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Update __str__ and __repr__ for Spectrum1D #1123

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Feb 13, 2024
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Update __str__ and __repr__ for Spectrum1D #1123

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f2e1cf9
Fixing numpy format error when printing Spectrum1D
rosteen Feb 6, 2024
6081ad0
Also shorten __repr__ to something more reasonable
rosteen Feb 6, 2024
0b7f428
Show actual spectral axis and flux if it's small
rosteen Feb 6, 2024
27e3136
str test updated
rosteen Feb 7, 2024
c0bd76d
Spectrum1D tests passing, more tweaks to format
rosteen Feb 7, 2024
e2251a1
Update docstrings
rosteen Feb 7, 2024
c4bd1c2
Fixing doc outputs
rosteen Feb 7, 2024
9f0a4a2
Fix typo
rosteen Feb 7, 2024
ee0b4ce
More docs fixes
rosteen Feb 7, 2024
3a4a64c
Surprised this changed, testing...
rosteen Feb 7, 2024
66d7138
Finish changing docs
rosteen Feb 7, 2024
a9334fc
Fix remote data doc tests
rosteen Feb 8, 2024
e788f72
Went back to = over :, other improvements
rosteen Feb 12, 2024
822f173
Reconcile resample docstring updates
rosteen Feb 12, 2024
1e00460
Add changelog
rosteen Feb 13, 2024
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4 changes: 4 additions & 0 deletions CHANGES.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -13,9 +13,13 @@ Bug Fixes
- ``with_spectral_unit`` has been changed to ``with_spectral_axis_unit`` and actually works
now. [#1119]

- Fixed numpy error when printing a ``Spectrum1D`` object. [#1123]

Other Changes and Additions
^^^^^^^^^^^^^^^^^^^^^^^^^^^

- Updated the format of ``Spectrum1D.__str__`` and ``Spectrum1D.__repr__``. [#1123]

1.12.0 (2023-10-17)
-------------------

Expand Down
16 changes: 2 additions & 14 deletions docs/arithmetic.rst
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Expand Up @@ -29,23 +29,11 @@ Arithmetic support includes addition, subtract, multiplication, and division.
>>> spec2 = Spectrum1D(spectral_axis=np.arange(1, 50) * u.nm, flux=rng.random(49)*u.Jy)
>>> spec3 = spec1 + spec2
>>> spec3 # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [0.85594057, 0.59914105, 0.86545315, 1.29308365, 0.56743587,
0.63720232, 1.03919556, 0.33693653, 0.89068491, 1.41613598,
0.72461457, 1.20411351, 0.96480272, 0.37496506, 0.70241888,
1.36924151, 0.90943254, 0.82210346, 0.98018949, 1.05861761,
0.26172516, 1.02205189, 0.51839963, 1.21572449, 0.87754143,
1.02493144, 0.95316681, 0.37872965, 0.17723648, 1.21662474,
1.39171024, 1.23614795, 1.10636247, 0.97294585, 1.5453743 ,
1.01020945, 1.42125961, 1.36636734, 1.11338214, 0.58687869,
0.63074156, 0.67475105, 0.54093389, 1.77345469, 1.22990398,
0.78162068, 0.63760289, 0.63139356, 0.97112644] Jy>, spectral_axis=<SpectralAxis
<Spectrum1D(flux=[0.8559405665668484 ... 0.9711264429515736] Jy (shape=(49,), mean=0.91592 Jy); spectral_axis=<SpectralAxis
(observer to target:
radial_velocity=0.0 km / s
redshift=0.0)
[ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14.,
15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,
29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,
43., 44., 45., 46., 47., 48., 49.] nm>)>
[ 1. 2. 3. ... 47. 48. 49.] nm> (length=49))>


Propagation of Uncertainties
Expand Down
56 changes: 9 additions & 47 deletions docs/manipulation.rst
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Expand Up @@ -59,19 +59,7 @@ along the spectral dimension.
>>> spec1_gsmooth = gaussian_smooth(spec1, stddev=3)
>>> spec1_tsmooth = trapezoid_smooth(spec1, width=3)
>>> gaussian_smooth(spec1, stddev=3) # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [0.25860917, 0.32640733, 0.38562205, 0.43159269, 0.46445898,
0.48828727, 0.50822537, 0.52741247, 0.54565787, 0.56035736,
0.56880835, 0.57015658, 0.56561802, 0.55700108, 0.54472603,
0.52720679, 0.50217622, 0.46914624, 0.43114785, 0.39432907,
0.36548049, 0.34885759, 0.34456742, 0.34936895, 0.35949514,
0.37376516, 0.39451092, 0.42591854, 0.47068509, 0.5272207 ,
0.58920337, 0.64763434, 0.69379067, 0.72157276, 0.7284874 ,
0.71560131, 0.68696137, 0.64870578, 0.60757162, 0.56898454,
0.53520565, 0.5047466 , 0.47338241, 0.43641424, 0.39090495,
0.3368543 , 0.27706956, 0.21605198, 0.15868783] Jy>, spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14.,
15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,
29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,
43., 44., 45., 46., 47., 48., 49.] nm>)>
<Spectrum1D(flux=[0.25860917267578276 ... 0.15868783272966752] Jy (shape=(49,), mean=0.48009 Jy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 47. 48. 49.] nm> (length=49))>

