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)
