denoising.abstract_cleaning_algorithm

class pywicta.denoising.abstract_cleaning_algorithm.AbstractCleaningAlgorithm[source]

A convenient optional wrapper to simplify the image cleaning analysis.

Common processing to run and assess the image cleaning procedure on a set of images and save results. This class gather some common procedures to avoid code duplication in image cleaning modules:

  • call the cleaning algorithm on an image set;
  • assess the cleaning procedure using a set of estimators;
  • apply various pre-processing and post-processing procedures (e.g. geometry conversion);
  • collect and save metadata, results and intermediate values that are useful for analysis;
  • measure and save the execution time;
  • manage exceptions;
  • …

This abstract class is supposed to be inherited by the others image cleaning classes.

run(cleaning_function_params, input_file_or_dir_path_list, benchmark_method, output_file_path, plot=False, saveplot=None, ref_img_as_input=False, max_num_img=None, tel_id=None, event_id=None, cam_id=None, debug=False, rejection_criteria=None)[source]

A convenient optional wrapper to simplify the image cleaning analysis.

Apply the image cleaning analysis on input_file_or_dir_path_list, apply some pre-processing and post-processing procedures, collect and return results, intermediate values and metadata.

Parameters:
  • cleaning_function_params – A dictionary containing the parameters required for the image cleaning method.
  • input_file_or_dir_path_list – A list of file to clean. Can be a list of simtel files, fits files or directories containing such files.
  • benchmark_method – The list of estimators to use to assess the image cleaning. If None, images are cleaned but nothing is returned (can be used with e.g. the plot and/or saveplot options).
  • output_file_path – The result file path (a JSON file).
  • plot – The result of each cleaning is plot if True.
  • saveplot – The result of each cleaning is saved if True.
  • ref_img_as_input – This option is a hack to easily produce a “flatten” CSV results files.
  • max_num_img – The number of images to process among the input set (input_file_or_dir_path_list).
  • debug – Stop the execution and print the full traceback when an exception is encountered if this parameter is True. Report exceptions and continue with the next input image if this parameter is False.
Returns:

Results, intermediate values and metadata.
Return type:

dict