def main(): path_gamma = get_astri_2019("d2019-05-15_simulations/gamma_1deg.h5") path_proton = get_astri_2019("d2019-05-15_simulations/proton.h5") base_output = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gamma1deg") n_off = 1 process(path_gamma, path_proton, base_output, n_off) path_gamma = get_astri_2019("d2019-05-15_simulations/gamma_1deg.h5") path_proton = get_astri_2019("d2019-05-15_simulations/proton.h5") base_output = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gamma1deg_5off" ) n_off = 5 process(path_gamma, path_proton, base_output, n_off) path_gamma = get_astri_2019("d2019-05-15_simulations/gamma_0deg.h5") path_proton = get_astri_2019("d2019-05-15_simulations/proton.h5") base_output = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gamma0deg") n_off = 1 process(path_gamma, path_proton, base_output, n_off) path_gamma = get_astri_2019("d2019-05-15_simulations/gamma_1deg.h5") path_proton = path_gamma base_output = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gammaonly") n_off = 1 process_gamma_only(path_gamma, base_output, n_off)
def process_file(file): name = file.__class__.__name__ amplitude_path = get_data("d190117_trigger_stability/{}/amplitudes.h5".format(name)) hv_path = get_data("d190117_trigger_stability/{}/hv.h5".format(name)) output_dir = get_plot("d190117_trigger_stability/amp_vs_hv/{}".format(name)) spoi = file.spoi process(amplitude_path, hv_path, output_dir, spoi)
def main(): paths = dict( self=get_data("d191118_pedestal_temperature/d191118/residuals_self.h5"), single_31degree=get_data("d191118_pedestal_temperature/d191118/residuals_single_30.h5"), lookup=get_data("d191118_pedestal_temperature/d191118/residuals_lookup.h5"), interp=get_data("d191118_pedestal_temperature/d191118/residuals_interp.h5"), pchip=get_data("d191118_pedestal_temperature/d191118/residuals_pchip.h5"), ) p_hist = dict() for label, path in paths.items(): with HDF5Reader(path) as reader: df = reader.read("data") df = df.set_index("temperature_r0_primary").sort_index() for temperature, row in df.iterrows(): hist = row['hist'] edges = row['edges'] mean = row['mean'] std = row['std'] if temperature not in p_hist: p_hist[temperature] = HistPlot() p_hist[temperature].ax.set_title(f"TM Primary Temperature = {temperature:.2f} °C") p_hist[temperature].plot(hist, edges, mean, std, label) for temperature, plot in p_hist.items(): plot.save(get_plot(f"d191118_pedestal_temperature/d191118/hist/T{temperature:.2f}.pdf"))
def main(): path_ac_23 = get_data( "d191122_dc_tf/ac_tf/TFInput_File_SN0038_temp_23_180317.tcal") path_ac_cc_23 = get_data("d191122_dc_tf/ac_tf/ac_23deg_tf.h5") path_dc_ext23 = get_data( "d191122_dc_tf/dc_tf/dc_externalsync_23deg_tf.tcal") path_vped_23 = get_data("d191122_dc_tf/vped/VPED_23deg.h5") path_pedestal_23 = get_checs( "d181203_erlangen/pedestal/Pedestal_23deg_ped.tcal") tf_ac_23 = get_ac_tf(path_ac_23) tf_ac_cc_23 = get_ac_cc_tf(path_ac_cc_23) tf_dc_ext23 = get_dc_tf(path_dc_ext23, path_vped_23) pedestal_23 = get_pedestal(path_pedestal_23) # r0_paths = glob(get_checs("d181203_erlangen/dynrange/23deg/r0/Amplitude_*_Run_0_r0.tio")) # output_path = get_data("d191122_dc_tf/charge/dc_externalsync_23deg_charge.h5") # process(r0_paths, pedestal_23, tf_dc_ext23, output_path) # # r0_paths = glob(get_checs("d181203_erlangen/dynrange/23deg/r0/Amplitude_*_Run_0_r0.tio")) # output_path = get_data("d191122_dc_tf/charge/ac_23deg_charge.h5") # process(r0_paths, pedestal_23, tf_ac_23, output_path) r0_paths = glob( get_checs( "d181203_erlangen/dynrange/23deg/r0/Amplitude_*_Run_0_r0.tio")) output_path = get_data("d191122_dc_tf/charge/ac_cc_23deg_charge.h5") process(r0_paths, pedestal_23, tf_ac_cc_23, output_path)
