def __init__(SMG, goniometer):
from scitbx.array_family import flex
import math
SMG.goniometer = goniometer
coords = flex.vec3_double()
axis = flex.size_t()
# FACE A: Sample holder
# Defined as semi-circle of radius r(A) = 10 mm (centred on PHI axis)
# with rectangle of size a(A) = 12.8 mm (x 20 mm)
offsetA = 33.0
# semi-circle for phi=-90 ... +90
radiusA = 10.0
phi = flex.double_range(-90, 100, step=10) * math.pi / 180
x = flex.double(phi.size(), -offsetA)
y = radiusA * flex.cos(phi)
z = radiusA * flex.sin(phi)
# corners of square
sqdA = 12.8 # square depth
nsteps = 10
for i in range(nsteps + 1):
for sign in (+1, -1):
x.append(-offsetA)
y.append(i * -sqdA / nsteps)
z.append(sign * radiusA)
x.append(-offsetA)
y.append(-sqdA)
z.append(0)
SMG.faceA = flex.vec3_double(x, y, z)
# FACE B: Lower arm
sx = -28.50
sy = -4.90
sz = 8.50
mx = -13.80
my = -26.00
nx = -27.50
ny = -29.50
px = -65.50
py = -29.50
SMG.faceB = flex.vec3_double(
((sx, sy, sz), (mx, my, 0), (nx, ny, 0), (px, py, 0)))
# FACE E: Rim of sample holder
# Defined as circle of radius r(E) = 6 mm (centred on PHI axis) at an
# offset o(E) = 19 mm
offsetE = 19.0
radiusE = 6.0
phi = flex.double_range(0, 360, step=15) * math.pi / 180
x = flex.double(phi.size(), -offsetE)
y = radiusE * flex.cos(phi)
z = radiusE * flex.sin(phi)
SMG.faceE = flex.vec3_double(x, y, z)
def __init__(self, goniometer):
# FACE A: Sample holder
# Defined as semi-circle of radius r(A) = 10 mm (centred on PHI axis)
# with rectangle of size a(A) = 12.8 mm (x 20 mm)
offsetA = 33.0
# semi-circle for phi=-90 ... +90
radiusA = 10.0
phi = flex.double_range(-90, 100, step=10) * math.pi / 180
x = flex.double(phi.size(), -offsetA)
y = radiusA * flex.cos(phi)
z = radiusA * flex.sin(phi)
# corners of square
sqdA = 12.8 # square depth
nsteps = 10
for i in range(nsteps + 1):
for sign in (+1, -1):
x.append(-offsetA)
y.append(i * -sqdA / nsteps)
z.append(sign * radiusA)
x.append(-offsetA)
y.append(-sqdA)
z.append(0)
self.faceA = flex.vec3_double(-x, -y, z)
# FACE B: Lower arm
sx = -28.50
sy = -4.90
sz = 8.50
mx = -13.80
my = -26.00
nx = -27.50
ny = -29.50
px = -65.50
py = -29.50
self.faceB = flex.vec3_double(
((-sx, -sy, sz), (-mx, -my, 0), (-nx, -ny, 0), (-px, -py, 0))
)
# FACE E: Rim of sample holder
# Defined as circle of radius r(E) = 6 mm (centred on PHI axis) at an
# offset o(E) = 19 mm
offsetE = 19.0
radiusE = 6.0
phi = flex.double_range(0, 360, step=15) * math.pi / 180
x = flex.double(phi.size(), -offsetE)
y = radiusE * flex.cos(phi)
z = radiusE * flex.sin(phi)
self.faceE = flex.vec3_double(-x, -y, z)
extrema_at_datum = self.faceA.deep_copy()
extrema_at_datum.extend(self.faceE)
super().__init__(
goniometer, extrema_at_datum, flex.size_t(extrema_at_datum.size(), 1)
)
def __init__(self, goniometer):
from scitbx.array_family import flex
import math
self.goniometer = goniometer
coords = flex.vec3_double()
axis = flex.size_t()
# FACE A: Sample holder
# Defined as semi-circle of radius r(A) = 10 mm (centred on PHI axis)
# with rectangle of size a(A) = 12.8 mm (x 20 mm)
offsetA = 33.0
radiusA = 10.0
sqdA = 12.8 # square depth
phi = flex.double_range(-90, 100, step=10) * math.pi / 180
x = flex.double(phi.size(), -offsetA)
y = radiusA * flex.cos(phi)
z = radiusA * flex.sin(phi)
x.extend(flex.double(5, -offsetA))
y.extend(flex.double((-sqdA / 2, -sqdA, -sqdA, -sqdA, -sqdA / 2)))
z.extend(flex.double((radiusA, radiusA, 0, -radiusA, -radiusA)))
self.faceA = flex.vec3_double(x, y, z)
# FACE B: Lower arm
sx = -28.50
sy = -4.90
sz = 8.50
mx = -13.80
my = -26.00
nx = -27.50
ny = -29.50
px = -65.50
py = -29.50
self.faceB = flex.vec3_double(
((sx, sy, sz), (mx, my, 0), (nx, ny, 0), (px, py, 0)))
# FACE E: Rim of sample holder
# Defined as circle of radius r(E) = 6 mm (centred on PHI axis) at an
# offset o(E) = 19 mm
offsetE = 19.0
radiusE = 6.0
phi = flex.double_range(0, 360, step=15) * math.pi / 180
x = flex.double(phi.size(), -offsetE)
y = radiusE * flex.cos(phi)
z = radiusE * flex.sin(phi)
self.faceE = flex.vec3_double(x, y, z)
def __init__(self, goniometer):
from scitbx.array_family import flex
import math
self.goniometer = goniometer
coords = flex.vec3_double()
axis = flex.size_t()
# FACE A: Sample holder
# Defined as semi-circle of radius r(A) = 10 mm (centred on PHI axis)
# with rectangle of size a(A) = 12.8 mm (x 20 mm)
offsetA = 33.0
radiusA = 10.0
sqdA = 12.8 # square depth
phi = flex.double_range(-90, 100, step=10) * math.pi/180
x = flex.double(phi.size(), -offsetA)
y = radiusA * flex.cos(phi)
z = radiusA * flex.sin(phi)
x.extend(flex.double(5, -offsetA))
y.extend(flex.double((-sqdA/2, -sqdA, -sqdA, -sqdA, -sqdA/2)))
z.extend(flex.double((radiusA, radiusA, 0, -radiusA, -radiusA)))
self.faceA = flex.vec3_double(x, y, z)
# FACE B: Lower arm
sx = -28.50
sy = -4.90
sz = 8.50
mx = -13.80
my = -26.00
nx = -27.50
ny = -29.50
px = -65.50
py = -29.50
self.faceB = flex.vec3_double(((sx,sy,sz),(mx,my,0),(nx,ny,0),(px,py,0)))
# FACE E: Rim of sample holder
# Defined as circle of radius r(E) = 6 mm (centred on PHI axis) at an
# offset o(E) = 19 mm
offsetE = 19.0
radiusE = 6.0
phi = flex.double_range(0, 360, step=15) * math.pi/180
x = flex.double(phi.size(), -offsetE)
y = radiusE * flex.cos(phi)
z = radiusE * flex.sin(phi)
self.faceE = flex.vec3_double(x, y, z)
def get_goniometer_shadow_masker(self, goniometer=None):
if goniometer is None:
goniometer = self.get_goniometer()
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
import math
