def get_xray_beams(spectrum, beam):
"""
:param spectrum: list of tuples where one tuple is (wavelength_Angstrom, flux)
:param beam: beam where we derive the s0 vector and polarization and divergence
:return: flex_Beam array to be set as a nanoBragg property
"""
nb = NBbeam()
nb.spectrum = spectrum
nb.polarization_fraction = beam.get_polarization_fraction()
nb.divergence = beam.get_divergence()
nb.unit_s0 = beam.get_unit_s0()
return nb.xray_beams
def flexBeam_sim_colors(CRYSTAL,
DETECTOR,
BEAM,
Famp,
energies,
fluxes,
pids=None,
cuda=False,
oversample=0,
Ncells_abc=(50, 50, 50),
mos_dom=1,
mos_spread=0,
beamsize_mm=0.001,
device_Id=0,
omp=False,
show_params=False,
crystal_size_mm=0.01,
printout_pix=None,
time_panels=True,
verbose=0,
default_F=0,
interpolate=0,
recenter=True,
profile="gauss",
spot_scale_override=None,
background_raw_pixels=None,
include_noise=False,
add_water=False,
add_air=False,
water_path_mm=0.005,
air_path_mm=0,
rois_perpanel=None,
adc_offset=0,
readout_noise=3,
psf_fwhm=0,
gain=1,
mosaicity_random_seeds=None):
"""
:param CRYSTAL: dxtbx Crystal model
:param DETECTOR: dxtbx detector model
:param BEAM: dxtbx beam model
:param Famp: cctbx miller array (amplitudes)
:param energies: list of energies to simulate the scattering
:param fluxes: list of pulse fluences per energy (same length as energies)
:param pids: panel ids to simulate on (None means all panels)
:param cuda: whether to use GPU (only works for nvidia builds)
:param oversample: pixel oversample factor (0 means nanoBragg will decide)
:param Ncells_abc: number of unit cells along each crystal direction in the mosaic block
:param mos_dom: number of mosaic domains in used to sample mosaic spread (texture)
:param mos_spread: mosaicity in degrees (spherical cap width)
:param beamsize_mm: focal size of the beam
:param device_Id: cuda device id (ignore if cuda=False)
:param omp: whether to use open mp (required open MP build configuration)
:param show_params: show the nanoBragg parameters
:param crystal_size_mm: size of the crystal (increases the intensity of the spots)
:param printout_pix: debug pixel position : tuple of (pixel_fast_coord, pixel_slow_coord)
:param time_panels: show timing info
:param verbose: verbosity level for nanoBragg (0-10), 0 is quiet
:param default_F: default amplitude value for nanoBragg
:param interpolate: whether to interpolate for small mosaic domains
:param recenter: recenter for tilted cameras, deprecated
:param profile: profile shape, can be : gauss, round, square, or tophat
:param spot_scale_override: scale the simulated scattering bythis amounth (overrides value based on crystal thickness)
:param background_raw_pixels: dictionary of {panel_id: raw_pixels}, add these background pixels to the simulated Bragg
:param include_noise: add noise to simulated pattern
:param add_water: add water to similated pattern
:param add_air: add ait to simulated pattern
:param water_path_mm: length of water the beam travels through
:param air_path_mm: length of air the beam travels through
:param rois_perpanel: regions of intererest on each panel
:param adc_offset: add this value to each pixel in simulated pattern
:param readout_noise: readout noise level (usually 3-5 ADU)
:param psf_fwhm: point spread kernel FWHM
:param gain: photon gain
:param mosaicity_random_seeds: random seeds to simulating mosaic texture
:return: list of [(panel_id0,simulated pattern0), (panel_id1, simulated_pattern1), ...]
