Upgrade black to v22.3.0

Makefile

@@ -30,7 +30,7 @@ build-docs:
 	cd docs && make html
 
 dev:
-	pip install black==21.4b2 coverage isort flake8 flake8-bugbear flake8-comprehensions
+	pip install black==22.3.0 coverage isort flake8 flake8-bugbear flake8-comprehensions
 	pip install --upgrade mistune==0.8.4 sphinx sphinx-rtd-theme recommonmark m2r2
 	pip install -r docs/requirements.txt
 

dosma/core/fitting.py

@@ -935,11 +935,11 @@ def _compute_r2_matrix(_x, _y, _popts):
         xp = get_array_module(_y)
 
         _x = _x.flatten()
-        _xs = xp.stack([_x ** i for i in range(len(_popts) - 1, -1, -1)], axis=-1)
+        _xs = xp.stack([_x**i for i in range(len(_popts) - 1, -1, -1)], axis=-1)
         yhat = _xs @ _popts  # (M, K)
 
         residuals = yhat - _y
-        ss_res = xp.sum(residuals ** 2, axis=0)
+        ss_res = xp.sum(residuals**2, axis=0)
         ss_tot = xp.sum((_y - xp.mean(_y, axis=0, keepdims=True)) ** 2, axis=0)
         return 1 - (ss_res / (ss_tot + eps))
 
@@ -1030,7 +1030,7 @@ def _fit_internal(_x, _y):
         popt, _ = sop.curve_fit(func, _x, _y, p0=p0, ftol=ftol, **kwargs)
 
         residuals = _y - func(_x, *popt)
-        ss_res = np.sum(residuals ** 2)
+        ss_res = np.sum(residuals**2)
         ss_tot = np.sum((_y - np.mean(_y)) ** 2)
         r_squared = 1 - (ss_res / (ss_tot + eps))
 
@@ -1078,7 +1078,7 @@ def _fit_internal(_x, _y):
         popt = xp.polyfit(_x, _y, deg, rcond=rcond, w=w)
 
         residuals = _y - xp.polyval(popt, _x)
-        ss_res = xp.sum(residuals ** 2)
+        ss_res = xp.sum(residuals**2)
         ss_tot = xp.sum((_y - xp.mean(_y)) ** 2)
         r_squared = 1 - (ss_res / (ss_tot + eps))
 
@@ -1178,7 +1178,7 @@ def func(t, a, b):
     popt, _ = sop.curve_fit(func, x, y, p0=p0, maxfev=100, ftol=1e-5)
 
     residuals = y - func(x, popt[0], popt[1])
-    ss_res = np.sum(residuals ** 2)
+    ss_res = np.sum(residuals**2)
     ss_tot = np.sum((y - np.mean(y)) ** 2)
 
     r_squared = 1 - (ss_res / (ss_tot + __EPSILON__))

dosma/core/io/dicom_io.py

@@ -687,8 +687,8 @@ def _update_np_dtype(arr: np.ndarray, bit_depth: int):
     dtype_dict = {
         8: [(np.int8, -128, 127), (np.uint8, 0, 255)],
         16: [
-            (np.uint16, 0, 2 ** 16 - 1),
-            (np.int16, -(2 ** 15), 2 ** 15),
+            (np.uint16, 0, 2**16 - 1),
+            (np.int16, -(2**15), 2**15),
             (np.float16, -6.55e4, 6.55e4 - 1),
         ],
     }

dosma/core/med_volume.py

@@ -848,7 +848,7 @@ def volume(self, value):
     def pixel_spacing(self):
         """tuple[float]: Pixel spacing in order of current orientation."""
         vecs = self._affine[:3, :3]
-        ps = tuple(np.sqrt(np.sum(vecs ** 2, axis=0)))
+        ps = tuple(np.sqrt(np.sum(vecs**2, axis=0)))
 
         assert len(ps) == 3, "Pixel spacing must have length of 3"
         return ps

dosma/models/oaiunet2d.py

@@ -53,7 +53,7 @@ def __load_keras_model__(self, input_shape, force_weights=False):
         if type(input_shape) is not tuple or len(input_shape) != 3 or input_shape[2] != 1:
             raise ValueError("input_size must be a tuple of size (height, width, 1)")
 
-        nfeatures = [2 ** feat * 32 for feat in np.arange(6)]
+        nfeatures = [2**feat * 32 for feat in np.arange(6)]
         depth = len(nfeatures)
 
         conv_ptr = []
@@ -198,7 +198,7 @@ def __load_keras_model__(self, input_shape):
         if type(input_shape) is not tuple or len(input_shape) != 3 or input_shape[2] != 1:
             raise ValueError("input_size must be a tuple of size (height, width, 1)")
 