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 10 # mm
cone_opening_angle = 2 * 38 * math.pi / 180
radius_height_ratio = math.tan(1 / 2 * cone_opening_angle)
radius = radius_height_ratio * height
# print 2 * math.atan(radius/height) * 180 / math.pi
steps_per_degree = 1
theta = (flex.double([range(360 * steps_per_degree)]) * math.pi / 180 *
1 / steps_per_degree)
x = radius * flex.cos(theta) # x
z = radius * flex.sin(theta) # y
y = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.extend(flex.vec3_double(zip(x, -y, z)))
coords.insert(0, (0, 0, 0))
if goniometer is None:
goniometer = self.get_goniometer()
return GoniometerShadowMaskGenerator(goniometer, coords,
flex.size_t(len(coords), 0))
def _construct_shadow_masker(goniometer):
if request.param == "cpp":
return GoniometerMaskerFactory.mini_kappa(goniometer)
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 50 # mm
radius = 20 # mm
steps_per_degree = 1
theta = (
flex.double(range(360 * steps_per_degree))
* math.pi
/ 180
* 1
/ steps_per_degree
)
y = radius * flex.cos(-theta)
z = radius * flex.sin(-theta)
x = flex.double(theta.size(), height)
coords = flex.vec3_double(zip(x, y, z))
coords.insert(0, (0, 0, 0))
return PyGoniometerShadowMasker(goniometer, coords, flex.size_t(len(coords), 0))
def parts(self,fpp):
dano_summation = None
Ddanocalc_Dp = []
for j,idx in enumerate(self.scatterer_idx):
bool_array = self.xray_structure.by_index_selection([idx])
xrs_atom = self.xray_structure.select(bool_array)
#xrs_atom.show_scatterers()
f_calc_atom = self.f_calc.structure_factors_from_scatterers(
xray_structure=xrs_atom, algorithm=algorithm).f_calc()
adata = f_calc_atom.data().parts()[0]
bdata = f_calc_atom.data().parts()[1]
product_factor = bdata * flex.cos(self.phases.data()) - adata * flex.sin(self.phases.data())
# correspnds to -b cos(alpha) + a sin(alpha)
#print list(xrs_atom.scattering_types())
#xrs_atom.scattering_type_registry().show_summary()
#xrs_atom.scattering_type_registry().show()
f_zero = xrs_atom.scattering_type_registry().sum_of_scattering_factors_at_diffraction_angle_0()
#print f_zero
Ddanocalc_Dp.append((-2./f_zero)*product_factor)
term = (-2.*fpp[j]/f_zero)*product_factor
if dano_summation is None:
dano_summation = term
else:
dano_summation += term
return dano_summation,Ddanocalc_Dp
"""
def parts(self, fpp):
dano_summation = None
Ddanocalc_Dp = []
for j, idx in enumerate(self.scatterer_idx):
bool_array = self.xray_structure.by_index_selection([idx])
xrs_atom = self.xray_structure.select(bool_array)
#xrs_atom.show_scatterers()
f_calc_atom = self.f_calc.structure_factors_from_scatterers(
xray_structure=xrs_atom, algorithm=algorithm).f_calc()
adata = f_calc_atom.data().parts()[0]
bdata = f_calc_atom.data().parts()[1]
product_factor = bdata * flex.cos(
self.phases.data()) - adata * flex.sin(self.phases.data())
# correspnds to -b cos(alpha) + a sin(alpha)
#print list(xrs_atom.scattering_types())
#xrs_atom.scattering_type_registry().show_summary()
#xrs_atom.scattering_type_registry().show()
f_zero = xrs_atom.scattering_type_registry(
).sum_of_scattering_factors_at_diffraction_angle_0()
#print f_zero
Ddanocalc_Dp.append((-2. / f_zero) * product_factor)
term = (-2. * fpp[j] / f_zero) * product_factor
if dano_summation is None:
dano_summation = term
else:
dano_summation += term
return dano_summation, Ddanocalc_Dp
"""
def circ_mean(t, deg=True):
assert (len(t) > 0)
from scitbx.array_family import flex
if (deg):
t = math.pi * (t / 180)
sx = flex.sum(flex.cos(t)) / len(t)
sy = flex.sum(flex.sin(t)) / len(t)
return math.degrees(math.atan2(sy, sx))
def circ_mean (t, deg=True) :
assert (len(t) > 0)
from scitbx.array_family import flex
if (deg) :
t = math.pi * (t/180)
sx = flex.sum(flex.cos(t)) / len(t)
sy = flex.sum(flex.sin(t)) / len(t)
return math.degrees(math.atan2(sy, sx))
def circ_len (t, deg=True) :
assert (len(t) > 0)
from scitbx.array_family import flex
if (deg) :
t = math.pi * (t/180)
sx = flex.sum(flex.cos(t)) / len(t)
sy = flex.sum(flex.sin(t)) / len(t)
return math.sqrt(sx**2 + sy**2)
def circ_len(t, deg=True):
assert (len(t) > 0)
from scitbx.array_family import flex
if (deg):
t = math.pi * (t / 180)
sx = flex.sum(flex.cos(t)) / len(t)
sy = flex.sum(flex.sin(t)) / len(t)
return math.sqrt(sx**2 + sy**2)
def __init__(self,working_phil):
self.working_phil = working_phil
self.two_theta_experimental = flex.double([
1.5114,3.0160,4.5289,6.0422,7.5575,9.0733,10.5922,12.1106,13.6320,15.1563,16.6836,18.2107])
# first 12 orders of silver behenate rings reported by Huang (1993) J Appl Cryst 26, 180-184.
copper_Kalpha = 1.5418 # Angstroms
d = flex.double(len(self.two_theta_experimental), copper_Kalpha/2.)
self.experimental_d = d/flex.sin((math.pi/360.)*self.two_theta_experimental)
def compute_functional_and_gradients(self, vector):
assert len(vector) == 3
two_pi_S_dot_v = 2 * math.pi * self.reciprocal_lattice_points.dot(vector)
f = -flex.sum(flex.cos(two_pi_S_dot_v))
sin_part = flex.sin(two_pi_S_dot_v)
g = flex.double(
[flex.sum(2 * math.pi * self._xyz_parts[i] * sin_part) for i in range(3)]
)
return f, g
def __init__(self, working_phil):
self.working_phil = working_phil
self.two_theta_experimental = flex.double([
1.5114, 3.0160, 4.5289, 6.0422, 7.5575, 9.0733, 10.5922, 12.1106,
13.6320, 15.1563, 16.6836, 18.2107
])
# first 12 orders of silver behenate rings reported by Huang (1993) J Appl Cryst 26, 180-184.
copper_Kalpha = 1.5418 # Angstroms
d = flex.double(len(self.two_theta_experimental), copper_Kalpha / 2.)
