Formatting

skued/__main__.py

@@ -39,7 +39,7 @@ def main(args=None):
 
 
 def main_diffshow(fname):
-    """ Display an interactive window """
+    """Display an interactive window"""
     if not WITH_PYQTGRAPH:
         print(
             "PyQtGraph is required for this functionality. You can install PyQtGraph either with \

skued/baseline/tests/test_algorithms.py

@@ -15,13 +15,13 @@
 
 
 def test_zero_level():
-    """ baseline computed at the zero-th level should not affect the array """
+    """baseline computed at the zero-th level should not affect the array"""
     array = np.random.random(size=(101,))
     assert np.allclose(array, baseline_dwt(array, max_iter=5, level=0))
 
 
 def test_approx_rec():
-    """ Test that the underlying _dwt_approx_rec function is working properly """
+    """Test that the underlying _dwt_approx_rec function is working properly"""
 
     arr = np.random.random(size=(102,))
     rec_arr = _dwt_approx_rec(arr, level=2, wavelet="db6", mode="constant", axis=-1)
@@ -45,19 +45,19 @@ def test_approx_rec():
 
 
 def test_trivial_case_1d():
-    """ The baseline for a 1d array of zeros should be zeros """
+    """The baseline for a 1d array of zeros should be zeros"""
     arr = np.zeros(shape=(101,))
     assert np.allclose(arr, baseline_dwt(arr, max_iter=10, level=None))
 
 
 def test_trivial_case_2d():
-    """ The baseline for a 2d array of zeros should be zeros """
+    """The baseline for a 2d array of zeros should be zeros"""
     arr = np.zeros((21, 31, 5))
     assert np.allclose(arr, baseline_dwt(arr, max_iter=10, level=None, axis=(0, 1)))
 
 
 def test_1d_along_axis():
-    """ Test that iterating over array rows and baseline_dwt along axis are equivalent """
+    """Test that iterating over array rows and baseline_dwt along axis are equivalent"""
     block = np.random.random(size=(21, 51))
 
     # Iterate over rows
@@ -72,13 +72,13 @@ def test_1d_along_axis():
 
 
 def test_zero_level():
-    """ baseline computed at the zero-th level should not affect the array """
+    """baseline computed at the zero-th level should not affect the array"""
     array = np.random.random(size=(101,))
     assert np.allclose(array, baseline_dt(array, max_iter=5, level=0))
 
 
 def test_approx_rec():
-    """ Test that the underlying _dwt_approx_rec function is working properly """
+    """Test that the underlying _dwt_approx_rec function is working properly"""
 
     arr = np.random.random(size=(102,))
     rec_arr = _dt_approx_rec(
@@ -104,29 +104,29 @@ def test_approx_rec():
 
 
 def test_trivial_case():
-    """ The baseline for an array of zeros should be zeros """
+    """The baseline for an array of zeros should be zeros"""
     arr = np.zeros(shape=(101,))
     assert np.allclose(arr, baseline_dt(arr, max_iter=10, level=None))
 
 
 def test_positive_baseline():
-    """ Test that the baseline is never negative """
+    """Test that the baseline is never negative"""
     arr = 10 * np.random.random(size=(128,))
     baseline = baseline_dt(arr, max_iter=10)
 
     assert np.all(np.greater_equal(baseline, 0))
 
 
 def test_baseline_limit():
-    """ Test that the baseline is never more than the original signal """
+    """Test that the baseline is never more than the original signal"""
     arr = 10 * np.random.random(size=(128,))
     baseline = baseline_dt(arr, max_iter=10)
 
     assert np.all(np.greater_equal(arr, baseline))
 
 
 def test_final_shape():
-    """ Test that baseline_dt returns an array of the same shape as input """
+    """Test that baseline_dt returns an array of the same shape as input"""
 
     arr = np.random.random(size=(101,))
     b = baseline_dt(arr, max_iter=10, level=None)
@@ -146,7 +146,7 @@ def test_final_shape():
 
 
 def test_2d_along_axis():
-    """ Test that iterating over array rows and baseline_dt along axis are equivalent """
+    """Test that iterating over array rows and baseline_dt along axis are equivalent"""
     block = np.random.random(size=(21, 51))
 
     # Iterate over rows
@@ -161,7 +161,7 @@ def test_2d_along_axis():
 
 
 def test_background_regions():
-    """ Test that background_regions is used correctly along certain axes """
+    """Test that background_regions is used correctly along certain axes"""
     block = np.random.random(size=(21, 51))
 
     baseline_params = {"max_iter": 50, "background_regions": [(..., range(0, 3))]}

skued/baseline/tests/test_dtcwt.py

@@ -18,7 +18,7 @@
 
 
 def test_first_stage():
-    """ Test of perfect reconstruction of first stage wavelets. """
+    """Test of perfect reconstruction of first stage wavelets."""
     array = np.sin(np.arange(0, 10, step=0.01))
     for wavelet in available_first_stage_filters():
         # Using waverec and wavedec instead of dwt and idwt because parameters
@@ -27,7 +27,7 @@ def test_first_stage():
 
 
 def gen_input(n_dimensions):
-    """ Generate random array with the appropriate dimensions """
+    """Generate random array with the appropriate dimensions"""
     shape = {1: (100,), 2: (50, 50), 3: (10, 10, 10)}[n_dimensions]
     return np.random.random(size=shape)
 
