def test_cbf_writer(image_file, dials_regression, run_in_tmpdir):
filename = os.path.join(dials_regression, image_file)
datablock = DataBlockFactory.from_filenames([filename])[0]
imageset = datablock.extract_imagesets()[0]
FormatCBFMini.as_file(
imageset.get_detector(),
imageset.get_beam(),
imageset.get_goniometer(),
imageset.get_scan(),
imageset.get_raw_data(0)[0],
"image_0001.cbf",
)
assert datablock.format_class()
datablock2 = DataBlockFactory.from_filenames(["image_0001.cbf"])[0]
imageset2 = datablock2.extract_imagesets()[0]
tolerance = tolerance_phil_scope.extract().tolerance
diff = SweepDiff(tolerance)
print("\n".join(diff(imageset, imageset2)))
assert BeamComparison()(imageset.get_beam(), imageset2.get_beam())
assert DetectorComparison(origin_tolerance=tolerance.detector.origin)(
imageset.get_detector(), imageset2.get_detector())
assert GoniometerComparison()(imageset.get_goniometer(),
imageset2.get_goniometer())
s1 = imageset.get_scan()
s2 = imageset.get_scan()
assert s1.get_exposure_times() == s2.get_exposure_times()
assert s1.get_oscillation() == s2.get_oscillation()
assert s1.get_image_range() == s2.get_image_range()
assert imageset.get_raw_data(0) == imageset2.get_raw_data(0)
def make_images(data, tag):
pixel_size = 0.1 # mm/pixel
detector = DetectorFactory.simple(
'PAD', 100,
(pixel_size * data.focus()[1] / 2, pixel_size * data.focus()[2] / 2),
'+x', '-y', (pixel_size, pixel_size),
(data.focus()[2], data.focus()[1]), (-1, 1e6 - 1), [], None)
beam = BeamFactory.simple(1.0)
sf = ScanFactory()
scan = sf.make_scan(image_range=(1, 180),
exposure_times=0.1,
oscillation=(0, 1.0),
epochs=range(180),
deg=True)
# write images in each of three directions
for slice_id in [0, 1, 2]:
for idx in xrange(data.focus()[slice_id]):
if slice_id == 0: # slow
data_slice = data[idx:idx + 1, :, :]
data_slice.reshape(flex.grid(data.focus()[1], data.focus()[2]))
filename = "fft_frame_%s_mf_%04d.cbf" % (tag, idx)
elif slice_id == 1: # med
data_slice = data[:, idx:idx + 1, :]
data_slice.reshape(flex.grid(data.focus()[0], data.focus()[2]))
filename = "fft_frame_%s_sf_%04d.cbf" % (tag, idx)
elif slice_id == 2: # fast
data_slice = data[:, :, idx:idx + 1]
data_slice.reshape(flex.grid(data.focus()[0], data.focus()[1]))
filename = "fft_frame_%s_sm_%04d.cbf" % (tag, idx)
print['slow', 'med', 'fast'][slice_id], idx
FormatCBFMini.as_file(detector, beam, None, scan, data_slice,
filename)
def make_images(data, tag):
pixel_size = 0.1
detector = DetectorFactory.simple(
'PAD', 100,
(pixel_size * data.focus()[1] / 2, pixel_size * data.focus()[2] / 2),
'+x', '-y', (pixel_size, pixel_size),
(data.focus()[2], data.focus()[1]), (-1, 1e6 - 1), [], None)
beam = BeamFactory.simple(1.0)
for slice_id in [0, 1, 2]:
for idx in xrange(data.focus()[slice_id]):
if slice_id == 0: # slow
data_slice = data[idx:idx + 1, :, :]
data_slice.reshape(flex.grid(data.focus()[1], data.focus()[2]))
filename = "fft_frame_%s_mf_%04d.cbf" % (tag, idx)
elif slice_id == 1: # med
data_slice = data[:, idx:idx + 1, :]
data_slice.reshape(flex.grid(data.focus()[0], data.focus()[2]))
filename = "fft_frame_%s_sf_%04d.cbf" % (tag, idx)
elif slice_id == 2: # fast
data_slice = data[:, :, idx:idx + 1]
data_slice.reshape(flex.grid(data.focus()[0], data.focus()[1]))
filename = "fft_frame_%s_sm_%04d.cbf" % (tag, idx)
print['slow', 'med', 'fast'][slice_id], idx
FormatCBFMini.as_file(detector, beam, None, None, data_slice,
filename)
def _start(self):
