C2 = Crystal(a2_real, b2_real, c2_real, symbol)
C2.rotate_around_origin(rot_axis, rot_ang)
assert np.allclose(C2.get_U(), C.get_U())
C2.rotate_around_origin(col(perturb_rot_axis), perturb_rot_ang)
# Setup the simulation and create a realistic image
# with background and noise
# <><><><><><><><><><><><><><><><><><><><><><><><><>
nbcryst = NBcrystal()
nbcryst.dxtbx_crystal = C # simulate ground truth
nbcryst.thick_mm = 0.1
nbcryst.isotropic_ncells = False
if "eta" in args.perturb:
nbcryst.n_mos_domains = 1000
ETA_ABC_GT = args.eta
nbcryst.anisotropic_mos_spread_deg = ETA_ABC_GT
NCELLS_GT = 12, 12, 11
else:
NCELLS_GT = 12, 12, 11
nbcryst.Ncells_abc = NCELLS_GT
SIM = SimData(use_default_crystal=True)
#SIM.detector = SimData.simple_detector(150, 0.1, (513, 512))
if "eta" in args.perturb:
shape = 513 * 3, 512 * 3
#detdist = 70
else:
shape = 513, 512
detdist = 150
SIM.detector = SimData.simple_detector(detdist, 0.1, shape)
SIM.crystal = nbcryst
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
a_real = M * col(a_real)
b_real = M * col(b_real)
c_real = M * col(c_real)
C = Crystal(a_real, b_real, c_real, symbol)
C.rotate_around_origin(rot_axis, rot_ang)
# Setup the simulation and create a realistic image
# with background and noise
# <><><><><><><><><><><><><><><><><><><><><><><><><>
nbcryst = NBcrystal(init_defaults=True)
nbcryst.dxtbx_crystal = C # simulate ground truth
nbcryst.thick_mm = 0.1
nbcryst.Ncells_abc = Ncells_gt # ground truth Ncells
nbcryst.mos_spread_deg = MOS_SPREAD
if args.aniso is not None:
nbcryst.anisotropic_mos_spread_deg = ANISO_MOS_SPREAD
assert nbcryst.has_anisotropic_mosaicity
else:
assert not nbcryst.has_anisotropic_mosaicity
nbcryst.n_mos_domains = N_MOS_DOMAINS
nbcryst.miller_array = miller_array_GT
print("Ground truth ncells = %f" % (nbcryst.Ncells_abc[0]))
# ground truth detector
DET_gt = SimData.simple_detector(150, 0.177, (600, 600))
# initialize the simulator
SIM = SimData()
if args.aniso is None:
SIM.Umats_method = 2