self.experimental_d = d / flex.sin(
(math.pi / 360.) * self.two_theta_experimental)
def get_goniometer_shadow_masker(self, goniometer=None):
if goniometer is None:
goniometer = self.get_goniometer()
assert goniometer is not None
# avoid a module-level import from the DIALS namespace that kills LABELIT
from dials.util.masking import GoniometerShadowMaskGenerator
if goniometer.get_names()[1] == "GON_CHI":
# SmarGon
from dxtbx.format.SmarGonShadowMask import SmarGonShadowMaskGenerator
return SmarGonShadowMaskGenerator(goniometer)
elif goniometer.get_names()[1] == "GON_KAPPA":
# mini Kappa
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 50 # mm
radius = 20 # mm
steps_per_degree = 1
theta = (
flex.double([range(360 * steps_per_degree)])
* math.pi
/ 180
* 1
/ steps_per_degree
)
y = radius * flex.cos(theta) # x
z = radius * flex.sin(theta) # y
x = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.insert(0, (0, 0, 0))
return GoniometerShadowMaskGenerator(
goniometer, coords, flex.size_t(len(coords), 0)
)
else:
raise RuntimeError(
"Don't understand this goniometer: %s" % list(goniometer.get_names())
)
def diamond_anvil_cell(goniometer, cone_opening_angle):
radius_height_ratio = math.tan(1 / 2 * cone_opening_angle)
height = 10 # mm
radius = radius_height_ratio * height
steps_per_degree = 1
theta = (flex.double([list(range(360 * steps_per_degree))]) * math.pi /
180 * 1 / steps_per_degree)
x = radius * flex.cos(theta) # x
z = radius * flex.sin(theta) # y
y = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.extend(flex.vec3_double(zip(x, -y, z)))
coords.insert(0, (0, 0, 0))
return GoniometerShadowMasker(goniometer, coords,
flex.size_t(len(coords), 0), True)
def tst_sphere():
bli = intensity.block_integrator(50.0, 0.1, 1.0, 0.001)
q = flex.double(range(1, 300)) / 1000.0
bli.setup_arrays(q)
r = flex.double(range(500)) / 500.0
r = r
pr = 6.0 * r * r * (2 - 3.0 * r + r * r * r)
r = r * 50
#for rr, pp in zip(r,pr):
# print rr, pp
iii = bli.get_intensity(pr)
iii = iii / 25.0
jjj = (flex.sin(25.0 * q) -
25.0 * q * flex.cos(q * 25.0)) / (1e-12 + q * q * q * 25 * 25 * 25)
jjj = jjj * jjj
jjj = jjj / jjj[0]
for q, i, j in zip(q, iii, jjj):
assert (abs(i - j) < 1e-2)
def get_goniometer_shadow_masker(self, goniometer=None):
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
import math
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 50 # mm
radius = 20 # mm
steps_per_degree = 1
theta = flex.double([range(360*steps_per_degree)]) * math.pi/180 * 1/steps_per_degree
y = radius * flex.cos(theta) # x
z = radius * flex.sin(theta) # y
x = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.insert(0, (0,0,0))
if goniometer is None:
goniometer = self.get_goniometer()
return GoniometerShadowMaskGenerator(
goniometer, coords, flex.size_t(len(coords), 0))
def get_goniometer_shadow_masker(self, goniometer=None):
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
import math
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 50 # mm
radius = 20 # mm
steps_per_degree = 1
theta = flex.double([range(360*steps_per_degree)]) * math.pi/180 * 1/steps_per_degree
y = radius * flex.cos(theta) # x
z = radius * flex.sin(theta) # y
x = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.insert(0, (0,0,0))
if goniometer is None:
goniometer = self.get_goniometer()
return GoniometerShadowMaskGenerator(
goniometer, coords, flex.size_t(len(coords), 0))
def mini_kappa(goniometer, cone_opening_angle=43.60281897270362):
"""Construct a GoniometerShadowMasker for a mini-kappa goniometer.
This is modelled a simple cone with the opening angle specified by
`cone_opening_angle`.
Args:
goniometer (`dxtbx.model.Goniometer`): The goniometer instance.
cone_opening_angle (float): The opening angle of the cone (in degrees).
Returns:
`dxtbx.masking.GoniometerShadowMasker`
"""
assert isinstance(goniometer, MultiAxisGoniometer)
assert len(goniometer.get_axes()) == 3
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 50 # mm
radius_height_ratio = math.tan(1 / 2 * cone_opening_angle * math.pi /
180)
radius = radius_height_ratio * height
steps_per_degree = 1
theta = (flex.double(range(360 * steps_per_degree)) * math.pi / 180 *
1 / steps_per_degree)
y = radius * flex.cos(-theta) # x
z = radius * flex.sin(-theta) # y
x = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.insert(0, (0, 0, 0))
return GoniometerShadowMasker(goniometer, coords,
flex.size_t(len(coords), 0))
def get_sinc(self, q, r):
sinc = flex.sin(r * q) / (r * q)
return sinc
def run(args, imageset=None):
# Parse input
try:
len(args)
except Exception:
params = args
else:
user_phil = []
for arg in args:
if "=" in arg:
try:
user_phil.append(libtbx.phil.parse(arg))
except RuntimeError as e:
raise Sorry("Unrecognized argument '%s' (error: %s)" %
(arg, str(e)))
else:
try:
user_phil.append(
libtbx.phil.parse("""file_path=%s""" % arg))
except ValueError:
raise Sorry("Unrecognized argument '%s'" % arg)
params = master_phil.fetch(sources=user_phil).extract()
if imageset is None:
if (params.file_path is None or len(params.file_path) == 0
or not all(os.path.isfile(f) for f in params.file_path)):
master_phil.show()
raise Usage(
"file_path must be defined (either file_path=XXX, or the path alone)."
)
assert params.n_bins is not None
assert params.verbose is not None
assert params.output_bins is not None
# Allow writing to a file instead of stdout
if params.output_file is None:
logger = sys.stdout
else:
logger = open(params.output_file, "w")
logger.write("%s " % params.output_file)
if params.show_plots:
from matplotlib import pyplot as plt
colormap = plt.cm.gist_ncar
plt.gca().set_color_cycle(
[colormap(i) for i in np.linspace(0, 0.9, len(params.file_path))])
if params.mask is not None:
params.mask = easy_pickle.load(params.mask)
if imageset is None:
iterable = params.file_path
def load_func(x):
try:
obj = dxtbx.datablock.DataBlockFactory.from_filenames(
[x])[0].extract_imagesets()[0]
except IndexError:
try:
obj = dxtbx.datablock.DataBlockFactory.from_json_file(
x)[0].extract_imagesets()[0]
except dxtbx.datablock.InvalidDataBlockError:
obj = ExperimentListFactory.from_json_file(x)[0].imageset
return obj
else:
iterable = [imageset]
def load_func(x):
return x
# Iterate over each file provided
for item in iterable:
iset = load_func(item)
n_images = len(iset)
if params.image_number is None:
if params.max_images is None:
subiterable = range(n_images)
else:
subiterable = range(0, min(params.max_images, n_images))
else:
subiterable = [params.image_number]
for image_number in subiterable:
beam = iset.get_beam(image_number)
detector = iset.get_detector(image_number)
s0 = col(beam.get_s0())
