MultiBeamMixinClass

class spectral_cube.base_class.MultiBeamMixinClass

Bases: object

A mixin class to handle multibeam objects. To be used by VaryingResolutionSpectralCube’s and OneDSpectrum’s

Attributes Summary

beams
goodbeams_mask
pixels_per_beam
unmasked_beams

Methods Summary

average_beams(threshold[, mask, warn])	Average the beams.
identify_bad_beams(threshold[, ...])	Mask out any layers in the cube that have beams that differ from the central value of the beam by more than the specified threshold.
jtok_factors([equivalencies])	Compute an array of multiplicative factors that will convert from Jy/beam to K
mask_out_bad_beams(threshold[, ...])	See identify_bad_beams.
with_beams(beams[, goodbeams_mask, ...])	Attach a new beams object to the VaryingResolutionSpectralCube.

Attributes Documentation

beams

goodbeams_mask

pixels_per_beam

unmasked_beams

Methods Documentation

average_beams(threshold, mask='compute', warn=False)

Average the beams. Note that this operation only makes sense in limited contexts! Generally one would want to convolve all the beams to a common shape, but this method is meant to handle the “simple” case when all your beams are the same to within some small factor and can therefore be arithmetically averaged.

Parameters:

thresholdfloat

The fractional difference between beam major, minor, and pa to permit

mask‘compute’, None, or boolean array

The mask to apply to the beams. Useful for excluding bad channels and edge beams.

warnbool

Warn if successful?

Returns:

new_beamradio_beam.Beam

A new radio beam object that is the average of the unmasked beams

identify_bad_beams(threshold, reference_beam=None, criteria=['sr', 'major', 'minor'], mid_value=<function nanmedian>)

Mask out any layers in the cube that have beams that differ from the central value of the beam by more than the specified threshold.

Parameters:

thresholdfloat

Fractional threshold

reference_beamBeam

A beam to use as the reference. If unspecified, mid_value will be used to select a middle beam

criterialist

A list of criteria to compare. Can include ‘sr’,’major’,’minor’,’pa’ or any subset of those.

mid_valuefunction

The function used to determine the ‘mid’ value to compare to. This will identify the middle-valued beam area/major/minor/pa.

Returns:

includemasknp.array

A boolean array where True indicates the good beams

jtok_factors(equivalencies=())

Compute an array of multiplicative factors that will convert from Jy/beam to K

mask_out_bad_beams(threshold, reference_beam=None, criteria=['sr', 'major', 'minor'], mid_value=<function nanmedian>)

See identify_bad_beams. This function returns a masked cube

Returns:

newcubeVaryingResolutionSpectralCube

The cube with bad beams masked out

with_beams(beams, goodbeams_mask=None, raise_error_jybm=True)

Attach a new beams object to the VaryingResolutionSpectralCube.

Parameters:

beamsBeams

A new beams object.