py

@@ -1,16 +1,18 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
+    # You can install amplpy with "python -m pip install amplpy"
     from amplpy import AMPL, DataFrame
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
 
+    # Note: If you want to perform data transformations use pandas dataframes.
+    # amplpy dataframes are simple dataframes for data communication only.
+
     # Create first dataframe (for data indexed over NUTR)
     # Add data row by row
     df1 = DataFrame("NUTR", ("n_min", "n_max"))

examples/dietmodel.py

@@ -1,18 +1,18 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
+import pandas as pd
 
 
 def main(argc, argv):
-    from amplpy import AMPL, DataFrame
+    # You can install amplpy with "python -m pip install amplpy"
+    from amplpy import AMPL
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
+
     # Create an AMPL instance
     ampl = AMPL()
-
     """
     # If the AMPL installation directory is not in the system search path:
     from amplpy import Environment
@@ -27,27 +27,31 @@ def main(argc, argv):
     model_directory = argv[2] if argc == 3 else os.path.join("..", "models")
     ampl.read(os.path.join(model_directory, "diet/diet.mod"))
 
+    # Create a pandas dataframe with data for cost, f_min, f_max
     foods = ["BEEF", "CHK", "FISH", "HAM", "MCH", "MTL", "SPG", "TUR"]
     costs = [3.59, 2.59, 2.29, 2.89, 1.89, 1.99, 1.99, 2.49]
-
     fmin = [2, 2, 2, 2, 2, 2, 2, 2]
     fmax = [10, 10, 10, 10, 10, 10, 10, 10]
 
-    df = DataFrame("FOOD")
-    df.set_column("FOOD", foods)
-    df.add_column("cost", costs)
-    df.add_column("f_min", fmin)
-    df.add_column("f_max", fmax)
+    df = pd.DataFrame(
+        list(zip(foods, costs, fmin, fmax)),
+        columns=["FOOD", "cost", "f_min", "f_max"],
+    ).set_index("FOOD")
+
+    # Send the data to AMPL and initialize the indexing set "FOOD"
     ampl.set_data(df, "FOOD")
 
+    # Create a pandas dataframe with data for n_min, n_max
     nutrients = ["A", "C", "B1", "B2", "NA", "CAL"]
     nmin = [700, 700, 700, 700, 0, 16000]
     nmax = [20000, 20000, 20000, 20000, 50000, 24000]
 
-    df = DataFrame("NUTR")
-    df.setColumn("NUTR", nutrients)
-    df.add_column("n_min", nmin)
-    df.add_column("n_max", nmax)
+    df = pd.DataFrame(
+        list(zip(nutrients, nmin, nmax)),
+        columns=["NUTR", "n_min", "n_max"],
+    ).set_index("NUTR")
+
+    # Send the data to AMPL and initialize the indexing set "NUTR"
     ampl.set_data(df, "NUTR")
 
     amounts = [
@@ -59,19 +63,22 @@ def main(argc, argv):
         [295, 770, 440, 430, 315, 400, 379, 450],
     ]
 
-    df = DataFrame(("NUTR", "FOOD"), "amt")
-    df.setValues(
-        {
-            (nutrient, food): amounts[i][j]
-            for i, nutrient in enumerate(nutrients)
-            for j, food in enumerate(foods)
-        }
-    )
-    ampl.set_data(df)
+    # Set the values for the parameter "amt"
+    ampl.param["amt"] = {
+        (nutrient, food): amounts[i][j]
+        for i, nutrient in enumerate(nutrients)
+        for j, food in enumerate(foods)
+    }
 
+    # Solve the problem
     ampl.solve()
 