@@ -37,7 +37,7 @@ def gen_input(n_dimensions):
 
 @multidim
 def test_perfect_reconstruction_level_0(n_dimensions):
-    """ Test perfect reconstruction for a 0-level decomposition """
+    """Test perfect reconstruction for a 0-level decomposition"""
     array = gen_input(n_dimensions)
     coeffs = dtcwt(data=array, level=0, first_stage="sym6", wavelet="qshift1")
     reconstructed = idtcwt(coeffs=coeffs, first_stage="sym6", wavelet="qshift1")
@@ -46,7 +46,7 @@ def test_perfect_reconstruction_level_0(n_dimensions):
 
 @multidim
 def test_perfect_reconstruction_level_1(n_dimensions):
-    """ Test perfect reconstruction for a single decomposition level """
+    """Test perfect reconstruction for a single decomposition level"""
     array = gen_input(n_dimensions)
     for first_stage in available_first_stage_filters():
         coeffs = dtcwt(data=array, level=1, first_stage=first_stage, wavelet="qshift1")
@@ -58,7 +58,7 @@ def test_perfect_reconstruction_level_1(n_dimensions):
 
 @multidim
 def test_perfect_reconstruction_multilevel(n_dimensions):
-    """ Test perfect reconstruction for all levels, for all first_stage wavelets, for all DT wavelets """
+    """Test perfect reconstruction for all levels, for all first_stage wavelets, for all DT wavelets"""
     array = gen_input(n_dimensions)
 
     for first_stage in available_first_stage_filters():
@@ -81,7 +81,7 @@ def test_perfect_reconstruction_multilevel(n_dimensions):
 
 @multidim
 def test_axis(n_dimensions):
-    """ Test perfect reconstruction along all axes """
+    """Test perfect reconstruction along all axes"""
     array = gen_input(n_dimensions)
     for axis in range(0, array.ndim):
         coeffs = dtcwt(
@@ -99,7 +99,7 @@ def test_axis(n_dimensions):
 
 @multidim
 def test_axis_limits(n_dimensions):
-    """ Test that an exception is raised for an invalid 'axis' parameter """
+    """Test that an exception is raised for an invalid 'axis' parameter"""
     array = gen_input(n_dimensions)
     with pytest.raises(ValueError):
         coeffs = dtcwt(
@@ -113,7 +113,7 @@ def test_axis_limits(n_dimensions):
 
 @multidim
 def test_even_length_along_axis(n_dimensions):
-    """ Test that an exception is raised when array is not even along transform axis """
+    """Test that an exception is raised when array is not even along transform axis"""
     with pytest.raises(ValueError):
         dtcwt(
             data=np.zeros((17, 8)),

skued/fft.py

@@ -36,7 +36,7 @@ def __ua_function__(method, args, kwargs):
 
 
 def with_skued_fft(f):
-    """ Ensure the use of the SkuedPocketFFTBackend whenever the `scipy.fft` module is used. """
+    """Ensure the use of the SkuedPocketFFTBackend whenever the `scipy.fft` module is used."""
 
     @wraps(f)
     def newf(*args, **kwargs):

skued/image/calibration.py

@@ -6,7 +6,7 @@
 
 
 def hypot(*args):
-    """ Generalized np.hypot """
+    """Generalized np.hypot"""
     return np.sqrt(np.sum(np.square(args)))
 
 

skued/image/powder.py

@@ -93,7 +93,7 @@ def azimuthal_average(image, center, mask=None, angular_bounds=None, trim=True):
 
 
 def _trim_bounds(arr):
-    """ Returns the bounds which would be used in numpy.trim_zeros """
+    """Returns the bounds which would be used in numpy.trim_zeros"""
     first = 0
     for i in arr:
         if i != 0.0:

skued/image/tests/test_alignment.py

@@ -19,7 +19,7 @@
 
 
 def circle_image(shape, center, radii, intensities):
-    """ Creates an image with circle or thickness 2 """
+    """Creates an image with circle or thickness 2"""
     im = np.zeros(shape=shape, dtype=float)
     xx, yy = np.ogrid[0 : shape[0], 0 : shape[1]]
     xx, yy = xx - center[0], yy - center[1]
@@ -36,7 +36,7 @@ def camera():
 