def main(): input_path = get_data("d191122_dc_tf/vped/VPED_13deg.h5") output_path = get_plot("d191122_dc_tf/vped/VPED_13deg.pdf") process(input_path, output_path) input_path = get_data("d191122_dc_tf/vped/VPED_23deg.h5") output_path = get_plot("d191122_dc_tf/vped/VPED_23deg.pdf") process(input_path, output_path) input_path = get_data("d191122_dc_tf/vped/VPED_33deg.h5") output_path = get_plot("d191122_dc_tf/vped/VPED_33deg.pdf") process(input_path, output_path) input_path = get_data("d191122_dc_tf/vped/VPED_43deg.h5") output_path = get_plot("d191122_dc_tf/vped/VPED_43deg.pdf") process(input_path, output_path) input_path = get_data("d191122_dc_tf/vped/VPED_23deg.h5") output_path = get_plot("d191122_dc_tf/vped/VPED_23deg_sc.pdf") process_single_channel(input_path, 8, output_path) input_paths = [ get_data("d191122_dc_tf/vped/VPED_13deg.h5"), get_data("d191122_dc_tf/vped/VPED_23deg.h5"), get_data("d191122_dc_tf/vped/VPED_33deg.h5"), get_data("d191122_dc_tf/vped/VPED_43deg.h5"), ] output_path = get_plot("d191122_dc_tf/vped/temperature_comparison.pdf") process_different_temps(input_paths, 8, output_path) input_path = get_data("d191122_dc_tf/vped/VPED_23deg.h5") mean_path = get_plot("d191122_dc_tf/vped/VPED_23deg_mean.pdf") std_path = get_plot("d191122_dc_tf/vped/VPED_23deg_std.pdf") process_mean_std(input_path, mean_path, std_path)
def main(): # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/before_25deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp35/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/before_35deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp35_440pF_2/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_440pF/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/after_35deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) # # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_440pF/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_440pF/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/after_25deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_440pF_3/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_440pF_3/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/after_25deg_3.h5") # process(tf_r0_paths, pedestal_path, tf_path) # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp35_440pF_3/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_440pF_3/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/after_35deg_3.h5") # process(tf_r0_paths, pedestal_path, tf_path) # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_100pF/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_100pF/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/100pF_25deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) # # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp35_100pF/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_100pF/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/100pF_35deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) # tf_r0_paths = glob("/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_100_pF_1k/*.tio") # pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_100pF/VPED_1095_ped.tcal" # tf_path = get_data("d191128_pedestal_lab/dc_tf/100pF_1k_25deg.h5") # process(tf_r0_paths, pedestal_path, tf_path) tf_r0_paths = glob( "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_200_pF/*.tio" ) pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_200_pF/VPED_1095_ped.tcal" tf_path = get_data("d191128_pedestal_lab/dc_tf/200pF_25deg.h5") process(tf_r0_paths, pedestal_path, tf_path) tf_r0_paths = glob( "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp35_200_pF/*.tio" ) pedestal_path = "/Users/Jason/Downloads/tempdata/d191128_pedestal_lab/dc_tf_tm_temp25_200_pF/VPED_1095_ped.tcal" tf_path = get_data("d191128_pedestal_lab/dc_tf/200pF_35deg.h5") process(tf_r0_paths, pedestal_path, tf_path)
