import os import galsim import numpy as np from astropy.io import fits from ObservationSim.Instrument.Chip import ChipUtils as chip_utils from ObservationSim.Instrument.Chip import Effects def add_prescan_overscan(self, chip, filt, tel, pointing, catalog, obs_param): self.chip_output.Log_info("Apply pre/over-scan") chip.img = chip_utils.AddPreScan(GSImage=chip.img, pre1=chip.prescan_x, pre2=chip.prescan_y, over1=chip.overscan_x, over2=chip.overscan_y) if obs_param["poisson_and_dark"]["add_dark"] == True: ny = int(chip.npix_y/2) base_dark = (ny-1)*(chip.readout_time/ny)*chip.dark_noise chip.img.array[(chip.prescan_y+ny):-(chip.prescan_y+ny),:] = bese_dark return chip, filt, tel, pointing def add_readout_noise(self, chip, filt, tel, pointing, catalog, obs_param): seed = int(self.overall_config["random_seeds"]["seed_readout"]) + pointing.id*30 + chip.chipID rng_readout = galsim.BaseDeviate(seed) readout_noise = galsim.GaussianNoise(rng=rng_readout, sigma=chip.read_noise) chip.img.addNoise(readout_noise) return chip, filt, tel, pointing def apply_gain(self, chip, filt, tel, pointing, catalog, obs_param): self.chip_output.Log_info(" Applying Gain") if obs_param["gain_16channel"] == True: chip.img, chip.gain_channel = Effects.ApplyGainNonUniform16(chip.img, gain=chip.gain, nsecy = chip.nsecy, nsecx=chip.nsecx, seed=self.overall_config["random_seeds"]["seed_gainNonUniform"]+chip.chipID) elif obs_param["gain_16channel"] == False: chip.img /= chip.gain return chip, filt, tel, pointing def quantization_and_output(self, chip, filt, tel, pointing, catalog, obs_param): if not hasattr(self, 'h_ext'): _, _ = self.prepare_headers(chip=chip, pointing=pointing) self.updateHeaderInfo(header_flag='ext', keys = ['SHTSTAT','SHTOPEN0','SHTOPEN1','SHTCLOS0','SHTCLOS1'], values = [False,'','','','']) if obs_param["format_output"] == True: self.chip_output.Log_info(" Apply 1*16 format") chip.img = chip_utils.formatOutput(GSImage=chip.img) chip.nsecy = 1 chip.nsecx = 16 chip.img.array[chip.img.array > 65535] = 65535 chip.img.replaceNegative(replace_value=0) chip.img.quantize() chip.img = galsim.Image(chip.img.array, dtype=np.uint16) fname = os.path.join(self.chip_output.subdir, self.h_prim['FILENAME'] + '.fits') f_name_size = 68 if(len(self.h_prim['FILENAME'])>f_name_size): self.updateHeaderInfo(header_flag='prim', keys = ['FILENAME'], values = [self.h_prim['FILENAME'][0:f_name_size]]) hdu1 = fits.PrimaryHDU(header=self.h_prim) hdu1.add_checksum() hdu1.header.comments['CHECKSUM'] = 'HDU checksum' hdu1.header.comments['DATASUM'] = 'data unit checksum' self.updateHeaderInfo(header_flag='ext', keys = ['DATASECT'], values = [str(chip.img.array.shape[1])+'x'+str(chip.img.array.shape[0])]) hdu2 = fits.ImageHDU(chip.img.array, header=self.h_ext) hdu2.add_checksum() hdu2.header.comments['XTENSION'] = 'extension type' hdu2.header.comments['CHECKSUM'] = 'HDU checksum' hdu2.header.comments['DATASUM'] = 'data unit checksum' hdu2.header.comments["XTENSION"] = "image extension" hdu1 = fits.HDUList([hdu1, hdu2]) hdu1.writeto(fname, output_verify='ignore', overwrite=True) return chip, filt, tel, pointing