-    print("Objective: {}".format(ampl.get_objective("Total_Cost").value()))
+    # Check if the problem was solved successfully
+    solve_result = ampl.get_value("solve_result")
+    if solve_result != "solved":
+        raise Exception("Failed to solve (solve_result: {})".format(solve_result))
+
+    print("Objective: {}".format(ampl.obj["Total_Cost"].value()))
 
 
 if __name__ == "__main__":

examples/efficientfrontier.py

@@ -1,12 +1,11 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
+    # You can install amplpy with "python -m pip install amplpy"
     from amplpy import AMPL
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
@@ -16,7 +15,6 @@ def main(argc, argv):
 
     # Create an AMPL instance
     ampl = AMPL()
-
     """
     # If the AMPL installation directory is not in the system search path:
     from amplpy import Environment
@@ -62,9 +60,9 @@ def main(argc, argv):
     returns = [None] * steps
     variances = [None] * steps
     for i in range(steps):
-        print("Solving for return = {:g}".format(maxret - (i - 1) * stepsize))
+        print("Solving for return = {:g}".format(maxret - i * stepsize))
         # Set target return to the desired point
-        target_return.set(maxret - (i - 1) * stepsize)
+        target_return.set(maxret - i * stepsize)
         ampl.eval("let stockopall:={};let stockrun:=stockall;")
         # Relax integrality
         ampl.set_option("relax_integrality", True)
@@ -75,7 +73,12 @@ def main(argc, argv):
         ampl.eval("let stockopall:={i in stockrun:weights[i]>0.5};")
         # Set integrality back
         ampl.set_option("relax_integrality", False)
+        # Solve the problem
         ampl.solve()
+        # Check if the problem was solved successfully
+        solve_result = ampl.get_value("solve_result")
+        if solve_result != "solved":
+            raise Exception("Failed to solve (solve_result: {})".format(solve_result))
         print("QMIP result = {:g}".format(variance.value()))
         # Store data of corrent frontier point
         returns[i] = maxret - (i - 1) * stepsize

examples/firstexample.py

@@ -1,19 +1,17 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
+    # You can install amplpy with "python -m pip install amplpy"
     from amplpy import AMPL
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
 
     # Create an AMPL instance
     ampl = AMPL()
-
     """
     # If the AMPL installation directory is not in the system search path:
     from amplpy import Environment
@@ -31,6 +29,9 @@ def main(argc, argv):
 
     # Solve
     ampl.solve()
+    solve_result = ampl.get_value("solve_result")
+    if solve_result != "solved":
+        raise Exception("Failed to solve (solve_result: {})".format(solve_result))
 
     # Get objective entity by AMPL name
     totalcost = ampl.get_objective("Total_Cost")
@@ -44,6 +45,9 @@ def main(argc, argv):
 
     # Resolve and display objective
     ampl.solve()
+    solve_result = ampl.get_value("solve_result")
+    if solve_result != "solved":
+        raise Exception("Failed to solve (solve_result: {})".format(solve_result))
     print("New objective value:", totalcost.value())
 
     # Reassign data - all instances
@@ -53,18 +57,21 @@ def main(argc, argv):
 
     # Resolve and display objective
     ampl.solve()
+    solve_result = ampl.get_value("solve_result")
+    if solve_result != "solved":
+        raise Exception("Failed to solve (solve_result: {})".format(solve_result))
     print("New objective value:", totalcost.value())
 
     # Get the values of the variable Buy in a dataframe object
     buy = ampl.get_variable("Buy")
     df = buy.get_values()
-    # Print them
-    print(df)
+    # Print as pandas dataframe
+    print(df.to_pandas())
 
