Image (image)

Introduction

Module containing image processing customly implemented in lstchain. This includes:

• Dynamic image cleaning.

• Noise adder at DL1 level to mimic real NSB conditions.

• Muon fit and analysis.

Muon analysis

IACTs use camera calibration systems to estimate the conversion between the measured signal and the total number of received photons. This method, does not take into account effects of the optical system and the efficiency of the mirror of the telescope is not considered. To carry out an absolute calibration of light throughput, it is essential to analyze a signal of known nature, as for example the peculiar ring-shaped images produced by cosmic ray muons.

To perform this analysis:

1. We fit ellipses to the bright images in the camera and extract the fitted parameters such as the image intensity or the ring width

2. We compare the fit results with those obtained using MC simulations and different optical efficiencies.

3. The overall optical efficiency of the telescope corresponds to the fitted value that is closer to

Muon analysis is automatically performed by LSTOSA when running lstchain.scripts.lstchain_data_r0_to_dl1. You can find the table with the outputs in muons_LST-1.Runxxxxx.yyyy.fits, where xxxxx is the run number and yyyy the subrun number analyzed.

If you want to perform a custom muon analysis, you can run the script lstchain.scripts.lstchain_dl1_muon_analysis, that performs the analysis of DL1 files and writes out a table with the results for the fitted muons. In order to reduce the differences between the analysis of Real data and MC, muon analysis uses a different signal extractor (GlobalPeakWindowSum) than real data (LocalPeakWindowSum), that can be specified in the image_extractor_for_muons keyword from the standard input card located in lstchain.data.lstchain_standard_config.json

Muon analysis can also be performed to check the Point Spread Function of the telescope, although small changes in the point spread function may not be spotted using it.

Reference/API

lstchain.image Package

lstchain.image.cleaning Module

Functions

apply_dynamic_cleaning(image, signal_pixels, ...)

Application of the dynamic cleaning

lstchain.image.modifier Module

Functions

add_noise_in_pixels(rng, image, ...)	Addition of Poissonian noise to the pixels
calculate_required_additional_nsb(...[, config])	Calculates the additional NSB needed in the MC waveforms to match a real data DL1 file
calculate_noise_parameters(simtel_filename, ...)	Calculates the parameters needed to increase the noise in an MC DL1 file to match the noise in a real data DL1 file, using add_noise_in_pixels The returned parameters are those needed by the function add_noise_in_pixels (see description in its documentation above).
random_psf_smearer(image, fraction, indices, ...)	Random PSF smearer
set_numba_seed(seed)

Classes

WaveformNsbTuner(added_nsb, pulse_template, ...)

Handles the injection of additional NSB pulses in waveforms.

lstchain.image.muon.muon_analysis Module

Functions

analyze_muon_event(subarray, tel_id, ...)	Analyze an event to fit a muon ring
create_muon_table()	Create the empty dictionary to include the parameters of the fitted muon
fill_muon_event(mc_energy, ...[, ...])	Fill the dictionary with the parameters of a muon event
fit_muon(x, y, image, geom[, tailcuts])	Fit the muon ring
muon_filter(image[, thr_low, thr_up])	Tag muon with a double threshold on the image photoelectron size Default values apply no tagging
pixel_coords_to_telescope(geom, ...)	Get the x, y coordinates of the pixels in the telescope frame
radial_light_distribution(center_x, ...)	Calculate the radial distribution of the muon ring
tag_pix_thr(image[, thr_low, thr_up, pe_thr])	Tag event with a double threshold on the number of pixels above 10 photoelectrons.
update_parameters(config, n_pixels)	Create the parameters used to select good muon rings and perform the muon analysis.

lstchain.image.muon.plot_muon Module

Functions

plot_muon_event(ax, geom, image, centroid, ...)

Function to plot single muon events