def main(): input_path = "/Users/Jason/Software/TargetCalib/source/dev/mapping_checs_V1-1-0.cfg" output_path = get_data("d181105_sim_telarray_cfg/tc_mapping.cfg") create_new_mapping(input_path, output_path) input_path = get_data("d181105_sim_telarray_cfg/tc_mapping.cfg") output_path = get_data("d181105_sim_telarray_cfg/pixel_mapping.dat") create_new_camera_cfg(input_path, output_path)
def __init__(self): self.pde_x, self.pde_y = np.loadtxt( get_data('charge_resolution/pe_to_photons/PDE.csv'), unpack=True, delimiter=', ') self.crosstalk_x, self.crosstalk_y = np.loadtxt( get_data('charge_resolution/pe_to_photons/crosstalk.csv'), unpack=True, delimiter=', ')
def __init__(self, **kwargs): super().__init__(**kwargs) self.dl1_path = "/Volumes/gct-jason/sim_telarray/d180907_illumination_profile/Run43489_dl1.h5" self.illumination_profile_path = get_data( "d181021_charge_resolution/illumination_profile/d180907_MC.h5") self.plot_dir = get_plot( "d181021_charge_resolution/illumination_profile/d180907_MC") self.angular_response_path = get_data( "d181021_charge_resolution/illumination_profile/transmission_pmma_vs_theta_20150422.dat" )
def main(): path = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gamma1deg_onoff.h5" ) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_onoff_nocut.pdf") title = "ON/OFF MC (1deg) (No cuts)" process(path, output, title, None) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_onoff_softcut.pdf") title = "ON/OFF MC (1deg) (Soft cuts)" process(path, output, title, CUTS_ONOFF_SOFT) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_onoff_harshcut.pdf" ) title = "ON/OFF MC (1deg) (Harsh cuts)" process(path, output, title, CUTS_ONOFF_HARSH) path = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gamma1deg_wobble.h5" ) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_wobble_nocut.pdf") title = "Wobble MC (1deg) (No cuts)" process(path, output, title, None) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_wobble_cut.pdf") title = "Wobble MC (1deg)" process(path, output, title, CUTS_WOBBLE) path = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gamma1deg_5off_wobble.h5" ) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_5off_wobble_nocut.pdf" ) title = "Wobble MC (1deg) (5 OFF) (No cuts)" process(path, output, title, None) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gamma1deg_5off_wobble_cut.pdf" ) title = "Wobble MC (1deg) (5 OFF)" process(path, output, title, CUTS_WOBBLE) path = get_data( "d190918_alpha/extract_alpha_mc/d2019-05-15_simulations_gammaonly_wobble.h5" ) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gammaonly_wobble_nocut.pdf") title = "Wobble MC (1deg) (No cuts)" process(path, output, title, None) output = get_plot( "d190918_alpha/mc/d2019-05-15_simulations_gammaonly_wobble_cut.pdf") title = "Wobble MC (1deg)" process(path, output, title, CUTS_WOBBLE)
def main(): r0_path = get_checs("d181203_erlangen/ac_tf/23deg/Amplitude_600_r0.tio") pedestal_path = get_checs( "d181203_erlangen/pedestal/Pedestal_23deg_ped.tcal") tf_path = get_data("d191122_dc_tf/ac_tf/ac_23deg_tf.h5") pedestal = get_pedestal(pedestal_path) tf = get_ac_cc_tf(tf_path) output_path = get_data("d191122_dc_tf/average_wf.txt") process(r0_path, pedestal, tf, output_path)
