ism3d.xyhelper.maskmoment.momfuncs.smcube

ism3d.xyhelper.maskmoment.momfuncs.smcube(snrcube, header=None, fwhm=None, vsm=None, vsm_type='gauss', edgech=None)[source]

Smooth an SNRcube to produce a higher signal-to-noise SNRcube.

Parameters

  • snrcube (SpectralCube or ~numpy.ndarray) – The image cube normalized by the estimated RMS noise. If a numpy array is provided the header must also be provided.

  • header (astropy.io.fits.Header) – The cube FITS header, required if a numpy array is given.

  • fwhm (float or Quantity, optional) – Final spatial resolution to smooth to. If not astropy quantity, assumed to be given in arcsec. Default: 10 arcsec

  • vsm (float or Quantity, optional) – Full width of the spectral smoothing kernel (or FWHM if gaussian). If given as astropy quantity, should be given in velocity units. If not given as astropy quantity, interpreted as number of channels. Default: No spectral smoothing is applied.

  • vsm_type (string, optional) – What type of spectral smoothing to employ. Currently three options: (1) ‘boxcar’ - 1D boxcar smoothing, vsm rounded to integer # of chans. (2) ‘gauss’ - 1D gaussian smoothing, vsm is the convolving gaussian FWHM. (3) ‘gaussfinal’ - 1D gaussian smoothing, vsm is the gaussian FWHM after convolution, assuming FWHM before convolution is 1 channel. Default: ‘gauss’

  • edgech (int, optional) – Number of channels at left and right edges of each spectrum to use for rms estimation. Default is to use all channels.

Returns

sm_snrcube – A cube is SNR units after smoothing to the desired resolution.

Return type

SpectralCube