Each of the specific smoothing methods create the appropriate `astropy.convolution.convolve`
kernel and then call a helper function :func:`~specutils.manipulation.convolution_smooth`
Expand All @@ -87,19 +75,7 @@ that takes the spectrum and an astropy 1D kernel. So, one could also do:
>>> spec1 = Spectrum1D(spectral_axis=np.arange(1, 50) * u.nm,
... flux=np.random.default_rng(12345).random(49) * u.Jy)
>>> convolution_smooth(spec1, box1d_kernel) # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [0.18136479, 0.44715327, 0.59679282, 0.62157656, 0.46672605,
0.44074408, 0.37261896, 0.48593299, 0.60043103, 0.62093487,
0.71297658, 0.62145477, 0.57067218, 0.40165835, 0.47473917,
0.6752577 , 0.63680209, 0.58595151, 0.42684533, 0.34521923,
0.15387504, 0.19386345, 0.32172965, 0.35723812, 0.51579686,
0.42516394, 0.37951329, 0.13814274, 0.27323395, 0.51499156,
0.68497705, 0.79611717, 0.75279699, 0.83910701, 0.83822349,
0.77869171, 0.80439892, 0.65961564, 0.56881136, 0.40684661,
0.46353027, 0.48256952, 0.63312795, 0.4971397 , 0.50011884,
0.28525197, 0.31804274, 0.20644074, 0.12015627] Jy>, spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14.,
15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,
29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,
43., 44., 45., 46., 47., 48., 49.] nm>)>
<Spectrum1D(flux=[0.1813647873923075 ... 0.1201562712204726] Jy (shape=(49,), mean=0.49378 Jy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 47. 48. 49.] nm> (length=49))>

In this case, the ``spec1_bsmooth2`` result should be equivalent to the ``spec1_bsmooth`` in
the section above (assuming the flux data of the input ``spec`` is the same). Note that,
Expand Down Expand Up @@ -131,19 +107,7 @@ method applys the median filter across the flux.
>>> spec1 = Spectrum1D(spectral_axis=np.arange(1, 50) * u.nm,
... flux=np.random.default_rng(12345).random(49) * u.Jy)
>>> median_smooth(spec1, width=3) # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [0.22733602, 0.31675834, 0.67625467, 0.67625467, 0.39110955,
0.39110955, 0.33281393, 0.59830875, 0.67275604, 0.67275604,
0.94180287, 0.66723745, 0.66723745, 0.44183967, 0.44183967,
0.6974535 , 0.6974535 , 0.6974535 , 0.32647286, 0.22013496,
0.1598956 , 0.1598956 , 0.34010018, 0.34010018, 0.46519315,
0.26642103, 0.19329439, 0.12946908, 0.12946908, 0.59856801,
0.60162124, 0.8547419 , 0.72478136, 0.86055132, 0.86055132,
0.86055132, 0.9293378 , 0.54618601, 0.49498794, 0.45177871,
0.45177871, 0.45177871, 0.66503892, 0.33089093, 0.33982834,
0.2588534 , 0.33982834, 0.2588534 , 0.00502233] Jy>, spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14.,
15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,
29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,
43., 44., 45., 46., 47., 48., 49.] nm>)>
<Spectrum1D(flux=[0.22733602246716966 ... 0.005022333717131788] Jy (shape=(49,), mean=0.48620 Jy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 47. 48. 49.] nm> (length=49))>

Resampling
----------
Expand Down Expand Up @@ -374,14 +338,14 @@ the ``spectral_axis``. Therefore one can use a construct like this:
>>> spectrum # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [ 30.47170798, 103.99841062, 75.04511958, 94.05647164,
195.10351887, 130.21795069, 12.78404032, 31.62425923,
1.68011575, 85.30439276] Jy>, spectral_axis=<SpectralAxis [0., 1., 2., 3., 4., 5., 6., 7., 8., 9.] um>)>
1.68011575, 85.30439276] Jy> (shape=(10,), mean=76.02860 Jy); spectral_axis=<SpectralAxis [0. 1. 2. ... 7. 8. 9.] um> (length=10))>

