get_masked_moment#

mufasa.UltraCube.get_masked_moment(cube, model, order=0, expand=10, mask=None)[source]#

Calculate a masked moment of a spectral cube.

This function generates a moment map (e.g., integrated intensity, centroid) for the input spectral cube, applying a mask derived from the provided model and optionally expanding the mask region.

Parameters:

  • cube (SpectralCube) – The spectral cube containing the observed data, from which the moment is calculated.

  • model (numpy.ndarray) – A 3D array representing the model cube, used to derive the mask. The dimensions must match the cube.

  • order (int, optional) – The order of the moment to compute: - 0 for integrated intensity (default), - 1 for centroid, - 2 for line width.

  • expand (int, optional) – Number of spectral channels to expand the mask around the model. Default is 10.

  • mask (numpy.ndarray, optional) – A 3D boolean array specifying which elements to include in the moment calculation. If provided, it is combined with the mask derived from the model. Default is None.

Returns:

The computed moment map, with the unit determined by the input cube and the moment order.

Return type:

astropy.units.Quantity

Notes

  • The mask is generated by identifying non-zero elements in the model and optionally expanding this region by the expand parameter.

  • Pixels with low signal-to-noise ratios are excluded from the moment map based on the mask.

  • The function uses the spectral axis of the cube for moment calculations.

Raises:

ValueError – If the cube and model dimensions do not match.

Examples

>>> from spectral_cube import SpectralCube
>>> cube = SpectralCube.read("example_cube.fits")
>>> model = np.random.random(cube.shape)
>>> moment_map = get_masked_moment(cube, model, order=0, expand=5)
>>> moment_map.write("masked_moment.fits")
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