FormatCBFMini._start(self)
self._array_size = (
int(self._cif_header_dictionary["X-Binary-Size-Fastest-Dimension"]
),
int(self._cif_header_dictionary["X-Binary-Size-Second-Dimension"]),
)
def _start(self):
FormatCBFMini._start(self)
try:
from iotbx.detectors.pilatus_minicbf import PilatusImage
self.detectorbase = PilatusImage(self._image_file)
self.detectorbase.readHeader()
except KeyError, e:
pass
def _start(self):
FormatCBFMini._start(self)
try:
from iotbx.detectors.adsc_minicbf import ADSCHF4MImage
self.detectorbase = ADSCHF4MImage(self._image_file)
self.detectorbase.readHeader()
except KeyError, e:
pass
def __init__(self, image_file, **kwargs):
'''Initialise the image structure from the given file, including a
proper model of the experiment.'''
assert(self.understand(image_file))
FormatCBFMini.__init__(self, image_file, **kwargs)
return
def __init__(self, image_file):
'''Initialise the image structure from the given file, including a
proper model of the experiment.'''
assert(self.understand(image_file))
FormatCBFMini.__init__(self, image_file)
return
def as_file(detector,
beam,
gonio,
scan,
data,
path,
header_convention="PILATUS_1.2",
det_type="PILATUS3 6M"):
FormatCBFMini.as_file(detector, beam, gonio, scan, data, path,
header_convention, det_type)
def __init__(self, image_file, **kwargs):
"""Initialise the image structure from the given file, including a
proper model of the experiment."""
from dxtbx import IncorrectFormatError
if not self.understand(image_file):
raise IncorrectFormatError(self, image_file)
FormatCBFMini.__init__(self, image_file, **kwargs)
def convert_to_cbf(imageset, template):
from dxtbx.format.FormatCBFMini import FormatCBFMini
for i in range(len(imageset)):
print(template % (i + 1))
FormatCBFMini.as_file(
imageset.get_detector(),
imageset.get_beam(),
imageset.get_goniometer(),
imageset.get_scan()[i],
imageset.get_raw_data(i)[0],
template % (i + 1),
)
def understand(image_file):
'''Check to see if this looks like an Pilatus mini CBF format image,
i.e. we can make sense of it.'''
if 'ENABLE_PHOTON_FACTORY_TWO_EIGER' in os.environ:
return False
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split('\n'):
if '# Detector' in record and \
'EIGER' in record.upper():
return False
for record in header.split('\n'):
if '_array_data.header_convention' in record and \
'PILATUS' in record:
return True
if '_array_data.header_convention' in record and \
'SLS' in record:
return True
if '_array_data.header_convention' in record and \
'?' in record:
return True
if '# Detector' in record and \
'PILATUS' in record: #CBFlib v0.8.0 allowed
return True
return False
def understand(image_file):
'''Check to see if this looks like an Pilatus mini CBF format image,
i.e. we can make sense of it.'''
if 'ENABLE_PHOTON_FACTORY_TWO_EIGER' in os.environ:
return False
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split('\n'):
if '# Detector' in record and \
'EIGER' in record.upper():
return False
for record in header.split('\n'):
if '_array_data.header_convention' in record and \
'PILATUS' in record:
return True
if '_array_data.header_convention' in record and \
'SLS' in record:
return True
if '_array_data.header_convention' in record and \
'?' in record:
return True
if '# Detector' in record and \
'PILATUS' in record: #CBFlib v0.8.0 allowed
return True
return False
def understand(image_file):
"""Check to see if this looks like an Pilatus mini CBF format image,
i.e. we can make sense of it."""
