def __call__(self, x, f, g, diag=None, diagco=False):
for i,v in enumerate(x): self.x[i] = v
for i,v in enumerate(g): self.g[i] = v
if (diag is not None):
for i,v in enumerate(diag): self.diag[i] = v
from fortran_lbfgs import lbfgs as fortran_lbfgs
fortran_lbfgs(
self.n, self.m,
self.x, f, self.g, diagco, self.diag,
self.iprint, self.eps, self.xtol, self.w, self.iflag)
for i,v in enumerate(self.x): x[i] = v
for i,v in enumerate(self.g): g[i] = v
if (diag is not None):
for i,v in enumerate(self.diag): diag[i] = v
def run_fortran(target_evaluator, termination_params=None, core_params=None):
"For debugging only!"
from scitbx.python_utils.misc import store
from fortran_lbfgs import lbfgs as fortran_lbfgs
import Numeric
if (termination_params is None):
termination_params = termination_parameters()
if (core_params is None):
core_params = core_parameters()
assert termination_params.traditional_convergence_test
assert core_params.maxfev == 20
x = target_evaluator.x
n = x.size()
m = core_params.m
gtol = core_params.gtol
xtol = core_params.xtol
stpmin = core_params.stpmin
stpmax = core_params.stpmax
eps = termination_params.traditional_convergence_test_eps
x_numeric = Numeric.array(Numeric.arange(n), Numeric.Float64)
g_numeric = Numeric.array(Numeric.arange(n), Numeric.Float64)
size_w = n * (2 * m + 1) + 2 * m
w = Numeric.array(Numeric.arange(size_w), Numeric.Float64)
diag = Numeric.array(Numeric.arange(n), Numeric.Float64)
iprint = [1, 0]
diagco = 0
iflag = Numeric.array([0], Numeric.Int32)
minimizer = store(error=None)
while 1:
f, g = target_evaluator.compute_functional_and_gradients()
for i, xi in enumerate(x):
x_numeric[i] = xi
for i, gi in enumerate(g):
g_numeric[i] = gi
fortran_lbfgs(n, m, x_numeric, f, g_numeric, diagco, diag, iprint, eps,
xtol, w, iflag)
for i, xi in enumerate(x_numeric):
x[i] = xi
if (iflag[0] == 0):
break
if (iflag[0] < 0):
minimizer.error = "fortran lbfgs error"
break
return minimizer
def run_fortran(target_evaluator,
termination_params=None,
core_params=None):
"For debugging only!"
from scitbx.python_utils.misc import store
from fortran_lbfgs import lbfgs as fortran_lbfgs
import Numeric
if (termination_params is None):
termination_params = termination_parameters()
if (core_params is None):
core_params = core_parameters()
assert termination_params.traditional_convergence_test
assert core_params.maxfev == 20
x = target_evaluator.x
n = x.size()
m = core_params.m
gtol = core_params.gtol
xtol = core_params.xtol
stpmin = core_params.stpmin
stpmax = core_params.stpmax
eps = termination_params.traditional_convergence_test_eps
x_numeric = Numeric.array(Numeric.arange(n), Numeric.Float64)
g_numeric = Numeric.array(Numeric.arange(n), Numeric.Float64)
size_w = n*(2*m+1)+2*m
w = Numeric.array(Numeric.arange(size_w), Numeric.Float64)
diag = Numeric.array(Numeric.arange(n), Numeric.Float64)
iprint = [1, 0]
diagco = 0
iflag = Numeric.array([0], Numeric.Int32)
minimizer = store(error=None)
while 1:
f, g = target_evaluator.compute_functional_and_gradients()
for i,xi in enumerate(x): x_numeric[i] = xi
for i,gi in enumerate(g): g_numeric[i] = gi
fortran_lbfgs(n, m, x_numeric, f, g_numeric, diagco, diag,
iprint, eps, xtol, w, iflag)
for i,xi in enumerate(x_numeric): x[i] = xi
if (iflag[0] == 0):
break
if (iflag[0] < 0):
minimizer.error = "fortran lbfgs error"
break
return minimizer