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 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
# initialize the simulator SIM = SimData() if args.aniso is None: SIM.Umats_method = 2 else: SIM.Umats_method = 3 SIM.detector = DET_gt SIM.crystal = nbcryst SIM.instantiate_diffBragg(oversample=1, verbose=0) SIM.D.refine(eta_diffBragg_id) SIM.D.initialize_managers() SIM.D.spot_scale = 100000 SIM.D.default_F = 0 SIM.D.progress_meter = False SIM.water_path_mm = 0.15 SIM.air_path_mm = 0.1 SIM.add_air = True SIM.add_water = True SIM.include_noise = True SIM.D.use_cuda = args.cuda SIM.D.compute_curvatures = args.curvatures SIM.D.add_diffBragg_spots() if args.aniso is None: deriv = SIM.D.get_derivative_pixels(eta_diffBragg_id).as_numpy_array() else: deriv = SIM.D.get_aniso_eta_deriv_pixels()[args.aniso].as_numpy_array() if args.curvatures: if args.aniso is None:
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 SIM.instantiate_diffBragg(oversample=0, auto_set_spotscale=True) SIM.D.default_F = 0 SIM.D.F000 = 0 SIM.D.progress_meter = False SIM.water_path_mm = 0.005 SIM.air_path_mm = 0.1 SIM.add_air = True SIM.add_Water = True SIM.include_noise = True SIM.D.verbose = 2 SIM.D.add_diffBragg_spots() SIM.D.verbose = 0 spots = SIM.D.raw_pixels.as_numpy_array() SIM._add_background() SIM.D.readout_noise_adu = args.readout SIM._add_noise() # This is the ground truth image: img = SIM.D.raw_pixels.as_numpy_array() if args.plot:
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