Went back to = over :, other improvements

astropy · Feb 12, 2024 · 160c09e · 160c09e
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diff --git a/docs/arithmetic.rst b/docs/arithmetic.rst
@@ -29,10 +29,10 @@ 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:  shape (49,), mean=0.91592 Jy; spectral_axis: <SpectralAxis
-        (observer to target:
-           radial_velocity=0.0 km / s
-           redshift=0.0)
+    <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. ... 47. 48. 49.] nm> (length=49))>
 
 

diff --git a/docs/manipulation.rst b/docs/manipulation.rst
@@ -59,7 +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:  shape (49,), mean=0.48009 Jy; spectral_axis: <SpectralAxis [ 1.  2.  3. ... 47. 48. 49.] nm> (length=49))>
+    <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`
@@ -75,7 +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:  shape (49,), mean=0.49378 Jy; spectral_axis: <SpectralAxis [ 1.  2.  3. ... 47. 48. 49.] nm> (length=49))>
+    <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,
@@ -107,7 +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:  shape (49,), mean=0.48620 Jy; spectral_axis: <SpectralAxis [ 1.  2.  3. ... 47. 48. 49.] nm> (length=49))>
+    <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
 ----------
@@ -333,16 +333,16 @@ the ``spectral_axis``. Therefore one can use a construct like this:
     >>> flux = 100 * np.abs(np.random.default_rng(42).standard_normal(10)) * u.Jy
     >>> spectrum = Spectrum1D(spectral_axis=wavelengths, flux=flux)
     >>> 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>, mean=76.02860 Jy; spectral_axis: <SpectralAxis [0. 1. 2. ... 7. 8. 9.] um> (length=10))>
+    <Spectrum1D(flux=<Quantity [ 30.47170798, 103.99841062,  75.04511958,  94.05647164,
+               195.10351887, 130.21795069,  12.78404032,  31.62425923,
+                 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,
+    <Spectrum1D(flux=<Quantity [ 30.47170798, 103.99841062,  75.04511958,  94.05647164,
                195.10351887, 130.21795069,  12.78404032,  31.62425923,
-                 1.68011575,  85.30439276] Jy>, mean=76.02860 Jy; spectral_axis: <SpectralAxis [ 1.23  2.23  3.23 ...  8.23  9.23 10.23] um> (length=10))>
+                 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
 ------------------
@@ -364,7 +364,7 @@ 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>, mean=11.00000 mJy; spectral_axis: <SpectralAxis [ 1.  2.  3. ...  8.  9. 10.] Angstrom> (length=10))>
+    <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:
@@ -374,7 +374,7 @@ 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>, mean=4.40000 mJy; spectral_axis: <SpectralAxis [ 1.  2.  3. ...  8.  9. 10.] Angstrom> (length=10))>
+    <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:
@@ -385,7 +385,7 @@ 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>, mean=11.00000 mJy; spectral_axis: <SpectralAxis [ 1.  2.  3. ...  8.  9. 10.] Angstrom> (length=10))>
+    <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:
 
@@ -400,8 +400,8 @@ A model fitted over the region can also be used to replace the spectrum flux val
     >>> region = SpectralRegion(3.5*u.AA, 7.1*u.AA)
     >>> 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>, mean=2.67887 mJy; spectral_axis: <SpectralAxis [ 1.  2.  3. ...  8.  9. 10.] Angstrom> (length=10))>
+    <Spectrum1D(flux=<Quantity [1.        , 1.1       , 0.9       , 4.40801804, 9.58271877,
+               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
 -------------

diff --git a/docs/spectral_cube.rst b/docs/spectral_cube.rst
@@ -49,11 +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:  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> (length=3); uncertainty: InverseVariance)>
+    <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> (length=3); uncertainty=InverseVariance)>
 
 
 Spectral slab extraction
@@ -70,11 +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:  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> (length=3); uncertainty: InverseVariance)>
+    <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> (length=3); uncertainty=InverseVariance)>
 