# Search the detector for the panel farthest from the beam. The
# number of bins in the radial average will be equal to the
# farthest point from the beam on the detector, in pixels, unless
# overridden at the command line
panel_res = [p.get_max_resolution_at_corners(s0) for p in detector]
farthest_panel = detector[panel_res.index(min(panel_res))]
size2, size1 = farthest_panel.get_image_size()
corners = [(0, 0), (size1 - 1, 0), (0, size2 - 1),
(size1 - 1, size2 - 1)]
corners_lab = [
col(farthest_panel.get_pixel_lab_coord(c)) for c in corners
]
corner_two_thetas = [
farthest_panel.get_two_theta_at_pixel(s0, c) for c in corners
]
extent_two_theta = max(corner_two_thetas)
max_corner = corners_lab[corner_two_thetas.index(extent_two_theta)]
extent = int(
math.ceil(max_corner.length() * math.sin(extent_two_theta) /
max(farthest_panel.get_pixel_size())))
extent_two_theta *= 180 / math.pi
if params.n_bins < extent:
params.n_bins = extent
# These arrays will store the radial average info
sums = flex.double(params.n_bins) * 0
sums_sq = flex.double(params.n_bins) * 0
counts = flex.int(params.n_bins) * 0
all_data = iset[image_number]
if not isinstance(all_data, tuple):
all_data = (all_data, )
for tile, (panel, data) in enumerate(zip(detector, all_data)):
if params.panel is not None and tile != params.panel:
continue
if params.mask is None:
mask = flex.bool(flex.grid(data.focus()), True)
else:
mask = params.mask[tile]
if hasattr(data, "as_double"):
data = data.as_double()
logger.flush()
if params.verbose:
logger.write("Average intensity tile %d: %9.3f\n" %
(tile, flex.mean(data)))
logger.write("N bins: %d\n" % params.n_bins)
logger.flush()
x1, y1, x2, y2 = (
0,
0,
panel.get_image_size()[1],
panel.get_image_size()[0],
)
bc = panel.get_beam_centre_px(beam.get_s0())
bc = int(round(bc[1])), int(round(bc[0]))
# compute the average
radial_average(
data,
mask,
bc,
sums,
sums_sq,
counts,
panel.get_pixel_size()[0],
panel.get_distance(),
(x1, y1),
(x2, y2),
)
# average the results, avoiding division by zero
results = sums.set_selected(counts <= 0, 0)
results /= counts.set_selected(counts <= 0, 1).as_double()
if params.median_filter_size is not None:
logger.write(
"WARNING, the median filter is not fully propagated to the variances\n"
)
from scipy.ndimage.filters import median_filter
results = flex.double(
median_filter(results.as_numpy_array(),
size=params.median_filter_size))
# calculate standard devations
stddev_sel = ((sums_sq - sums * results) >= 0) & (counts > 0)
std_devs = flex.double(len(sums), 0)
std_devs.set_selected(
stddev_sel,
(sums_sq.select(stddev_sel) -
sums.select(stddev_sel) * results.select(stddev_sel)) /
counts.select(stddev_sel).as_double(),
)
std_devs = flex.sqrt(std_devs)
twotheta = (flex.double(range(len(results))) * extent_two_theta /
params.n_bins)
q_vals = (4 * math.pi * flex.sin(math.pi * twotheta / 360) /
beam.get_wavelength())
# nlmbda = 2dsin(theta)
resolution = flex.double(len(twotheta), 0)
nonzero = twotheta > 0
resolution.set_selected(
nonzero,
beam.get_wavelength() / (2 * flex.asin(
(math.pi / 180) * twotheta.select(nonzero) / 2)),
)
if params.low_max_two_theta_limit is None:
subset = results
else:
subset = results.select(
twotheta >= params.low_max_two_theta_limit)
max_result = flex.max(subset)
if params.x_axis == "two_theta":
xvals = twotheta
max_x = twotheta[flex.first_index(results, max_result)]
elif params.x_axis == "q":
xvals = q_vals
max_x = q_vals[flex.first_index(results, max_result)]
elif params.x_axis == "resolution":
xvals = resolution
max_x = resolution[flex.first_index(results, max_result)]
for i, r in enumerate(results):
val = xvals[i]
if params.output_bins and "%.3f" % r != "nan":
# logger.write("%9.3f %9.3f\n"% (val,r)) #.xy format for Rex.cell.
logger.write(
"%9.3f %9.3f %9.3f\n" %
(val, r, std_devs[i])) # .xye format for GSASII
# logger.write("%.3f %.3f %.3f\n"%(val,r,ds[i])) # include calculated d spacings
logger.write("Maximum %s: %f, value: %f\n" %
(params.x_axis, max_x, max_result))
if params.show_plots:
if params.plot_x_max is not None:
results = results.select(xvals <= params.plot_x_max)
xvals = xvals.select(xvals <= params.plot_x_max)
if params.normalize:
plt.plot(
xvals.as_numpy_array(),
(results / flex.max(results)).as_numpy_array(),
"-",
)
else:
plt.plot(xvals.as_numpy_array(), results.as_numpy_array(),
"-")
if params.x_axis == "two_theta":
plt.xlabel("2 theta")
elif params.x_axis == "q":
plt.xlabel("q")
elif params.x_axis == "resolution":
plt.xlabel("Resolution ($\\AA$)")
plt.gca().set_xscale("log")
plt.gca().invert_xaxis()
plt.xlim(0, 50)
plt.ylabel("Avg ADUs")
if params.plot_y_max is not None:
plt.ylim(0, params.plot_y_max)
if params.show_plots:
# plt.legend([os.path.basename(os.path.splitext(f)[0]) for f in params.file_path], ncol=2)
plt.show()
return xvals, results
def background(imageset, indx, n_bins, mask_params=None):
from dials.array_family import flex
from libtbx.phil import parse
from scitbx import matrix
if mask_params is None:
# Default mask params for trusted range
mask_params = phil_scope.fetch(parse("")).extract().masking
from dials.util.masking import MaskGenerator
mask_generator = MaskGenerator(mask_params)
mask = mask_generator.generate(imageset)
detector = imageset.get_detector()
beam = imageset.get_beam()
# Only working with single panel detector for now
assert len(detector) == 1
panel = detector[0]
mask = mask[0]
n = matrix.col(panel.get_normal()).normalize()
b = matrix.col(beam.get_s0()).normalize()
wavelength = beam.get_wavelength()
if math.fabs(b.dot(n)) < 0.95:
raise Sorry("Detector not perpendicular to beam")
data = imageset.get_raw_data(indx)
assert len(data) == 1
data = data[0]
data = data.as_double()
spot_params = spot_phil.fetch(source=parse("")).extract()
threshold_function = SpotFinderFactory.configure_threshold(spot_params)
peak_pixels = threshold_function.compute_threshold(data, mask)
signal = data.select(peak_pixels.iselection())
background_pixels = mask & ~peak_pixels
background = data.select(background_pixels.iselection())
# print some summary information
print("Mean background: %.3f" % (flex.sum(background) / background.size()))
if len(signal) > 0:
print("Max/total signal pixels: %.0f / %.0f" %
(flex.max(signal), flex.sum(signal)))
else:
print("No signal pixels on this image")
print("Peak/background/masked pixels: %d / %d / %d" %
(peak_pixels.count(True), background.size(), mask.count(False)))
# compute histogram of two-theta values, then same weighted
# by pixel values, finally divide latter by former to get
# the radial profile out, need to set the number of bins
# sensibly; inspired by method in PyFAI
two_theta_array = panel.get_two_theta_array(beam.get_s0())
two_theta_array = two_theta_array.as_1d().select(
background_pixels.iselection())
