Coverage tests for extract1d

jwst/extract_1d/extract1d.py

@@ -307,7 +307,7 @@ def extract1d(image, profiles_2d, variance_rn, variance_phnoise, variance_flat,
 
         else:
             raise ValueError("bkg_fit_type should be 'median' or 'poly'. "
-                             "If 'poly', bkg_order must be a nonnegative integer.")
+                             "If 'poly', bkg_order must be an integer >= 0.")
 
         image_sub = image - bkg_2d
     else:

jwst/extract_1d/tests/test_extract_src_flux.py

@@ -151,3 +151,12 @@ def test_extract_optimal(inputs_with_source):
     # Now the flux can no longer be estimated in that column
     assert np.isnan(total_flux[0][2])
     assert npixels[0][2] == 0.
+
+
+def test_too_many_profiles(inputs_constant):
+    (image, var_rnoise, var_poisson, var_rflat,
+     profile, weights, profile_bg) = inputs_constant
+
+    with pytest.raises(ValueError, match="not supported with 2 input profiles"):
+        extract1d.extract1d(image, [profile, profile.copy()],
+                            var_rnoise, var_poisson, var_rflat)

jwst/extract_1d/tests/test_fit_background_model.py

@@ -172,6 +172,40 @@ def test_handles_empty_interval(inputs_constant):
     assert np.allclose(b_var_flat[0], 0.0)
 
 
+def test_bad_fit_type(inputs_constant):
+    (image, var_rnoise, var_poisson, var_rflat,
+     profile, weights, profile_bg, bkg_fit, bkg_order) = inputs_constant
+    with pytest.raises(ValueError, match="bkg_fit_type should be 'median' or 'poly'"):
+        extract1d.extract1d(
+            image, [profile], var_rnoise, var_poisson, var_rflat,
+            weights=weights, profile_bg=profile_bg, fit_bkg=True,
+            bkg_fit_type='mean', bkg_order=bkg_order)
+
+
+@pytest.mark.parametrize('smooth', [1.5, 2])
+def test_smooth_length(inputs_constant, smooth):
+    (image, var_rnoise, var_poisson, var_rflat,
+     profile, weights, profile_bg, bkg_fit, bkg_order) = inputs_constant
+    with pytest.raises(ValueError, match="should be an odd integer >= 1"):
+        extract1d.extract1d(
+            image, [profile], var_rnoise, var_poisson, var_rflat,
+            weights=weights, profile_bg=profile_bg, fit_bkg=True,
+            bkg_fit_type=bkg_fit, bkg_order=bkg_order, bg_smooth_length=smooth)
+
+
+@pytest.mark.parametrize('extraction_type', ['box', 'optimal'])
+@pytest.mark.parametrize('bkg_order_val', [-1, 2.3])
+def test_bad_fit_order(inputs_constant, extraction_type, bkg_order_val):
+    (image, var_rnoise, var_poisson, var_rflat,
+     profile, weights, profile_bg, bkg_fit, bkg_order) = inputs_constant
+    with pytest.raises(ValueError, match="bkg_order must be an integer >= 0"):
+        extract1d.extract1d(
+            image, [profile], var_rnoise, var_poisson, var_rflat,
+            weights=weights, profile_bg=profile_bg, fit_bkg=True,
+            bkg_fit_type='poly', bkg_order=bkg_order_val,
+            extraction_type=extraction_type)
+
+
 @pytest.mark.parametrize('bkg_order_val', [0, 1, 2])
 def test_fit_background_optimal(inputs_with_source, bkg_order_val):
     (image, var_rnoise, var_poisson, var_rflat,