def _detector(self):
"""
Create the detector model
"""
from scitbx import matrix
from dxtbx.model.detector import DetectorFactory
configuration = self.header["configuration"]
info = self.header["info"]
# from pprint import pprint
# pprint(configuration)
# Set the trusted range
# trusted_range = 0, configuration['countrate_correction_count_cutoff']
trusted_range = 0, 2**configuration["bit_depth_readout"] - 1
# Get the sensor material and thickness
sensor_material = str(configuration["sensor_material"])
sensor_thickness = configuration["sensor_thickness"]
beam_center = configuration["beam_center_x"], configuration[
"beam_center_y"]
distance = configuration["detector_distance"]
# Get the pixel and image sizes
pixel_size = (configuration["x_pixel_size"],
configuration["y_pixel_size"])
# Image size is not x/y_pixels_in_detector, which are likely the physical dimensions
image_size = (info["shape"][0], info["shape"][1])
# Get the detector axes
# TODO Spec doesn't have detector_orientation
# TODO THIS NEEDS FIXING
# fast_axis = (1, 0, 0)
# slow_axis = (0, 1, 0)
# origin = (0, 0, -1)
fast_axis = configuration["detector_orientation"][0:3]
slow_axis = configuration["detector_orientation"][3:6]
origin = matrix.col(
configuration["detector_translation"]) + matrix.col(
(0, 0, -distance))
# Create the detector model
return DetectorFactory.make_detector(
"SENSOR_PAD",
fast_axis,
slow_axis,
origin,
pixel_size,
image_size,
trusted_range,
px_mm=None,
name="Panel",
thickness=sensor_thickness,
material=sensor_material,
mu=0.0,
)
def simple_detector(detector_distance_mm, pixelsize_mm, image_shape, fast=(1, 0, 0), slow=(0, -1, 0)):
from dxtbx.model.detector import DetectorFactory
import numpy as np
trusted_range = (0, 200000000000000.0)
detsize_s = image_shape[0] * pixelsize_mm
detsize_f = image_shape[1] * pixelsize_mm
cent_s = (detsize_s + pixelsize_mm * 2) / 2.0
cent_f = (detsize_f + pixelsize_mm * 2) / 2.0
beam_axis = np.cross(fast, slow)
origin = -np.array(fast) * cent_f - np.array(slow) * cent_s + beam_axis * detector_distance_mm
return DetectorFactory.make_detector('', fast, slow, origin, (
pixelsize_mm, pixelsize_mm), image_shape, trusted_range)
def _detector(self):
'''
Create the detector model
'''
from scitbx import matrix
from dxtbx.model.detector import DetectorFactory
configuration = self.header['configuration']
# Set the trusted range
trusted_range = 0, configuration['countrate_correction_count_cutoff']
# Get the sensor material and thickness
sensor_material = str(configuration['sensor_material'])
sensor_thickness = configuration['sensor_thickness']
beam_center = configuration['beam_center_x'], configuration[
'beam_center_y']
distance = configuration['detector_distance']
# Get the pixel and image sizes
pixel_size = (configuration['x_pixel_size'],
configuration['y_pixel_size'])
image_size = (configuration['x_pixels_in_detector'],
configuration['y_pixels_in_detector'])
# Get the detector axes
# TODO Spec doesn't have detector_orientation
# TODO THIS NEEDS FIXING
fast_axis = (1, 0, 0)
slow_axis = (0, 1, 0)
origin = (0, 0, -1)
# fast_axis = configuration['detector_orientation'][0:3]
# slow_axis = configuration['detector_orientation'][3:6]
#origin = matrix.col(configuration['detector_translation']) + matrix.col((0,0,-distance))
# Create the detector model
return DetectorFactory.make_detector('SENSOR_PAD',
fast_axis,
slow_axis,
origin,
pixel_size,
image_size,
trusted_range,
px_mm=None,
name='Panel',
thickness=sensor_thickness,
material=sensor_material,
mu=0.0)
def _detector(self):
"""
Create the detector model
"""
configuration = self.header["configuration"]
info = self.header["info"]
# from pprint import pprint
# pprint(configuration)
# Set the trusted range
trusted_range = 0, 2**configuration["bit_depth_readout"] - 1
# Get the sensor material and thickness
sensor_material = str(configuration["sensor_material"])
sensor_thickness = configuration["sensor_thickness"]
distance = configuration["detector_distance"]
# Get the pixel and image sizes
pixel_size = (configuration["x_pixel_size"],
configuration["y_pixel_size"])
# Image size is not x/y_pixels_in_detector, which are likely the physical dimensions
image_size = (info["shape"][0], info["shape"][1])
# Get the detector axes
fast_axis = configuration["detector_orientation"][0:3]
slow_axis = configuration["detector_orientation"][3:6]
origin = matrix.col(
configuration["detector_translation"]) + matrix.col(
(0, 0, -distance))
# Create the detector model
return DetectorFactory.make_detector(
"SENSOR_PAD",
fast_axis,
slow_axis,
origin,
pixel_size,
image_size,
trusted_range,
px_mm=None,
name="Panel",
thickness=sensor_thickness,
material=sensor_material,
mu=0.0,
)
# ------------------------
if lab_geom == "canonical":
s = 1 # scale factor, divide pixel size by this factor
pixsize = .10992/s # mm
detdist = 125 # mm
wavelen = 1.385
orig = col((-s*1536*pixsize/2.,
s*1536*pixsize/2.,
-detdist))
# Initialise detector frame
fast = col((1.0, 0.0, 0.0))
slow = col((0.0, -1.0, 0.0))
det = DetectorFactory.make_detector(
"", fast, slow, orig,
(pixsize, pixsize), (s*1536,s*1536)) #, trusted_range=(0, 10000000))
beam_descr = {
'direction': (7.010833160725592e-06, -3.710515413340211e-06, 0.9999999999685403),
'divergence': 0.0,
'flux': 0.0,
'polarization_fraction': 0.999,
'polarization_normal': (0.0, 1.0, 0.0),
'sigma_divergence': 0.0,
'transmission': 1.0,
'wavelength': 1.385}
#beam = BeamFactory.simple(wavelen)
beam = BeamFactory.from_dict(beam_descr)
elif lab_geom == "cspad":
det = DetectorFactory.from_dict(dxtbx_cspad.cspad)