if "ENABLE_PHOTON_FACTORY_TWO_EIGER" in os.environ:
return False
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split("\n"):
if "# Detector" in record:
if "EIGER" in record.upper():
return False
if "TIMEPIX" in record.upper():
return False
for record in header.split("\n"):
if "_array_data.header_convention" in record and "PILATUS" in record:
return True
if "_array_data.header_convention" in record and "SLS" in record:
return True
if "_array_data.header_convention" in record and "?" in record:
return True
if "# Detector" in record and "PILATUS" in record: # CBFlib v0.8.0 allowed
return True
return False
def remove_bragg_peaks(self, reference=None, write_lunus=None):
start_cpu = time.clock()
start_real = time.time()
image = LunusDIFFIMAGE()
image.set_image(self.raw_data)
print 'Removing beamstop shadow from image'
image.LunusPunchim(self.punchim_xmin, self.punchim_ymin, self.punchim_xmax, self.punchim_ymax)
print 'Cleaning up edge of image'
image.LunusWindim(self.windim_xmin, self.windim_ymin, self.windim_xmax, self.windim_ymax)
print "Setting detection threshold"
image.LunusThrshim(self.thrshim_min, self.thrshim_max)
print "Removing Bragg peaks from image"
image.LunusModeim(self.mode_filter_footprint)
print "Mode filter finished."
print "Correcting for beam polarization"
image.LunusPolarim(self.beam_center_mm_x, self.beam_center_mm_y, self.detector_distance, self.polarization_fraction, self.polarization_offset, self.pixel_size)
print "Solid-angle normalization of image"
image.LunusNormim(self.beam_center_mm_x, self.beam_center_mm_y, self.detector_distance, self.cassette_x, self.cassette_y, self.pixel_size)
self.lunus_data_scitbx = image.get_image();
self.radial_avg = image.LunusRadialAvgim(self.beam_center_mm_x, self.beam_center_mm_y, self.pixel_size)
self.lunus_data = self.lunus_data_scitbx.as_numpy_array()
print("shape of lunus data at step 1: {}".format(self.lunus_data.shape))
end_cpu = time.clock()
end_real = time.time()
print("%f Real Seconds" % (end_real - start_real))
print("%f CPU seconds" % (end_cpu - start_cpu))
### write files, if desired
if write_lunus:
FormatCBFMini.as_file(self.detector,self.beam,self.gonio,self.scan,self.lunus_data_scitbx,self.lunus)
else:
pass
if reference:
np.savez("reference_radial_average", rad=self.radial_avg)
else:
pass
return
def _detector(self):
'''Return a model for a simple detector, presuming no one has
one of these on a two-theta stage. Assert that the beam centre is
provided in the Mosflm coordinate frame.'''
detector = FormatCBFMini._detector(self)
for f0, s0, f1, s1 in determine_pilatus_mask(detector):
detector[0].add_mask(f0, s0, f1, s1)
return detector
def understand(image_file):
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split("\n"):
if "# Detector" in record and "ADSC" in record and "HF-4M" in header:
return True
if "_array_data.header_convention" in record and "ADSC" in record:
return True
return False
def understand(image_file):
"""Check to see if this looks like an Eiger mini CBF format image,
i.e. we can make sense of it."""
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split("\n"):
if "# detector" in record.lower() and "eiger" in record.lower():
return True
return False
def understand(image_file):
'''Check to see if this looks like an Eiger mini CBF format image,
i.e. we can make sense of it.'''
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split('\n'):
if '# Detector' in record and \
'EIGER' in record:
return True
return False
def understand(image_file):
'''Check to see if this looks like an Eiger mini CBF format image,
i.e. we can make sense of it.'''