# Use flex.weighted_histogram
h0 = flex.weighted_histogram(two_theta_array, n_slots=n_bins)
h1 = flex.weighted_histogram(two_theta_array, background, n_slots=n_bins)
h2 = flex.weighted_histogram(two_theta_array,
background * background,
n_slots=n_bins)
d0 = h0.slots()
d1 = h1.slots()
d2 = h2.slots()
I = d1 / d0
I2 = d2 / d0
sig = flex.sqrt(I2 - flex.pow2(I))
tt = h0.slot_centers()
d_spacings = wavelength / (2.0 * flex.sin(0.5 * tt))
return d_spacings, I, sig
def get_goniometer_shadow_masker(self, goniometer=None):
if goniometer is None:
goniometer = self.get_goniometer()
assert goniometer is not None
#avoid a module-level import from the DIALS namespace that kills LABELIT
from dials.util.masking import GoniometerShadowMaskGenerator
if goniometer.get_names()[1] == 'GON_CHI':
# SmarGon
class SmarGonShadowMaskGenerator(GoniometerShadowMaskGenerator):
def __init__(SMG, goniometer):
from scitbx.array_family import flex
import math
SMG.goniometer = goniometer
coords = flex.vec3_double()
axis = flex.size_t()
# FACE A: Sample holder
# Defined as semi-circle of radius r(A) = 10 mm (centred on PHI axis)
# with rectangle of size a(A) = 12.8 mm (x 20 mm)
offsetA = 33.0
# semi-circle for phi=-90 ... +90
radiusA = 10.0
phi = flex.double_range(-90, 100, step=10) * math.pi / 180
x = flex.double(phi.size(), -offsetA)
y = radiusA * flex.cos(phi)
z = radiusA * flex.sin(phi)
# corners of square
sqdA = 12.8 # square depth
nsteps = 10
for i in range(nsteps + 1):
for sign in (+1, -1):
x.append(-offsetA)
y.append(i * -sqdA / nsteps)
z.append(sign * radiusA)
x.append(-offsetA)
y.append(-sqdA)
z.append(0)
SMG.faceA = flex.vec3_double(x, y, z)
# FACE B: Lower arm
sx = -28.50
sy = -4.90
sz = 8.50
mx = -13.80
my = -26.00
nx = -27.50
ny = -29.50
px = -65.50
py = -29.50
SMG.faceB = flex.vec3_double(
((sx, sy, sz), (mx, my, 0), (nx, ny, 0), (px, py, 0)))
# FACE E: Rim of sample holder
# Defined as circle of radius r(E) = 6 mm (centred on PHI axis) at an
# offset o(E) = 19 mm
offsetE = 19.0
radiusE = 6.0
phi = flex.double_range(0, 360, step=15) * math.pi / 180
x = flex.double(phi.size(), -offsetE)
y = radiusE * flex.cos(phi)
z = radiusE * flex.sin(phi)
SMG.faceE = flex.vec3_double(x, y, z)
def extrema_at_scan_angle(SMG, scan_angle):
from scitbx.array_family import flex
# Align end station coordinate system with ImgCIF coordinate system
from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame
from scitbx import matrix
R = align_reference_frame(matrix.col((-1, 0, 0)),
matrix.col((1, 0, 0)),
matrix.col((0, -1, 0)),
matrix.col((0, 1, 0)))
faceA = R.elems * SMG.faceA
faceE = R.elems * SMG.faceE
axes = SMG.goniometer.get_axes()
angles = SMG.goniometer.get_angles()
scan_axis = SMG.goniometer.get_scan_axis()
angles[scan_axis] = scan_angle
extrema = flex.vec3_double()
for coords in (faceA, faceE):
coords = coords.deep_copy()
for i, axis in enumerate(axes):
if i == 0:
continue # shadow doesn't change with phi setting
sel = flex.bool(len(coords), True)
rotation = matrix.col(
axis).axis_and_angle_as_r3_rotation_matrix(
angles[i], deg=True)
coords.set_selected(
sel, rotation.elems * coords.select(sel))
extrema.extend(coords)
s = matrix.col(SMG.faceB[0])
mx, my, _ = SMG.faceB[1]
nx, ny, _ = SMG.faceB[2]
px, py, _ = SMG.faceB[3]
Rchi = (R.inverse() * matrix.col(axes[1])
).axis_and_angle_as_r3_rotation_matrix(angles[1],
deg=True)
sk = Rchi * s
sxk, syk, szk = sk.elems
coords = flex.vec3_double((
(sxk, syk, 0),
(sxk, syk, szk),
(sxk + mx / 2, syk + my / 2, szk),
(sxk + mx, syk + my, szk),
(sxk + (mx + nx) / 2, syk + (my + ny) / 2, szk),
(sxk + nx, syk + ny, szk),
(sxk + (nx + px) / 2, syk + (ny + py) / 2, szk),
(sxk + px, syk + py, szk),
(sxk + px, syk + py, 0),
(sxk + px, syk + py, -szk),
(sxk + (nx + px) / 2, syk + (ny + py) / 2, -szk),
(sxk + nx, syk + ny, -szk),
(sxk + (mx + nx) / 2, syk + (my + ny) / 2, -szk),
(sxk + mx, syk + my, -szk),
(sxk + mx / 2, syk + my / 2, -szk),
(sxk, syk, -szk),
))
coords = R.elems * coords
Romega = matrix.col(
axes[2]).axis_and_angle_as_r3_rotation_matrix(
angles[2], deg=True)
coords = Romega.elems * coords
extrema.extend(coords)
return extrema
#------------------ finished defining SmarGonShadowMaskGenerator
return SmarGonShadowMaskGenerator(goniometer)
elif goniometer.get_names()[1] == 'GON_KAPPA':
# mini Kappa
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
import math
# Simple model of cone around goniometer phi axis
# Exact values don't matter, only the ratio of height/radius
height = 50 # mm
radius = 20 # mm
steps_per_degree = 1
theta = flex.double([range(360 * steps_per_degree)
]) * math.pi / 180 * 1 / steps_per_degree
y = radius * flex.cos(theta) # x
z = radius * flex.sin(theta) # y
x = flex.double(theta.size(), height) # z
coords = flex.vec3_double(zip(x, y, z))
coords.insert(0, (0, 0, 0))
if goniometer is None:
goniometer = self.get_goniometer()
return GoniometerShadowMaskGenerator(goniometer, coords,
flex.size_t(len(coords), 0))
else:
raise RuntimeError("Don't understand this goniometer: %s" %
list(goniometer.get_names()))
def sphere_data(q, d_max): r=d_max/2.0 a = r*r*r*( flex.sin(q*r)-q*r*flex.cos(q*r) )/( r*r*r*q*q*q ) return a*a
def get_goniometer_shadow_masker(self, goniometer=None):
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
import math
coords = flex.vec3_double(((0, 0, 0), ))
alpha = flex.double_range(0, 190, step=10) * math.pi / 180
r = flex.double(alpha.size(), 40)
x = flex.double(r.size(), 107.61)
y = -r * flex.sin(alpha)
z = -r * flex.cos(alpha)
coords.extend(flex.vec3_double(x, y, z))
coords.extend(
flex.vec3_double((
# fixed
(107.49, 7.84, 39.49),
(107.39, 15.69, 38.97),
(107.27, 23.53, 38.46),
(107.16, 31.37, 37.94),
(101.76, 33.99, 36.25),
(96.37, 36.63, 34.56),
(90.98, 39.25, 33.00),
(85.58, 41.88, 31.18),
(80.89, 47.06, 31.00),
(76.55, 51.51, 31.03),
(72.90, 55.04, 31.18),
(66.86, 60.46, 31.67),
(62.10, 64.41, 32.25),
)))
alpha = flex.double_range(180, 370, step=10) * math.pi / 180
r = flex.double(alpha.size(), 33)
x = (flex.sqrt(flex.pow2(r * flex.sin(alpha)) + 89.02**2) *
flex.cos((50 * math.pi / 180) -
flex.atan(r / 89.02 * flex.sin(alpha))))
y = (flex.sqrt(flex.pow2(r * flex.sin(alpha)) + 89.02**2) *
flex.sin((50 * math.pi / 180) -
flex.atan(r / 89.02 * flex.sin(alpha))))
z = -r * flex.cos(alpha)
coords.extend(flex.vec3_double(x, y, z))
coords.extend(
flex.vec3_double((
# fixed
(62.10, 64.41, -32.25),
(66.86, 60.46, -31.67),
(72.90, 55.04, -31.18),
(76.55, 51.51, -31.03),
(80.89, 47.06, -31.00),
(85.58, 41.88, -31.18),
(90.98, 39.25, -33.00),
(96.37, 36.63, -34.56),
(101.76, 33.99, -36.25),
(107.16, 31.37, -37.94),
(107.27, 23.53, -38.46),
(107.39, 15.69, -38.97),
(107.49, 7.84, -39.49),
(107.61, 0.00, -40.00))))
