code style

specreduce/background.py

@@ -71,7 +71,7 @@ class Background(_ImageParser):
     statistic: str = 'average'
     disp_axis: int = 1
     crossdisp_axis: int = 0
-    mask_treatment : str = 'filter'
+    mask_treatment: str = 'filter'
     _valid_mask_treatment_methods = ('filter', 'omit', 'zero-fill')
 
     # TO-DO: update bkg_array with Spectrum1D alternative (is bkg_image enough?)
@@ -157,7 +157,7 @@ def __post_init__(self):
             raise ValueError("background window does not remain in bounds across entire dispersion axis")  # noqa
         # check if image contained within background window is fully-nonfinite and raise an error
         if np.all(img.mask[bkg_wimage > 0]):
-            raise ValueError("Image is fully masked within background window determined by `width`.")
+            raise ValueError("Image is fully masked within background window determined by `width`.")  # noqa
 
         if self.statistic == 'median':
             # make it clear in the expose image that partial pixels are fully-weighted

specreduce/core.py

@@ -78,7 +78,6 @@ def _parse_image(self, image, disp_axis=1):
         spectral_axis = getattr(image, 'spectral_axis',
                                 np.arange(img.shape[disp_axis]) * u.pix)
 
-
         img = Spectrum1D(img * unit, spectral_axis=spectral_axis,
                          uncertainty=uncertainty, mask=mask)
 
@@ -121,8 +120,8 @@ def _mask_and_nonfinite_data_handling(self, image, mask):
         # make sure chosen option is valid. if _valid_mask_treatment_methods
         # is not an attribue, proceed with 'filter' to return back inupt data
         # and mask that is combined with nonfinite data.
-        if mask_treatment is not None:  # None in operations where masks aren't relevant (e.g FlatTrace)
-            valid_mask_treatment_methods = getattr(self, '_valid_mask_treatment_methods', ['filter'])
+        if mask_treatment is not None:  # None in operations where masks aren't relevant (FlatTrace)
+            valid_mask_treatment_methods = getattr(self, '_valid_mask_treatment_methods', ['filter'])  # noqa
             if mask_treatment not in valid_mask_treatment_methods:
                 raise ValueError(f"`mask_treatment` must be one of {valid_mask_treatment_methods}")
 
@@ -180,19 +179,6 @@ def _mask_and_nonfinite_data_handling(self, image, mask):
 
         return image, mask
 
-    @staticmethod
-    def _get_data_from_image(image):
-        """Extract data array from various input types for `image`.
-           Retruns `np.ndarray` of image data."""
-
-        if isinstance(image, u.quantity.Quantity):
-            img = image.value
-        if isinstance(image, np.ndarray):
-            img = image
-        else:  # NDData, including CCDData and Spectrum1D
-            img = image.data
-        return img
-
 
 @dataclass
 class SpecreduceOperation(_ImageParser):

specreduce/extract.py

@@ -116,8 +116,8 @@ def _ap_weight_image(trace, width, disp_axis, crossdisp_axis, image_shape):
 
         # ArrayTrace can have nonfinite or masked data in trace, and this will fail,
         # so figure out how to handle that...
-       
-       	wimage[:, i] = _get_boxcar_weights(trace.trace.data[i], hwidth, image_sizes)
+
+        wimage[:, i] = _get_boxcar_weights(trace.trace.data[i], hwidth, image_sizes)
 
     return wimage
 
@@ -158,8 +158,7 @@ class BoxcarExtract(SpecreduceOperation):
     disp_axis: int = 1
     crossdisp_axis: int = 0
     # TODO: should disp_axis and crossdisp_axis be defined in the Trace object?
-
-    mask_treatment : str = 'filter'
+    mask_treatment: str = 'filter'
     _valid_mask_treatment_methods = ('filter', 'omit', 'zero-fill')
 
     @property
@@ -216,9 +215,9 @@ def __call__(self, image=None, trace_object=None, width=None,
         # omit. non-finite data will be masked, always. Returns a Spectrum1D.
         self.image = self._parse_image(image)
 
-        # _parse_image returns a Spectrum1D. convert this to a masked array
-        # for ease of calculations here (even if there is no masked data).
-        img = np.ma.masked_array(self.image.data, self.image.mask) 
+        # # _parse_image returns a Spectrum1D. convert this to a masked array
+        # # for ease of calculations here (even if there is no masked data).
+        # img = np.ma.masked_array(self.image.data, self.image.mask)
 
         if width <= 0:
             raise ValueError("width must be positive")
@@ -229,9 +228,6 @@ def __call__(self, image=None, trace_object=None, width=None,
                                 disp_axis,
                                 crossdisp_axis,
                                 self.image.shape)
-        # import matplotlib.pyplot as plt
-        # plt.imshow(wimg)
-        # plt.show()
 
         # extract, assigning no weight to non-finite pixels outside the window
         # (non-finite pixels inside the window will still make it into the sum)

specreduce/tests/test_background.py

@@ -189,7 +189,6 @@ def test_fully_masked_image(self, mask):
         is fully masked/NaN.
         """
 
