Updates from the package template

.cruft.json

@@ -1,6 +1,6 @@
 {
   "template": "https://github.com/sunpy/package-template",
-  "commit": "d6b86e07efa31959f43e99ba32d323cf76736a05",
+  "commit": "37ffb52646450caa4de8ea084725dbff65fe0995",
   "checkout": null,
   "context": {
     "cookiecutter": {
@@ -32,7 +32,7 @@
         ".github/workflows/sub_package_update.yml"
       ],
       "_template": "https://github.com/sunpy/package-template",
-      "_commit": "d6b86e07efa31959f43e99ba32d323cf76736a05"
+      "_commit": "37ffb52646450caa4de8ea084725dbff65fe0995"
     }
   },
   "directory": null

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 repos:
     # This should be before any formatting hooks like isort
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.8.6"
+    rev: "v0.9.2"
     hooks:
       - id: ruff
         args: ["--fix"]
@@ -27,7 +27,7 @@ repos:
       - id: mixed-line-ending
         exclude: ".*(.fits|.fts|.fit|.header|.txt|tca.*)$"
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.3.0
+    rev: v2.4.0
     hooks:
       - id: codespell
         additional_dependencies:

.ruff.toml

@@ -54,6 +54,7 @@ extend-ignore = [
   "N802", # Function name should be lowercase
   "N803", # Argument name should be lowercase
   "N806", # Variable in function should be lowercase
+  "A005", # Module `io` shadows a Python standard-library module
 ]
 
 [lint.per-file-ignores]

sunkit_spex/legacy/emission.py

@@ -525,7 +525,7 @@ def _split_and_integrate(*, model, photon_energies, maxfcn, rerr, eelow, eebrk,
     clight = const.get_constant("clight")
 
     if not eelow <= eebrk <= eehigh:
-        raise ValueError(f"Condition eelow <= eebrek <= eehigh not satisfied " f"({eelow}<={eebrk}<={eehigh}).")
+        raise ValueError(f"Condition eelow <= eebrek <= eehigh not satisfied ({eelow}<={eebrk}<={eehigh}).")
 
     # Create arrays for integral sums and error flags.
     intsum1 = np.zeros_like(photon_energies, dtype=np.float64)
@@ -740,7 +740,7 @@ def bremsstrahlung_thin_target(photon_energies, p, eebrk, q, eelow, eehigh, efd=
         flux *= fcoeff
 
         return flux
-    raise Warning("The photon energies are higher than the highest electron energy or not " "greater than zero")
+    raise Warning("The photon energies are higher than the highest electron energy or not greater than zero")
 
 
 def bremsstrahlung_thick_target(photon_energies, p, eebrk, q, eelow, eehigh, integrator=None):
@@ -835,4 +835,4 @@ def bremsstrahlung_thick_target(photon_energies, p, eebrk, q, eelow, eehigh, int
 
         return (fcoeff / decoeff) * flux
 
-    raise Warning("The photon energies are higher than the highest electron energy or not " "greater than zero")
+    raise Warning("The photon energies are higher than the highest electron energy or not greater than zero")

sunkit_spex/legacy/fitting/photon_models_for_fitting.py

@@ -18,7 +18,7 @@
 defined_photon_models = {
     "f_vth": ["T", "EM"],
     "thick_fn": ["total_eflux", "index", "e_c"],
-    "thick_warm": ["tot_eflux", "indx", "ec", "plasma_d", "loop_temp", "length"],
+    "thick_warm": ["tot_eflux", "index", "ec", "plasma_d", "loop_temp", "length"],
 }
 
 

sunkit_spex/legacy/integrate.py

@@ -154,6 +154,6 @@ def fixed_quad(func, a, b, n=5, args=(), func_kwargs={}):
     x, w = _cached_roots_legendre(n)
     x = np.real(x)
     if np.any(np.isinf(a)) or np.any(np.isinf(b)):
-        raise ValueError("Gaussian quadrature is only available for " "finite limits.")
+        raise ValueError("Gaussian quadrature is only available for finite limits.")
     y = (b - a).reshape(-1, 1) * (x + 1) / 2.0 + a.reshape(-1, 1)
     return np.squeeze((b - a).reshape(1, -1) / 2.0 * np.sum(w * func(y, *args, **func_kwargs), axis=1))