# I23 end station coordinate system:
# X-axis: positive direction is facing away from the storage ring (from
# sample towards goniometer)
# Y-axis: positive direction is vertically up
# Z-axis: positive direction is in the direction of the beam (from
# sample towards detector)
# K-axis (kappa): at an angle of +50 degrees from the X-axis
# K & phi rotation axes: clockwise rotation is positive (right hand
# thumb rule)
# Omega-axis: along the X-axis; clockwise rotation is positive
# End station x-axis is parallel to ImgCIF x-axis
# End station z-axis points in opposite direction to ImgCIF definition
# (ImgCIF: The Z-axis is derived from the source axis which goes from
# the sample to the source)
# Consequently end station y-axis (to complete set following right hand
# rule) points in opposite direction to ImgCIF y-axis.
# Kappa arm aligned with -y in ImgCIF convention
from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame
from scitbx import matrix
R = align_reference_frame(matrix.col((1, 0, 0)), matrix.col((1, 0, 0)),
matrix.col((0, 1, 0)), matrix.col(
(0, -1, 0)))
coords = R.elems * coords
if goniometer is None:
goniometer = self.get_goniometer()
return GoniometerShadowMaskGenerator(goniometer, coords,
flex.size_t(len(coords), 1))
def get_sinc(self, q, x):
r = 0.5 * (x + 1) * self.d_max
sinc = flex.sin(r * q) / (r * q)
return sinc
def example():
x_obs = (flex.double(range(100)) + 1.0) / 101.0
y_ideal = flex.sin(x_obs * 6.0 * 3.1415) + flex.exp(x_obs)
y_obs = y_ideal + (flex.random_double(size=x_obs.size()) - 0.5) * 0.5
w_obs = flex.double(x_obs.size(), 1)
print "Trying to determine the best number of terms "
print " via cross validation techniques"
print
n_terms = chebyshev_lsq_fit.cross_validate_to_determine_number_of_terms(
x_obs, y_obs, w_obs, min_terms=5, max_terms=20, n_goes=20, n_free=20)
print "Fitting with", n_terms, "terms"
print
fit = chebyshev_lsq_fit.chebyshev_lsq_fit(n_terms, x_obs, y_obs)
print "Least Squares residual: %7.6f" % (fit.f)
print " R2-value : %7.6f" % (fit.f / flex.sum(y_obs * y_obs))
print
fit_funct = chebyshev_polynome(n_terms, fit.low_limit, fit.high_limit,
fit.coefs)
y_fitted = fit_funct.f(x_obs)
abs_deviation = flex.max(flex.abs((y_ideal - y_fitted)))
print "Maximum deviation between fitted and error free data:"
print " %4.3f" % (abs_deviation)
abs_deviation = flex.mean(flex.abs((y_ideal - y_fitted)))
print "Mean deviation between fitted and error free data:"
print " %4.3f" % (abs_deviation)
print
abs_deviation = flex.max(flex.abs((y_obs - y_fitted)))
print "Maximum deviation between fitted and observed data:"
print " %4.3f" % (abs_deviation)
abs_deviation = flex.mean(flex.abs((y_obs - y_fitted)))
print "Mean deviation between fitted and observed data:"
print " %4.3f" % (abs_deviation)
print
print "Showing 10 points"
print " x y_obs y_ideal y_fit"
for ii in range(10):
print "%6.3f %6.3f %6.3f %6.3f" \
%(x_obs[ii*9], y_obs[ii*9], y_ideal[ii*9], y_fitted[ii*9])
try:
from iotbx import data_plots
except ImportError:
pass
else:
print "Preparing output for loggraph in a file called"
print " chebyshev.loggraph"
chebyshev_plot = data_plots.plot_data(plot_title='Chebyshev fitting',
x_label='x values',
y_label='y values',
x_data=x_obs,
y_data=y_obs,
y_legend='Observed y values',
comments='Chebyshev fit')
chebyshev_plot.add_data(y_data=y_ideal, y_legend='Error free y values')
chebyshev_plot.add_data(y_data=y_fitted,
y_legend='Fitted chebyshev approximation')
output_logfile = open('chebyshev.loggraph', 'w')
f = StringIO()
data_plots.plot_data_loggraph(chebyshev_plot, f)
output_logfile.write(f.getvalue())
def background(imageset, indx, n_bins):
from dials.array_family import flex
from libtbx.phil import parse
from scitbx import matrix
import math
detector = imageset.get_detector()
beam = imageset.get_beam()
assert(len(detector) == 1)
detector = detector[0]
trusted = detector.get_trusted_range()
n = matrix.col(detector.get_normal()).normalize()
b = matrix.col(beam.get_s0()).normalize()
wavelength = beam.get_wavelength()
if math.fabs(b.dot(n)) < 0.95:
from libtbx.utils import Sorry
raise Sorry('Detector not perpendicular to beam')
data = imageset.get_raw_data(indx)
assert(len(data) == 1)
data = data[0]
negative = (data < 0)
hot = (data > int(round(trusted[1])))
bad = negative | hot
from dials.algorithms.spot_finding.factory import SpotFinderFactory
from dials.algorithms.spot_finding.factory import phil_scope
data = data.as_double()
from dxtbx import datablock
spot_params = phil_scope.fetch(source=parse("")).extract()
threshold_function = SpotFinderFactory.configure_threshold(
spot_params, datablock.DataBlock([imageset]))
peak_pixels = threshold_function.compute_threshold(data, ~bad)
signal = data.select(peak_pixels.iselection())
background = data.select((~bad & ~peak_pixels).iselection())
# print some summary information
print('Mean background: %.3f' % (flex.sum(background) / background.size()))
print('Max/total signal pixels: %.0f / %.0f' % (flex.max(signal),
flex.sum(signal)))
print('Peak/background/hot pixels: %d / %d / %d' % (peak_pixels.count(True),
background.size(),
hot.count(True)))
# compute histogram of two-theta values, then same weighted
# by pixel values, finally divide latter by former to get
# the radial profile out, need to set the number of bins
# sensibly; flex.histogram does not allow weights so use
# numpy.histogram to get the same effect... inspired by
# method in PyFAI
data = data.as_1d()
two_theta_array = detector.get_two_theta_array(beam.get_s0())
two_theta_array.set_selected((bad | peak_pixels).iselection(), 0.0)
data.set_selected((bad | peak_pixels).iselection(), 0.0)
# new fangled flex.weighted_histogram :-)
h0 = flex.weighted_histogram(two_theta_array, n_slots=n_bins)
h1 = flex.weighted_histogram(two_theta_array, data, n_slots=n_bins)
h2 = flex.weighted_histogram(two_theta_array, data * data, n_slots=n_bins)