>>> shift = 12300 * u.AA
>>> new_spec = Spectrum1D(spectral_axis=spectrum.spectral_axis + shift, flux=spectrum.flux)
>>> new_spec # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [ 30.47170798, 103.99841062, 75.04511958, 94.05647164,
195.10351887, 130.21795069, 12.78404032, 31.62425923,
1.68011575, 85.30439276] Jy>, spectral_axis=<SpectralAxis [ 1.23, 2.23, 3.23, 4.23, 5.23, 6.23, 7.23, 8.23, 9.23, 10.23] um>)>
1.68011575, 85.30439276] Jy> (shape=(10,), mean=76.02860 Jy); spectral_axis=<SpectralAxis [ 1.23 2.23 3.23 ... 8.23 9.23 10.23] um> (length=10))>

Replacing a region
------------------
Expand All @@ -403,7 +367,7 @@ with the spline knots:
>>> spline_knots = [3.5, 4.7, 6.8, 7.1] * u.AA
>>> result = model_replace(input_spectrum, None, model=spline_knots)
>>> result
<Spectrum1D(flux=<Quantity [ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20.] mJy>, spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.] Angstrom>)>
<Spectrum1D(flux=<Quantity [ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20.] mJy> (shape=(10,), mean=11.00000 mJy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 8. 9. 10.] Angstrom> (length=10))>

The default behavior is to keep the data outside the replaced region unchanged.
Alternatively, the spectrum outside the replaced region can be filled with zeros:
Expand All @@ -413,8 +377,7 @@ Alternatively, the spectrum outside the replaced region can be filled with zeros
>>> spline_knots = [3.5, 4.7, 6.8, 7.1] * u.AA
>>> result = model_replace(input_spectrum, None, model=spline_knots, extrapolation_treatment='zero_fill')
>>> result
<Spectrum1D(flux=<Quantity [ 0., 0., 0., 8., 10., 12., 14., 0., 0., 0.] mJy>,
spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.] Angstrom>)>
<Spectrum1D(flux=<Quantity [ 0., 0., 0., 8., 10., 12., 14., 0., 0., 0.] mJy> (shape=(10,), mean=4.40000 mJy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 8. 9. 10.] Angstrom> (length=10))>

One can define the spline knots by providing an instance of `~specutils.SpectralRegion`,
and the number of knots to be evenly spread along the region:
Expand All @@ -425,8 +388,7 @@ and the number of knots to be evenly spread along the region:
>>> region = SpectralRegion(3.5*u.AA, 7.1*u.AA)
>>> result = model_replace(input_spectrum, region, model=4)
>>> result
<Spectrum1D(flux=<Quantity [ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20.] mJy>,
spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.] Angstrom>)>
<Spectrum1D(flux=<Quantity [ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20.] mJy> (shape=(10,), mean=11.00000 mJy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 8. 9. 10.] Angstrom> (length=10))>

A model fitted over the region can also be used to replace the spectrum flux values:

Expand All @@ -442,7 +404,7 @@ A model fitted over the region can also be used to replace the spectrum flux val
>>> result = model_replace(input_spectrum, region, model=fitted_model)
>>> result # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [1. , 1.1 , 0.9 , 4.40801804, 9.58271877,
5.61238054, 0.88556096, 1. , 1.2 , 1.1 ] mJy>, spectral_axis=<SpectralAxis [ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.] Angstrom>)>
5.61238054, 0.88556096, 1. , 1.2 , 1.1 ] mJy> (shape=(10,), mean=2.67887 mJy); spectral_axis=<SpectralAxis [ 1. 2. 3. ... 8. 9. 10.] Angstrom> (length=10))>

Reference/API
-------------
Expand Down
48 changes: 4 additions & 44 deletions docs/spectral_cube.rst
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Expand Up @@ -49,31 +49,11 @@ Print the contents of 3 spectral axis points in a 3x3 spaxel array:
.. code-block:: python

