Imaging (image)

ctapipe.image contains all algorithms that operate on Cherenkov camera images.

A Cherenkov image is defined as two pieces of data:

• a numpy array of pixel values (which can either be 1D, or 2D if time samples are included)

• a description of the Camera geometry (pixel positions, etc), usually a ctapipe.instrument.CameraGeometry object

This module contains the following sub-modules, but the most important functions of each are imported into the ctapipe.image namespace

• Hillas Parameterization
• Image Cleaning
• Muon Image Analysis
• Toy Model Image Generation
• Pixel Likelihood Calculation
• Image Extraction (Waveform Cube to Image)
• Image Volume Reduction
• Image Modifications
• Invalid Pixels Handling

Reference/API

ctapipe.image Package

Functions

hillas_parameters(geom, image)	Compute Hillas parameters for a given shower image.
camera_to_shower_coordinates(x, y, cog_x, ...)	Return longitudinal and transverse coordinates for x and y for a given set of hillas parameters
timing_parameters(geom, image, peak_time, ...)	Function to extract timing parameters from a cleaned image.
leakage_parameters(geom, image, cleaning_mask)	Calculating the leakage-values for a given image.
concentration_parameters(geom, image, ...)	Calculate concentraion values.
descriptive_statistics(values[, container_class])	compute intensity statistics of an image
number_of_islands(geom, mask)	Search a given pixel mask for connected clusters.
number_of_island_sizes(island_labels)	Return number of small, medium and large islands
morphology_parameters(geom, image_mask)	Compute image morphology parameters
largest_island(island_labels)	Find the biggest island and filter it from the image.
brightest_island(n_islands, island_labels, image)	Find the brightest island and filter it from the image.
tailcuts_clean(geom, image[, ...])	Clean an image by selection pixels that pass a two-threshold tail-cuts procedure.
bright_cleaning(image, threshold, fraction)	Clean an image by removing pixels below a fraction of the mean charge in the n_pixels brightest pixels.
dilate(geom, mask)	Add one row of neighbors to the true values of a pixel mask and return the new mask.
mars_cleaning_1st_pass(geom, image[, ...])	Clean an image by selecting pixels that pass a three-threshold tail-cuts procedure.
nsb_image_cleaning(geom, image, arrival_times)	Clean an image in 5 Steps:
fact_image_cleaning(geom, image, arrival_times)	Clean an image by selection pixels that pass the fact cleaning procedure.
apply_time_delta_cleaning(geom, mask, ...)	Identify all pixels from selection that have less than N neighbors that arrived within a given timeframe.
time_constrained_clean(geom, image, ...[, ...])	Time constrained cleaning by MAGIC
neg_log_likelihood_approx(image, prediction, ...)	Calculate negative log likelihood for telescope.
neg_log_likelihood_numeric(image, ...[, ...])	Calculate likelihood of prediction given the measured signal, full numerical integration from [DNR09].
neg_log_likelihood(image, prediction, ...[, ...])	Safe implementation of the poissonian likelihood implementation, adaptively switches between the full solution and the gaussian approx depending on the prediction.
mean_poisson_likelihood_gaussian(prediction, ...)	Calculation of the mean of twice the negative log likelihood for a give expectation value of pixel intensity in the gaussian approximation.
mean_poisson_likelihood_full(prediction, ...)	Calculation of the mean of twice the negative log likelihood for a give expectation value of pixel intensity using the full numerical integration.
chi_squared(image, prediction, pedestal[, ...])	Simple chi-squared statistic from Le Bohec et al 2008
kundu_chaudhuri_circle_fit(x, y, weights[, ...])	Fast and reliable analytical circle fitting method.
mean_squared_error(pixel_fov_lon, ...)	Calculate the weighted mean squared error for a circle.
intensity_ratio_inside_ring(pixel_fov_lon, ...)	Calculate the ratio of the photons inside a given ring with coordinates (center_fov_lon, center_fov_lat), radius and width.
ring_completeness(pixel_fov_lon, ...[, ...])	Estimate how complete a muon ring is by binning the light distribution along the ring and applying a threshold to the bin content.
ring_containment(ring, camera_radius)	Estimate the angular containment of a muon ring inside the camera's field of view.
neighbor_average_maximum(waveforms, ...)	Obtain the average waveform built from the neighbors of each pixel
subtract_baseline(waveforms, baseline_start, ...)	Subtracts the waveform baseline, estimated as the mean waveform value in the interval [baseline_start:baseline_end]
integration_correction(...)	Obtain the correction for the integration window specified.

Classes

ImageModifier(**kwargs)	Component to tune simulated background to overserved NSB values.
ImageProcessor(**kwargs)	Takes DL1/Image data and cleans and parametrizes the images into DL1/parameters.
HillasParameterizationError
ImageCleaner(**kwargs)	Abstract class for all configurable Image Cleaning algorithms.
TailcutsImageCleaner(**kwargs)	Clean images using the standard picture/boundary technique.
NSBImageCleaner(**kwargs)	Clean images based on lstchains image cleaning technique described in [LST23].
PixelLikelihoodError
MuonIntensityFitter(**kwargs)	Fit muon ring images with a theoretical model to estimate optical efficiency.
MuonRingFitter(**kwargs)	Different ring fit algorithms for muon rings
MuonProcessor(**kwargs)	Takes cleaned images and extracts muon rings.
ImageExtractor(**kwargs)
FullWaveformSum(**kwargs)	Extractor that sums the entire waveform.
FixedWindowSum(**kwargs)	Extractor that sums within a fixed window defined by the user.
GlobalPeakWindowSum(**kwargs)	Extractor which sums in a window about the peak from the global average waveform.
LocalPeakWindowSum(**kwargs)	Extractor which sums in a window about the peak in each pixel's waveform.
SlidingWindowMaxSum(**kwargs)	Sliding window extractor that maximizes the signal in window_width consecutive slices.
NeighborPeakWindowSum(**kwargs)	Extractor which sums in a window about the peak defined by the waveforms in neighboring pixels.
BaselineSubtractedNeighborPeakWindowSum(**kwargs)	Extractor that first subtracts the baseline before summing in a window about the peak defined by the waveforms in neighboring pixels.
TwoPassWindowSum(**kwargs)	Extractor based on [R51f2a41efcc4-1] which integrates the waveform a second time using a time-gradient linear fit.
VarianceExtractor(**kwargs)	Calculate the variance over samples in each waveform.
DataVolumeReducer(**kwargs)	Base component for data volume reducers.
NullDataVolumeReducer(**kwargs)	Perform no data volume reduction
TailCutsDataVolumeReducer(**kwargs)	Reduce the time integrated shower image in 3 Steps:
InvalidPixelHandler(**kwargs)	An abstract base class for algorithms treating invalid pixel data in images
NeighborAverage(**kwargs)