Add test coverage

CHANGES.rst

@@ -13,7 +13,7 @@ Bug Fixes
 - Output 1D spectra from Background no longer include NaNs. Output 1D
 spectra from BoxcarExtract no longer include NaNs when none are present
 in the extraction window. NaNs in the window will still propagate to
-Boxcar1D's extracted 1D spectrum. [#159]
+BoxcarExtract's extracted 1D spectrum. [#159]
 
 - Backgrounds using median statistic properly ignore zero-weighted pixels
 [#159]

specreduce/tests/test_background.py

@@ -13,11 +13,11 @@
 # Test image is comprised of 30 rows with 10 columns each. Row content
 # is row index itself. This makes it easy to predict what should be the
 # value extracted from a region centered at any arbitrary Y position.
-image = np.ones(shape=(30, 10))
-for j in range(image.shape[0]):
-    image[j, ::] *= j
-image = Spectrum1D(image * u.DN,
-                   uncertainty=VarianceUncertainty(np.ones_like(image)))
+img = np.ones(shape=(30, 10))
+for j in range(img.shape[0]):
+    img[j, ::] *= j
+image = Spectrum1D(img * u.DN,
+                   uncertainty=VarianceUncertainty(np.ones_like(img)))
 image_um = Spectrum1D(image.flux,
                       spectral_axis=np.arange(image.data.shape[1]) * u.um,
                       uncertainty=VarianceUncertainty(np.ones_like(image.data)))
@@ -28,7 +28,7 @@ def test_background():
     # Try combinations of extraction center, and even/odd
     # extraction aperture sizes.
     #
-    trace_pos = 15.0
+    trace_pos = 15
     trace = FlatTrace(image, trace_pos)
     bkg_sep = 5
     bkg_width = 2
@@ -72,10 +72,25 @@ def test_background():
     assert isinstance(bkg_spec, Spectrum1D)
     sub_spec = bg1.sub_spectrum()
     assert isinstance(sub_spec, Spectrum1D)
+
     # test that width==0 results in no background
     bg = Background.two_sided(image, trace, bkg_sep, width=0)
     assert np.all(bg.bkg_image().flux == 0)
 
+    # test that any NaNs in input image (whether in or outside the window) don't
+    # propagate to _bkg_array (which affects bkg_image and sub_image methods) or
+    # the final 1D spectra.
+    img[0, 0] = np.nan  # out of window
+    img[trace_pos, 0] = np.nan  # in window
+    stats = ['average', 'median']
+
+    for st in stats:
+        bg = Background(img, trace-bkg_sep, width=bkg_width, statistic=st)
+        assert np.isnan(bg.image.flux).sum() == 2
+        assert np.isnan(bg._bkg_array).sum() == 0
+        assert np.isnan(bg.bkg_spectrum().flux).sum() == 0
+        assert np.isnan(bg.sub_spectrum().flux).sum() == 0
+
 
 def test_warnings_errors():
     # image.shape (30, 10)