sunkit_spex/legacy/thermal.py

@@ -551,11 +551,11 @@ def _calculate_abundance_normalized_line_intensities(logT, data_grid, line_logT_
     for i in range(n_temperatures):
         # Identify the "temperature" bin to which the input "temperature"
         # corresponds and its two nearest neighbors.
-        indx = temperature_bins[i] - 1 + np.arange(3)
+        index = temperature_bins[i] - 1 + np.arange(3)
         # Interpolate the 2nd axis to produce a function that gives the data
         # as a function of 1st axis, say energy, at a given value along the 2nd axis,
         # say "temperature".
-        get_intensities_at_logT = interpolate.interp1d(line_logT_bins[indx], data_grid[:, indx], kind="quadratic")
+        get_intensities_at_logT = interpolate.interp1d(line_logT_bins[index], data_grid[:, index], kind="quadratic")
         # Use function to get interpolated_data as a function of the first axis at
         # the input value along the 2nd axis,
         # e.g. line intensities as a function of energy at a given temperature.
@@ -733,8 +733,7 @@ def _error_if_input_outside_valid_range(input_values, grid_range, param_name, pa
             grid_range = u.Quantity(grid_range, unit=param_unit).to_value(message_unit)
             param_unit = message_unit
         message = (
-            f"All input {param_name} values must be within the range "
-            f"{grid_range[0]}--{grid_range[1]} {param_unit}. "
+            f"All input {param_name} values must be within the range {grid_range[0]}--{grid_range[1]} {param_unit}. "
         )
         raise ValueError(message)
 
@@ -925,8 +924,8 @@ def _calculate_abundances(abundance_type, relative_abundances):
 #     logt = LOGT # grid temperatures = log(temperature)
 #     ntemp = len(logt)
 #     selt = np.argwhere(logt<=u)[-1] # what gap does my temp land in the logt array (inclusive of the lower boundary)
-#     indx = np.clip([selt-1, selt, selt+1], 0, ntemp-1) # find the indexes either side of that gap
-#     tband = logt[indx]
+#     index = np.clip([selt-1, selt, selt+1], 0, ntemp-1) # find the indexes either side of that gap
+#     tband = logt[index]
 #     s=1
 #     x0, x1, x2 = tband[0][0], tband[1][0], tband[2][0] # temperatures either side of that gap
 
@@ -936,7 +935,7 @@ def _calculate_abundances(abundance_type, relative_abundances):
 
 #     # all wavelengths divided by corresponding temp[0] (first row), then exvl/temp[1] second row, exvl/temp[2] third row
 #     # inverse boltzmann factor of hv/kT and 11.6e6 from keV-to-J conversion over k = 1.6e-16 / 1.381e-23 ~ 11.6e6
-#     exponential = (np.ones((3,1)) @ ewvl_exp) / ((10**logt[indx]/11.6e6) @ np.ones((1,nwvl)))
+#     exponential = (np.ones((3,1)) @ ewvl_exp) / ((10**logt[index]/11.6e6) @ np.ones((1,nwvl)))
 #     exponential = np.exp(np.clip(exponential, None, 80)) #  not sure why clipping at 80
 #     # this is just from dE/dA = E/A from E=hc/A (A=wavelength) for change of variables from Angstrom to keV: dE = dA * (E/A)
 #     # have this repeated for 3 rows since this is the form of the expontial's different temps
@@ -966,7 +965,7 @@ def _calculate_abundances(abundance_type, relative_abundances):
 #     # totcont_lo is the continuum <1 keV I think and totcont is >=1 keV, so adding the wavelength dimension of each of these you get the number of wavlengths provided by continuum_info[1]['edge_str']['WVL']
 #     # look here for more info on how the CHIANTI file is set-up **** https://hesperia.gsfc.nasa.gov/ssw/packages/xray/idl/setup_chianti_cont.pro ****
 #     # this exact script won't create the folder Python is using the now since some of the wavelengths and deltas don't match-up
-#     totcontindx = np.concatenate((continuum_info[1]["totcont_lo"][:, indx.T[0], :], continuum_info[1]["totcont"][:, indx.T[0], :]), axis=2) # isolate temps and then combine along wavelength axis
+#     totcontindx = np.concatenate((continuum_info[1]["totcont_lo"][:, index.T[0], :], continuum_info[1]["totcont"][:, index.T[0], :]), axis=2) # isolate temps and then combine along wavelength axis
 #     # careful from here on out. IDL's indexes are backwards to Pythons
 #     # Python's a[:,:,0] == IDL's a[0,*,*], a[:,0,:] == a[*,0,*], and then a[0,:,:] == a[*,*,0]
 #     tcdbase = totcontindx # double(totcontindx[*, *, *])

sunkit_spex/models/physical/thermal.py

@@ -555,11 +555,11 @@ def _calculate_abundance_normalized_line_intensities(logT, data_grid, line_logT_
     for i in range(n_temperatures):
         # Identify the "temperature" bin to which the input "temperature"
         # corresponds and its two nearest neighbors.
-        indx = temperature_bins[i] - 1 + np.arange(3)
+        index = temperature_bins[i] - 1 + np.arange(3)
         # Interpolate the 2nd axis to produce a function that gives the data
         # as a function of 1st axis, say energy, at a given value along the 2nd axis,
         # say "temperature".
-        get_intensities_at_logT = interpolate.interp1d(line_logT_bins[indx], data_grid[:, indx], kind="quadratic")
+        get_intensities_at_logT = interpolate.interp1d(line_logT_bins[index], data_grid[:, index], kind="quadratic")
         # Use function to get interpolated_data as a function of the first axis at
         # the input value along the 2nd axis,
         # e.g. line intensities as a function of energy at a given temperature.
@@ -737,8 +737,7 @@ def _error_if_input_outside_valid_range(input_values, grid_range, param_name, pa
             grid_range = u.Quantity(grid_range, unit=param_unit).to_value(message_unit)
             param_unit = message_unit
         message = (
-            f"All input {param_name} values must be within the range "
-            f"{grid_range[0]}--{grid_range[1]} {param_unit}. "
+            f"All input {param_name} values must be within the range {grid_range[0]}--{grid_range[1]} {param_unit}. "
         )
         raise ValueError(message)
 
