Imaging (image
)¶
ctapipe.image
contains all algortihms 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 submodules, but the most important functions of each are imported into the ctapipe.image
namespace
Reference/API¶
ctapipe.image Package¶
Functions¶

Compute Hillas parameters for a given shower image. 

Return longitudinal and transverse coordinates for x and y for a given set of hillas parameters 

Function to extract timing parameters from a cleaned image. 

Calculating the leakagevalues for a given image. 

Calculate concentraion values. 

compute intensity statistics of an image 

Search a given pixel mask for connected clusters. 

Return number of small, medium and large islands 

Compute image morphology parameters 

Find the biggest island and filter it from the image. 

Find the brightest island and filter it from the image. 

Clean an image by selection pixels that pass a twothreshold tailcuts procedure. 

Add one row of neighbors to the True values of a pixel mask and return the new mask. 

Clean an image by selection pixels that pass a threethreshold tailcuts procedure. 

Clean an image by selection pixels that pass the fact cleaning procedure. 

Identify all pixels from selection that have less than N neighbors that arrived within a given timeframe. 

Calculate negative log likelihood for telescope. 

Calculate likelihood of prediction given the measured signal, full numerical integration from [denaurois2009]. 

Safe implementation of the poissonian likelihood implementation, adaptively switches between the full solution and the gaussian approx depending on the prediction. 

Calculation of the mean likelihood for a give expectation value of pixel intensity in the gaussian approximation. 

Calculation of the mean likelihood for a give expectation value of pixel intensity using the full numerical integration. 

Simple chisquared statistic from Le Bohec et al 2008 

Fast and reliable analytical circle fitting method previously used in the H.E.S.S. 

Calculate the weighted mean squared error for a circle 

Calculate the ratio of the photons inside a given ring with coordinates (center_x, center_y), radius and width. 

Estimate how complete a ring is. 

Estimate angular containment of a ring inside the camera (camera center is (0,0)) 

Obtain the average waveform built from the neighbors of each pixel 

Subtracts the waveform baseline, estimated as the mean waveform value in the interval [baseline_start:baseline_end] 
Obtain the correction for the integration window specified. 
Classes¶

Takes DL1/Image data and cleans and parametrizes the images into DL1/parameters. 

Abstract class for all configurable Image Cleaning algorithms. 

Clean images using the standard picture/boundary technique. 



Different ring fit algorithms for muon rings 



Extractor that sums the entire waveform. 

Extractor that sums within a fixed window defined by the user. 

Extractor which sums in a window about the peak from the global average waveform. 

Extractor which sums in a window about the peak in each pixel’s waveform. 

Sliding window extractor that maximizes the signal in window_width consecutive slices. 

Extractor which sums in a window about the peak defined by the wavefroms in neighboring pixels. 

Extractor that first subtracts the baseline before summing in a window about the peak defined by the wavefroms in neighboring pixels. 

Extractor based on [R51f2a41efcc41] which integrates the waveform a second time using a timegradient linear fit. 

Base component for data volume reducers. 

Perform no data volume reduction 

Reduce the time integrated shower image in 3 Steps: 