 
 Spectral Bounding Region

diff --git a/docs/spectrum1d.rst b/docs/spectrum1d.rst
@@ -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:  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)>
+    <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:
@@ -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:  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)>
+     <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
@@ -326,7 +326,7 @@ 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:  shape (10, 5, 1), mean=0.49653 Jy; spectral_axis: <SpectralAxis
+    <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)
@@ -356,8 +356,8 @@ spectral axis, or 'spatial', which will collapse along all non-spectral axes.
 .. code-block:: python
 
     >>> 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>, mean=0.49803 Jy; spectral_axis: <SpectralAxis
+    <Spectrum1D(flux=<Quantity [0.37273938, 0.53843905, 0.61351648, 0.57311623, 0.44339915,
+               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)

diff --git a/specutils/manipulation/model_replace.py b/specutils/manipulation/model_replace.py
@@ -65,7 +65,7 @@ def model_replace(spectrum, replace_region, model=10, extrapolation_treatment='d
     >>> input_spectrum = Spectrum1D(spectral_axis=wave_val * u.AA, flux=flux_val * u.mJy)
     >>> spline_knots = [3.5, 4.7, 6.8, 7.1] * u.AA
     >>> model_replace(input_spectrum, None, spline_knots)
-    <Spectrum1D(flux: <Quantity [ 2.,  4.,  6.,  8., 10., 12., 14., 16., 18., 20.] mJy>, mean=11.00000 mJy; spectral_axis: <SpectralAxis [ 1.  2.  3. ...  8.  9. 10.] Angstrom> (length=10))>
+    <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))>
 
     """
     if extrapolation_treatment not in ('data_fill', 'zero_fill'):

diff --git a/specutils/manipulation/resample.py b/specutils/manipulation/resample.py
@@ -74,7 +74,9 @@ class FluxConservingResampler(ResamplerBase):
     >>> resample_grid = [1, 5, 9, 13, 14, 17, 21, 22, 23]  *u.nm
     >>> fluxc_resample = FluxConservingResampler()
     >>> fluxc_resample(input_spectra, resample_grid)  # doctest: +FLOAT_CMP
-    <Spectrum1D(flux: <Quantity [  nan,  3.  ,  6.  ,  7.  ,  6.25, 10.  , 20.  ,   nan,   nan] mJy>, mean=8.70833 mJy; spectral_axis: <SpectralAxis [ 1.  5.  9. ... 21. 22. 23.] nm> (length=9))>    """
+    <Spectrum1D(flux=<Quantity [  nan,  3.  ,  6.  ,  7.  ,  6.25, 10.  , 20.  ,   nan,   nan] mJy> (shape=(9,), mean=8.70833 mJy); spectral_axis=<SpectralAxis [ 1.  5.  9. ... 21. 22. 23.] nm> (length=9))>
+
+    """
 
     def _fluxc_resample(self, input_bin_centers, output_bin_centers,
                         input_bin_fluxes, errs):
@@ -322,7 +324,7 @@ class LinearInterpolatedResampler(ResamplerBase):
     >>> resample_grid = [1, 5, 9, 13, 14, 17, 21, 22, 23] * u.nm
     >>> fluxc_resample = LinearInterpolatedResampler()
     >>> fluxc_resample(input_spectra, resample_grid)  # doctest: +FLOAT_CMP
-    <Spectrum1D(flux: <Quantity [ nan, 3.5 , 5.5 , 6.75, 6.5 , 9.5 ,  nan,  nan,  nan] mJy>, mean=6.35000 mJy; spectral_axis: <SpectralAxis [ 1.  5.  9. ... 21. 22. 23.] nm> (length=9))>
+    <Spectrum1D(flux=<Quantity [ nan, 3.5 , 5.5 , 6.75, 6.5 , 9.5 ,  nan,  nan,  nan] mJy> (shape=(9,), mean=6.35000 mJy); spectral_axis=<SpectralAxis [ 1.  5.  9. ... 21. 22. 23.] nm> (length=9))>
 