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split('\n'):
if '# detector' in record.lower() and \
'eiger' in record.lower():
return True
return False
def understand(image_file):
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split('\n'):
if '# Detector' in record and \
'ADSC' in record and 'HF-4M' in header:
return True
if '_array_data.header_convention' in record and \
'ADSC' in record:
return True
return False
def understand(image_file):
header = FormatCBFMini.get_cbf_header(image_file)
for record in header.split('\n'):
if '# Detector' in record and \
'ADSC' in record and 'HF-4M' in header:
return True
if '_array_data.header_convention' in record and \
'ADSC' in record:
return True
return False
def understand(image_file):
"""Check to see if this looks like a Timepix mini CBF format image,
i.e. we can make sense of it."""
header = FormatCBFMini.get_cbf_header(image_file)
# Look for 'TIMEPIX' string. The headers also contain 'S/N 24-0109-F'
# but this may not be trustworthy and anyway we want to recognise all
# Timepix CBFs here
for record in header.split("\n"):
if "# Detector" in record and "TIMEPIX" in record:
return True
return False
def understand(image_file):
"""Check to see if this looks like a Timepix mini CBF format image,
i.e. we can make sense of it."""
mime_header = ""
in_binary_format_section = False
for record in FormatCBFMini.open_file(image_file, "rb"):
if "--CIF-BINARY-FORMAT-SECTION--" in record:
in_binary_format_section = True
elif in_binary_format_section and record[0] == "X":
mime_header += record
if in_binary_format_section and len(record.strip()) == 0:
# http://sourceforge.net/apps/trac/cbflib/wiki/ARRAY_DATA%20Category
# In an imgCIF file, the encoded binary data begins after
# the empty line terminating the header.
break
# Look for 1032 pixels
for record in mime_header.split("\n"):
if ("-Binary-Size-Fastest-Dimension:" in record
and int(record.split()[1]) == 1032):
return True
return False
def process_one_glob():
from dxtbx.imageset import ImageSetFactory
from dxtbx.model.experiment_list import Experiment, ExperimentList
from dxtbx.serialize import dump
imnum = 1
metrolist = glob.glob(metro_glob)
metrolist.sort()
filelist = glob.glob(image_glob)
filelist.sort()
if (rotation_series):
experiments = ExperimentListFactory.from_json_file(metrolist[0],
check_format=False)
x = get_experiment_xvectors(experiments)
npx = np.asarray(x)
Isize1, Isize2 = experiments[0].detector[0].get_image_size()
# cf = correction_factor(Isize1,Isize2,experiments,x[0])
for i in range(len(filelist)):
print("{0}...".format(i), )
sys.stdout.flush()
if (not rotation_series):
experiments = ExperimentListFactory.from_json_file(
metrolist[i], check_format=False)
x = get_experiment_xvectors(experiments)
npx = np.asarray(x)
imgname = filelist[i]
img = dxtbx.load(imgname)
# data = img.get_raw_data()
# print "min of data = ",flex.min(data)
# print "max of data = ",flex.max(data)
beam = img.get_beam()
detector = img.get_detector()
crystal = copy.deepcopy(experiments.crystals()[0])
scan = img.get_scan()
start_angle, delta_angle = scan.get_oscillation()
gonio = img.get_goniometer()
axis = gonio.get_rotation_axis()
pixel_values = flex.int(range(Isize1 * Isize2))
pixel_values.reshape(flex.grid(Isize2, Isize1))
if (rotation_series):
crystal.rotate_around_origin(axis,
start_angle + (delta_angle / 2),
deg=True)
