def objective(self, obj):
if isinstance(obj, CyLPExpr):
self.objective_ = obj.evaluate()
obj = None
#for varName in self.allVarNames:
for varName in self.varNames:
v_coef = self.generateVarObjCoef(varName)
obj = sparseConcat(obj, v_coef, how='h')
self.objective_ = obj
def objective(self, obj):
if isinstance(obj, CyLPExpr):
self.objective_ = obj.evaluate()
obj = None
#for varName in self.allVarNames:
for varName in self.varNames:
v_coef = self.generateVarObjCoef(varName)
obj = sparseConcat(obj, v_coef, how='h')
obj = np.squeeze(np.asarray(obj.todense()))
self.objective_ = obj
def removeVariable(self, name):
'''
Remove a variable named ``name`` from the model
'''
if not self.inds.hasVar(name):
raise Exception('Variable "%s" does not exist.' % name)
self.nVars -= self.pvdims[name]
start = self.inds.varIndex[name][0]
end = start + self.pvdims[name]
o = self.objective_
if isinstance(o, np.ndarray):
o = np.concatenate((o[:start], o[end:]), axis=0)
else:
if end == o.shape[1]:
if start == 0:
print('Problem empty.')
else:
o = o[0, :start]
elif start == 0:
o = o[0, end:]
else:
o = sparseConcat(o[0, :start], o[0, end:], how='h')
# I'm not exactly sure why the objective gets changed into
# csr_matrixPlus here when it may not be coming in. Shouldn't it
# just always be?
self.objective_ = csr_matrixPlus(o)
del self.pvdims[name]
self.varNames.remove(name)
self.inds.removeVar(name)
for i in range(len(self.variables)):
var = self.variables[i]
if var.name == name:
del self.variables[i]
break
#Removing the variable from the constraints
cons = self.constraints
for c in cons:
if name in c.varNames:
c.varNames.remove(name)
del c.parentVarDims[name]
for v in list(c.varCoefs.keys()):
if v.name == name:
del c.varCoefs[v]
for c in cons[:]:
self.inds
if not c.varCoefs:
self.removeConstraint(c.name)
def removeVariable(self, name):
'''
Remove a variable named ``name`` from the model
'''
if not self.inds.hasVar(name):
raise Exception('Variable "%s" does not exist.' % name)
self.nVars -= self.pvdims[name]
start = self.inds.varIndex[name][0]
end = start + self.pvdims[name]
o = self.objective_
if isinstance(o, np.ndarray):
o = np.concatenate((o[:start], o[end:]), axis=0)
else:
if end == o.shape[1]:
if start == 0:
print 'Problem empty.'
else:
o = o[0, :start]
elif start == 0:
o = o[0, end:]
else:
o = sparseConcat(o[0, :start], o[0, end:], how='h')
self.objective_ = csr_matrixPlus(o)
del self.pvdims[name]
self.varNames.remove(name)
self.inds.removeVar(name)
for i in range(len(self.variables)):
var = self.variables[i]
if var.name == name:
del self.variables[i]
break
#Removing the variable from the constraints
cons = self.constraints
for c in cons:
if name in c.varNames:
c.varNames.remove(name)
del c.parentVarDims[name]
for v in c.varCoefs.keys():
if v.name == name:
del c.varCoefs[v]
for c in cons[:]:
self.inds
if not c.varCoefs:
self.removeConstraint(c.name)
def generateVarMatrix(self, varName):
'''
Create the coefficient matrix for a variable named
varName. Return a csr_matrixPlus.
'''
#dim = self.allParentVarDims[varName]
dim = self.pvdims[varName]
mainCoef = None
for c in self.constraints:
coef = sparse.coo_matrix((c.nRows, dim))
keys = [k for k in c.varCoefs.keys() if k.name == varName]
for var in keys:
coef = coef + c.varCoefs[var]
mainCoef = sparseConcat(mainCoef, coef, 'v')
return mainCoef
def generateVarMatrix(self, varName):
'''
Create the coefficient matrix for a variable named
varName. Return a csr_matrixPlus.
