cwitools.variance.estimate_variance

cwitools.variance.estimate_variance(inputfits, zwindow=5, zmask=(0, 0), fmin=0.9)

Estimates the 3D variance cube of an input cube.

Args:

inputfits (astropy.io.fits.HDUList): FITS object to estimate variance of. zWindow (int): Size of z-axis bins to use for 2D variance estimation. Default: 10. rescale (bool): Set to TRUE to perform layer-by-layer rescaling of 2D variance. sclip (float): Threshold (in stddevs) for sigma-clipping data before estimation. zmask (int tuple): Wavelength layers to exclude while estimating variance. fMin (float): The minimum rescaling factor (Default 0.9) fileExt (str): The extension to use for the output cube (Default .var.fits)

Returns:

NumPy ndarray: Estimated variance cube

Examples:

>>> from astropy.io import fits
>>> from cwitools.variance import estimate_variance
>>> myfits = fits.open("mydata.fits")
>>> varcube = estimate_variance(myfits)
>>> varfits = fits.HDUList([fits.primaryHDU(varcube)])
>>> varfits[0].header = myfits[0].header
>>> varfits.writeto("mydata_var.fits")