     """
     def __init__(self, extrapolation_treatment='nan_fill'):
@@ -398,8 +400,8 @@ class SplineInterpolatedResampler(ResamplerBase):
     >>> resample_grid = [1, 5, 9, 13, 14, 17, 21, 22, 23] * u.nm
     >>> fluxc_resample = SplineInterpolatedResampler()
     >>> fluxc_resample(input_spectra, resample_grid)  # doctest: +FLOAT_CMP
-    <Spectrum1D(flux: <Quantity [       nan, 3.98808594, 6.94042969, 6.45869141, 5.89921875,
-               7.29736328,        nan,        nan,        nan] mJy>, mean=6.11676 mJy; spectral_axis: <SpectralAxis [ 1.  5.  9. ... 21. 22. 23.] nm> (length=9))>
+    <Spectrum1D(flux=<Quantity [       nan, 3.98808594, 6.94042969, 6.45869141, 5.89921875,
+               7.29736328,        nan,        nan,        nan] mJy> (shape=(9,), mean=6.11676 mJy); spectral_axis=<SpectralAxis [ 1.  5.  9. ... 21. 22. 23.] nm> (length=9))>
 
     """
     def __init__(self, bin_edges='nan_fill'):

diff --git a/specutils/spectra/spectrum1d.py b/specutils/spectra/spectrum1d.py
@@ -727,7 +727,7 @@ def _format_array_summary(self, label, array):
         array_str = np.array2string(array, threshold=8, prefix=label)
         if len(array) >= 1:
             mean = np.nanmean(array)
-            s = f"{label} {array_str} {array.unit},  mean={mean:.5f}"
+            s = f"{label}{array_str} {array.unit},  mean={mean:.5f}"
             return s
         else:
             return "{:17} [ ],  mean= n/a".format(label+':')
@@ -737,32 +737,37 @@ def __str__(self):
         result += "(length={})\n".format(len(self.spectral_axis))
 
         # Add Flux information
-        result += self._format_array_summary('Flux:', self.flux) + '\n'
+        result += self._format_array_summary('Flux=', self.flux) + '\n'
 
         # Add information about spectral axis
-        result += self._format_array_summary('Spectral Axis:', self.spectral_axis)
+        result += self._format_array_summary('Spectral Axis=', self.spectral_axis)
 
         # Add information about uncertainties if available
         if self.uncertainty:
-            result += (f'\nUncertainty: {type(self.uncertainty).__name__} '
+            result += (f'\nUncertainty={type(self.uncertainty).__name__} '
                        f'({np.array2string(self.uncertainty.array, threshold=8)}'
                        f' {self.uncertainty.unit})')
 
         return result
 
     def __repr__(self):
+        flux_str  = "flux="
         if (self.flux.ndim == 1 and self.flux.size <= 10) or self.flux.size <= 20:
-            flux_str = repr(self.flux)
+            flux_str += repr(self.flux)
         else:
-            flux_str = f" shape {self.flux.shape}"
+            flux_summary = f"{self.flux.value.flat[0]} ... {self.flux.value.flat[-1]}"
+            flux_str = flux_str + "[" * self.flux.ndim + flux_summary + "]" * self.flux.ndim
+            flux_str += f" {self.flux.unit}"
+
+        flux_str += f" (shape={self.flux.shape}, mean={np.nanmean(self.flux):.5f}); "
         spectral_axis_str = (repr(self.spectral_axis).split("[")[0] +
                              np.array2string(self.spectral_axis, threshold=8) +
                              f" {self.spectral_axis.unit}>")
-        inner_str = (f"flux: {flux_str}, mean={np.nanmean(self.flux):.5f}; "
-                     f"spectral_axis: {spectral_axis_str} (length={len(self.spectral_axis)})")
+        spectral_axis_str = f"spectral_axis={spectral_axis_str} (length={len(self.spectral_axis)})"
+        inner_str = (flux_str + spectral_axis_str)
 
         if self.uncertainty is not None:
-            inner_str += f"; uncertainty: {self.uncertainty.__class__.__name__}"
+            inner_str += f"; uncertainty={self.uncertainty.__class__.__name__}"
 
         result = "<Spectrum1D({})>".format(inner_str)