本文整理汇总了Python中pylpsolve.LP.solve方法的典型用法代码示例。如果您正苦于以下问题:Python LP.solve方法的具体用法?Python LP.solve怎么用?Python LP.solve使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pylpsolve.LP
的用法示例。
在下文中一共展示了LP.solve方法的6个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: checkLBUBMix
# 需要导入模块: from pylpsolve import LP [as 别名]
# 或者: from pylpsolve.LP import solve [as 别名]
def checkLBUBMix(self, opts, lb, ub):
# these are indices to bound
lbindices = (0,3)
ubindices = {}
ubindices["t"] = (3,6)
ubindices["n"] = "a"
ubindices["N"] = "a"
ubindices["l"] = [3,4,5]
ubindices["a"] = ar([3,4,5],dtype=uint)
ubindices["f"] = ar([3,4,5],dtype=float64)
ubvalues = {}
ubvalues["s"] = ub
ubvalues["l"] = [ub, ub, ub]
ubvalues["a"] = ar([ub, ub, ub])
lbvalues = {}
lbvalues["s"] = lb
lbvalues["l"] = [lb, lb, lb]
lbvalues["a"] = ar([lb, lb, lb])
lp = LP()
lp.setLowerBound(lbindices, lbvalues[opts[1]])
if opts[0] == "N":
lp.getIndexBlock(ubindices["N"], 3)
lp.setUpperBound(ubindices[opts[0]], ubvalues[opts[1]])
lp.setObjective([1,1,1,-1,-1,-1])
for num_times in range(2): # make sure it's same anser second time
lp.solve()
self.assertAlmostEqual(lp.getObjectiveValue(), lb*3 - ub*3)
v = lp.getSolution()
self.assert_(len(v) == 6)
self.assertAlmostEqual(v[0], lb)
self.assertAlmostEqual(v[1], lb)
self.assertAlmostEqual(v[2], lb)
self.assertAlmostEqual(v[3], ub)
self.assertAlmostEqual(v[4], ub)
self.assertAlmostEqual(v[5], ub)
示例2: testBasicBasis
# 需要导入模块: from pylpsolve import LP [as 别名]
# 或者: from pylpsolve.LP import solve [as 别名]
def testBasicBasis(self):
# this should work as it's in the examples
lp = LP()
lp.addConstraint( (0, 1), "<", 3)
lp.addConstraint( (1, 1), "<", 3)
lp.setMaximize()
lp.setObjective([1,1])
lp.solve(guess = [3,3])
self.assert_(lp.getInfo("Iterations") == 0, lp.getInfo("Iterations"))
示例3: checkUB
# 需要导入模块: from pylpsolve import LP [as 别名]
# 或者: from pylpsolve.LP import solve [as 别名]
def checkUB(self, opts, ub):
# these are indices to bound
indices = {}
indices["t"] = (0,3)
indices["N"] = "a"
indices["l"] = [0,1,2]
indices["a"] = ar([0,1,2],dtype=uint)
indices["f"] = ar([0,1,2],dtype=float64)
ubvalues = {}
ubvalues["s"] = ub
ubvalues["l"] = [ub, ub, ub]
ubvalues["a"] = ar([ub, ub, ub])
lp = LP()
if opts[0] == "N":
lp.getIndexBlock(indices["N"], 3)
lp.setObjective([1,1,1,1,1,1])
lp.addConstraint( ((3,6), [[1,0,0],[0,1,0],[0,0,1]]), "<=", 10)
lp.setMaximize()
lp.setLowerBound(indices[opts[0]], None)
lp.setUpperBound(indices[opts[0]], ubvalues[opts[1]])
for num_times in range(2): # make sure it's same anser second time
lp.solve()
self.assertAlmostEqual(lp.getObjectiveValue(), ub*3 + 10 * 3)
v = lp.getSolution()
self.assert_(len(v) == 6)
self.assertAlmostEqual(v[0], ub)
self.assertAlmostEqual(v[1], ub)
self.assertAlmostEqual(v[2], ub)
self.assertAlmostEqual(v[3], 10)
self.assertAlmostEqual(v[4], 10)
self.assertAlmostEqual(v[5], 10)
示例4: checkLB
# 需要导入模块: from pylpsolve import LP [as 别名]
# 或者: from pylpsolve.LP import solve [as 别名]
def checkLB(self, opts, lb):
# these are indices to bound
indices = {}
indices["t"] = (0,3)
indices["N"] = "a"
indices["l"] = [0,1,2]
indices["a"] = ar([0,1,2],dtype=uint)
indices["f"] = ar([0,1,2],dtype=float64)
lbvalues = {}
lbvalues["s"] = lb
lbvalues["l"] = [lb, lb, lb]
lbvalues["a"] = ar([lb, lb, lb])
lp = LP()
if opts[0] == "N":
lp.getIndexBlock(indices["N"], 3)
lp.setObjective([1,1,1,1,1,1])
lp.setLowerBound(indices[opts[0]], lbvalues[opts[1]])
for num_times in range(2): # make sure it's same anser second time
lp.solve()
self.assertAlmostEqual(lp.getObjectiveValue(), lb*3)
v = lp.getSolution()
self.assert_(len(v) == 6)
self.assertAlmostEqual(v[0], lb)
self.assertAlmostEqual(v[1], lb)