>>> sc[30:33,30:33,2000:2003] # doctest: +REMOTE_DATA
<Spectrum1D(flux=<Quantity [[[0.48920232, 0.4987253 , 0.5098349 ],
[0.493365 , 0.4964812 , 0.5223962 ],
[0.49446177, 0.4909543 , 0.5304416 ]],
<BLANKLINE>
[[0.53114057, 0.53538376, 0.5467784 ],
[0.53761804, 0.533159 , 0.554437 ],
[0.5470889 , 0.54905874, 0.57109433]],
<BLANKLINE>
[[0.5599331 , 0.554316 , 0.5618426 ],
[0.5763055 , 0.5668046 , 0.5774939 ],
[0.59571505, 0.60118765, 0.59942234]]] 1e-17 erg / (Angstrom s spaxel cm2)>, spectral_axis=<SpectralAxis
<Spectrum1D(flux=[[[0.4892023205757141 ... 0.5994223356246948]]] 1e-17 erg / (Angstrom s spaxel cm2) (shape=(3, 3, 3), mean=0.54165 1e-17 erg / (Angstrom s spaxel cm2)); spectral_axis=<SpectralAxis
(observer to target:
radial_velocity=0.0 km / s
redshift=0.0)
[5.73984286e-07, 5.74116466e-07, 5.74248676e-07] m>, uncertainty=InverseVariance([[[4324.235 , 4326.87 , 4268.985 ],
[5128.3867, 5142.5005, 4998.457 ],
[4529.9097, 4545.8345, 4255.305 ]],
<BLANKLINE>
[[4786.163 , 4811.216 , 4735.3135],
[4992.71 , 5082.1294, 4927.881 ],
[4992.9683, 5046.971 , 4798.005 ]],
<BLANKLINE>
[[4831.2236, 4887.096 , 4806.84 ],
[3895.8677, 4027.9104, 3896.0195],
[4521.258 , 4630.997 , 4503.0396]]]))>
[5.73984286e-07 5.74116466e-07 5.74248676e-07] m> (length=3); uncertainty=InverseVariance)>


Spectral slab extraction
Expand All @@ -90,31 +70,11 @@ spectral regions from the cube.
>>> ss.shape # doctest: +REMOTE_DATA
(74, 74, 3)
>>> ss[30:33,30:33,::] # doctest: +REMOTE_DATA
<Spectrum1D(flux=<Quantity [[[0.6103081 , 0.95697385, 1.0791174 ],
[0.5663384 , 0.8872061 , 1.0814004 ],
[0.520966 , 0.7819859 , 1.024845 ]],
<BLANKLINE>
[[0.64514536, 0.96376216, 1.083235 ],
[0.6112465 , 0.89025146, 1.058679 ],
[0.56316894, 0.77895504, 0.99165994]],
<BLANKLINE>
[[0.65954393, 0.9084677 , 0.9965009 ],
[0.6255246 , 0.84401435, 0.9930112 ],
[0.59066033, 0.762025 , 0.9361185 ]]] 1e-17 erg / (Angstrom s spaxel cm2)>, spectral_axis=<SpectralAxis
<Spectrum1D(flux=[[[0.6103081107139587 ... 0.936118483543396]]] 1e-17 erg / (Angstrom s spaxel cm2) (shape=(3, 3, 3), mean=0.83004 1e-17 erg / (Angstrom s spaxel cm2)); spectral_axis=<SpectralAxis
(observer to target:
radial_velocity=0.0 km / s
redshift=0.0)
[5.00034537e-07, 5.00149688e-07, 5.00264865e-07] m>, uncertainty=InverseVariance([[[3449.242 , 2389.292 , 2225.105 ],
[4098.7485, 2965.88 , 2632.497 ],
[3589.92 , 2902.7622, 2292.3823]],
<BLANKLINE>
[[3563.3342, 2586.58 , 2416.039 ],
[4090.8855, 3179.1702, 2851.823 ],
[4158.919 , 3457.0115, 2841.1965]],
<BLANKLINE>
[[3684.6013, 3056.2 , 2880.6592],
[3221.7888, 2801.3518, 2525.541 ],
[3936.68 , 3461.534 , 3047.6135]]]))>
[5.00034537e-07 5.00149688e-07 5.00264865e-07] m> (length=3); uncertainty=InverseVariance)>


Spectral Bounding Region
Expand Down
76 changes: 9 additions & 67 deletions docs/spectrum1d.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,7 @@ a loader.
>>> import urllib
>>> specs = urllib.request.urlopen('https://data.sdss.org/sas/dr14/sdss/spectro/redux/26/spectra/0751/spec-0751-52251-0160.fits') # doctest: +REMOTE_DATA
>>> Spectrum1D.read(specs, format="SDSS-III/IV spec") # doctest: +REMOTE_DATA
<Spectrum1D(flux=<Quantity [30.596626,...]...>
<Spectrum1D(flux=[30.59662628173828 ... 51.70271682739258] 1e-17 erg / (Angstrom s cm2) (shape=(3841,), mean=51.88042 1e-17 erg / (Angstrom s cm2)); spectral_axis=<SpectralAxis [3799.2686 3800.1426 3801.0188 ... 9193.905 9196.0205 9198.141 ] Angstrom> (length=3841); uncertainty=InverseVariance)>

