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Spectral Extraction
===================
A commonly required operation is extracting a spectrum from a part of a cube.
The simplest way to get a spectrum from the cube is simply to slice it along
a single pixel::
>>> spectrum = cube[:, 50, 60] # doctest: +SKIP
Slicing along the first dimension will create a
`~spectral_cube.lower_dimensional_structures.OneDSpectrum` object, which has a few
useful capabilities.
Aperture Extraction
-------------------
Going one level further, you can extract a spectrum from an aperture.
We'll start with the simplest variant: a square aperture. The
cube can be sliced in pixel coordinates to produce a sub-cube
which we then average spatially to get the spectrum::
>>> subcube = cube[:, 50:53, 60:63] # doctest: +SKIP
>>> spectrum = subcube.mean(axis=(1,2)) # doctest: +SKIP
The spectrum can be obtained using any mathematical operation, such as the
``max`` or ``std``, e.g., if you wanted to obtain the noise spectrum.
Slightly more sophisticated aperture extraction
-----------------------------------------------
To get the flux in a circular aperture, you need to mask the data. In this
example, we don't use any external libraries, but show how to create a circular
mask from scratch and apply it to the data.::
>>> yy, xx = np.indices([5,5], dtype='float') # doctest: +SKIP
>>> radius = ((yy-2)**2 + (xx-2)**2)**0.5 # doctest: +SKIP
>>> mask = radius <= 2 # doctest: +SKIP
>>> subcube = cube[:, 50:55, 60:65] # doctest: +SKIP
>>> maskedsubcube = subcube.with_mask(mask) # doctest: +SKIP
>>> spectrum = maskedsubcube.mean(axis=(1,2)) # doctest: +SKIP
Aperture and spectral extraction using regions
----------------------------------------------
Spectral-cube supports ds9 and crtf regions, so you can use them to create a
mask. The ds9/crtf region support relies on `regions
<https://astropy-regions.readthedocs.io/en/latest/>`_, which supports most
shapes in ds9 and crtf, so you are not limited to circular apertures.
In this example, we'll extract a subcube from ds9 region string using
:meth:`~spectral_cube.spectral_cube.BaseSpectralCube.subcube_from_ds9region`::
>>> ds9_str = 'fk5; circle(19:23:43.907, +14:30:34.66, 3")' # doctest: +SKIP
>>> subcube = cube.subcube_from_ds9region(ds9_str) # doctest: +SKIP
>>> spectrum = subcube.mean(axis=(1, 2)) # doctest: +SKIP
Similarly, one can extract a subcube from a crtf region string using
:meth:`~spectral_cube.spectral_cube.BaseSpectralCube.subcube_from_crtfregion`::
>>> crtf_str = 'circle[[19:23:43.907, +14:30:34.66], 3"], coord=fk5, range=[150km/s, 300km/s]' # doctest: +SKIP
>>> subcube = cube.subcube_from_crtfregion(crtf_str) # doctest: +SKIP
>>> spectrum = subcube.mean(axis=(1, 2)) # doctest: +SKIP
You can also use a _list_ of `~regions.Region` objects to extract a subcube using
:meth:`~spectral_cube.spectral_cube.BaseSpectralCube.subcube_from_regions`::
>>> import regions # doctest: +SKIP
>>> regpix = regions.RectanglePixelRegion(regions.PixCoord(0.5, 1), width=4, height=2) # doctest: +SKIP
>>> subcube = cube.subcube_from_regions([regpix]) # doctest: +SKIP
>>> spectrum = subcube.mean(axis=(1, 2)) # doctest: +SKIP
To learn more, go to :ref:`reg`.
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