def get_predicted_spot_positions_and_status(
self,
old_status=None
): #similar to above function; above can be refactored
panel = self.detector[0]
from scitbx import matrix
Astar = matrix.sqr(self.getOrientation().reciprocal_matrix())
# must have set the basis in order to generate Astar matrix. How to assert this has been done???
import math, copy
xyz = self.getXyzData()
if old_status is None:
spot_status = [SpotClass.GOOD] * len(xyz)
else:
assert len(old_status) == len(xyz)
spot_status = copy.copy(
old_status) # valid way of copying enums w/o reference
self.assigned_hkl = [(0, 0, 0)] * len(xyz)
# step 1. Deduce fractional HKL values from the XyzData. start with x = A* h
# solve for h: h = (A*^-1) x
Astarinv = Astar.inverse()
Hint = flex.vec3_double()
results = flex.vec3_double()
for x in xyz:
H = Astarinv * x
Hint.append((round(H[0], 0), round(H[1], 0), round(H[2], 0)))
xyz_miller = flex.vec3_double()
from rstbx.diffraction import rotation_angles
ra = rotation_angles(limiting_resolution=1.0,
orientation=Astar,
wavelength=1. / self.inv_wave,
axial_direction=self.axis)
for ij, hkl in enumerate(Hint):
xyz_miller.append(
Astar *
hkl) # figure out how to do this efficiently on vector data
if ra(hkl):
omegas = ra.get_intersection_angles()
rotational_diffs = [
abs((-omegas[omegaidx] * 180. / math.pi) -
self.raw_spot_input[ij][2]) for omegaidx in [0, 1]
]
min_diff = min(rotational_diffs)
min_index = rotational_diffs.index(min_diff)
omega = omegas[min_index]
rot_mat = self.axis.axis_and_angle_as_r3_rotation_matrix(omega)
Svec = (rot_mat * Astar) * hkl + self.S0_vector
if self.panelID is not None:
panel = self.detector[self.panelID[ij]]
xy = panel.get_ray_intersection(Svec)
results.append((xy[0], xy[1], 0.0))
self.assigned_hkl[ij] = hkl
else:
results.append((0.0, 0.0, 0.0))
spot_status[ij] = SpotClass.NONE
return results, spot_status
def model_likelihood(self, separation_mm):
TOLERANCE = 0.5
fraction_properly_predicted = 0.0
#help(self.detector)
#print self.detector[0]
#help(self.detector[0])
panel = self.detector[0]
from scitbx import matrix
Astar = matrix.sqr(self.getOrientation().reciprocal_matrix())
import math
xyz = self.getXyzData()
# step 1. Deduce fractional HKL values from the XyzData. start with x = A* h
# solve for h: h = (A*^-1) x
Astarinv = Astar.inverse()
Hint = flex.vec3_double()
for x in xyz:
H = Astarinv * x
#print "%7.3f %7.3f %7.3f"%(H[0],H[1],H[2])
Hint.append((round(H[0], 0), round(H[1], 0), round(H[2], 0)))
xyz_miller = flex.vec3_double()
from rstbx.diffraction import rotation_angles
# XXX limiting shell of 1.0 angstroms probably needs to be changed/ removed. How?
ra = rotation_angles(limiting_resolution=1.0,
orientation=Astar,
wavelength=1. / self.inv_wave,
axial_direction=self.axis)
for ij, hkl in enumerate(Hint):
xyz_miller.append(
Astar *
hkl) # figure out how to do this efficiently on vector data
if ra(hkl):
omegas = ra.get_intersection_angles()
rotational_diffs = [
abs((-omegas[omegaidx] * 180. / math.pi) -
self.raw_spot_input[ij][2]) for omegaidx in [0, 1]
]
min_diff = min(rotational_diffs)
min_index = rotational_diffs.index(min_diff)
omega = omegas[min_index]
rot_mat = self.axis.axis_and_angle_as_r3_rotation_matrix(omega)
Svec = (rot_mat * Astar) * hkl + self.S0_vector
# print panel.get_ray_intersection(Svec), self.raw_spot_input[ij]
if self.panelID is not None:
panel = self.detector[self.panelID[ij]]
calc = matrix.col(panel.get_ray_intersection(Svec))
pred = matrix.col(self.raw_spot_input[ij][0:2])
# print (calc-pred).length(), separation_mm * TOLERANCE
if ((calc - pred).length() < separation_mm * TOLERANCE):
fraction_properly_predicted += 1. / self.raw_spot_input.size(
)
#print "fraction properly predicted",fraction_properly_predicted,"with spot sep (mm)",separation_mm
return fraction_properly_predicted
def model_likelihood(self,separation_mm):
TOLERANCE = 0.5
fraction_properly_predicted = 0.0
#help(self.detector)
#print self.detector[0]
#help(self.detector[0])
panel = self.detector[0]
from scitbx import matrix
Astar = matrix.sqr(self.getOrientation().reciprocal_matrix())
import math
xyz = self.getXyzData()
# step 1. Deduce fractional HKL values from the XyzData. start with x = A* h
# solve for h: h = (A*^-1) x
Astarinv = Astar.inverse()
Hint = flex.vec3_double()
for x in xyz:
H = Astarinv * x
#print "%7.3f %7.3f %7.3f"%(H[0],H[1],H[2])
Hint.append((round(H[0],0), round(H[1],0), round(H[2],0)))
xyz_miller = flex.vec3_double()