Note that the same spectrum could be more conveniently downloaded via
astroquery, if the user has that package installed:
Expand All @@ -74,7 +74,7 @@ astroquery, if the user has that package installed:
>>> from astroquery.sdss import SDSS # doctest: +REMOTE_DATA
>>> specs = SDSS.get_spectra(plate=751, mjd=52251, fiberID=160, data_release=14) # doctest: +REMOTE_DATA
>>> Spectrum1D.read(specs[0], format="SDSS-III/IV spec") # doctest: +REMOTE_DATA
<Spectrum1D(flux=<Quantity [30.596626,...]...>
<Spectrum1D(flux=[30.59662628173828 ... 51.70271682739258] 1e-17 erg / (Angstrom s cm2) (shape=(3841,), mean=51.88042 1e-17 erg / (Angstrom s cm2)); spectral_axis=<SpectralAxis [3799.2686 3800.1426 3801.0188 ... 9193.905 9196.0205 9198.141 ] Angstrom> (length=3841); uncertainty=InverseVariance)>


List of Loaders
Expand Down Expand Up @@ -326,69 +326,11 @@ value will apply to the lower bound input.
>>> lower = [SpectralCoord(4.9, unit=u.um), SkyCoord(ra=205, dec=26, unit=u.deg)]
>>> upper = [SpectralCoord(4.9, unit=u.um), SkyCoord(ra=205.5, dec=27.5, unit=u.deg)]
>>> spec.crop(lower, upper) # doctest: +IGNORE_WARNINGS +FLOAT_CMP
<Spectrum1D(flux=<Quantity [[[0.70861236],
[0.5663815 ],
[0.0606386 ],
[0.13811995],
[0.8974065 ]],
<BLANKLINE>
[[0.97618597],
[0.870499 ],
[0.01522275],
[0.59180312],
[0.29160346]],
<BLANKLINE>
[[0.13274479],
[0.99381789],
[0.767089 ],
[0.73765335],
[0.36185756]],
<BLANKLINE>
[[0.09635759],
[0.38060021],
[0.63263223],
[0.60785285],
[0.4914904 ]],
<BLANKLINE>
[[0.83173506],
[0.1679683 ],
[0.39415721],
[0.25540459],
[0.39779061]],
<BLANKLINE>
[[0.27625437],
[0.90381118],
[0.65453332],
[0.64141404],
[0.36941242]],
<BLANKLINE>
[[0.90620901],
[0.41437874],
[0.71279457],
[0.41105785],
[0.7459662 ]],
<BLANKLINE>
[[0.57160214],
[0.45227951],
[0.29112881],
[0.44654224],
[0.65356417]],
<BLANKLINE>
[[0.60171961],
[0.46916617],
[0.3919754 ],
[0.01304226],
[0.32085301]],
<BLANKLINE>
[[0.00470581],
[0.54743546],
[0.24740782],
[0.77903598],
[0.63457146]]] Jy>, spectral_axis=<SpectralAxis
(observer to target:
radial_velocity=0.0 km / s
redshift=0.0)
[4.90049987e-06] m>)>
<Spectrum1D(flux=[[[0.708612359963129 ... 0.6345714580773677]]] Jy (shape=(10, 5, 1), mean=0.49653 Jy); spectral_axis=<SpectralAxis
(observer to target:
radial_velocity=0.0 km / s
redshift=0.0)
[4.90049987e-06] m> (length=1))>

Collapsing
----------
Expand All @@ -415,11 +357,11 @@ spectral axis, or 'spatial', which will collapse along all non-spectral axes.

>>> spec.mean(axis='spatial') # doctest: +FLOAT_CMP
<Spectrum1D(flux=<Quantity [0.37273938, 0.53843905, 0.61351648, 0.57311623, 0.44339915,
0.66084728, 0.45881921, 0.38715911, 0.39967185, 0.53257671] Jy>, spectral_axis=<SpectralAxis
0.66084728, 0.45881921, 0.38715911, 0.39967185, 0.53257671] Jy> (shape=(10,), mean=0.49803 Jy); spectral_axis=<SpectralAxis
(observer to target:
radial_velocity=0.0 km / s
redshift=0.0)
[5000., 5001., 5002., 5003., 5004., 5005., 5006., 5007., 5008., 5009.] Angstrom>)>
[5000. 5001. 5002. ... 5007. 5008. 5009.] Angstrom> (length=10))>

Note that in this case, the result of the collapse operation is a
`~specutils.Spectrum1D` rather than an `astropy.units.Quantity`, because the
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