Ticket #9432: trac_9432.patch

sage/numerical/knapsack.py

@@ -50 +50 @@
 you can easily solve it this way::
 
     sage: from sage.numerical.knapsack import knapsack
-    sage: knapsack( [(1,2), (1.5,1), (0.5,3)], max=2) # optional - requires Glpk or COIN-OR/CBC
+    sage: knapsack( [(1,2), (1.5,1), (0.5,3)], max=2)
     [5.0, [(1, 2), (0.500000000000000, 3)]]
 
 Super-increasing sequences
@@ -593 +593 @@
     and a bag of maximum weight 2, you can easily solve it this way::
 
         sage: from sage.numerical.knapsack import knapsack
-        sage: knapsack( [(1,2), (1.5,1), (0.5,3)], max=2) # optional - requires Glpk or COIN-OR/CBC
+        sage: knapsack( [(1,2), (1.5,1), (0.5,3)], max=2)
         [5.0, [(1, 2), (0.500000000000000, 3)]]
 
-        sage: knapsack( [(1,2), (1.5,1), (0.5,3)], max=2, value_only=True) # optional - requires Glpk or COIN-OR/CBC
+        sage: knapsack( [(1,2), (1.5,1), (0.5,3)], max=2, value_only=True)
         5.0
 
     In the case where all the values (usefulness) of the items
@@ -605 +605 @@
     `(1,1), (1.5,1), (0.5,1)` the command::
 
         sage: from sage.numerical.knapsack import knapsack
-        sage: knapsack([1,1.5,0.5], max=2, value_only=True) # optional - requires Glpk or COIN-OR/CBC
+        sage: knapsack([1,1.5,0.5], max=2, value_only=True)
         2.0
 
     INPUT:

sage/numerical/mip.pyx

@@ -63 +63 @@
             sage: p = MixedIntegerLinearProgram(maximization=True)
         """
         
-        self._default_solver = None
+        self._default_solver = "GLPK"
         
         try:
             if self._default_solver == None:
@@ -79 +79 @@
         except ImportError:
             pass
 
-        try:
-            if self._default_solver == None:
-                from sage.numerical.mip_glpk import solve_glpk
-                self._default_solver = "GLPK"
-        except ImportError:
-            pass
-
-
         # List of all the MIPVariables linked to this instance of
         # MixedIntegerLinearProgram
         self._mipvariables = []
@@ -152 +144 @@
         self._constraints_matrix_j = []
         self._constraints_matrix_values = []
         self._constraints_bounds_max = []
-        self._constraints_bounds_min = []        
-
-
+        self._constraints_bounds_min = []
 
     def __repr__(self):
          r"""
@@ -492 +482 @@
         http://en.wikipedia.org/wiki/MPS_%28format%29
         """
         
-        try:
-            from sage.numerical.mip_glpk import write_mps
-        except ImportError:
-            from sage.misc.exceptions import OptionalPackageNotFoundError
-            raise OptionalPackageNotFoundError("You need GLPK installed to use this function. To install it, you can type in Sage: install_package('glpk')")
+        from sage.numerical.mip_glpk import write_mps
 
         self._update_variables_name()
         write_mps(self, filename, modern)
@@ -524 +510 @@
         For more information about the LP file format :
         http://lpsolve.sourceforge.net/5.5/lp-format.htm
         """
-        try:
-            from sage.numerical.mip_glpk import write_lp
-        except:
-            from sage.misc.exceptions import OptionalPackageNotFoundError
-            raise OptionalPackageNotFoundError("You need GLPK installed to use this function. To install it, you can type in Sage: install_package('glpk')")
+        from sage.numerical.mip_glpk import write_lp
 
         self._update_variables_name()
         write_lp(self, filename)
@@ -1052 +1034 @@
             sage: p.add_constraint(1.5*x[1] + 3*x[2], max=4)
             sage: round(p.solve(),6)
             6.666667
-            sage: p.get_values(x)
-            {0: 0.0, 1: 1.3333333333333333}
+            sage: x = p.get_values(x)
+            sage: round(x[1],6)
+            0.0
+            sage: round(x[2],6)
+            1.333333
 
          Computation of a maximum stable set in Petersen's graph::
 
@@ -1075 +1060 @@
         if solver == None:
             solver = self._default_solver
 
-
-        if solver == None:
-            from sage.misc.exceptions import OptionalPackageNotFoundError
-            raise OptionalPackageNotFoundError("There does not seem to be any (Mixed) Integer Linear Program solver installed. Please visit http://www.sagemath.org/doc/constructions/linear_programming.html to learn more about the solvers available.")
-
         try:
             if solver == "Coin":
                 from sage.numerical.mip_coin import solve_coin as solve

sage/numerical/optimize.py

@@ -698 +698 @@
 
         sage: from sage.numerical.optimize import binpacking
         sage: values = [1/5, 1/3, 2/3, 3/4, 5/7]
-        sage: bins = binpacking(values) # optional - GLPK, CBC 
-        sage: len(bins) # optional - GLPK, CBC
+        sage: bins = binpacking(values)
+        sage: len(bins)
         3
 
     Checking the bins are of correct size ::
 
-        sage: all([ sum(b)<= 1 for b in bins ]) # optional - GLPK, CBC
+        sage: all([ sum(b)<= 1 for b in bins ])
         True
 
     Checking every item is in a bin ::
 
-        sage: b1, b2, b3 = bins # optional - GLPK, CBC
-        sage: all([ (v in b1 or v in b2 or v in b3) for v in values ]) # optional - GLPK, CBC
+        sage: b1, b2, b3 = bins
+        sage: all([ (v in b1 or v in b2 or v in b3) for v in values ])
         True
 
     One way to use only three boxes (which is best possible) is to put
@@ -720 +720 @@
     Of course, we can also check that there is no solution using only two boxes ::
 
         sage: from sage.numerical.optimize import binpacking
-        sage: binpacking([0.2,0.3,0.8,0.9], k=2)              # optional - GLPK, CBC
+        sage: binpacking([0.2,0.3,0.8,0.9], k=2)
         Traceback (most recent call last):
         ...
         ValueError: This problem has no solution !