from rstbx.diffraction import rotation_angles
# XXX limiting shell of 1.0 angstroms probably needs to be changed/ removed. How?
ra = rotation_angles(limiting_resolution=1.0,orientation = Astar,
wavelength = 1./self.inv_wave, axial_direction = self.axis)
for ij,hkl in enumerate(Hint):
xyz_miller.append( Astar * hkl ) # figure out how to do this efficiently on vector data
if ra(hkl):
omegas = ra.get_intersection_angles()
rotational_diffs = [ abs((-omegas[omegaidx] * 180./math.pi)-self.raw_spot_input[ij][2])
for omegaidx in [0,1] ]
min_diff = min(rotational_diffs)
min_index = rotational_diffs.index(min_diff)
omega = omegas[min_index]
rot_mat = self.axis.axis_and_angle_as_r3_rotation_matrix(omega)
Svec = (rot_mat * Astar) * hkl + self.S0_vector
# print panel.get_ray_intersection(Svec), self.raw_spot_input[ij]
if self.panelID is not None: panel = self.detector[ self.panelID[ij] ]
calc = matrix.col(panel.get_ray_intersection(Svec))
pred = matrix.col(self.raw_spot_input[ij][0:2])
# print (calc-pred).length(), separation_mm * TOLERANCE
if ((calc-pred).length() < separation_mm * TOLERANCE):
fraction_properly_predicted += 1./ self.raw_spot_input.size()
#print "fraction properly predicted",fraction_properly_predicted,"with spot sep (mm)",separation_mm
return fraction_properly_predicted
def get_predicted_spot_positions_and_status(self, old_status=None): #similar to above function; above can be refactored
panel = self.detector[0]
from scitbx import matrix
Astar = matrix.sqr(self.getOrientation().reciprocal_matrix())
# must have set the basis in order to generate Astar matrix. How to assert this has been done???
import math,copy
xyz = self.getXyzData()
if old_status is None:
spot_status = [SpotClass.GOOD]*len(xyz)
else:
assert len(old_status)==len(xyz)
spot_status = copy.copy( old_status ) # valid way of copying enums w/o reference
self.assigned_hkl= [(0,0,0)]*len(xyz)
# step 1. Deduce fractional HKL values from the XyzData. start with x = A* h
# solve for h: h = (A*^-1) x
Astarinv = Astar.inverse()
Hint = flex.vec3_double()
results = flex.vec3_double()
for x in xyz:
H = Astarinv * x
Hint.append((round(H[0],0), round(H[1],0), round(H[2],0)))
xyz_miller = flex.vec3_double()
from rstbx.diffraction import rotation_angles
ra = rotation_angles(limiting_resolution=1.0,orientation = Astar,
wavelength = 1./self.inv_wave, axial_direction = self.axis)
for ij,hkl in enumerate(Hint):
xyz_miller.append( Astar * hkl ) # figure out how to do this efficiently on vector data
if ra(hkl):
omegas = ra.get_intersection_angles()
rotational_diffs = [ abs((-omegas[omegaidx] * 180./math.pi)-self.raw_spot_input[ij][2])
for omegaidx in [0,1] ]
min_diff = min(rotational_diffs)
min_index = rotational_diffs.index(min_diff)
omega = omegas[min_index]
rot_mat = self.axis.axis_and_angle_as_r3_rotation_matrix(omega)
Svec = (rot_mat * Astar) * hkl + self.S0_vector
if self.panelID is not None: panel = self.detector[ self.panelID[ij] ]
xy = panel.get_ray_intersection(Svec)
results.append((xy[0],xy[1],0.0))
self.assigned_hkl[ij]=hkl
else:
results.append((0.0,0.0,0.0))
spot_status[ij]=SpotClass.NONE
return results,spot_status
def parse_synthetic(filename):
G = open(filename, "r")
reciprocal_vectors = flex.vec3_double()
#Example of Silicon F d 3-bar m unit cell oriented along lab axes
A_mat = matrix.sqr((5.43, 0., 0., 0., 5.43, 0., 0., 0., 5.43))
A_star = A_mat.inverse()
for line in G.readlines()[1:]:
tokens = line.strip().split('\t')
assert len(tokens) == 5