d0 = h0.slots()
d1 = h1.slots()
d2 = h2.slots()
I = d1 / d0
I2 = d2 / d0
sig = flex.sqrt(I2 - flex.pow2(I))
tt = h0.slot_centers()
d_spacings = wavelength / (2.0 * flex.sin(0.5 * tt))
return d_spacings, I, sig
def example():
x_obs = (flex.double(range(100))+1.0)/101.0
y_ideal = flex.sin(x_obs*6.0*3.1415) + flex.exp(x_obs)
y_obs = y_ideal + (flex.random_double(size=x_obs.size())-0.5)*0.5
w_obs = flex.double(x_obs.size(),1)
print "Trying to determine the best number of terms "
print " via cross validation techniques"
print
n_terms = chebyshev_lsq_fit.cross_validate_to_determine_number_of_terms(
x_obs,y_obs,w_obs,
min_terms=5 ,max_terms=20,
n_goes=20,n_free=20)
print "Fitting with", n_terms, "terms"
print
fit = chebyshev_lsq_fit.chebyshev_lsq_fit(n_terms,x_obs,y_obs)
print "Least Squares residual: %7.6f" %(fit.f)
print " R2-value : %7.6f" %(fit.f/flex.sum(y_obs*y_obs))
print
fit_funct = chebyshev_polynome(
n_terms, fit.low_limit, fit.high_limit, fit.coefs)
y_fitted = fit_funct.f(x_obs)
abs_deviation = flex.max(
flex.abs( (y_ideal- y_fitted) ) )
print "Maximum deviation between fitted and error free data:"
print " %4.3f" %(abs_deviation)
abs_deviation = flex.mean(
flex.abs( (y_ideal- y_fitted) ) )
print "Mean deviation between fitted and error free data:"
print " %4.3f" %(abs_deviation)
print
abs_deviation = flex.max(
flex.abs( (y_obs- y_fitted) ) )
print "Maximum deviation between fitted and observed data:"
print " %4.3f" %(abs_deviation)
abs_deviation = flex.mean(
flex.abs( (y_obs- y_fitted) ) )
print "Mean deviation between fitted and observed data:"
print " %4.3f" %(abs_deviation)
print
print "Showing 10 points"
print " x y_obs y_ideal y_fit"
for ii in range(10):
print "%6.3f %6.3f %6.3f %6.3f" \
%(x_obs[ii*9], y_obs[ii*9], y_ideal[ii*9], y_fitted[ii*9])
try:
from iotbx import data_plots
except ImportError:
pass
else:
print "Preparing output for loggraph in a file called"
print " chebyshev.loggraph"
chebyshev_plot = data_plots.plot_data(plot_title='Chebyshev fitting',
x_label = 'x values',
y_label = 'y values',
x_data = x_obs,
y_data = y_obs,
y_legend = 'Observed y values',
comments = 'Chebyshev fit')
chebyshev_plot.add_data(y_data=y_ideal,
y_legend='Error free y values')
chebyshev_plot.add_data(y_data=y_fitted,
y_legend='Fitted chebyshev approximation')
output_logfile=open('chebyshev.loggraph','w')
f = StringIO()
data_plots.plot_data_loggraph(chebyshev_plot,f)
output_logfile.write(f.getvalue())
def get_sinc(self, q, x ): r = 0.5*(x+1)*self.d_max sinc = flex.sin( r*q )/(r*q) return sinc
def background(imageset, indx, n_bins):
from dials.array_family import flex
from libtbx.phil import parse
from scitbx import matrix
import math
detector = imageset.get_detector()
beam = imageset.get_beam()
assert(len(detector) == 1)
detector = detector[0]
trusted = detector.get_trusted_range()
n = matrix.col(detector.get_normal()).normalize()
b = matrix.col(beam.get_s0()).normalize()
wavelength = beam.get_wavelength()
if math.fabs(b.dot(n)) < 0.95:
from libtbx.utils import Sorry
raise Sorry('Detector not perpendicular to beam')
data = imageset.get_raw_data(indx)
assert(len(data) == 1)
data = data[0]
negative = (data < 0)
hot = (data > int(round(trusted[1])))
bad = negative | hot
from dials.algorithms.spot_finding.factory import SpotFinderFactory
from dials.algorithms.spot_finding.factory import phil_scope
data = data.as_double()
from dxtbx import datablock
spot_params = phil_scope.fetch(source=parse("")).extract()
threshold_function = SpotFinderFactory.configure_threshold(
spot_params, datablock.DataBlock([imageset]))
peak_pixels = threshold_function.compute_threshold(data, ~bad)
signal = data.select(peak_pixels.iselection())
background = data.select((~bad & ~peak_pixels).iselection())
# print some summary information
print 'Mean background: %.3f' % (flex.sum(background) / background.size())
print 'Max/total signal pixels: %.0f / %.0f' % (flex.max(signal),
flex.sum(signal))
print 'Peak/background/hot pixels: %d / %d / %d' % (peak_pixels.count(True),
background.size(),
hot.count(True))
# compute histogram of two-theta values, then same weighted
# by pixel values, finally divide latter by former to get
# the radial profile out, need to set the number of bins
# sensibly; flex.histogram does not allow weights so use
# numpy.histogram to get the same effect... inspired by
# method in PyFAI
data = data.as_1d()
two_theta_array = detector.get_two_theta_array(beam.get_s0())
two_theta_array.set_selected((bad | peak_pixels).iselection(), 0.0)
data.set_selected((bad | peak_pixels).iselection(), 0.0)
# new fangled flex.weighted_histogram :-)
h0 = flex.weighted_histogram(two_theta_array, n_slots=n_bins)
h1 = flex.weighted_histogram(two_theta_array, data, n_slots=n_bins)
h2 = flex.weighted_histogram(two_theta_array, data * data, n_slots=n_bins)
d0 = h0.slots()
d1 = h1.slots()
d2 = h2.slots()
I = d1 / d0
I2 = d2 / d0
sig = flex.sqrt(I2 - flex.pow2(I))
tt = h0.slot_centers()
d_spacings = wavelength / (2.0 * flex.sin(0.5 * tt))
return d_spacings, I, sig
def run (args, image = None):
from xfel import radial_average
from scitbx.array_family import flex
import os, sys
import dxtbx
# Parse input
try:
n = len(args)
except Exception:
params = args
else:
user_phil = []
for arg in args:
if (not "=" in arg):
try :
user_phil.append(libtbx.phil.parse("""file_path=%s""" % arg))
except ValueError:
raise Sorry("Unrecognized argument '%s'" % arg)
else:
try:
user_phil.append(libtbx.phil.parse(arg))
except RuntimeError as e:
raise Sorry("Unrecognized argument '%s' (error: %s)" % (arg, str(e)))
params = master_phil.fetch(sources=user_phil).extract()
if image is None:
if params.file_path is None or len(params.file_path) == 0 or not all([os.path.isfile(f) for f in params.file_path]):
master_phil.show()
raise Usage("file_path must be defined (either file_path=XXX, or the path alone).")