def main(): # path = get_data("d191018_alpha/d2019-05-15_simulations_gamma1deg_onoff.h5") # output = get_plot("d191018_alpha/optimise_alpha_cut/d2019-05-15_simulations_gamma1deg_onoff_nocut.pdf") # title = "ON/OFF MC (1deg) (No cuts)" # process(path, output, title, None) # output = get_plot("d191018_alpha/optimise_alpha_cut/d2019-05-15_simulations_gamma1deg_onoff_softcut.pdf") # title = "ON/OFF MC (1deg) (Soft cuts)" # process(path, output, title, CUTS_ONOFF_SOFT) # output = get_plot("d191018_alpha/optimise_alpha_cut/d2019-05-15_simulations_gamma1deg_onoff_harshcut.pdf") # title = "ON/OFF MC (1deg) (Harsh cuts)" # process(path, output, title, CUTS_ONOFF_HARSH) # # path = get_data("d191018_alpha/d2019-05-15_simulations_gamma1deg_wobble.h5") # output = get_plot("d191018_alpha/optimise_alpha_cut/d2019-05-15_simulations_gamma1deg_wobble_nocut.pdf") # title = "Wobble MC (1deg) (No cuts)" # process(path, output, title, None) # output = get_plot("d191018_alpha/optimise_alpha_cut/d2019-05-15_simulations_gamma1deg_wobble_cut.pdf") # title = "Wobble MC (1deg)" # process(path, output, title, CUTS_WOBBLE) path = get_data( "d191018_alpha/extract_alpha_mc/d2019-10-03_simulations_gamma1deg_onoff.h5" ) output = get_plot( "d191018_alpha/optimise_alpha_cut/d2019-10-03_simulations_gamma1deg_onoff_nocut.pdf" ) title = "ON/OFF MC (1deg) (No cuts)" process(path, output, title, None) output = get_plot( "d191018_alpha/optimise_alpha_cut/d2019-10-03_simulations_gamma1deg_onoff_softcut.pdf" ) title = "ON/OFF MC (1deg) (Soft cuts)" process(path, output, title, CUTS_ONOFF_SOFT) output = get_plot( "d191018_alpha/optimise_alpha_cut/d2019-10-03_simulations_gamma1deg_onoff_harshcut.pdf" ) title = "ON/OFF MC (1deg) (Harsh cuts)" process(path, output, title, CUTS_ONOFF_HARSH) path = get_data( "d191018_alpha/extract_alpha_mc/d2019-10-03_simulations_gamma1deg_wobble.h5" ) output = get_plot( "d191018_alpha/optimise_alpha_cut/d2019-10-03_simulations_gamma1deg_wobble_nocut.pdf" ) title = "Wobble MC (1deg) (No cuts)" process(path, output, title, None) output = get_plot( "d191018_alpha/optimise_alpha_cut/d2019-10-03_simulations_gamma1deg_wobble_cut.pdf" ) title = "Wobble MC (1deg)" process(path, output, title, CUTS_WOBBLE)
def main(): paths = dict( self=get_data( "d191118_pedestal_temperature/d191118/residuals_self.h5"), single_31degree=get_data( "d191118_pedestal_temperature/d191118/residuals_single_30.h5"), lookup=get_data( "d191118_pedestal_temperature/d191118/residuals_lookup.h5"), interp=get_data( "d191118_pedestal_temperature/d191118/residuals_interp.h5"), pchip=get_data( "d191118_pedestal_temperature/d191118/residuals_pchip.h5"), ) p_mean = MeanVsTemperature() p_std = StdVsTemperature() p_relstd = RelativeStdVsTemperature() with HDF5Reader(paths['self']) as reader: df = reader.read("data") df = df.set_index("temperature_r0_primary").sort_index() ref_std = df['std'].values for label, path in paths.items(): with HDF5Reader(path) as reader: df = reader.read("data") df = df.set_index("temperature_r0_primary").sort_index() temperature = df.index.values mean = df['mean'].values std = df['std'].values p_mean.plot(temperature, mean, label) p_std.plot(temperature, std, label) p_relstd.plot(temperature, std, ref_std, label) p_mean.save(get_plot(f"d191118_pedestal_temperature/d191118/mean.pdf")) p_std.save(get_plot(f"d191118_pedestal_temperature/d191118/std.pdf")) p_relstd.save( get_plot(f"d191118_pedestal_temperature/d191118/rel_std.pdf")) with HDF5Reader(paths['self']) as reader: df = reader.read("data") df = df.set_index("temperature_r0_chamber").sort_index() chamber = df.index.values primary = df['temperature_r0_primary'].values p_temp = TemperatureComparison() p_temp.plot(chamber, primary) p_temp.save(get_plot(f"d191118_pedestal_temperature/d191118/temp.pdf"))
