def compute(miller_array, step_scale=0.0005):
miller_array.show_comprehensive_summary(prefix=" ")
step = miller_array.d_min() * step_scale
#
ma_p1 = miller_array.expand_to_p1()
#
n_h = {}
n_k = {}
n_l = {}
indices = ma_p1.indices()
for ind in indices:
h, k, l = ind
n_h.setdefault(h, flex.int()).append(1)
n_k.setdefault(k, flex.int()).append(1)
n_l.setdefault(l, flex.int()).append(1)
def count(d):
for k in d.keys():
d[k] = d[k].size()
return d
n_h = count(n_h)
n_k = count(n_k)
n_l = count(n_l)
# resolutions along axes
a, b, c = miller_array.unit_cell().parameters()[:3]
x, rho_x = one_d_image_along_axis(n=n_h, step=step, uc_length=a)
y, rho_y = one_d_image_along_axis(n=n_k, step=step, uc_length=b)
z, rho_z = one_d_image_along_axis(n=n_l, step=step, uc_length=c)
# 2nd derivatives
r2x = second_derivatives(rho=rho_x, delta=step)
r2y = second_derivatives(rho=rho_y, delta=step)
r2z = second_derivatives(rho=rho_z, delta=step)
# effective resolution along axes
d_eff_a = compute_d_eff(r=x, rho_2nd=r2x)
d_eff_b = compute_d_eff(r=y, rho_2nd=r2y)
d_eff_c = compute_d_eff(r=z, rho_2nd=r2z)
print(" Effective resolution along axes a,b,c: %6.3f %6.3f %6.3f" %
(d_eff_a, d_eff_b, d_eff_c))
# all directions
l = 0.8 * min(d_eff_a / 2.5, d_eff_b / 2.5, d_eff_c / 2.5)
r = 1.2 * max(d_eff_a / 2.5, d_eff_b / 2.5, d_eff_c / 2.5)
us = regular_grid_on_unit_sphere.rosca(m=9, hemisphere=True)
d_effs = flex.double()
o = maptbx.ft_analytical_1d_point_scatterer_at_origin(N=100000)
for i, u in enumerate(us):
o.compute(miller_indices=indices,
step=step,
left=l,
right=r,
u_frac=miller_array.unit_cell().fractionalize(u))
dist, rho_ = o.distances(), o.rho()
rho2 = second_derivatives(rho=rho_, delta=step)
d_eff = compute_d_eff(r=dist, rho_2nd=rho2)
d_effs.append(d_eff)
print(" Effective resolution (min,max): %8.3f%8.3f" %
(flex.min(d_effs), flex.max(d_effs)))
def compute(miller_array, step_scale=0.0005):
miller_array.show_comprehensive_summary(prefix=" ")
step = miller_array.d_min()*step_scale
#
ma_p1 = miller_array.expand_to_p1()
#
n_h = {}
n_k = {}
n_l = {}
indices = ma_p1.indices()
for ind in indices:
h,k,l = ind
n_h.setdefault(h, flex.int()).append(1)
n_k.setdefault(k, flex.int()).append(1)
n_l.setdefault(l, flex.int()).append(1)
def count(d):
for k in d.keys():
d[k] = d[k].size()
return d
n_h = count(n_h)
n_k = count(n_k)
n_l = count(n_l)
# resolutions along axes
a,b,c = miller_array.unit_cell().parameters()[:3]
x, rho_x = one_d_image_along_axis(n=n_h, step=step, uc_length=a)
y, rho_y = one_d_image_along_axis(n=n_k, step=step, uc_length=b)
z, rho_z = one_d_image_along_axis(n=n_l, step=step, uc_length=c)
# 2nd derivatives
r2x = second_derivatives(rho=rho_x, delta=step)
r2y = second_derivatives(rho=rho_y, delta=step)
r2z = second_derivatives(rho=rho_z, delta=step)
# effective resolution along axes
d_eff_a = compute_d_eff(r=x, rho_2nd=r2x)
d_eff_b = compute_d_eff(r=y, rho_2nd=r2y)
d_eff_c = compute_d_eff(r=z, rho_2nd=r2z)
print " Effective resolution along axes a,b,c: %6.3f %6.3f %6.3f"%(
d_eff_a, d_eff_b, d_eff_c)
# all directions
l = 0.8 * min(d_eff_a/2.5, d_eff_b/2.5, d_eff_c/2.5)
r = 1.2 * max(d_eff_a/2.5, d_eff_b/2.5, d_eff_c/2.5)
us = regular_grid_on_unit_sphere.rosca(m=9, hemisphere=True)
d_effs = flex.double()
o = maptbx.ft_analytical_1d_point_scatterer_at_origin(N=100000)
for i, u in enumerate(us):
o.compute(
miller_indices=indices,
step=step,
left=l,
right=r,
u_frac=miller_array.unit_cell().fractionalize(u))
dist, rho_ = o.distances(), o.rho()
rho2 = second_derivatives(rho=rho_, delta=step)
d_eff = compute_d_eff(r=dist, rho_2nd=rho2)
d_effs.append(d_eff)
print " Effective resolution (min,max): %8.3f%8.3f"%(
flex.min(d_effs), flex.max(d_effs))
def run(): r = regular_grid_on_unit_sphere.rosca(m=9, hemisphere=False) assert r.size() == 649 r = regular_grid_on_unit_sphere.rosca(m=9, hemisphere=True) assert r.size() == 361
def run(): r = regular_grid_on_unit_sphere.rosca(m=9, hemisphere=False) assert r.size() == 649 r = regular_grid_on_unit_sphere.rosca(m=9, hemisphere=True) assert r.size() == 361