miller = matrix.col([float(i) for i in tokens[0:3]])
reciprocal_vector = A_star * miller
reciprocal_vectors.append(reciprocal_vector.elems)
return reciprocal_vectors
def parse_synthetic(filename):
G = open(filename,"r")
reciprocal_vectors = flex.vec3_double()
#Example of Silicon F d 3-bar m unit cell oriented along lab axes
A_mat = matrix.sqr((5.43,0.,0.,0.,5.43,0.,0.,0.,5.43))
A_star = A_mat.inverse()
for line in G.readlines()[1:]:
tokens = line.strip().split('\t')
assert len(tokens)==5
miller = matrix.col([float(i) for i in tokens[0:3]])
reciprocal_vector = A_star*miller
reciprocal_vectors.append(reciprocal_vector.elems)
return reciprocal_vectors
def parse_input(filename):
with open(filename,"r") as G:
lines = G.readlines()
reciprocal_vectors = flex.vec3_double()
qvec = ('qx','qy','qz')
for line in lines[1:len(lines)]:
l_buffer = line.rstrip()
assert len(l_buffer)==132
extended_q_nm = matrix.col(
[get_token(qvec[i],l_buffer) for i in range(3)]
)
checklength = math.sqrt(extended_q_nm.dot(extended_q_nm))
assert approx_equal(1./checklength, get_token('dspacing',l_buffer), eps=0.0001)
#convert from nanometers to Angstroms
extended_q_Angstrom = 0.1 * extended_q_nm
reciprocal_vectors.append(extended_q_Angstrom.elems)
return reciprocal_vectors
def score_vectors(self, reciprocal_lattice_vectors):
"""Compute the functional for the given directions.
Args:
directions: An iterable of the search directions.
reciprocal_lattice_vectors (scitbx.array_family.flex.vec3_double):
The list of reciprocal lattice vectors.
Returns:
A tuple containing the list of search vectors and their scores.
"""
vectors = flex.vec3_double()
scores = flex.double()
for i, v in enumerate(self.search_vectors):
f = self.compute_functional(v.elems, reciprocal_lattice_vectors)
vectors.append(v.elems)
scores.append(f)
return vectors, scores
def parse_input(filename):
with open(filename, "r") as G:
lines = G.readlines()
reciprocal_vectors = flex.vec3_double()
for line in lines[0:len(lines) - 0]:
tokens = line.strip().split('\t')
assert len(tokens) == 7
q_vector = matrix.col([float(i) for i in tokens[4:7]])
checklength = q_vector.dot(q_vector)
assert approx_equal(checklength, 1.0, eps=0.001)
energy_keV = float(tokens[2])
theta = (math.pi / 180.) * float(tokens[3])
inv_lambda_Angstrom = keV_to_inv_Angstrom * energy_keV
inv_d_Angstrom = 2. * math.sin(theta) * inv_lambda_Angstrom
extended_q_Angstrom = inv_d_Angstrom * q_vector
E = extended_q_Angstrom
reciprocal_vectors.append(extended_q_Angstrom.elems)
return reciprocal_vectors
def parse_input(filename):
G = open(filename,"r")
reciprocal_vectors = flex.vec3_double()
lines = G.readlines()
for line in lines[0:len(lines)-0]:
tokens = line.strip().split('\t')
assert len(tokens)==7
q_vector = matrix.col([float(i) for i in tokens[4:7]])
checklength = q_vector.dot(q_vector)
assert approx_equal(checklength, 1.0, eps=0.001)
energy_keV = float(tokens[2])
theta = (math.pi/180.) * float(tokens[3])
inv_lambda_Angstrom = keV_to_inv_Angstrom * energy_keV
inv_d_Angstrom = 2. * math.sin(theta) * inv_lambda_Angstrom
extended_q_Angstrom = inv_d_Angstrom * q_vector
E=extended_q_Angstrom
reciprocal_vectors.append(extended_q_Angstrom.elems)
return reciprocal_vectors
def raw_spot_positions_mm_to_S1_vector( raw_spot_input, # as vec3_double
detector, inverse_wave,
panelID=None
):
if panelID is None:
panelID = flex.int(len(raw_spot_input),0)
reciprocal_space_vectors = flex.vec3_double()
# tile surface to laboratory transformation
for n in xrange(len(raw_spot_input)):