-        nfeatures = [2 ** feat * 32 for feat in np.arange(6)]
+        nfeatures = [2**feat * 32 for feat in np.arange(6)]
         depth = len(nfeatures)
 
         conv_ptr = []

dosma/models/stanford_qdess.py

@@ -65,7 +65,7 @@ def __load_keras_model__(self, input_shape):
         if type(input_shape) is not tuple or len(input_shape) != 3 or input_shape[2] != 1:
             raise ValueError("input_size must be a tuple of size (height, width, 1)")
 
-        nfeatures = [2 ** feat * 32 for feat in np.arange(6)]
+        nfeatures = [2**feat * 32 for feat in np.arange(6)]
         depth = len(nfeatures)
 
         conv_ptr = []
@@ -170,7 +170,7 @@ def generate_mask(self, volume: MedicalVolume):
 
         vol_copy = deepcopy(volume)
         if ndim == 4:
-            vol_copy = np.sqrt(np.sum(vol_copy ** 2, axis=-1))
+            vol_copy = np.sqrt(np.sum(vol_copy**2, axis=-1))
 
         # reorient to the sagittal plane
         vol_copy.reformat(SAGITTAL, inplace=True)

dosma/scan_sequences/mri/qdess.py

@@ -283,9 +283,9 @@ def _combine_echoes(self, method="rss"):
         assert (~xp.iscomplex(echo1)).all() and (~xp.iscomplex(echo2)).all()
 
         if method == "rss":
-            vol = xp.sqrt(echo1 ** 2 + echo2 ** 2)
+            vol = xp.sqrt(echo1**2 + echo2**2)
         elif method == "rms":
-            vol = xp.sqrt((echo1 ** 2 + echo2 ** 2) / 2)
+            vol = xp.sqrt((echo1**2 + echo2**2) / 2)
         else:
             raise ValueError(f"`method={method}` is not supported")
 

dosma/tissues/femoral_cartilage.py

@@ -50,20 +50,20 @@ class FemoralCartilage(Tissue):
     # Keys correspond to integer representing bit location for each region
     # bit string: 'T D S M L A C P' (stored as integer)
     # Coronal Keys
-    _POSTERIOR_KEY = 2 ** 0
-    _CENTRAL_KEY = 2 ** 1
-    _ANTERIOR_KEY = 2 ** 2
+    _POSTERIOR_KEY = 2**0
+    _CENTRAL_KEY = 2**1
+    _ANTERIOR_KEY = 2**2
     _CORONAL_KEYS = [_POSTERIOR_KEY, _CENTRAL_KEY, _ANTERIOR_KEY]
 
     # Sagittal Keys
-    _MEDIAL_KEY = 2 ** 3
-    _LATERAL_KEY = 2 ** 4
+    _MEDIAL_KEY = 2**3
+    _LATERAL_KEY = 2**4
     _SAGITTAL_KEYS = [_MEDIAL_KEY, _LATERAL_KEY]
 
     # Axial Keys
-    _DEEP_KEY = 2 ** 5
-    _SUPERFICIAL_KEY = 2 ** 6
-    _TOTAL_AXIAL_KEY = 2 ** 7
+    _DEEP_KEY = 2**5
+    _SUPERFICIAL_KEY = 2**6
+    _TOTAL_AXIAL_KEY = 2**7
     _AXIAL_KEYS = [_DEEP_KEY, _SUPERFICIAL_KEY, _TOTAL_AXIAL_KEY]
 
     # Do not change order of below.

dosma/utils/geometry_utils.py

@@ -80,7 +80,7 @@ def cart2pol(x, y):
     Returns:
         tuple[float, float]: radius (rho) and angle (phi).
     """
-    rho = np.sqrt(x ** 2 + y ** 2)
+    rho = np.sqrt(x**2 + y**2)
     phi = np.arctan2(y, x)
 
     phi = phi * (180 / np.pi)  # degrees

setup.py

@@ -125,7 +125,7 @@ def run(self):
         "flake8-bugbear",
         "flake8-comprehensions",
         "isort",
-        "black==21.4b2",
+        "black==22.3.0",
         "simpleitk",
         "sphinx",
         "sphinxcontrib.bibtex",

tests/core/test_med_volume.py

@@ -292,7 +292,7 @@ def test_math(self):
         assert np.all(mv2._volume == 2)
         assert np.all(out._volume == 0)
 
-        out = mv1 ** mv2
+        out = mv1**mv2
         assert np.all(mv1._volume == 1)
         assert np.all(mv2._volume == 2)
         assert np.all(out._volume == 1)