OneDSpectrum

class spectral_cube.lower_dimensional_structures.OneDSpectrum

Bases: spectral_cube.lower_dimensional_structures.LowerDimensionalObject, spectral_cube.base_class.SpectralAxisMixinClass

Attributes Summary

hdu
hdulist
header
spectral_axis	A Quantity array containing the central values of each channel along the spectral axis.

Methods Summary

quicklook([filename, drawstyle])	Plot the spectrum with current spectral units in the currently open
spectral_interpolate(spectral_grid[, ...])	Resample the spectrum onto a specific grid
spectral_smooth(kernel[, convolve])	Smooth the spectrum
with_spectral_unit(unit[, ...])

Attributes Documentation

hdu

hdulist

header

spectral_axis

A Quantity array containing the central values of each channel along the spectral axis.

Methods Documentation

quicklook(filename=None, drawstyle='steps-mid', **kwargs)

Plot the spectrum with current spectral units in the currently open figure

kwargs are passed to matplotlib.pyplot.plot

Parameters:

filename : str or Non

Optional - the filename to save the quicklook to.

spectral_interpolate(spectral_grid, suppress_smooth_warning=False)

Resample the spectrum onto a specific grid

Parameters:

spectral_grid : array

An array of the spectral positions to regrid onto

suppress_smooth_warning : bool

If disabled, a warning will be raised when interpolating onto a grid that does not nyquist sample the existing grid. Disable this if you have already appropriately smoothed the data.

Returns:

cube : SpectralCube

spectral_smooth(kernel, convolve=<function convolve>, **kwargs)

Smooth the spectrum

Parameters:

kernel : Kernel1D

A 1D kernel from astropy

convolve : function

The astropy convolution function to use, either astropy.convolution.convolve or astropy.convolution.convolve_fft

kwargs : dict

Passed to the convolve function

with_spectral_unit(unit, velocity_convention=None, rest_value=None)