"""
if pids is None:
pids = range(len(DETECTOR))
if background_raw_pixels is None:
background_raw_pixels = {pid: None for pid in pids}
if rois_perpanel is None:
rois_perpanel = {pid: None for pid in pids}
nbBeam = NBbeam()
nbBeam.size_mm = beamsize_mm
nbBeam.unit_s0 = BEAM.get_unit_s0()
wavelengths = ENERGY_CONV / np.array(energies)
nbBeam.spectrum = list(zip(wavelengths, fluxes))
nbCrystal = NBcrystal()
nbCrystal.dxtbx_crystal = CRYSTAL
nbCrystal.miller_array = Famp
nbCrystal.Ncells_abc = Ncells_abc
nbCrystal.symbol = CRYSTAL.get_space_group().info().type().lookup_symbol()
nbCrystal.thick_mm = crystal_size_mm
nbCrystal.xtal_shape = profile
nbCrystal.n_mos_domains = mos_dom
nbCrystal.mos_spread_deg = mos_spread
panel_images = []
tinit = time.time()
S = SimData()
S.detector = DETECTOR
S.beam = nbBeam
S.crystal = nbCrystal
S.using_cuda = cuda
S.using_omp = omp
S.add_air = add_air
S.air_path_mm = air_path_mm
S.add_water = add_water
S.water_path_mm = water_path_mm
S.readout_noise = readout_noise
S.gain = gain
S.psf_fwhm = psf_fwhm
S.include_noise = include_noise
if mosaicity_random_seeds is not None:
S.mosaic_seeds = mosaicity_random_seeds
S.instantiate_nanoBragg(verbose=verbose,
oversample=oversample,
interpolate=interpolate,
device_Id=device_Id,
default_F=default_F,
adc_offset=adc_offset)
if printout_pix is not None:
S.update_nanoBragg_instance("printout_pixel_fastslow", printout_pix)
if spot_scale_override is not None:
S.update_nanoBragg_instance("spot_scale", spot_scale_override)
for pid in pids:
t_panel = time.time()
S.background_raw_pixels = background_raw_pixels[pid]
S.panel_id = pid
S.rois = rois_perpanel[pid]
S.generate_simulated_image()
if show_params:
S.D.show_params()
print('spot scale: %2.7g' % S.D.spot_scale)
panel_image = S.D.raw_pixels.as_numpy_array()
panel_images.append([pid, panel_image])
S.D.raw_pixels *= 0
if time_panels:
tdone = time.time() - tinit
t_panel = time.time() - t_panel
print(
'Panel %d took %.4f seconds (Total sim time = %.4f seconds)' %
(pid, t_panel, tdone))
S.D.free_all()
return panel_images
def diffBragg_forward(CRYSTAL,
DETECTOR,
BEAM,
Famp,
energies,
fluxes,
oversample=0,
Ncells_abc=(50, 50, 50),
mos_dom=1,
mos_spread=0,
beamsize_mm=0.001,
device_Id=0,
show_params=True,
crystal_size_mm=None,
printout_pix=None,
verbose=0,
default_F=0,
interpolate=0,
profile="gauss",
spot_scale_override=None,
mosaicity_random_seeds=None,
nopolar=False,
diffuse_params=None,
cuda=False,
show_timings=False):
if cuda:
os.environ["DIFFBRAGG_USE_CUDA"] = "1"
CRYSTAL, Famp = nanoBragg_utils.ensure_p1(CRYSTAL, Famp)
nbBeam = NBbeam()
nbBeam.size_mm = beamsize_mm
nbBeam.unit_s0 = BEAM.get_unit_s0()
wavelengths = utils.ENERGY_CONV / np.array(energies)
nbBeam.spectrum = list(zip(wavelengths, fluxes))
nbCrystal = NBcrystal(init_defaults=False)
nbCrystal.isotropic_ncells = False
nbCrystal.dxtbx_crystal = CRYSTAL
nbCrystal.miller_array = Famp
nbCrystal.Ncells_abc = Ncells_abc
nbCrystal.symbol = CRYSTAL.get_space_group().info().type().lookup_symbol()
nbCrystal.thick_mm = crystal_size_mm
nbCrystal.xtal_shape = profile
nbCrystal.n_mos_domains = mos_dom
nbCrystal.mos_spread_deg = mos_spread
S = SimData()
S.detector = DETECTOR