pid = panelID[n]
lab_direct = col(detector[pid].get_lab_coord(raw_spot_input[n][0:2]))
# laboratory direct to reciprocal space xyz transformation
lab_recip = (lab_direct.normalize() * inverse_wave)
reciprocal_space_vectors.append ( lab_recip )
return reciprocal_space_vectors
def raw_spot_positions_mm_to_reciprocal_space(
raw_spot_input, # as vec3_double
detector,
inverse_wave,
beam,
axis, # beam, axis as scitbx.matrix.col
panelID=None):
if panelID is None:
panelID = flex.int(len(raw_spot_input), 0)
if axis is None:
return raw_spot_positions_mm_to_reciprocal_space_xyz(
raw_spot_input, detector, inverse_wave, beam, panelID)
else:
return raw_spot_positions_mm_to_reciprocal_space_xyz(
raw_spot_input, detector, inverse_wave, beam, axis, panelID)
"""Assumptions:
1) the raw_spot_input is in the same units of measure as the origin vector (mm).
they are given in physical length, not pixel units
2) the raw_spot centers of mass are given with the same corner/center convention
as the origin vector. E.g., spotfinder assumes that the mm scale starts in
the middle of the lower-corner pixel.
"""
reciprocal_space_vectors = flex.vec3_double()
# tile surface to laboratory transformation
for n in range(len(raw_spot_input)):
pid = panelID[n]
lab_direct = col(detector[pid].get_lab_coord(
raw_spot_input[n][0:2]))
# laboratory direct to reciprocal space xyz transformation
lab_recip = (lab_direct.normalize() * inverse_wave) - beam
reciprocal_space_vectors.append(
lab_recip.rotate_around_origin(axis=axis,
angle=raw_spot_input[n][2],
deg=True))
return reciprocal_space_vectors
def raw_spot_positions_mm_to_S1_vector(
raw_spot_input, # as vec3_double
detector,
inverse_wave,
panelID=None):
if panelID is None:
panelID = flex.int(len(raw_spot_input), 0)
reciprocal_space_vectors = flex.vec3_double()
# tile surface to laboratory transformation
for n in range(len(raw_spot_input)):
pid = panelID[n]
lab_direct = col(detector[pid].get_lab_coord(
raw_spot_input[n][0:2]))
# laboratory direct to reciprocal space xyz transformation
lab_recip = (lab_direct.normalize() * inverse_wave)
reciprocal_space_vectors.append(lab_recip)
return reciprocal_space_vectors
def raw_spot_positions_mm_to_reciprocal_space( raw_spot_input, # as vec3_double
detector, inverse_wave, beam, axis, # beam, axis as scitbx.matrix.col
panelID=None
):
if panelID is None:
panelID = flex.int(len(raw_spot_input),0)
if axis is None:
return raw_spot_positions_mm_to_reciprocal_space_xyz (
raw_spot_input, detector, inverse_wave, beam, panelID )
else:
return raw_spot_positions_mm_to_reciprocal_space_xyz (
raw_spot_input, detector, inverse_wave, beam, axis, panelID )
"""Assumptions:
1) the raw_spot_input is in the same units of measure as the origin vector (mm).
they are given in physical length, not pixel units
2) the raw_spot centers of mass are given with the same corner/center convention
as the origin vector. E.g., spotfinder assumes that the mm scale starts in
the middle of the lower-corner pixel.
"""
reciprocal_space_vectors = flex.vec3_double()
# tile surface to laboratory transformation
for n in xrange(len(raw_spot_input)):
pid = panelID[n]
lab_direct = col(detector[pid].get_lab_coord(raw_spot_input[n][0:2]))
# laboratory direct to reciprocal space xyz transformation
lab_recip = (lab_direct.normalize() * inverse_wave) - beam
reciprocal_space_vectors.append ( lab_recip.rotate_around_origin(
axis=axis, angle=raw_spot_input[n][2], deg=True)
)
return reciprocal_space_vectors