@@ -929,8 +928,8 @@ def _calculate_abundances(abundance_type, relative_abundances):
 #     logt = LOGT # grid temperatures = log(temperature)
 #     ntemp = len(logt)
 #     selt = np.argwhere(logt<=u)[-1] # what gap does my temp land in the logt array (inclusive of the lower boundary)
-#     indx = np.clip([selt-1, selt, selt+1], 0, ntemp-1) # find the indexes either side of that gap
-#     tband = logt[indx]
+#     index = np.clip([selt-1, selt, selt+1], 0, ntemp-1) # find the indexes either side of that gap
+#     tband = logt[index]
 #     s=1
 #     x0, x1, x2 = tband[0][0], tband[1][0], tband[2][0] # temperatures either side of that gap
 
@@ -940,7 +939,7 @@ def _calculate_abundances(abundance_type, relative_abundances):
 
 #     # all wavelengths divided by corresponding temp[0] (first row), then exvl/temp[1] second row, exvl/temp[2] third row
 #     # inverse boltzmann factor of hv/kT and 11.6e6 from keV-to-J conversion over k = 1.6e-16 / 1.381e-23 ~ 11.6e6
-#     exponential = (np.ones((3,1)) @ ewvl_exp) / ((10**logt[indx]/11.6e6) @ np.ones((1,nwvl)))
+#     exponential = (np.ones((3,1)) @ ewvl_exp) / ((10**logt[index]/11.6e6) @ np.ones((1,nwvl)))
 #     exponential = np.exp(np.clip(exponential, None, 80)) #  not sure why clipping at 80
 #     # this is just from dE/dA = E/A from E=hc/A (A=wavelength) for change of variables from Angstrom to keV: dE = dA * (E/A)
 #     # have this repeated for 3 rows since this is the form of the expontial's different temps
@@ -970,7 +969,7 @@ def _calculate_abundances(abundance_type, relative_abundances):
 #     # totcont_lo is the continuum <1 keV I think and totcont is >=1 keV, so adding the wavelength dimension of each of these you get the number of wavlengths provided by continuum_info[1]['edge_str']['WVL']
 #     # look here for more info on how the CHIANTI file is set-up **** https://hesperia.gsfc.nasa.gov/ssw/packages/xray/idl/setup_chianti_cont.pro ****
 #     # this exact script won't create the folder Python is using the now since some of the wavelengths and deltas don't match-up
-#     totcontindx = np.concatenate((continuum_info[1]["totcont_lo"][:, indx.T[0], :], continuum_info[1]["totcont"][:, indx.T[0], :]), axis=2) # isolate temps and then combine along wavelength axis
+#     totcontindx = np.concatenate((continuum_info[1]["totcont_lo"][:, index.T[0], :], continuum_info[1]["totcont"][:, index.T[0], :]), axis=2) # isolate temps and then combine along wavelength axis
 #     # careful from here on out. IDL's indexes are backwards to Pythons
 #     # Python's a[:,:,0] == IDL's a[0,*,*], a[:,0,:] == a[*,0,*], and then a[0,:,:] == a[*,*,0]
 #     tcdbase = totcontindx # double(totcontindx[*, *, *])

sunkit_spex/spectrum/spectrum.py

@@ -9,6 +9,7 @@
 from astropy.utils import lazyproperty
 
 __all__ = ["SpectralAxis", "Spectrum", "gwcs_from_array"]
+__doctest_requires__ = {"Spectrum": ["ndcube>=2.3"]}
 
 
 def gwcs_from_array(array):
@@ -158,7 +159,7 @@ class Spectrum(NDCube):
     <sunkit_spex.spectrum.spectrum.Spectrum object at ...
     NDCube
     ------
-    Dimensions: [10.] pix
+    Shape: (10,)
     Physical Types of Axes: [('em.energy',)]
     Unit: W
     Data Type: float64
@@ -204,7 +205,7 @@ def __init__(
         if spectral_axis is not None:
             # Ensure that the spectral axis is an astropy Quantity
             if not isinstance(spectral_axis, u.Quantity):
-                raise ValueError("Spectral axis must be a `Quantity` or " "`SpectralAxis` object.")
+                raise ValueError("Spectral axis must be a `Quantity` or `SpectralAxis` object.")
 
             # If a spectral axis is provided as an astropy Quantity, convert it
             # to a SpectralAxis object.