npan = len(DETECTOR)
nfast, nslow = DETECTOR[0].get_image_size()
img_shape = npan, nslow, nfast
S.beam = nbBeam
S.crystal = nbCrystal
if mosaicity_random_seeds is not None:
S.mosaic_seeds = mosaicity_random_seeds
S.instantiate_diffBragg(verbose=verbose,
oversample=oversample,
interpolate=interpolate,
device_Id=device_Id,
default_F=default_F,
auto_set_spotscale=crystal_size_mm is not None
and spot_scale_override is None)
if spot_scale_override is not None:
S.update_nanoBragg_instance("spot_scale", spot_scale_override)
S.update_nanoBragg_instance("nopolar", nopolar)
if show_params:
S.D.show_params()
print("Spot scale=%f" % S.D.spot_scale)
if show_timings and verbose < 2:
S.D.verbose = 2
S.D.record_time = True
if diffuse_params is not None:
S.D.use_diffuse = True
S.D.gamma_miller_units = diffuse_params["gamma_miller_units"]
S.D.diffuse_gamma = diffuse_params["gamma"]
S.D.diffuse_sigma = diffuse_params["sigma"]
S.D.add_diffBragg_spots_full()
if show_timings:
S.D.show_timings()
t = time.time()
data = S.D.raw_pixels_roi.as_numpy_array().reshape(img_shape)
t = time.time() - t
if show_timings:
print("Took %f sec to recast and reshape" % t)
if printout_pix is not None:
S.D.raw_pixels_roi *= 0
p, f, s = printout_pix
S.D.printout_pixel_fastslow = f, s
S.D.show_params()
S.D.add_diffBragg_spots(printout_pix)
# free up memory
S.D.free_all()
S.D.free_Fhkl2()
if S.D.gpu_free is not None:
S.D.gpu_free()
return data
def multipanel_sim(
CRYSTAL, DETECTOR, BEAM, Famp, energies, fluxes,
background_wavelengths=None, background_wavelength_weights=None,
background_total_flux=None, background_sample_thick_mm=None,
density_gcm3=1, molecular_weight=18,
cuda=False, oversample=0, Ncells_abc=(50, 50, 50),
mos_dom=1, mos_spread=0, mosaic_method="double_uniform",
mos_aniso=None, beamsize_mm=0.001,
crystal_size_mm=0.01,
verbose=0, default_F=0, interpolate=0, profile="gauss",
spot_scale_override=None, show_params=False, time_panels=False,
add_water = False, add_air=False, water_path_mm=0.005, air_path_mm=0,
adc_offset=0, readout_noise=3, psf_fwhm=0, gain=1, mosaicity_random_seeds=None,
include_background=True, mask_file="",skip_numpy=False,relevant_whitelist_order=None):
from simtbx.nanoBragg.nanoBragg_beam import NBbeam
from simtbx.nanoBragg.nanoBragg_crystal import NBcrystal
from simtbx.nanoBragg.sim_data import SimData
from simtbx.nanoBragg.utils import get_xray_beams
from scitbx.array_family import flex
from scipy import constants
import numpy as np
ENERGY_CONV = 10000000000.0 * constants.c * constants.h / constants.electron_volt
assert cuda # disallow the default
nbBeam = NBbeam()
nbBeam.size_mm = beamsize_mm
nbBeam.unit_s0 = BEAM.get_unit_s0()
wavelengths = ENERGY_CONV / np.array(energies)
nbBeam.spectrum = list(zip(wavelengths, fluxes))
nbCrystal = NBcrystal(False)
nbCrystal.dxtbx_crystal = CRYSTAL
#nbCrystal.miller_array = None # use the gpu_channels_singleton mechanism instead
nbCrystal.Ncells_abc = Ncells_abc
nbCrystal.symbol = CRYSTAL.get_space_group().info().type().lookup_symbol()
nbCrystal.thick_mm = crystal_size_mm
nbCrystal.xtal_shape = profile
nbCrystal.n_mos_domains = mos_dom
nbCrystal.mos_spread_deg = mos_spread
nbCrystal.anisotropic_mos_spread_deg = mos_aniso
