Created: 2012-03-24 12:40
Updated: 2018-10-30 10:37


A project on survey design for precise self-calibration.


  • Rory Holmes (MPIA)
  • David W. Hogg (NYU)


Copyright 2012 the authors. All rights reserved.

If you want to license this code for use or re-use, get in touch.


  • Hans-Walter Rix (MPIA)


  • numpy
  • matplotlib
  • scipy

Running the code:

A self-calibration simulation can be run by calling the simulation.run_sim(parameter_dictionary) function, where the parameter_dictionary contains all the parameters for this simulation run. This functions controls a full self-calibration simulation: it generates the synthetic sky, surveys the sky according to the specified survey strategy and then self-calibrates the resultant dataset. This function then returns the performance of the self-calibration procedure. See for all of the required simulation parameters. Running the script on the output directory will produce plots from this self-calibration run. The package has been built in this way to allow for simple multiprocessing, as the simulation.run_sim(parameter_dictionary) function can be called multiple times in parallel with different parameter dictionaries. For example, to test how the self-calibration procedure is sensitive to the number of sources, one can simply run this function with multiple parameter dictionaries in which the number of sources parameter is varied. A number of sample scripts have been included to show how this package can be used.


This package contains seven modules for the self-calibration simulations:

  • contains the functions used to analyze the fitted instrument response relative to the true instrument response.
  • contains the functions that save out all the data from the simulation. NB that data_dir parameter in the parameter dictionary must be specified, otherwise no data is saved out from a simulation run.
  • contains the self-calibration procedures.
  • contains the master function that controls a full the full self-calibration simulation.
  • contains the functions used to perform a survey of the synthetic sky, such as the imager measurement model.
  • contains useful transformation functions that are used throughout the code.
  • contains all the functions representing the true parts of the simulations, such as the actual instrument response that is fitted for in the self-calibration simulations.


Plots for a simulation run can be generated by: [output_directory].


A complete parameter dictionary must be past to simulation.run_sim() for each simulation run. The code does not check for missing parameters before beginning the simulations. See for a full list of required parameters.

Known issues:

  • ...

Migration from svn:

Hogg migrated this from svn with something like

git svn clone svn+ssh:// --no-minimize-url --authors-file ~/authors
cd euclid
git remote add origin
git push origin master
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