def imgCIF(cif_file, sensor):
'''Initialize a detector model from an imgCIF file.'''
cbf_handle = pycbf.cbf_handle_struct()
cbf_handle.read_file(cif_file, pycbf.MSG_DIGEST)
cbf_detector = cbf_handle.construct_detector(0)
pixel = (cbf_detector.get_inferred_pixel_size(1),
cbf_detector.get_inferred_pixel_size(2))
# FIXME can probably simplify the code which follows below by
# making proper use of cctbx vector calls - should not be as
# complex as it appears to be...
origin = tuple(cbf_detector.get_pixel_coordinates(0, 0))
fast = cbf_detector.get_pixel_coordinates(0, 1)
slow = cbf_detector.get_pixel_coordinates(1, 0)
dfast = [fast[j] - origin[j] for j in range(3)]
dslow = [slow[j] - origin[j] for j in range(3)]
lfast = math.sqrt(sum([dfast[j] * dfast[j] for j in range(3)]))
lslow = math.sqrt(sum([dslow[j] * dslow[j] for j in range(3)]))
fast = tuple([dfast[j] / lfast for j in range(3)])
slow = tuple([dslow[j] / lslow for j in range(3)])
size = tuple(reversed(cbf_handle.get_image_size(0)))
try:
underload = find_undefined_value(cbf_handle)
overload = cbf_handle.get_overload(0) * dxtbx_overload_scale
trusted_range = (underload, overload)
except: # intentional
trusted_range = (0.0, 0.0)
cbf_detector.__swig_destroy__(cbf_detector)
del(cbf_detector)
# Get the sensor type
dtype = detector_factory.sensor(sensor)
# If the sensor type is PAD then create the detector with a
# parallax corrected pixel to millimeter function
#if dtype == detector_helper_sensors.SENSOR_PAD:
#px_mm = ParallaxCorrectedPxMmStrategy(0.252500934883)
#else:
px_mm = SimplePxMmStrategy()
return detector_factory.make_detector(
dtype, fast, slow, origin, pixel, size,
trusted_range, px_mm)
def imgCIF(cif_file, sensor):
'''Initialize a detector model from an imgCIF file.'''
cbf_handle = pycbf.cbf_handle_struct()
cbf_handle.read_file(cif_file, pycbf.MSG_DIGEST)
cbf_detector = cbf_handle.construct_detector(0)
pixel = (cbf_detector.get_inferred_pixel_size(1),
cbf_detector.get_inferred_pixel_size(2))
# FIXME can probably simplify the code which follows below by
# making proper use of cctbx vector calls - should not be as
# complex as it appears to be...
origin = tuple(cbf_detector.get_pixel_coordinates(0, 0))
fast = cbf_detector.get_pixel_coordinates(0, 1)
slow = cbf_detector.get_pixel_coordinates(1, 0)
dfast = [fast[j] - origin[j] for j in range(3)]
dslow = [slow[j] - origin[j] for j in range(3)]
lfast = math.sqrt(sum([dfast[j] * dfast[j] for j in range(3)]))
lslow = math.sqrt(sum([dslow[j] * dslow[j] for j in range(3)]))
fast = tuple([dfast[j] / lfast for j in range(3)])
slow = tuple([dslow[j] / lslow for j in range(3)])
size = tuple(reversed(cbf_handle.get_image_size(0)))
try:
underload = find_undefined_value(cbf_handle)
overload = cbf_handle.get_overload(0) * dxtbx_overload_scale
trusted_range = (underload, overload)
except: # intentional
trusted_range = (0.0, 0.0)
cbf_detector.__swig_destroy__(cbf_detector)
del (cbf_detector)
# Get the sensor type
dtype = detector_factory.sensor(sensor)
# If the sensor type is PAD then create the detector with a
# parallax corrected pixel to millimeter function
#if dtype == detector_helper_sensors.SENSOR_PAD:
#px_mm = ParallaxCorrectedPxMmStrategy(0.252500934883)
#else:
px_mm = SimplePxMmStrategy()
return detector_factory.make_detector(dtype, fast, slow, origin, pixel,
size, trusted_range, px_mm)
def imgCIF_H(cbf_handle, sensor):
'''Initialize a detector model from an imgCIF file handle, where it
is assumed that the file has already been read.'''
cbf_detector = cbf_handle.construct_detector(0)
pixel = (cbf_detector.get_inferred_pixel_size(1),
cbf_detector.get_inferred_pixel_size(2))
# FIXME can probably simplify the code which follows below by
# making proper use of cctbx vector calls - should not be as
# complex as it appears to be...
origin = tuple(cbf_detector.get_pixel_coordinates(0, 0))
fast = cbf_detector.get_pixel_coordinates(0, 1)
slow = cbf_detector.get_pixel_coordinates(1, 0)
dfast = [fast[j] - origin[j] for j in range(3)]
dslow = [slow[j] - origin[j] for j in range(3)]
lfast = math.sqrt(sum([dfast[j] * dfast[j] for j in range(3)]))
lslow = math.sqrt(sum([dslow[j] * dslow[j] for j in range(3)]))
fast = tuple([dfast[j] / lfast for j in range(3)])
slow = tuple([dslow[j] / lslow for j in range(3)])
size = tuple(reversed(cbf_handle.get_image_size(0)))
try:
underload = find_undefined_value(cbf_handle)
overload = cbf_handle.get_overload(0)
trusted_range = (underload, overload * dxtbx_overload_scale)
except: # intentional
trusted_range = (0.0, 0.0)
cbf_detector.__swig_destroy__(cbf_detector)
del(cbf_detector)
return detector_factory.make_detector(
detector_factory.sensor(sensor),
fast, slow, origin, pixel, size, trusted_range)
def imgCIF_H(cbf_handle, sensor):
'''Initialize a detector model from an imgCIF file handle, where it
is assumed that the file has already been read.'''
cbf_detector = cbf_handle.construct_detector(0)
pixel = (cbf_detector.get_inferred_pixel_size(1),
cbf_detector.get_inferred_pixel_size(2))
# FIXME can probably simplify the code which follows below by
# making proper use of cctbx vector calls - should not be as
# complex as it appears to be...
origin = tuple(cbf_detector.get_pixel_coordinates(0, 0))
fast = cbf_detector.get_pixel_coordinates(0, 1)
slow = cbf_detector.get_pixel_coordinates(1, 0)
dfast = [fast[j] - origin[j] for j in range(3)]
dslow = [slow[j] - origin[j] for j in range(3)]
lfast = math.sqrt(sum([dfast[j] * dfast[j] for j in range(3)]))
lslow = math.sqrt(sum([dslow[j] * dslow[j] for j in range(3)]))
fast = tuple([dfast[j] / lfast for j in range(3)])
slow = tuple([dslow[j] / lslow for j in range(3)])
size = tuple(reversed(cbf_handle.get_image_size(0)))
try:
underload = find_undefined_value(cbf_handle)
overload = cbf_handle.get_overload(0)
trusted_range = (underload, overload * dxtbx_overload_scale)
except: # intentional
trusted_range = (0.0, 0.0)
cbf_detector.__swig_destroy__(cbf_detector)
del (cbf_detector)
return detector_factory.make_detector(detector_factory.sensor(sensor),
fast, slow, origin, pixel, size,
trusted_range)
