def spGradSolve(fun,
x0,
nf=None,
nG=None,
xlb=None,
xub=None,
clb=None,
cub=None,
cfg=None):
"""Directly solve the optimization problem described using fun with guess x0
:param fun: A function like y, spJ = f(x) where x, y are np.ndarray, J is scipy.sparse.csc_matrix
:param nf: int, length of y
:param nG: int, nnz of spJ
:param x0: np.ndarray (nx,) the initial guess to the solver
:param xlb: np.ndarray (nx,) lower bound on decision variable x
:param xub: np.ndarray (nx,) upper bound on decision variable x
:param clb: np.ndarray (nc,) lower bound on return function c
:param cub: np.ndarray (nc,) upper bound on return function c
:param cfg: libsnopt.SnoptConfig, configuration of snopt solver
:returns: a dictionary containing the solution
"""
nx = len(x0)
if nf is None:
if clb is not None and cub is not None:
assert len(clb) == len(cub)
nf = len(clb)
else:
y, spJ = fun(x0)
nf = len(y)
nG = spJ.nnz
if nG is None:
y, spJ = fun(x0)
nG = spJ.nnz
assert nf is not None
assert nG is not None
if xlb is None or xub is None:
xlb = np.empty(0)
xub = np.empty(0)
if clb is None or cub is None:
clb = np.empty(0)
cub = np.empty(0)
if cfg is None:
cfg = libsnopt.SnoptConfig()
rst = libsnopt.spGradSolve(fun, x0, nx, nf, nG, xlb, xub, clb, cub, cfg)
return parseResult(rst)
def inDirectSolve(fun,
x0,
nf=None,
xlb=None,
xub=None,
clb=None,
cub=None,
cfg=None):
"""Directly solve the optimization problem described using fun with guess x0
:param fun: A function like f(x, y) where x, y are np.ndarray
:param x0: np.ndarray (nx,) the initial guess to the solver
:param nf: int, length of y
:param xlb: np.ndarray (nx,) lower bound on decision variable x
:param xub: np.ndarray (nx,) upper bound on decision variable x
:param clb: np.ndarray (nc,) lower bound on return function c
:param cub: np.ndarray (nc,) upper bound on return function c
:param cfg: libsnopt.SnoptConfig, configuration of snopt solver
:returns: a dictionary containing the solution
"""
nx = len(x0)
if nf is None:
if clb is not None and cub is not None:
assert len(clb) == len(cub)
nf = len(clb)
assert nf is not None
if xlb is None or xub is None:
xlb = np.empty(0)
xub = np.empty(0)
if clb is None or cub is None:
clb = np.empty(0)
cub = np.empty(0)
if cfg is None:
cfg = libsnopt.SnoptConfig()
rst = libsnopt.inDirectSolve(fun, x0, nx, nf, xlb, xub, clb, cub, cfg)
return parseResult(rst)