def lbfgs_emulation(O, memory_range=5):
assert len(O.xfgc_infos) == 1
for O.i_step in xrange(O.params.iteration_limit):
if (O.i_step == 0):
dests = -O.grads
stp = 1 / O.grads.norm()
else:
active_infos = O.get_active_infos()
assert len(active_infos) > 1
if (memory_range is not None):
active_infos = active_infos[-(memory_range+1):]
memory = O.build_bfgs_memory(active_infos=active_infos)
assert memory is not None
k_1 = active_infos[-1]
k_2 = active_infos[-2]
gamma = bfgs.h0_scaling(
sk=k_1.x-k_2.x,
yk=k_1.grads-k_2.grads)
hk0 = flex.double(O.x.size(), gamma)
dests = -bfgs.hg_two_loop_recursion(
memory=memory, hk0=hk0, gk=O.grads)
stp = 1
stp = O.line_search(dests, stp=stp)
assert stp is not None
O.update_fgc(is_iterate=True)
print "%4d: %s" % (O.i_step+1, O.format_rms_info())
sys.stdout.flush()
if (O.grads_mean_sq < O.params.grads_mean_sq_threshold):
O.termination_remark = ""
break
else:
O.termination_remark = " (iteration limit reached)"
def check(bk, hk): hl = bfgs.h_update(hk, xl-xk, gl-gk) bl = bfgs.b_update(bk, xl-xk, gl-gk) assert approx_equal(matrix.sqr(hl).inverse(), bl) es = eigensystem.real_symmetric(bl) assert es.values().all_gt(0) assert bfgs.h0_scaling(sk=xl-xk, yk=gl-gk) > 0
def lbfgs_emulation(O, memory_range=5):
assert len(O.xfgc_infos) == 1
for O.i_step in xrange(O.params.iteration_limit):
if (O.i_step == 0):
dests = -O.grads
stp = 1 / O.grads.norm()
else:
active_infos = O.get_active_infos()
assert len(active_infos) > 1
if (memory_range is not None):
active_infos = active_infos[-(memory_range+1):]
memory = O.build_bfgs_memory(active_infos=active_infos)
assert memory is not None
k_1 = active_infos[-1]
k_2 = active_infos[-2]
gamma = bfgs.h0_scaling(
sk=k_1.x-k_2.x,
yk=k_1.grads-k_2.grads)
hk0 = flex.double(O.x.size(), gamma)
dests = -bfgs.hg_two_loop_recursion(
memory=memory, hk0=hk0, gk=O.grads)
stp = 1
stp = O.line_search(dests, stp=stp)
assert stp is not None
O.update_fgc(is_iterate=True)
print "%4d: %s" % (O.i_step+1, O.format_rms_info())
sys.stdout.flush()
if (O.grads_mean_sq < O.params.grads_mean_sq_threshold):
O.termination_remark = ""
break
else:
O.termination_remark = " (iteration limit reached)"
