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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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README

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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