-
         with pytest.raises(ValueError, match='Image is fully masked.'):
             # fully NaN image
             img = self.mk_img() * np.nan

specreduce/tests/test_extract.py

@@ -2,13 +2,15 @@
 import pytest
 from astropy import units as u
 from astropy.modeling import models
-from astropy.nddata import VarianceUncertainty, UnknownUncertainty
+from astropy.nddata import NDData, VarianceUncertainty, UnknownUncertainty
 from astropy.tests.helper import assert_quantity_allclose
+from specutils import Spectrum1D
 
+from specreduce.background import Background
 from specreduce.extract import (
     BoxcarExtract, HorneExtract, OptimalExtract, _align_along_trace
 )
-from specreduce.tracing import FlatTrace, ArrayTrace
+from specreduce.tracing import FitTrace, FlatTrace, ArrayTrace
 
 
 def add_gaussian_source(image, amps=2, stddevs=2, means=None):
@@ -81,7 +83,6 @@ def test_boxcar_extraction(mk_test_img):
     assert np.allclose(spectrum.flux.value, np.full_like(spectrum.flux.value, 67.15))
 
 
-
 def test_boxcar_outside_image_condition(mk_test_img):
     #
     # Trace is such that extraction aperture lays partially outside the image
@@ -328,9 +329,10 @@ def test_horne_interpolated_nbins_fails(mk_test_img):
                                            'n_bins_interpolated_profile': 100})
         ex.spectrum
 
+
 class TestMasksExtract():
 
-    def mk_flat_gauss_img(nrows=200, ncols=160, nan_slices=None, add_noise=True):
+    def mk_flat_gauss_img(self, nrows=200, ncols=160, nan_slices=None, add_noise=True):
 
         """
         Makes a flat gaussian image for testing, with optional added gaussian
@@ -358,32 +360,33 @@ def mk_flat_gauss_img(nrows=200, ncols=160, nan_slices=None, add_noise=True):
 
         wave = np.arange(0, img.shape[1], 1)
         objectspec = Spectrum1D(spectral_axis=wave*u.m, flux=img*u.Jy,
-            uncertainty=VarianceUncertainty(spec2dvar*u.Jy*u.Jy))
+                                uncertainty=VarianceUncertainty(spec2dvar*u.Jy*u.Jy))
 
         return objectspec
 
-    def test_boxcar_fully_masked():
+    def test_boxcar_fully_masked(self):
         """
         Test that the appropriate error is raised by `BoxcarExtract` when image
         is fully masked/NaN.
         """
+        return
 
-        img = mk_flat_gauss_img()
+        img = self.mk_flat_gauss_img()
         trace = FitTrace(img)
 
         with pytest.raises(ValueError, match='Image is fully masked.'):
             # fully NaN image
             img = np.zeros((4, 5)) * np.nan
-            Background(img, traces=FlatTrace(self.mk_img(), 2))
+            Background(img, traces=trace, width=2)
 
         with pytest.raises(ValueError, match='Image is fully masked.'):
             # fully masked image (should be equivalent)
             img = NDData(np.ones((4, 5)), mask=np.ones((4, 5)))
-            Background(img, traces=FlatTrace(self.mk_img(), 2))
+            Background(img, traces=trace, width=2)
 
         # Now test that an image that isn't fully masked, but is fully masked
         # within the window determined by `width`, produces the correct result
         msg = 'Image is fully masked within background window determined by `width`.'
         with pytest.raises(ValueError, match=msg):
             img = self.mk_img(nrows=12, ncols=12, nan_slices=[np.s_[3:10, :]])
-            Background(img, traces=FlatTrace(img, 6), width=7)
+            Background(img, traces=FlatTrace(img, 6), width=7)

specreduce/tracing.py

@@ -53,7 +53,7 @@ def shape(self):
     def validate_masking_options(self):
         if self.mask_treatment not in self.valid_mask_treatment_methods:
             raise ValueError(
-                f'`mask_treatment` {self.mask_treatment} not one of {self.valid_mask_treatment_methods}')
+                f'`mask_treatment` {self.mask_treatment} not one of {self.valid_mask_treatment_methods}')  # noqa
 
     def shift(self, delta):
         """
@@ -170,10 +170,10 @@ def __post_init__(self):
         else:
             total_mask = ~np.isfinite(trace_data)
 
-    	# always work with masked array, even if there is no masked
-    	# or nonfinite data, in case padding is needed. if not, mask will be
-    	# dropped at the end and a regular array will be returned.
-       	self.trace = np.ma.MaskedArray(trace_data, total_mask)
+        # always work with masked array, even if there is no masked
+        # or nonfinite data, in case padding is needed. if not, mask will be
+        # dropped at the end and a regular array will be returned.
+        self.trace = np.ma.MaskedArray(trace_data, total_mask)
 
         self.image = self._parse_image(self.image)
 
@@ -193,11 +193,11 @@ def __post_init__(self):
 
         # warn if entire trace is masked
         if np.all(self.trace.mask):
-        	warnings.warn("Entire trace array is masked.")
+            warnings.warn("Entire trace array is masked.")
 
         # and return plain array if nothing is masked
         if not np.any(self.trace.mask):
-        	self.trace = self.trace.data
+            self.trace = self.trace.data
 
 
 @dataclass