def __init__(self, **kwargs): super().__init__(**kwargs) self.illumination_profile_path = get_data( "d181021_charge_resolution/illumination_profile/d180907_MC.h5" ) # TODO: get lab_illumination_profile_correction.h5 self.dead = [677, 293, 27, 1925, 1955] self.calib_class = None
def main(): d_list = [] for file in tqdm(all_files): tcal_path = file.tcal ped_reader = PedestalArrayReader(tcal_path) hits_tcal = np.array(ped_reader.GetHits()) std_tcal = np.array(ped_reader.GetStdDev()) mask = (hits_tcal < 6) | np.isnan(std_tcal) std_tcal = np.ma.masked_array(std_tcal, mask=mask) n_noisy = (std_tcal > 5).sum() d_list.append(dict( name=file.name, mean=std_tcal.mean(), std=std_tcal.std(), min=std_tcal.min(), max=std_tcal.max(), n_noisy=n_noisy, )) df = pd.DataFrame(d_list) # embed() with HDF5Writer(get_data(f"d190730_pedestal/tcal_std.h5")) as w: w.write(data=df)
def main(): runlist_path = get_astri_2019("d2019-05-01_mrk501/runlist.txt") directory = dirname(runlist_path) df = pd.read_csv(runlist_path, sep='\t') paths = [join(directory, f"Run{run:05d}_r1.tio") for run in df['run']] output_path = get_data("d190505_dtack/d2019-05-01_mrk501.h5") process(paths, output_path)
def process_file(file): name = file.__class__.__name__ input_path = file.r0_path output_path = get_data( "d181206_pedestal_investigation/cell_info/{}.h5".format(name)) poi = 10 process(input_path, output_path, poi)
def process(input_path, function): pattern = '(.+)(SN\d{4})(.+)' reg_exp = re.search(pattern, input_path) sn = reg_exp[2] name = function.__name__ output_path = get_data("d181027_tf_generation/alter_tf/{}_{}.tcal".format( name, sn)) plot_path = get_plot("d181027_tf_generation/alter_tf/{}_{}.pdf".format( name, sn)) print("Reading TF: {}".format(input_path)) reader = TFArrayReader(input_path) tf = np.array(reader.GetTF()) steps = np.array(reader.GetAdcSteps()) steps, tf = function(steps, tf) print("Writing TF: {}".format(output_path)) rw = CalibReadWriter() rw.WriteTfData(output_path, steps.tolist(), tf, True) reader = TFArrayReader(output_path) tf = np.array(reader.GetTF()) steps = np.array(reader.GetAdcSteps()) p_tf = TFPlot() p_tf.plot(steps, tf) p_tf.save(plot_path)
def process_file(file): readers = file.tio_readers name = file.__class__.__name__ output_path = get_data( "d190111_trigger_stability/{}/amplitudes.h5".format(name)) superpixels = file.spoi process(readers, output_path, superpixels)
def main(): path = get_data("d190717_alpha/wobble.h5") with pd.HDFStore(path, mode='r') as store: df = store['data'] mapping = store['mapping'] with warnings.catch_warnings(): warnings.simplefilter('ignore', UserWarning) mapping.metadata = store.get_storer('mapping').attrs.metadata p_camera = CameraMovie(mapping, get_plot("d190717_alpha/wobble_animation/frames")) n_row = df.index.size for _, row in tqdm(df.iterrows(), total=n_row): timestamp = row['timestamp'] x_src = row['x_src'] y_src = row['y_src'] dl1 = row['dl1'] r1 = row['r1'] x_cog = row['x_cog'] y_cog = row['y_cog'] psi = row['psi'] p_camera.set_source_position(x_src, y_src) p_camera.set_image(dl1) # p_camera.set_alpha_line(x_cog, y_cog, psi) p_camera.save_frame()