assert params.n_bins is not None
assert params.verbose is not None
assert params.output_bins is not None
# Allow writing to a file instead of stdout
if params.output_file is None:
logger = sys.stdout
else:
logger = open(params.output_file, 'w')
logger.write("%s "%params.output_file)
if params.show_plots:
from matplotlib import pyplot as plt
import numpy as np
colormap = plt.cm.gist_ncar
plt.gca().set_color_cycle([colormap(i) for i in np.linspace(0, 0.9, len(params.file_path))])
if params.mask is not None:
params.mask = easy_pickle.load(params.mask)
if image is None:
iterable = params.file_path
load_func = lambda x: dxtbx.load(x)
else:
iterable = [image]
load_func = lambda x: x
# Iterate over each file provided
for item in iterable:
img = load_func(item)
try:
n_images = img.get_num_images()
subiterable = xrange(n_images)
except AttributeError:
n_images = None
subiterable = [0]
for image_number in subiterable:
if n_images is None:
beam = img.get_beam()
detector = img.get_detector()
else:
beam = img.get_beam(image_number)
detector = img.get_detector(image_number)
s0 = col(beam.get_s0())
# Search the detector for the panel farthest from the beam. The number of bins in the radial average will be
# equal to the farthest point from the beam on the detector, in pixels, unless overridden at the command line
panel_res = [p.get_max_resolution_at_corners(s0) for p in detector]
farthest_panel = detector[panel_res.index(min(panel_res))]
size2, size1 = farthest_panel.get_image_size()
corners = [(0,0), (size1-1,0), (0,size2-1), (size1-1,size2-1)]
corners_lab = [col(farthest_panel.get_pixel_lab_coord(c)) for c in corners]
corner_two_thetas = [farthest_panel.get_two_theta_at_pixel(s0, c) for c in corners]
extent_two_theta = max(corner_two_thetas)
max_corner = corners_lab[corner_two_thetas.index(extent_two_theta)]
extent = int(math.ceil(max_corner.length()*math.sin(extent_two_theta)/max(farthest_panel.get_pixel_size())))
extent_two_theta *= 180/math.pi
if params.n_bins < extent:
params.n_bins = extent
# These arrays will store the radial average info
sums = flex.double(params.n_bins) * 0
sums_sq = flex.double(params.n_bins) * 0
counts = flex.int(params.n_bins) * 0
if n_images is None:
all_data = img.get_raw_data()
else:
all_data = img.get_raw_data(image_number)
if not isinstance(all_data, tuple):
all_data = (all_data,)
for tile, (panel, data) in enumerate(zip(detector, all_data)):
if params.mask is None:
mask = flex.bool(flex.grid(data.focus()), True)
else:
mask = params.mask[tile]
if hasattr(data,"as_double"):
data = data.as_double()
logger.flush()
if params.verbose:
logger.write("Average intensity tile %d: %9.3f\n"%(tile, flex.mean(data)))
logger.write("N bins: %d\n"%params.n_bins)
logger.flush()
x1,y1,x2,y2 = 0,0,panel.get_image_size()[1],panel.get_image_size()[0]
bc = panel.get_beam_centre_px(beam.get_s0())
bc = int(round(bc[1])), int(round(bc[0]))
# compute the average
radial_average(data,mask,bc,sums,sums_sq,counts,panel.get_pixel_size()[0],panel.get_distance(),
(x1,y1),(x2,y2))
# average the results, avoiding division by zero
results = sums.set_selected(counts <= 0, 0)
results /= counts.set_selected(counts <= 0, 1).as_double()
if params.median_filter_size is not None:
logger.write("WARNING, the median filter is not fully propogated to the variances\n")
from scipy.ndimage.filters import median_filter
results = flex.double(median_filter(results.as_numpy_array(), size = params.median_filter_size))
# calculate standard devations
stddev_sel = ((sums_sq-sums*results) >= 0) & (counts > 0)
std_devs = flex.double(len(sums), 0)
std_devs.set_selected(stddev_sel,
(sums_sq.select(stddev_sel)-sums.select(stddev_sel)* \
results.select(stddev_sel))/counts.select(stddev_sel).as_double())
std_devs = flex.sqrt(std_devs)
twotheta = flex.double(xrange(len(results)))*extent_two_theta/params.n_bins
q_vals = 4*math.pi*flex.sin(math.pi*twotheta/360)/beam.get_wavelength()
if params.low_max_two_theta_limit is None:
subset = results
else:
subset = results.select(twotheta >= params.low_max_two_theta_limit)
max_result = flex.max(subset)
if params.x_axis == 'two_theta':
xvals = twotheta
max_x = twotheta[flex.first_index(results, max_result)]
elif params.x_axis == 'q':
xvals = q_vals
max_x = q_vals[flex.first_index(results, max_result)]
for i in xrange(len(results)):
val = xvals[i]
if params.output_bins and "%.3f"%results[i] != "nan":
#logger.write("%9.3f %9.3f\n"% (val,results[i])) #.xy format for Rex.cell.
logger.write("%9.3f %9.3f %9.3f\n"%(val,results[i],std_devs[i])) #.xye format for GSASII
#logger.write("%.3f %.3f %.3f\n"%(val,results[i],ds[i])) # include calculated d spacings
logger.write("Maximum %s: %f, value: %f\n"%(params.x_axis, max_x, max_result))
if params.show_plots:
if params.plot_x_max is not None:
results = results.select(xvals <= params.plot_x_max)
xvals = xvals.select(xvals <= params.plot_x_max)
if params.normalize:
plt.plot(xvals.as_numpy_array(),(results/flex.max(results)).as_numpy_array(),'-')
else:
plt.plot(xvals.as_numpy_array(),results.as_numpy_array(),'-')
if params.x_axis == 'two_theta':
plt.xlabel("2 theta")
elif params.x_axis == 'q':
plt.xlabel("q")
plt.ylabel("Avg ADUs")
if params.plot_y_max is not None:
plt.ylim(0, params.plot_y_max)
if params.show_plots:
#plt.legend([os.path.basename(os.path.splitext(f)[0]) for f in params.file_path], ncol=2)
plt.show()
return xvals, results
def get_goniometer_shadow_masker(self, goniometer=None):
from dials.util.masking import GoniometerShadowMaskGenerator
from scitbx.array_family import flex
import math
coords = flex.vec3_double((
(0,0,0),
))
alpha = flex.double_range(0, 190, step=10) * math.pi / 180
r = flex.double(alpha.size(), 40)
x = flex.double(r.size(), 107.61)
y = -r*flex.sin(alpha)
z = -r*flex.cos(alpha)
coords.extend(flex.vec3_double(x, y, z))
coords.extend(flex.vec3_double((
# fixed
(107.49, 7.84, 39.49),
(107.39, 15.69, 38.97),
(107.27, 23.53, 38.46),
(107.16, 31.37, 37.94),
(101.76, 33.99, 36.25),
(96.37, 36.63, 34.56),
(90.98, 39.25, 33.00),
(85.58, 41.88, 31.18),
(80.89, 47.06, 31.00),
(76.55, 51.51, 31.03),
(72.90, 55.04, 31.18),
(66.86, 60.46, 31.67),
(62.10, 64.41, 32.25),
)))
alpha = flex.double_range(180, 370, step=10) * math.pi / 180
r = flex.double(alpha.size(), 33)
x = (flex.sqrt(flex.pow2(r * flex.sin(alpha)) + 89.02**2) * flex.cos((50 * math.pi/180) - flex.atan(r/89.02 * flex.sin(alpha))))
y = (flex.sqrt(flex.pow2(r * flex.sin(alpha)) + 89.02**2) * flex.sin((50 * math.pi/180) - flex.atan(r/89.02 * flex.sin(alpha))))
z = -r*flex.cos(alpha)
coords.extend(flex.vec3_double(x, y, z))
coords.extend(flex.vec3_double((
# fixed
(62.10, 64.41, -32.25),
(66.86, 60.46, -31.67),
(72.90, 55.04, -31.18),
(76.55, 51.51, -31.03),
(80.89, 47.06, -31.00),
(85.58, 41.88, -31.18),
(90.98, 39.25, -33.00),
(96.37, 36.63, -34.56),
(101.76, 33.99, -36.25),
(107.16, 31.37, -37.94),
(107.27, 23.53, -38.46),
(107.39, 15.69, -38.97),
(107.49, 7.84, -39.49),
(107.61, 0.00, -40.00)
)))
# I23 end station coordinate system:
# X-axis: positive direction is facing away from the storage ring (from
# sample towards goniometer)
# Y-axis: positive direction is vertically up
# Z-axis: positive direction is in the direction of the beam (from
# sample towards detector)
# K-axis (kappa): at an angle of +50 degrees from the X-axis
# K & phi rotation axes: clockwise rotation is positive (right hand
# thumb rule)
# Omega-axis: along the X-axis; clockwise rotation is positive
# End station x-axis is parallel to ImgCIF x-axis
# End station z-axis points in opposite direction to ImgCIF definition
# (ImgCIF: The Z-axis is derived from the source axis which goes from
# the sample to the source)
# Consequently end station y-axis (to complete set following right hand
# rule) points in opposite direction to ImgCIF y-axis.
# Kappa arm aligned with -y in ImgCIF convention
from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame
from scitbx import matrix
R = align_reference_frame(matrix.col((1,0,0)), matrix.col((1,0,0)),
matrix.col((0,1,0)), matrix.col((0,-1,0)))
coords = R.elems * coords
if goniometer is None:
goniometer = self.get_goniometer()
return GoniometerShadowMaskGenerator(
goniometer, coords, flex.size_t(len(coords), 1))