self.assertAlmostEqual(v[2], lb)
self.assertAlmostEqual(v[3], 0)
self.assertAlmostEqual(v[4], 0)
self.assertAlmostEqual(v[5], 0)
示例5: checkBindSandwich
# 需要导入模块: from pylpsolve import LP [as 别名]
# 或者: from pylpsolve.LP import solve [as 别名]
def checkBindSandwich(self, opts):
idxlist = [{}, {}]
idxlist[0]["t"] = (0,3)
idxlist[0]["N"] = "a"
idxlist[0]["l"] = [0,1,2]
idxlist[0]["a"] = ar([0,1,2])
idxlist[0]["r"] = ar([0,0,1,1,2,2])[::2]
idxlist[0]["f"] = ar([0,1,2],dtype=float64)
idxlist[1]["t"] = (3,6)
idxlist[1]["n"] = "b"
idxlist[1]["l"] = [3,4,5]
idxlist[1]["a"] = ar([3,4,5])
idxlist[1]["r"] = ar([3,3,4,4,5,5])[::2]
idxlist[1]["f"] = ar([3,4,5],dtype=float64)
lp = LP()
if opts[0] == "N":
self.assert_(lp.getIndexBlock(idxlist[0]["N"], 3) == (0,3) )
# Now bind the second group
lp.bindSandwich(idxlist[0][opts[0]], idxlist[1][opts[1]])
if opts[2] == "u":
lp.addConstraint( (idxlist[0][opts[0]], 1), ">=", 1)
elif opts[2] == "l":
lp.addConstraint( (idxlist[0][opts[0]], 1), "<=", -1)
lp.setUnbounded(idxlist[0][opts[0]])
else:
assert False
lp.setObjective( (idxlist[1][opts[1]], [1,2,3]) )
lp.setMinimize()
lp.solve()
v = lp.getSolution()
v0 = 1 if opts[2] == "u" else -1
self.assert_(len(v) == 6, "len(v) = %d != 6" % len(v))
self.assertAlmostEqual(v[0], v0)
self.assertAlmostEqual(v[1], 0)
self.assertAlmostEqual(v[2], 0)
self.assertAlmostEqual(v[3], 1)
self.assertAlmostEqual(v[4], 0)
self.assertAlmostEqual(v[5], 0)
if opts[0] in "nN" and opts[1] in "nN":
d = lp.getSolutionDict()
self.assert_(set(d.iterkeys()) == set(["a", "b"]))
self.assertAlmostEqual(d["a"][0], v0)
self.assertAlmostEqual(d["a"][1], 0)
self.assertAlmostEqual(d["a"][2], 0)
self.assertAlmostEqual(d["b"][0], 1)
self.assertAlmostEqual(d["b"][1], 0)
self.assertAlmostEqual(d["b"][2], 0)
示例6: checkBindEach
# 需要导入模块: from pylpsolve import LP [as 别名]
# 或者: from pylpsolve.LP import solve [as 别名]
def checkBindEach(self, opts):
idxlist = [{}, {}]
idxlist[0]["t"] = (0,3)
idxlist[0]["N"] = "a"
idxlist[0]["l"] = [0,1,2]
idxlist[0]["a"] = ar([0,1,2])
idxlist[0]["r"] = ar([0,0,1,1,2,2])[::2]
idxlist[0]["f"] = ar([0,1,2],dtype=float64)
idxlist[1]["t"] = (3,6)
idxlist[1]["n"] = "b"
idxlist[1]["l"] = [3,4,5]
idxlist[1]["a"] = ar([3,4,5])
idxlist[1]["r"] = ar([3,3,4,4,5,5])[::2]
idxlist[1]["f"] = ar([3,4,5],dtype=float64)
lp = LP()
if opts[0] == "N":
self.assert_(lp.getIndexBlock(idxlist[0]["N"], 3) == (0,3) )
# Now bind the second group
if opts[2] == "g":
self.assert_(
lp.bindEach(idxlist[1][opts[1]], ">", idxlist[0][opts[0]])
== [0,1,2])
elif opts[2] == "l":
self.assert_(
lp.bindEach(idxlist[0][opts[0]], "<", idxlist[1][opts[1]])
== [0,1,2])
elif opts[2] == "e":
self.assert_(
lp.bindEach(idxlist[0][opts[0]], "=", idxlist[1][opts[1]])
== [0,1,2])
elif opts[2] == "E":
self.assert_(
lp.bindEach(idxlist[1][opts[1]], "=", idxlist[0][opts[0]])
== [0,1,2])
else:
assert False
# Forces some to be defined implicitly above to catch that case
lp.addConstraint( (idxlist[0][opts[0]], 1), ">=", 1)
lp.setObjective( (idxlist[1][opts[1]], [1,2,3]) )
lp.setMinimize()
lp.solve()
v = lp.getSolution()
self.assert_(len(v) == 6, "len(v) = %d != 6" % len(v))
self.assertAlmostEqual(v[0], 1)
self.assertAlmostEqual(v[1], 0)
self.assertAlmostEqual(v[2], 0)
self.assertAlmostEqual(v[3], 1)
self.assertAlmostEqual(v[4], 0)
self.assertAlmostEqual(v[5], 0)
if opts[0] in "nN" and opts[1] in "nN":
d = lp.getSolutionDict()
self.assert_(set(d.iterkeys()) == set(["a", "b"]))
self.assertAlmostEqual(d["a"][0], 1)
self.assertAlmostEqual(d["a"][1], 0)
self.assertAlmostEqual(d["a"][2], 0)
self.assertAlmostEqual(d["b"][0], 1)
self.assertAlmostEqual(d["b"][1], 0)
self.assertAlmostEqual(d["b"][2], 0)