def kirian_delta_vs_ewald_proximity(unit_cell, miller_indices,
crystal_rotation_matrix, ewald_radius,
d_min, detector_distance, detector_size,
detector_pixels):
from scitbx import matrix
from libtbx.math_utils import nearest_integer
cr = matrix.sqr(crystal_rotation_matrix)
a_matrix = cr * matrix.sqr(
unit_cell.fractionalization_matrix()).transpose()
a_inv = a_matrix.inverse()
dsx, dsy = detector_size
dpx, dpy = detector_pixels
deltas = [[] for _ in xrange(len(miller_indices))]
h_lookup = {}
for i, h in enumerate(miller_indices):
h_lookup[h] = i
for pi in xrange(dpx):
for pj in xrange(dpy):
cx = ((pi + 0.5) / dpx - 0.5) * dsx
cy = ((pj + 0.5) / dpy - 0.5) * dsy
lo = matrix.col((cx, cy, -detector_distance))
ko = lo.normalize() * ewald_radius
ki = matrix.col((0, 0, -ewald_radius))
dk = ki - ko
h_frac = a_inv * dk
h = matrix.col([nearest_integer(_) for _ in h_frac])
if (h.elems == (0, 0, 0)):
continue
g_hkl = a_matrix * h
delta = (dk - g_hkl).length()
i = h_lookup.get(h.elems)
if (i is None):
assert unit_cell.d(h) < d_min
else:
deltas[i].append(delta)
def ewald_proximity(h): # compare with code in image_simple.hpp
rv = matrix.col(unit_cell.reciprocal_space_vector(h))
rvr = cr * rv
rvre = matrix.col((rvr[0], rvr[1], rvr[2] + ewald_radius))
rvre_len = rvre.length()
return abs(1 - rvre_len / ewald_radius)
def write_xy():
fn_xy = "kirian_delta_vs_ewald_proximity.xy"
print "Writing file:", fn_xy
f = open(fn_xy, "w")
print >> f, """\
@with g0
@ s0 symbol 1
@ s0 symbol size 0.1
@ s0 line type 0"""
for h, ds in zip(miller_indices, deltas):
if (len(ds) != 0):
print >> f, min(ds), ewald_proximity(h)
print >> f, "&"
print
write_xy()
STOP()
def exercise_integer():
from libtbx.math_utils import iround, iceil, ifloor, nearest_integer
assert iround(0) == 0
assert iround(1.4) == 1
assert iround(-1.4) == -1
assert iround(1.6) == 2
assert iround(-1.6) == -2
assert iceil(0) == 0
assert iceil(1.1) == 2
assert iceil(-1.1) == -1
assert iceil(1.9) == 2
assert iceil(-1.9) == -1
assert ifloor(0) == 0
assert ifloor(1.1) == 1
assert ifloor(-1.1) == -2
assert ifloor(1.9) == 1
assert ifloor(-1.9) == -2
for i in xrange(-3, 3 + 1):
assert nearest_integer(i + 0.3) == i
assert nearest_integer(i + 0.7) == i + 1
def exercise_integer():
from libtbx.math_utils import iround, iceil, ifloor, nearest_integer
assert iround(0) == 0
assert iround(1.4) == 1
assert iround(-1.4) == -1
assert iround(1.6) == 2
assert iround(-1.6) == -2
assert iceil(0) == 0
assert iceil(1.1) == 2
assert iceil(-1.1) == -1
assert iceil(1.9) == 2
assert iceil(-1.9) == -1
assert ifloor(0) == 0
assert ifloor(1.1) == 1
assert ifloor(-1.1) == -2
assert ifloor(1.9) == 1
assert ifloor(-1.9) == -2
for i in xrange(-3,3+1):
assert nearest_integer(i+0.3) == i
assert nearest_integer(i+0.7) == i+1
def kirian_delta_vs_ewald_proximity(
unit_cell,
miller_indices,
crystal_rotation_matrix,
ewald_radius,
d_min,
detector_distance,
detector_size,
detector_pixels):
from scitbx import matrix
from libtbx.math_utils import nearest_integer
cr = matrix.sqr(crystal_rotation_matrix)
a_matrix = cr * matrix.sqr(unit_cell.fractionalization_matrix()).transpose()
a_inv = a_matrix.inverse()
dsx, dsy = detector_size
dpx, dpy = detector_pixels
deltas = [[] for _ in xrange(len(miller_indices))]
h_lookup = {}
for i,h in enumerate(miller_indices):
h_lookup[h] = i
for pi in xrange(dpx):
for pj in xrange(dpy):
cx = ((pi + 0.5) / dpx - 0.5) * dsx
cy = ((pj + 0.5) / dpy - 0.5) * dsy
lo = matrix.col((cx, cy, -detector_distance))
ko = lo.normalize() * ewald_radius
ki = matrix.col((0,0,-ewald_radius))
dk = ki - ko
h_frac = a_inv * dk
h = matrix.col([nearest_integer(_) for _ in h_frac])
if (h.elems == (0,0,0)):
continue
g_hkl = a_matrix * h
delta = (dk - g_hkl).length()
i = h_lookup.get(h.elems)
if (i is None):
assert unit_cell.d(h) < d_min
else:
deltas[i].append(delta)
def ewald_proximity(h): # compare with code in image_simple.hpp
rv = matrix.col(unit_cell.reciprocal_space_vector(h))
rvr = cr * rv
rvre = matrix.col((rvr[0], rvr[1], rvr[2]+ewald_radius))
rvre_len = rvre.length()
return abs(1 - rvre_len / ewald_radius)
def write_xy():
fn_xy = "kirian_delta_vs_ewald_proximity.xy"
print "Writing file:", fn_xy
f = open(fn_xy, "w")
print >> f, """\
@with g0
@ s0 symbol 1
@ s0 symbol size 0.1
@ s0 line type 0"""
for h, ds in zip(miller_indices, deltas):
if (len(ds) != 0):
print >> f, min(ds), ewald_proximity(h)
print >> f, "&"
print
write_xy()
STOP()