pid = 0 # remove the loop, use C++ iteration over detector panels
use_exascale_api = True
if use_exascale_api:
S = SimData(use_default_crystal = False)
S.detector = DETECTOR
S.beam = nbBeam
S.crystal = nbCrystal
S.panel_id = pid
S.add_air = add_air
S.air_path_mm = air_path_mm
S.add_water = add_water
S.water_path_mm = water_path_mm
S.readout_noise = readout_noise
S.gain = gain
S.psf_fwhm = psf_fwhm
S.include_noise = False
S.Umats_method = dict(double_random=0, double_uniform=5)[mosaic_method]
if mosaicity_random_seeds is not None:
S.mosaic_seeds = mosaicity_random_seeds
S.instantiate_nanoBragg(verbose=verbose, oversample=oversample, interpolate=interpolate,
device_Id=Famp.get_deviceID(),default_F=default_F, adc_offset=adc_offset)
SIM = S.D # the nanoBragg instance
assert Famp.get_deviceID()==SIM.device_Id
if spot_scale_override is not None:
SIM.spot_scale = spot_scale_override
assert Famp.get_nchannels() == 1 # non-anomalous scenario
from simtbx.gpu import exascale_api
gpu_simulation = exascale_api(nanoBragg = SIM)
gpu_simulation.allocate() # presumably done once for each image
from simtbx.gpu import gpu_detector as gpud
gpu_detector = gpud(deviceId=SIM.device_Id, detector=DETECTOR,
beam=BEAM)
gpu_detector.each_image_allocate()
# revisit the allocate cuda for overlap with detector, sync up please
x = 0 # only one energy channel
if mask_file is "": # all-pixel kernel
P = Profiler("%40s"%"from gpu amplitudes cuda")
gpu_simulation.add_energy_channel_from_gpu_amplitudes(
x, Famp, gpu_detector)
elif type(mask_file) is flex.bool: # 1D bool array, flattened from ipanel, islow, ifast
P = Profiler("%40s"%"from gpu amplitudes cuda with bool mask")
gpu_simulation.add_energy_channel_mask_allpanel(
channel_number = x, gpu_amplitudes = Famp, gpu_detector = gpu_detector,
pixel_active_mask_bools = mask_file )
elif type(mask_file) is flex.int:
# precalculated active_pixel_list
P = Profiler("%40s"%"from gpu amplitudes cuda w/int whitelist")
gpu_simulation.add_energy_channel_mask_allpanel(
channel_number = x, gpu_amplitudes = Famp, gpu_detector = gpu_detector,
pixel_active_list_ints = mask_file )
else:
assert type(mask_file) is str
from LS49.adse13_187.adse13_221.mask_utils import mask_from_file
boolean_mask = mask_from_file(mask_file)
P = Profiler("%40s"%"from gpu amplitudes cuda with file mask")
gpu_simulation.add_energy_channel_mask_allpanel(
x, Famp, gpu_detector, boolean_mask )
TIME_BRAGG = time()-P.start_el
per_image_scale_factor = 1.
gpu_detector.scale_in_place(per_image_scale_factor) # apply scale directly on GPU
if include_background:
t_bkgrd_start = time()
SIM.beamsize_mm = beamsize_mm
wavelength_weights = np.array(background_wavelength_weights)
weights = wavelength_weights / wavelength_weights.sum() * background_total_flux
spectrum = list(zip(background_wavelengths, weights))
xray_beams = get_xray_beams(spectrum, BEAM)
SIM.xray_beams = xray_beams
SIM.Fbg_vs_stol = water
SIM.flux=sum(weights)
SIM.amorphous_sample_thick_mm = background_sample_thick_mm
SIM.amorphous_density_gcm3 = density_gcm3
SIM.amorphous_molecular_weight_Da = molecular_weight
gpu_simulation.add_background(gpu_detector)
TIME_BG = time()-t_bkgrd_start
else: TIME_BG=0.