from scitbx import matrix
A_matrix = matrix.sqr(crystal.get_A()).inverse()
diffim = procimg_single(Isize1, Isize2, scale, lattice_mask_tag,
A_matrix, npx[0], experiments, D)
# Apply correction factor for polarization and solid angle
# Scale pixel values
dmin = np.amin(diffim)
print("dmin = ", dmin)
# s = 256./(dmax-dmin)
for i in range(len(diffim)):
for j in range(len(diffim[i])):
if (diffim[i][j] != image_mask_tag):
diffim[i][j] = diffim[i][j] * scale
if (shift_min):
for i in range(len(diffim)):
for j in range(len(diffim[i])):
if (diffim[i][j] != image_mask_tag):
diffim[i][j] -= dmin * scale
# diffim *= scale
int_mask_tag = int(image_mask_tag)
for j in range(Isize2):
for i in range(Isize1):
pixel_values[j, i] = np.int(diffim[i, j])
if (pixel_values[j, i] == int_mask_tag):
pixel_values[j, i] = -1
outname = prefout + "_%05d.cbf" % (imnum)
FormatCBFMini.as_file(detector, beam, gonio, scan, pixel_values,
outname)
imnum = imnum + 1
print()
def _start(self):
FormatCBFMini._start(self)
scan = img.get_scan() A = LunusDIFFIMAGE() data = img.get_raw_data() A.set_image(data) deck = ''' #lunus input deck punchim_xmin=1203 punchim_ymin=1250 punchim_xmax=2459 punchim_ymax=1314 windim_xmin=100 windim_ymin=100 windim_xmax=2362 windim_ymax=2426 thrshim_min=0 thrshim_max=50 modeim_bin_size=1 modeim_kernel_width=20 ''' A.LunusSetparamsim(deck) A.LunusPunchim() A.LunusWindim() A.LunusThrshim() A.LunusModeim() print "Mode filter finished." data2 = A.get_image(); #dxtbx.format.FormatCBFMini.FormatCBFMini.as_file(detector,beam,gonio,scan,data,path,header_convention="GENERIC_MINI",det_type="GENERIC") FormatCBFMini.as_file(detector,beam,gonio,scan,data2,"g150aich_274_6_1_lunus_00001.cbf")
A = LunusDIFFIMAGE() data = img.get_raw_data() print data[0] A.set_image(data) deck = ''' #lunus input deck punchim_xmin=1203 punchim_ymin=1250 punchim_xmax=2459 punchim_ymax=1314 windim_xmin=100 windim_ymin=100 windim_xmax=2362 windim_ymax=2426 thrshim_min=0 thrshim_max=50 modeim_bin_size=1 modeim_kernel_width=20 ''' A.LunusSetparamsim(deck) A.LunusPunchim() A.LunusWindim() A.LunusThrshim() A.LunusModeim() print "Mode filter finished." data2 = A.get_image() #dxtbx.format.FormatCBFMini.FormatCBFMini.as_file(detector,beam,gonio,scan,data,path,header_convention="GENERIC_MINI",det_type="GENERIC") FormatCBFMini.as_file(detector, beam, gonio, scan, data2, out_name)
def run_sim2smv(fileout):
SIM = nanoBragg(detpixels_slowfast=(1000, 1000),
pixel_size_mm=0.1,
Ncells_abc=(5, 5, 5),
verbose=9)
import sys
if len(sys.argv) > 2:
SIM.seed = -int(sys.argv[2])
print "GOTHERE seed=", SIM.seed
if len(sys.argv) > 1:
if sys.argv[1] == "random": SIM.randomize_orientation()
SIM.distance_mm = 100
#SIM = nanoBragg(detpixels_slowfast=(2527,2463),pixel_size_mm=0.172,Ncells_abc=(5,5,5),verbose=9)
#SIM.distance_mm=200
# get same noise each time this test is run
SIM.seed = 1
SIM.oversample = 1
SIM.wavelength_A = 1
SIM.polarization = 1
#SIM.unit_cell_tuple=(50,50,50,90,90,90)
print "unit_cell_Adeg=", SIM.unit_cell_Adeg
print "unit_cell_tuple=", SIM.unit_cell_tuple
# this will become F000, marking the beam center
SIM.default_F = 100
#SIM.missets_deg= (10,20,30)
print "mosaic_seed=", SIM.mosaic_seed
print "seed=", SIM.seed
print "calib_seed=", SIM.calib_seed
print "missets_deg =", SIM.missets_deg
sfall = fcalc_from_pdb(resolution=1.6,
algorithm="direct",
wavelength=SIM.wavelength_A)
