def run(args):
assert len(args) in [0,2], "n_sites, n_trials"
if (len(args) == 0):
n_sites, n_trials = 3, 2
out = null_out()
else:
n_sites, n_trials = [int(arg) for arg in args]
out = sys.stdout
#
show_times_at_exit()
class type_info(object):
def __init__(O, type, use_analytical_gradients):
O.type = type
O.use_analytical_gradients = use_analytical_gradients
def __str__(O):
return "%s(use_analytical_gradients=%s)" % (
O.type.__name__, str(O.use_analytical_gradients))
spherical_types = [
type_info(euler_params, False),
type_info(euler_params, True),
type_info(euler_angles_xyz, False),
type_info(euler_angles_xyz, True),
type_info(euler_angles_zxz, False),
type_info(euler_angles_zxz, True),
type_info(euler_angles_yxyz, False),
type_info(euler_angles_xyzy, False),
type_info(inf_euler_params, False),
type_info(inf_axis_angle, False)]
nfun_accu = {}
n_failed = {}
for ti in spherical_types:
nfun_accu[str(ti)] = flex.size_t()
n_failed[str(ti)] = 0
mersenne_twister = flex.mersenne_twister(seed=0)
for i_trial in xrange(n_trials):
sites = [matrix.col(s) for s in flex.vec3_double(
mersenne_twister.random_double(size=n_sites*3)*2-1)]
c = center_of_mass_from_sites(sites)
r = matrix.sqr(mersenne_twister.random_double_r3_rotation_matrix())
wells = [r*(s-c)+c for s in sites]
for ti in spherical_types:
r = refinery(spherical_type_info=ti, sites=sites, wells=wells, out=out)
nfun_accu[str(ti)].append(r.nfun)
if (r.failed):
n_failed[str(ti)] += 1
nfun_sums = []
annotations = []
for ti in spherical_types:
print >> out, ti
nfuns = nfun_accu[str(ti)]
stats = nfuns.as_double().min_max_mean()
stats.show(out=out, prefix=" ")
nfun_sums.append((str(ti), flex.sum(nfuns)))
if (n_failed[str(ti)] == 0):
annotations.append(None)
else:
annotations.append("failed: %d" % n_failed[str(ti)])
print >> out
show_sorted_by_counts(
label_count_pairs=nfun_sums,
reverse=False,
out=out,
annotations=annotations)
print >> out
print "OK"
def __init__(O, sites): O.pivot = center_of_mass_from_sites(sites=sites) O.normal = None O.T0b = matrix.rt(((1,0,0,0,1,0,0,0,1), -O.pivot)) O.Tb0 = matrix.rt(((1,0,0,0,1,0,0,0,1), O.pivot))
def run(args):
assert len(args) in [0, 2], "n_sites, n_trials"
if (len(args) == 0):
n_sites, n_trials = 3, 2
out = null_out()
else:
n_sites, n_trials = [int(arg) for arg in args]
out = sys.stdout
#
show_times_at_exit()
class type_info(object):
def __init__(O, type, use_analytical_gradients):
O.type = type
O.use_analytical_gradients = use_analytical_gradients
def __str__(O):
return "%s(use_analytical_gradients=%s)" % (
O.type.__name__, str(O.use_analytical_gradients))
spherical_types = [
type_info(euler_params, False),
type_info(euler_params, True),
type_info(euler_angles_xyz, False),
type_info(euler_angles_xyz, True),
type_info(euler_angles_zxz, False),
type_info(euler_angles_zxz, True),
type_info(euler_angles_yxyz, False),
type_info(euler_angles_xyzy, False),
type_info(inf_euler_params, False),
type_info(inf_axis_angle, False)
]
nfun_accu = {}
n_failed = {}
for ti in spherical_types:
nfun_accu[str(ti)] = flex.size_t()
n_failed[str(ti)] = 0
mersenne_twister = flex.mersenne_twister(seed=0)
for i_trial in xrange(n_trials):
sites = [
matrix.col(s) for s in flex.vec3_double(
mersenne_twister.random_double(size=n_sites * 3) * 2 - 1)
]
c = center_of_mass_from_sites(sites)
r = matrix.sqr(mersenne_twister.random_double_r3_rotation_matrix())
wells = [r * (s - c) + c for s in sites]
for ti in spherical_types:
r = refinery(spherical_type_info=ti,
sites=sites,
wells=wells,
out=out)
nfun_accu[str(ti)].append(r.nfun)
if (r.failed):
n_failed[str(ti)] += 1
nfun_sums = []
annotations = []
for ti in spherical_types:
print >> out, ti
nfuns = nfun_accu[str(ti)]
stats = nfuns.as_double().min_max_mean()
stats.show(out=out, prefix=" ")
nfun_sums.append((str(ti), flex.sum(nfuns)))
if (n_failed[str(ti)] == 0):
annotations.append(None)
else:
annotations.append("failed: %d" % n_failed[str(ti)])
print >> out
show_sorted_by_counts(label_count_pairs=nfun_sums,
reverse=False,
out=out,
annotations=annotations)
print >> out
print "OK"
def __init__(O, sites):
O.pivot = center_of_mass_from_sites(sites=sites)
O.normal = None
O.T0b = matrix.rt(((1, 0, 0, 0, 1, 0, 0, 0, 1), -O.pivot))
O.Tb0 = matrix.rt(((1, 0, 0, 0, 1, 0, 0, 0, 1), O.pivot))
