Use simpler checks for invalid values

specreduce/core.py

@@ -63,7 +63,7 @@ def _parse_image(self, image, disp_axis=1):
         if getattr(image, 'mask', None) is not None:
             mask = image.mask
         else:
-            mask = np.ma.masked_invalid(img).mask
+            mask = ~np.isfinite(img)
 
         if getattr(image, 'uncertainty', None) is not None:
             uncertainty = image.uncertainty

specreduce/extract.py

@@ -357,7 +357,7 @@ def _parse_image(self, image,
         elif mask is not None:
             pass
         else:
-            mask = np.ma.masked_invalid(img).mask
+            mask = ~np.isfinite(img)
 
         if img.shape != mask.shape:
             raise ValueError('image and mask shapes must match.')
@@ -486,7 +486,7 @@ def __call__(self, image=None, trace_object=None,
 
         # mask any previously uncaught invalid values
         or_mask = np.logical_or(mask,
-                                np.ma.masked_invalid(self.image.data).mask)
+                                ~np.isfinite(self.image.data))
         img = np.ma.masked_array(self.image.data, or_mask)
         mask = img.mask
 

specreduce/tests/test_image_parsing.py

@@ -9,6 +9,7 @@
 from specreduce.tracing import FlatTrace
 from specutils import Spectrum1D, SpectralAxis
 
+
 # fetch test image
 fn = download_file('https://stsci.box.com/shared/static/exnkul627fcuhy5akf2gswytud5tazmw.fits',
                    cache=True)
@@ -96,7 +97,7 @@ def test_parse_horne():
             # requires a variance, so it's chosen here to be on equal footing
             # with the general case
             defaults = {'variance': unc_def,
-                        'mask': np.ma.masked_invalid(img).mask,
+                        'mask': ~np.isfinite(img),
                         'unit': getattr(img, 'unit', u.DN)}
 
         col[key] = HorneExtract._parse_image(object, img, **defaults)

specreduce/tests/test_tracing.py

@@ -144,15 +144,15 @@ def test_fit_trace():
     try:
         FitTrace(img_win_nans, guess=guess, window=window)
     except ValueError as e:
-        print(f"All-NaN window error message: {e}")
+        print(f"(expected) All-NaN window error message: {e}")
     else:
         raise RuntimeError('Trace was erroneously calculated on all-NaN window')
 
     # error on trace of all-nan image
     try:
         FitTrace(img_all_nans)
     except ValueError as e:
-        print(f"All-NaN image error message: {e}")
+        print(f"(expected) All-NaN image error message: {e}")
     else:
         raise RuntimeError('Trace was erroneously calculated on all-NaN image')
 

specreduce/tracing.py

@@ -212,8 +212,7 @@ def __post_init__(self):
         self.image = self._parse_image(self.image)
 
         # mask any previously uncaught invalid values
-        or_mask = np.logical_or(self.image.mask,
-                                np.ma.masked_invalid(self.image.data).mask)
+        or_mask = np.logical_or(self.image.mask, ~np.isfinite(self.image.data))
         img = np.ma.masked_array(self.image.data, or_mask)
 
         # validate arguments