def main(): # tf_r0_paths = glob(get_checs("d181203_erlangen/dc_tf/externalsync/23deg/*.tio")) # pedestal_path = get_checs("d181203_erlangen/pedestal/Pedestal_23deg_ped.tcal") # tf_path = get_data("d191122_dc_tf/dc_tf/dc_externalsync_23deg_tf.tcal") # tf_class = TFDC # process(tf_r0_paths, pedestal_path, tf_path, tf_class) # # tf_r0_paths = glob(get_checs("d181203_erlangen/dc_tf/externalsync/40deg/*.tio")) # pedestal_path = get_checs("d181203_erlangen/pedestal/Pedestal_40deg_ped.tcal") # tf_path = get_data("d191122_dc_tf/dc_tf/dc_externalsync_40deg_tf.tcal") # tf_class = TFDC # process(tf_r0_paths, pedestal_path, tf_path, tf_class) # # tf_r0_paths = glob(get_checs("d181203_erlangen/dc_tf/hardsync/23deg/*.tio")) # pedestal_path = get_checs("d181203_erlangen/pedestal/Pedestal_23deg_ped.tcal") # tf_path = get_data("d191122_dc_tf/dc_tf/dc_hardsync_23deg_tf.tcal") # tf_class = TFDC # process(tf_r0_paths, pedestal_path, tf_path, tf_class) # # tf_r0_paths = glob(get_checs("d181203_erlangen/dc_tf/hardsync/40deg/*.tio")) # pedestal_path = get_checs("d181203_erlangen/pedestal/Pedestal_40deg_ped.tcal") # tf_path = get_data("d191122_dc_tf/dc_tf/dc_hardsync_40deg_tf.tcal") # tf_class = TFDC # process(tf_r0_paths, pedestal_path, tf_path, tf_class) tf_r0_paths = glob( get_checs("d181203_erlangen/ac_tf/23deg/Amplitude_*.tio")) pedestal_path = get_checs( "d181203_erlangen/pedestal/Pedestal_23deg_ped.tcal") tf_path = get_data("d191122_dc_tf/ac_tf/ac_23deg_tf.h5") tf_class = TFACCrossCorrelation process(tf_r0_paths, pedestal_path, tf_path, tf_class)
def main(): r1_paths = dict( off=get_astri_2019("d2019-05-08_ledflashers_dynrange/Run13268_r1.tio"), on_50=get_astri_2019("d2019-05-08_ledflashers_dynrange/Run13272_r1.tio"), on_3=get_astri_2019("d2019-05-08_ledflashers_dynrange/Run13267_r1.tio") ) output = get_data("d190520_charge_extraction/data/charge.h5") poi = 2004 reader = ReaderR1(list(r1_paths.values())[0]) kw = dict( n_pixels=reader.n_pixels, n_samples=reader.n_samples, mapping=reader.mapping, reference_pulse_path=reader.reference_pulse_path, ) extractors = dict( cc_nn=(CrossCorrelationNeighbour(**kw), 'charge_cc_nn'), ) for width in range(1, 15): extractors[f'sliding_{width}'] = ( SlidingWindowNeighbour(**kw, window_size=width), "charge_sliding_nn" ) for shift in range(-3, 8): extractors[f'peak_{width}_{shift}'] = ( CtapipeNeighbourPeakIntegrator( **kw, window_size=width, window_shift=shift ), "charge_nn" ) with HDF5Writer(output) as writer: for key, path in r1_paths.items(): reader = ReaderR1(path, max_events=500) baseline_subtractor = BaselineSubtractor(reader) time_calibrator = TimeCalibrator() desc = "Looping over file" for wfs in tqdm(reader, total=reader.n_events, desc=desc): iev = wfs.iev if reader.stale.any(): continue wfs = time_calibrator(wfs) wfs = baseline_subtractor.subtract(wfs) global_params = dict( key=key, iev=iev, pixel=poi, ) for name, (extractor, column) in extractors.items(): params = global_params.copy() params['extractor'] = name params['charge'] = extractor.process(wfs)[column][poi] df = pd.DataFrame(params, index=[0]) writer.append(df, key='data')
def process_file(file): name = file.__class__.__name__ input_path = get_data( "d181206_pedestal_investigation/cell_info/{}.h5".format(name)) output_path = get_plot( "d181206_pedestal_investigation/cell_adc_vs_position/{}/{}.pdf".format( name, "{}")) process(input_path, output_path)
def main(): with HDF5Reader(get_data("d190730_pedestal/tcal_std.h5")) as r: df = r.read("data").iloc[2:] p_std = ComparisonPlotter() p_std.plot(df['name'].values, df['mean'].values, df['std'].values, df['max'].values) p_std.save(get_plot("d190730_pedestal/tcal_std.pdf"))
