Refactor and clean up code for code coverage #193

pyorc/cv.py

@@ -220,9 +220,7 @@ def get_ms_gftt(cap, start_frame=0, end_frame=None, n_pts=None, split=2, mask=No
 
     """
     # set end_frame to last if not defined
-    if end_frame is None:
-        end_frame = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-
+    end_frame = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) if end_frame is None else end_frame
     m = np.eye(3)[0:2]
     # m2 = np.eye(3)[0:2]
     ms = []
@@ -566,7 +564,6 @@ def calibrate_camera(
         idx = np.array(errs) < tolerance
         obj_pts = list(np.array(obj_pts)[idx])
         img_pts = list(np.array(img_pts)[idx])
-        print(len(img_pts))
         # do calibration
         ret, camera_matrix, dist_coeffs, rvecs, tvecs = cv2.calibrateCamera(obj_pts, img_pts, frame_size, None, None)
         errs = []
@@ -954,21 +951,14 @@ def get_time_frames(cap, start_frame, end_frame, lazy=True, fps=None, **kwargs):
     n = start_frame
     time = []
     frame_number = []
-    if lazy:
-        frames = None
-    else:
-        # already collect the frames
-        frames = []
+    frames = None if lazy else []
     while ret:
         if n > end_frame:
             break
         if not lazy:
             frames.append(img)
         t1 = cap.get(cv2.CAP_PROP_POS_MSEC)
-        if fps is not None:
-            time.append(n * 1000.0 / fps)
-        else:
-            time.append(t1)
+        time.append(n * 1000.0 / fps) if fps is not None else time.append(t1)
         frame_number.append(n)
         n += 1
         ret, img = get_frame(cap, **kwargs)  # read frame 1 + ...

pyorc/velocimetry/openpiv.py

@@ -141,11 +141,6 @@ def piv(
     return v_x * res_x, v_y * res_y, s2n, corr
 
 
-def get_piv_size(**kwargs):
-    """Get column, row coordinates of center of PIV windows."""
-    return openpiv.pyprocess.get_coordinates(**kwargs)
-
-
 def extended_search_area_piv(
     frame_a: np.ndarray,
     frame_b: np.ndarray,
@@ -270,8 +265,7 @@ def extended_search_area_piv(
         overlap = [overlap, overlap]
 
     # check the inputs for validity
-    if search_area_size is None:
-        search_area_size = window_size
+    search_area_size = window_size if search_area_size is None else search_area_size
 
     if overlap[0] >= window_size[0] or overlap[1] >= window_size[1]:
         raise ValueError("Overlap has to be smaller than the window_size")
@@ -321,15 +315,14 @@ def extended_search_area_piv(
         u, v = openpiv.pyprocess.correlation_to_displacement(corr, n_rows, n_cols, subpixel_method=subpixel_method)
 
     # return output depending if user wanted sig2noise information
+    sig2noise = np.zeros_like(u) * np.nan
     if sig2noise_method is not None:
         if use_vectorized == True:
             sig2noise = openpiv.pyprocess.vectorized_sig2noise_ratio(
                 corr, sig2noise_method=sig2noise_method, width=width
             )
         else:
             sig2noise = openpiv.pyprocess.sig2noise_ratio(corr, sig2noise_method=sig2noise_method, width=width)
-    else:
-        sig2noise = np.zeros_like(u) * np.nan
 
     sig2noise = sig2noise.reshape(n_rows, n_cols)
     # extended code for exporting the maximum found value for corr

tests/test_frames.py

@@ -45,6 +45,15 @@ def test_normalize(frames, samples, request):
     ), f'dtype of result is {frames_norm[0, 0, 0].values.dtype}, expected "uint8"'
 
 
+def test_smooth(frames_grayscale):
+    frames_smooth = frames_grayscale.frames.smooth()
+    assert frames_smooth.shape == frames_grayscale.shape
+    assert (
+        frames_smooth[0, 0, 0].values.dtype == "float32"
+    ), f'dtype of result is {frames_smooth[0, 0, 0].values.dtype}, expected "float32"'
+    assert np.allclose(frames_smooth.values.flatten()[-4:], [158.125, 153.5, 151.375, 151.0])
+
+
 def test_edge_detect(frames_proj):
     frames_edge = frames_proj.frames.edge_detect()
     assert frames_edge.shape == frames_proj.shape