 
 def test_ialign_trivial():
-    """ Test alignment of identical images """
+    """Test alignment of identical images"""
     aligned = tuple(ialign([camera() for _ in range(5)]))
 
     assert len(aligned) == 5
@@ -62,15 +62,15 @@ def test_ialign_misaligned_canned_images():
 
 
 def test_align_no_side_effects():
-    """ Test that aligned images are not modified in-place """
+    """Test that aligned images are not modified in-place"""
     im = np.array(camera()[0:64, 0:64])
     im.setflags(write=False)
     aligned = align(im, reference=im, fill_value=np.nan)
     assert im.dtype == camera().dtype
 
 
 def test_align_no_mask():
-    """ Test that alignment of images with no masks works """
+    """Test that alignment of images with no masks works"""
     reference = camera()
     image = ndi.shift(camera(), shift=(-7, 12))
     aligned = align(image, reference=reference)
@@ -79,7 +79,7 @@ def test_align_no_mask():
 
 
 def test_align_with_mask():
-    """ Test that alignment of images with no masks works """
+    """Test that alignment of images with no masks works"""
     reference = camera()
     image = ndi.shift(camera(), shift=(-7, 12))
 
@@ -92,7 +92,7 @@ def test_align_with_mask():
 
 
 def test_itrack_peak_trivial():
-    """ Test that shift is identically zero for images that are identical """
+    """Test that shift is identically zero for images that are identical"""
     # Array prototype is just zeros
     # with a 'peak' in the center
     prototype = np.zeros(shape=(17, 17))
@@ -105,7 +105,7 @@ def test_itrack_peak_trivial():
 
 
 def test_itrack_peak_length():
-    """ Test that shifts yielded by itrack_peak are as numerous as the number of input pictures """
+    """Test that shifts yielded by itrack_peak are as numerous as the number of input pictures"""
     images = [np.random.random(size=(4, 4)) for _ in range(20)]
     shifts = list(itrack_peak(images, row_slice=np.s_[:], col_slice=np.s_[:]))
 

skued/image/tests/test_calibration.py

@@ -74,7 +74,7 @@ def test_powder_calq_simulation_3_peaks():
 
 
 def test_detector_scattvectors_center():
-    """ Test that the placement of the center is working as intended. """
+    """Test that the placement of the center is working as intended."""
     qx, qy, qz = detector_scattvectors(
         keV=200,
         camera_length=1,

skued/image/tests/test_center.py

@@ -13,7 +13,7 @@
 
 
 def diff_pattern_sc(center):
-    """ Simulate a single-crystal diffraction pattern """
+    """Simulate a single-crystal diffraction pattern"""
     r, c = center
 
     cryst = Crystal.from_database("BaTiO3_cubic")
@@ -34,7 +34,7 @@ def diff_pattern_sc(center):
 
 
 def test_autocenter_trivial():
-    """ Test that autocenter() finds the center of perfect gaussian at (0,0) """
+    """Test that autocenter() finds the center of perfect gaussian at (0,0)"""
     im = np.zeros(shape=(256, 256), dtype=float)
     center = np.asarray(im.shape) / 2
     rows, cols = np.indices(im.shape)
@@ -44,7 +44,7 @@ def test_autocenter_trivial():
 
 
 def test_autocenter_no_side_effects():
-    """ Test that autocenter() does not modify the inputs """
+    """Test that autocenter() does not modify the inputs"""
     im = np.random.random(size=(256, 256))
     mask = np.ones_like(im, dtype=bool)
 
@@ -58,7 +58,7 @@ def test_autocenter_no_side_effects():
 @pytest.mark.parametrize("rc", range(-10, 10, 2))
 @pytest.mark.parametrize("cc", range(-10, 10, 2))
 def test_autocenter_gaussian_shifted(rc, cc):
-    """ Test that autocenter() finds the center of a shifted gaussian """
+    """Test that autocenter() finds the center of a shifted gaussian"""
     im = np.zeros(shape=(128, 128), dtype=float)
     rows, cols = np.indices(im.shape)
     center = np.array([64 + rc, 64 + cc])

skued/image/tests/test_indexing.py

@@ -12,7 +12,7 @@
 
 
 def diff_pattern_sc():
-    """ Simulate a single-crystal diffraction pattern """
+    """Simulate a single-crystal diffraction pattern"""
     cryst = Crystal.from_database("C")
     rr, cc = np.indices((DIFF_PATTERN_SIZE, DIFF_PATTERN_SIZE))
     rr -= rr.shape[1] // 2
@@ -32,7 +32,7 @@ def diff_pattern_sc():
 
 
 def test_bragg_peaks():
-    """ Test that the `bragg_peaks` function finds all Bragg peaks. """
+    """Test that the `bragg_peaks` function finds all Bragg peaks."""
     kx, ky, I, cryst = diff_pattern_sc()
     kk = np.sqrt(kx ** 2 + ky ** 2)