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Python module for calculating pixel-to-pixel RMS noise in astronomical images, taking into account autocorrelation, noise variations in the image weight map, and masking out objects. Intended as a Pythonic replacement to 'MEDRMS' iraf tasks
mmechtley/astroRMS
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Matt Mechtley - Dec 2011 - https://github.com/mmechtley Python implementation of Mark Dickinson's acall iraf tasks for calculating RMS noise maps for astronomical images, taking into account pixel autocorrelation, noise variations in the weight map, and masking out the objects themselves. This module is not intended to have exact parameter parity with the MEDRMS iraf package. Rather, it is intended to provide similar functionality with a Pythonic interface. There are many optional parameters. See the docstrings, especially calc_rms() and select_region_slices(), for more information. Required External Packages: --------------------------- numpy scipy astropy (for fits i/o) Installation: ------------- Standard: python setup.py install Using a non-standard library location (e.g. Dropbox): python setup.py install --prefix=~/Dropbox/Python Example Usage: -------------- import astroRMS sci_file = 'goodss_f160w_sci.fits' wht_file = scifile.replace('sci', 'wht') out_file = scifile.replace('sci', 'ivm') astroRMS.create_error_map(sci_file, wht_file, out_file)
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Python module for calculating pixel-to-pixel RMS noise in astronomical images, taking into account autocorrelation, noise variations in the image weight map, and masking out objects. Intended as a Pythonic replacement to 'MEDRMS' iraf tasks
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