if skip_numpy:
P = Profiler("%40s"%"get short whitelist values")
whitelist_only = gpu_detector.get_whitelist_raw_pixels(relevant_whitelist_order)
# whitelist_only, flex_double pixel values
# relevant_whitelist_order, flex.size_t detector addresses
assert len(whitelist_only) == len(relevant_whitelist_order) # guard against shoebox overlap bug
# when shoeboxes overlap, the overlapped pixels should be simulated once for each parent shoebox
P = Profiler("%40s"%"each image free cuda")
gpu_detector.each_image_free()
return whitelist_only, TIME_BG, TIME_BRAGG, S.exascale_mos_blocks or None
packed_numpy = gpu_detector.get_raw_pixels()
gpu_detector.each_image_free()
return packed_numpy.as_numpy_array(), TIME_BG, TIME_BRAGG, S.exascale_mos_blocks or None
def flexBeam_sim_colors(CRYSTAL,
DETECTOR,
BEAM,
Famp,
energies,
fluxes,
pids=None,
cuda=False,
oversample=0,
Ncells_abc=(50, 50, 50),
mos_dom=1,
mos_spread=0,
beamsize_mm=0.001,
device_Id=0,
omp=False,
show_params=False,
crystal_size_mm=0.01,
printout_pix=None,
time_panels=True,
verbose=0,
default_F=0,
interpolate=0,
recenter=True,
profile="gauss",
spot_scale_override=None,
background_raw_pixels=None,
include_noise=False,
add_water=False,
add_air=False,
water_path_mm=0.005,
air_path_mm=0,
rois_perpanel=None,
adc_offset=0,
readout_noise=3,
psf_fwhm=0,
gain=1,
mosaicity_random_seeds=None):
if pids is None:
pids = range(len(DETECTOR))
if background_raw_pixels is None:
background_raw_pixels = {pid: None for pid in pids}
if rois_perpanel is None:
rois_perpanel = {pid: None for pid in pids}
nbBeam = NBbeam()
nbBeam.size_mm = beamsize_mm
nbBeam.unit_s0 = BEAM.get_unit_s0()
wavelengths = ENERGY_CONV / np.array(energies)
nbBeam.spectrum = list(zip(wavelengths, fluxes))
nbCrystal = NBcrystal()
nbCrystal.dxtbx_crystal = CRYSTAL
nbCrystal.miller_array = Famp
nbCrystal.Ncells_abc = Ncells_abc
nbCrystal.symbol = CRYSTAL.get_space_group().info().type().lookup_symbol()
nbCrystal.thick_mm = crystal_size_mm
nbCrystal.xtal_shape = profile
nbCrystal.n_mos_domains = mos_dom
nbCrystal.mos_spread_deg = mos_spread
panel_images = []
for pid in pids:
tinit = time.time()
S = SimData()
S.detector = DETECTOR
S.beam = nbBeam
S.crystal = nbCrystal
S.panel_id = pid
S.using_cuda = cuda
S.using_omp = omp
S.add_air = add_air
S.air_path_mm = air_path_mm
S.add_water = add_water
S.water_path_mm = water_path_mm
S.background_raw_pixels = background_raw_pixels[pid]
S.rois = rois_perpanel[pid]
S.readout_noise = readout_noise
S.gain = gain
S.psf_fwhm = psf_fwhm
S.include_noise = include_noise
if mosaicity_random_seeds is not None:
S.mosaic_seeds = mosaicity_random_seeds
S.instantiate_nanoBragg(verbose=verbose,
oversample=oversample,
interpolate=interpolate,
device_Id=device_Id,
default_F=default_F,
adc_offset=adc_offset)
if recenter:
S.update_nanoBragg_instance(
"beam_center_mm",
DETECTOR[int(pid)].get_beam_centre(BEAM.get_s0()))
if printout_pix is not None:
S.update_nanoBragg_instance("printout_pixel_fastslow",
printout_pix)
if spot_scale_override is not None:
S.update_nanoBragg_instance("spot_scale", spot_scale_override)
S.generate_simulated_image()
if show_params:
S.D.show_params()
print('spot scale: %2.7g' % S.D.spot_scale)
panel_image = S.D.raw_pixels.as_numpy_array()
panel_images.append([pid, panel_image])
S.D.free_all()
if time_panels:
tdone = time.time() - tinit
print('Panel %d took %.4f seconds' % (pid, tdone))
del S.D
return panel_images