# use crystal structure to initialize Fhkl array
SIM.Fhkl = sfall
# fastest option, least realistic
SIM.xtal_shape = shapetype.Tophat
# only really useful for long runs
SIM.progress_meter = False
# prints out value of one pixel only. will not render full image!
#SIM.printout_pixel_fastslow=(500,500)
#SIM.printout=True
SIM.show_params()
# flux is always in photons/s
SIM.flux = 1e12
# assumes round beam
SIM.beamsize_mm = 0.1
SIM.exposure_s = 0.1
temp = SIM.Ncells_abc
print "Ncells_abc=", SIM.Ncells_abc
SIM.Ncells_abc = temp
print "Ncells_abc=", SIM.Ncells_abc
print "xtal_size_mm=", SIM.xtal_size_mm
print "unit_cell_Adeg=", SIM.unit_cell_Adeg
print "unit_cell_tuple=", SIM.unit_cell_tuple
print "missets_deg=", SIM.missets_deg
print "Amatrix=", SIM.Amatrix
print "beam_center_mm=", SIM.beam_center_mm
print "XDS_ORGXY=", SIM.XDS_ORGXY
print "detector_pivot=", SIM.detector_pivot
print "xtal_shape=", SIM.xtal_shape
print "beamcenter_convention=", SIM.beamcenter_convention
print "fdet_vector=", SIM.fdet_vector
print "sdet_vector=", SIM.sdet_vector
print "odet_vector=", SIM.odet_vector
print "beam_vector=", SIM.beam_vector
print "polar_vector=", SIM.polar_vector
print "spindle_axis=", SIM.spindle_axis
print "twotheta_axis=", SIM.twotheta_axis
print "distance_meters=", SIM.distance_meters
print "distance_mm=", SIM.distance_mm
print "close_distance_mm=", SIM.close_distance_mm
print "detector_twotheta_deg=", SIM.detector_twotheta_deg
print "detsize_fastslow_mm=", SIM.detsize_fastslow_mm
print "detpixels_fastslow=", SIM.detpixels_fastslow
print "detector_rot_deg=", SIM.detector_rot_deg
print "curved_detector=", SIM.curved_detector
print "pixel_size_mm=", SIM.pixel_size_mm
print "point_pixel=", SIM.point_pixel
print "polarization=", SIM.polarization
print "nopolar=", SIM.nopolar
print "oversample=", SIM.oversample
print "region_of_interest=", SIM.region_of_interest
print "wavelength_A=", SIM.wavelength_A
print "energy_eV=", SIM.energy_eV
print "fluence=", SIM.fluence
print "flux=", SIM.flux
print "exposure_s=", SIM.exposure_s
print "beamsize_mm=", SIM.beamsize_mm
print "dispersion_pct=", SIM.dispersion_pct
print "dispsteps=", SIM.dispsteps
print "divergence_hv_mrad=", SIM.divergence_hv_mrad
print "divsteps_hv=", SIM.divsteps_hv
print "divstep_hv_mrad=", SIM.divstep_hv_mrad
print "round_div=", SIM.round_div
print "phi_deg=", SIM.phi_deg
print "osc_deg=", SIM.osc_deg
print "phisteps=", SIM.phisteps
print "phistep_deg=", SIM.phistep_deg
print "detector_thick_mm=", SIM.detector_thick_mm
print "detector_thicksteps=", SIM.detector_thicksteps
print "detector_thickstep_mm=", SIM.detector_thickstep_mm
print "mosaic_spread_deg=", SIM.mosaic_spread_deg
print "mosaic_domains=", SIM.mosaic_domains
print "indices=", SIM.indices
print "amplitudes=", SIM.amplitudes
print "Fhkl_tuple=", SIM.Fhkl_tuple
print "default_F=", SIM.default_F
print "interpolate=", SIM.interpolate
print "integral_form=", SIM.integral_form