'''
#dim = self.allParentVarDims[varName]
dim = self.pvdims[varName]
mainCoef = None
for c in self.constraints:
coef = sparse.coo_matrix((c.nRows, dim))
keys = [k for k in c.varCoefs.keys() if k.name == varName]
for var in keys:
coef = coef + c.varCoefs[var]
mainCoef = sparseConcat(mainCoef, coef, 'v')
return mainCoef
def makeMatrices(self):
'''
Makes coef matrix and rhs vector from CyLPConstraints
in self.constraints
'''
#if len(self.constraints) == 0:
# return
self.makeIndexFactory()
#self.getVarBounds()
# Create the aggregated coef matrix
masterCoefMat = None
masterCoefMat = None
if self.nCons > 0:
for varName in self.varNames:# self.pvdims.keys():#self.allVarNames:
vmat = self.generateVarMatrix(varName)
if vmat is None:
vmat = csc_matrixPlus((self.nCons, self.pvdims[varName]))
masterCoefMat = sparseConcat(masterCoefMat, vmat, 'h')
# Create bound vectors
c_lower = np.array([])
c_upper = np.array([])
for c in self.constraints:
if not c.isRange:
c_lower = np.concatenate((c_lower, c.lower), axis=0)
c_upper = np.concatenate((c_upper, c.upper), axis=0)
# Create variables bound vectors
v_lower = np.array([])
v_upper = np.array([])
if self.nVars:
v_lower = -getCoinInfinity() * np.ones(self.nVars)
v_upper = getCoinInfinity() * np.ones(self.nVars)
for v in self.variables:
varinds = self.inds.varIndex[v.name]
v_lower[varinds] = v.lower
v_upper[varinds] = v.upper
#v_lower = np.concatenate((v_lower, v.lower), axis=0)
#v_upper = np.concatenate((v_upper, v.upper), axis=0)
#if masterCoefMat is not None:
return masterCoefMat, c_lower, c_upper, v_lower, v_upper
def makeMatrices(self):
'''
Makes coef matrix and rhs vector from CyLPConstraints
in self.constraints
'''
#if len(self.constraints) == 0:
# return
self.makeIndexFactory()
#self.getVarBounds()
# Create the aggregated coef matrix
masterCoefMat = None
masterCoefMat = None
if self.nCons > 0:
for varName in self.varNames:# self.pvdims.keys():#self.allVarNames:
vmat = self.generateVarMatrix(varName)
if vmat is None:
vmat = csc_matrixPlus((self.nCons, self.pvdims[varName]))
masterCoefMat = sparseConcat(masterCoefMat, vmat, 'h')
# Create bound vectors
c_lower = np.array([])
c_upper = np.array([])
for c in self.constraints:
if not c.isRange:
c_lower = np.concatenate((c_lower, c.lower), axis=0)
c_upper = np.concatenate((c_upper, c.upper), axis=0)
# Create variables bound vectors
v_lower = np.array([])
v_upper = np.array([])
if self.nVars:
v_lower = -getCoinInfinity() * np.ones(self.nVars)
v_upper = getCoinInfinity() * np.ones(self.nVars)
for v in self.variables:
varinds = self.inds.varIndex[v.name]
v_lower[varinds] = v.lower
v_upper[varinds] = v.upper
#v_lower = np.concatenate((v_lower, v.lower), axis=0)
#v_upper = np.concatenate((v_upper, v.upper), axis=0)
#if masterCoefMat is not None:
return masterCoefMat, c_lower, c_upper, v_lower, v_upper
def addVariable(self, name, dim, isInt=False):
'''
Create a new instance of :py:class:`CyLPVar` using the given
arguments and add it to current model's variable list.
'''
if dim == 0:
return
var = CyLPVar(name, dim, isInt)
self.variables.append(var)
#If mulidim, correct dim
if isinstance(dim, tuple):
dim = reduce(mul, dim)
if not self.inds.hasVar(var.name):
self.inds.addVar(var.name, dim)
self.nVars += dim
self.varNames.append(var.name)
self.pvdims[var.name] = dim
if var.dims:
var.mpsNames = [var.name + '_' + '_'.join(x) for x in \
product(*[map(str, range(i)) for i in var.dims])]
else:
var.mpsNames = [
'%s_%s' % (var.name, i) for i in range(var.dim)
]
o = self.objective_
if isinstance(o, np.ndarray):
o = np.concatenate((o, np.zeros(dim)), axis=0)
else:
o = sparseConcat(o, csr_matrixPlus(np.zeros(dim)), 'h')
# I'm not exactly sure why the objective gets changed into
# csr_matrixPlus here when it may not be coming in. Shouldn't it
# just always be?
self.objective_ = csr_matrixPlus(o)
else:
raise Exception('Varaible %s already exists.' % var.name)
return var
def addVariable(self, name, dim, isInt=False):
'''
Create a new instance of :py:class:`CyLPVar` using the given
arguments and add it to current model's variable list.
'''
if dim == 0:
return
var = CyLPVar(name, dim, isInt)
self.variables.append(var)
#If mulidim, correct dim
if isinstance(dim, tuple):
dim = reduce(mul, dim)
if not self.inds.hasVar(var.name):
self.inds.addVar(var.name, dim)
self.nVars += dim
self.varNames.append(var.name)
self.pvdims[var.name] = dim
if var.dims:
var.mpsNames = [var.name + '_' + '_'.join(x) for x in \
product(*[map(str, range(i)) for i in var.dims])]
else:
var.mpsNames = ['%s_%s' % (var.name, i) for i in xrange(var.dim)]
o = self.objective_
if isinstance(o, np.ndarray):
o = np.concatenate((o, np.zeros(dim)), axis=0)
else:
o = sparseConcat(o, csr_matrixPlus(np.zeros(dim)), 'h')
self.objective_ = csr_matrixPlus(o)
else:
raise Exception('Varaible %s already exists.' % var.name)
return var