def main(): x_checs, y_checs = np.loadtxt(get_data("d181031_sst_rfi/pde/CHECS.dat"), unpack=True) x_prod3, y_prod3 = np.loadtxt(get_data("d181031_sst_rfi/pde/Prod3.dat"), unpack=True) x_prod4, y_prod4 = np.loadtxt(get_data("d181031_sst_rfi/pde/Prod4.dat"), unpack=True) integral_checs = np.trapz(y_checs, x_checs) integral_prod3 = np.trapz(y_prod3, x_prod3) print(integral_checs / integral_prod3) p_pde = PDEPlotter() p_pde.plot(x_checs, y_checs, label="CHEC-S") p_pde.plot(x_prod3, y_prod3, label="Prod3") p_pde.plot(x_prod4, y_prod4, label="Prod4") p_pde.save(get_plot("d181031_sst_rfi/pde.pdf"))
def main(): r0_paths = glob( get_checs("d191118_pedestal_temperature/data/d191118/*.tio")) pedestal_paths = glob( get_checs("d191118_pedestal_temperature/lookup/*_ped.tcal")) output_path = get_data( f"d191118_pedestal_temperature/d191118/residuals_pchip.h5") process(r0_paths, pedestal_paths, output_path)
def main(): path = get_data(f"d191118_pedestal_temperature/d191118/adc_vs_temperature.h5") with HDF5Reader(path) as reader: df = reader.read("data") df = df.set_index("temperature").sort_index() temperature = df.index.values delta_mean = df['delta_mean'].values delta_std = df['delta_std'].values delta_channel_mean = df['delta_channel_mean'].values delta_channel_std = df['delta_channel_std'].values spead_mean = df['spread_mean'].values spread_std = df['spread_std'].values p_delta = ValueVsTemp() p_delta.plot(temperature, delta_mean, delta_std, "TM") p_delta.plot(temperature, delta_channel_mean, delta_channel_std, "Channel 0") p_delta.save(get_plot(f"d191118_pedestal_temperature/d191118/delta_vs_temp.pdf")) # p_delta = ValueVsTemp() # p_delta.plot(temperature, delta_channel_mean, delta_channel_std) # p_delta.save(get_plot(f"d191118_pedestal_temperature/d191118/delta_channel_vs_temp.pdf")) p_delta = SpreadVsTemp() p_delta.plot(temperature, spead_mean, spread_std) p_delta.save(get_plot(f"d191118_pedestal_temperature/d191118/spread_vs_temp.pdf")) paths = dict( d191118_60hz=get_data("d191118_pedestal_temperature/d191118/adc_vs_temperature.h5"), d191119_600hz=get_data("d191118_pedestal_temperature/d191119/adc_vs_temperature.h5"), d191120_200hz=get_data("d191118_pedestal_temperature/d191120/adc_vs_temperature.h5"), ) p_delta = ValueVsTemp() for label, path in paths.items(): with HDF5Reader(path) as reader: df = reader.read("data") df = df.set_index("temperature").sort_index() temperature = df.index.values delta_mean = df['delta_mean'].values delta_std = df['delta_std'].values p_delta.plot(temperature, delta_mean, delta_std, label) p_delta.save(get_plot(f"d191118_pedestal_temperature/delta_vs_temp_vs_day.pdf"))
def process_file(file): name = file.__class__.__name__ input_path = get_data( "d190104_vped_pedestal_steps/cell_info/{}.h5".format(name)) output_dir = get_plot( "d190104_vped_pedestal_steps/steps_vs_vped/{}".format(name)) coi = 12 process(input_path, output_dir, coi)
def main(): pedestal_paths = glob( get_checs("d191118_pedestal_temperature/data/d191118/*_ped.tcal")) output_path = get_data( f"d191118_pedestal_temperature/d191118/adc_vs_temperature.h5") process(pedestal_paths, output_path) pedestal_paths = glob( get_checs("d191118_pedestal_temperature/data/d191119/*_ped.tcal")) output_path = get_data( f"d191118_pedestal_temperature/d191119/adc_vs_temperature.h5") process(pedestal_paths, output_path) pedestal_paths = glob( get_checs("d191118_pedestal_temperature/data/d191120/*_ped.tcal")) output_path = get_data( f"d191118_pedestal_temperature/d191120/adc_vs_temperature.h5") process(pedestal_paths, output_path)
def process_file(file): name = file.__class__.__name__ input_paths = file.r0_paths amplitudes = file.amplitudes output_path = get_data( "d190104_vped_pedestal_steps/cell_info/{}.h5".format(name)) poi = 10 assert len(input_paths) > 0 process_list(input_paths, amplitudes, output_path, poi)