# now actually burn up some CPU
SIM.add_nanoBragg_spots()
# simulated crystal is only 125 unit cells (25 nm wide)
# amplify spot signal to simulate physical crystal of 4000x larger: 100 um (64e9 x the volume)
SIM.raw_pixels *= 64e9
SIM.to_smv_format(fileout="intimage_001.img")
# rough approximation to water: interpolation points for sin(theta/lambda) vs structure factor
bg = flex.vec2_double([(0, 2.57), (0.0365, 2.58), (0.07, 2.8), (0.12, 5),
(0.162, 8), (0.2, 6.75),
(0.18, 7.32), (0.216, 6.75), (0.236, 6.5),
(0.28, 4.5), (0.3, 4.3), (0.345, 4.36),
(0.436, 3.77), (0.5, 3.17)])
SIM.Fbg_vs_stol = bg
SIM.amorphous_sample_thick_mm = 0.1
SIM.amorphous_density_gcm3 = 1
SIM.amorphous_molecular_weight_Da = 18
SIM.flux = 1e12
SIM.beamsize_mm = 0.1
SIM.exposure_s = 0.1
SIM.add_background()
SIM.to_smv_format(fileout="intimage_002.img")
# rough approximation to air
bg = flex.vec2_double([(0, 14.1), (0.045, 13.5), (0.174, 8.35),
(0.35, 4.78), (0.5, 4.22)])
SIM.Fbg_vs_stol = bg
SIM.amorphous_sample_thick_mm = 35 # between beamstop and collimator
SIM.amorphous_density_gcm3 = 1.2e-3
SIM.amorphous_sample_molecular_weight_Da = 28 # nitrogen = N2
print "amorphous_sample_size_mm=", SIM.amorphous_sample_size_mm
print "amorphous_sample_thick_mm=", SIM.amorphous_sample_thick_mm
print "amorphous_density_gcm3=", SIM.amorphous_density_gcm3
print "amorphous_molecular_weight_Da=", SIM.amorphous_molecular_weight_Da
SIM.add_background()
# set this to 0 or -1 to trigger automatic radius. could be very slow with bright images
SIM.detector_psf_kernel_radius_pixels = 5
SIM.detector_psf_fwhm_mm = 0.08
SIM.detector_psf_type = shapetype.Fiber
#SIM.apply_psf()
print SIM.raw_pixels[500000]
SIM.to_smv_format(fileout="intimage_003.img")
#SIM.detector_psf_fwhm_mm=0
print "quantum_gain=", SIM.quantum_gain
print "adc_offset_adu=", SIM.adc_offset_adu
print "detector_calibration_noise_pct=", SIM.detector_calibration_noise_pct
print "flicker_noise_pct=", SIM.flicker_noise_pct
print "readout_noise_adu=", SIM.readout_noise_adu
print "detector_psf_type=", SIM.detector_psf_type
print "detector_psf_fwhm_mm=", SIM.detector_psf_fwhm_mm
print "detector_psf_kernel_radius_pixels=", SIM.detector_psf_kernel_radius_pixels
SIM.add_noise()
#fileout = "intimage_001.img"
print "raw_pixels=", SIM.raw_pixels
SIM.to_smv_format(fileout="noiseimage_001.img", intfile_scale=1)
# try to write as CBF
import dxtbx
from dxtbx.format.FormatCBFMini import FormatCBFMini
img = dxtbx.load("noiseimage_001.img")
print img
FormatCBFMini.as_file(detector=img.get_detector(),
beam=img.get_beam(),
gonio=img.get_goniometer(),
scan=img.get_scan(),
data=img.get_raw_data(),
path=fileout)
SIM.free_all()
def _start(self): FormatCBFMini._start(self)
def _detector(self):
"""Return a model for a simple detector, presuming no one has
one of these on a two-theta stage. Assert that the beam centre is
provided in the Mosflm coordinate frame."""