     # Get the values of an expression into a DataFrame object
     df2 = ampl.get_data("{j in FOOD} 100*Buy[j]/Buy[j].ub")
-    # Print them
-    print(df2)
+    # Print as pandas dataframe
+    print(df2.to_pandas())
 
 
 if __name__ == "__main__":

examples/locationtransportation.py

@@ -1,12 +1,11 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
+    # You can install amplpy with "python -m pip install amplpy"
     from amplpy import AMPL
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
@@ -62,7 +61,7 @@ def main(argc, argv):
         # Solve the subproblem.
         ampl.eval("solve Sub;")
         result = ship_cost.result()
-        if result.find("infeasible") != -1:
+        if result == "infeasible":
             # Add a feasibility cut.
             num_cut_param.set(num_cuts)
             cut_type.set(num_cuts, "ray")
@@ -85,6 +84,9 @@ def main(argc, argv):
         # Re-solve the master problem.
         print("RE-SOLVING MASTER PROBLEM")
         ampl.eval("solve Master;")
+        solve_result = ampl.get_value("solve_result")
+        if solve_result != "solved":
+            raise Exception("Failed to solve (solve_result: {})".format(solve_result))
         # Copy the data from the Build variable used in the master problem
         # to the build parameter used in the subproblem.
         build_param.set_values(build_var.get_values())

examples/multidimensionalexample.py

@@ -1,9 +1,8 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
+import pandas as pd
 
 
 def main(argc, argv):
@@ -29,6 +28,7 @@ def main(argc, argv):
     links_from = ["PITT", "PITT", "NE", "NE", "NE", "SE", "SE", "SE", "SE"]
     links_to = ["NE", "SE", "BOS", "EWR", "BWI", "EWR", "BWI", "ATL", "MCO"]
 
+    # Using amplpy.DataFrame
     df = DataFrame(("LINKSFrom", "LINKSTo"), ("cost", "capacity"))
     df.set_column("LINKSFrom", links_from)
     df.set_column("LINKSTo", links_to)
@@ -37,6 +37,18 @@ def main(argc, argv):
     print(df)
 
     ampl.set_data(df, "LINKS")
+    ampl.display("LINKS")
+
+    # Using pandas.DataFrame (recommended)
+    df = pd.DataFrame(
+        list(zip(links_from, links_to, cost, capacity)),
+        columns=["LINKSFrom", "LINKSTo", "cost", "capacity"],
+    ).set_index(["LINKSFrom", "LINKSTo"])
+    print(df)
+
+    ampl.eval("reset data LINKS;")
+    ampl.set_data(df, "LINKS")
+    ampl.display("LINKS")
 
 
 if __name__ == "__main__":

examples/optionsexample.py

@@ -1,19 +1,17 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
+    # You can install amplpy with "python -m pip install amplpy"
     from amplpy import AMPL
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
 
     # Create an AMPL instance
     ampl = AMPL()
-
     """
     # If the AMPL installation directory is not in the system search path:
     from amplpy import Environment

examples/trackingmodel.py

@@ -1,12 +1,11 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import print_function, absolute_import, division
-from builtins import map, range, object, zip, sorted
 import sys
 import os
 
 
 def main(argc, argv):
+    # You can install amplpy with "python -m pip install amplpy"
     from amplpy import AMPL
 
     os.chdir(os.path.dirname(__file__) or os.curdir)
@@ -44,8 +43,13 @@ def main(argc, argv):
 
     # Relax the integrality
     ampl.set_option("relax_integrality", True)
+
     # Solve the problem
     ampl.solve()
+    solve_result = ampl.get_value("solve_result")
+    if solve_result != "solved":
+        raise Exception("Failed to solve (solve_result: {})".format(solve_result))
+
     objectives = list(obj for name, obj in ampl.get_objectives())
     assert objectives[0].value() == ampl.get_objective("cst").value()
     print("QP objective value", ampl.get_objective("cst").value())
@@ -71,8 +75,13 @@ def main(argc, argv):
 
     # Get back to the integer problem
     ampl.set_option("relax_integrality", False)
+
     # Solve the (integer) problem
     ampl.solve()
+    solve_result = ampl.get_value("solve_result")
+    if solve_result != "solved":
+        raise Exception("Failed to solve (solve_result: {})".format(solve_result))
+
     print("QMIP objective value", ampl.get_objective("cst").value())