def getMin(*args):
"""Solves an unconstrained optimization problem
Basic solve: getMin(X,msg,fns,state)
Solve with a state manipulator: getMin(X,msg,fns,state,smanip)
"""
# Check the number of arguments
if len(args) != 4 and len(args) != 5:
raise Exception(
"The getMin function requires either 4 or 5 arguments, "
"but %d given." % len(args))
# Extract the arguments
X = args[0]
msg = args[1]
fns = args[2]
state = args[3]
smanip = Optizelle.StateManipulator() if len(args) == 4 else args[4]
# Check the arguments
Optizelle.checkVectorSpace("X", X)
Optizelle.checkMessaging("msg", msg)
Optizelle.Unconstrained.Functions.checkT("fns", fns)
Optizelle.Unconstrained.State.checkT("state", state)
Optizelle.checkStateManipulator("smanip", smanip)
# Call the optimization
Optizelle.Utility.UnconstrainedAlgorithmsGetMin(X, msg, fns, state, smanip)
#---ReadJson0---
Optizelle.json.EqualityConstrained.read(XX, YY, msg, fname, state)
#---ReadJson1---
# Create a bundle of functions
#---Functions0---
fns = Optizelle.EqualityConstrained.Functions.t()
#---Functions1---
# Do a null optimization
#---Solver0---
Optizelle.EqualityConstrained.Algorithms.getMin(XX, YY, msg, fns, state)
#---Solver1---
# Do a null optimization with a state manipulator
smanip = Optizelle.StateManipulator()
#---SmanipSolver0---
Optizelle.EqualityConstrained.Algorithms.getMin(XX, YY, msg, fns, state,
smanip)
#---SmanipSolver1---
# Read and write the state to file
fname = "restart.json"
#---WriteReadRestart0---
Optizelle.json.EqualityConstrained.write_restart(XX, YY, msg, fname, state)
Optizelle.json.EqualityConstrained.read_restart(XX, YY, msg, fname, x, y,
state)
#---WriteReadRestart1---
# Do a release
#---Release0---