if not self._multi_panel:
detector = FormatCBFMini._detector(self)
for f0, f1, s0, s1 in determine_pilatus_mask(detector):
detector[0].add_mask(f0 - 1, s0 - 1, f1, s1)
return detector
# got to here means 60-panel version
d = Detector()
distance = float(
self._cif_header_dictionary["Detector_distance"].split()[0])
beam_xy = (self._cif_header_dictionary["Beam_xy"].replace(
"(", "").replace(")", "").replace(",", "").split()[:2])
beam_x, beam_y = map(float, beam_xy)
wavelength = float(
self._cif_header_dictionary["Wavelength"].split()[0])
pixel_xy = (self._cif_header_dictionary["Pixel_size"].replace(
"m", "").replace("x", "").split())
pixel_x, pixel_y = map(float, pixel_xy)
thickness = float(
self._cif_header_dictionary["Silicon"].split()[2]) * 1000.0
nx = int(
self._cif_header_dictionary["X-Binary-Size-Fastest-Dimension"])
ny = int(self._cif_header_dictionary["X-Binary-Size-Second-Dimension"])
overload = int(self._cif_header_dictionary["Count_cutoff"].split()[0])
underload = -1
# take into consideration here the thickness of the sensor also the
# wavelength of the radiation (which we have in the same file...)
table = attenuation_coefficient.get_table("Si")
mu = table.mu_at_angstrom(wavelength) / 10.0
t0 = thickness
# FIXME would also be very nice to be able to take into account the
# misalignment of the individual modules given the calibration...
# single detector or multi-module detector
pixel_x *= 1000.0
pixel_y *= 1000.0
distance *= 1000.0
beam_centre = matrix.col((beam_x * pixel_x, beam_y * pixel_y, 0))
fast = matrix.col((1.0, 0.0, 0.0))
slow = matrix.col((0.0, -1.0, 0.0))
s0 = matrix.col((0, 0, -1))
origin = (distance * s0) - (fast * beam_centre[0]) - (slow *
beam_centre[1])
root = d.hierarchy()
root.set_local_frame(fast.elems, slow.elems, origin.elems)
det = _DetectorDatabase["Pilatus"]
# Edge dead areas not included, only gaps between modules matter
n_fast, remainder = divmod(nx, det.module_size_fast)
assert (n_fast - 1) * det.gap_fast == remainder
n_slow, remainder = divmod(ny, det.module_size_slow)
assert (n_slow - 1) * det.gap_slow == remainder
mx = det.module_size_fast
my = det.module_size_slow
dx = det.gap_fast
dy = det.gap_slow
xmins = [(mx + dx) * i for i in range(n_fast)]
xmaxes = [mx + (mx + dx) * i for i in range(n_fast)]
ymins = [(my + dy) * i for i in range(n_slow)]
ymaxes = [my + (my + dy) * i for i in range(n_slow)]
self.coords = {}
fast = matrix.col((1.0, 0.0, 0.0))
slow = matrix.col((0.0, 1.0, 0.0))
panel_idx = 0
for ymin, ymax in zip(ymins, ymaxes):
for xmin, xmax in zip(xmins, xmaxes):
xmin_mm = xmin * pixel_x
ymin_mm = ymin * pixel_y
origin_panel = fast * xmin_mm + slow * ymin_mm
panel_name = "Panel%d" % panel_idx
panel_idx += 1
p = d.add_panel()
p.set_type("SENSOR_PAD")
p.set_name(panel_name)
p.set_raw_image_offset((xmin, ymin))
p.set_image_size((xmax - xmin, ymax - ymin))
p.set_trusted_range((underload, overload))
p.set_pixel_size((pixel_x, pixel_y))
p.set_thickness(thickness)
p.set_material("Si")
p.set_mu(mu)
p.set_px_mm_strategy(ParallaxCorrectedPxMmStrategy(mu, t0))
p.set_local_frame(fast.elems, slow.elems, origin_panel.elems)
p.set_raw_image_offset((xmin, ymin))
self.coords[panel_name] = (xmin, ymin, xmax, ymax)
return d