Code clean up

Author: neon60

httomolibgpu/prep/stripe.py

@@ -413,8 +413,8 @@ def raven_filter(
 
     input_type = sinogram.dtype
 
-    if input_type not in ["float32", "float64"]:
-        raise ValueError("The input data should be either float32 or float64 data type")
+    if input_type not in ["float32"]:
+        raise ValueError("The input data should be float32 data type")
 
     # Padding of the sinogram
     sinogram = cp.pad(sinogram, ((pad_y, pad_y), (0, 0), (pad_x, pad_x)), mode=pad_method)
@@ -423,12 +423,15 @@ def raven_filter(
     fft_data = fft2(sinogram, axes=(0, 2), overwrite_x=True)
     fft_data_shifted = fftshift(fft_data, axes=(0, 2))
 
+    # Calculation type
+    calc_type = fft_data_shifted.dtype
+
     # Setup various values for the filter
     height, images, width = sinogram.shape
 
     # Set the input type of the kernel
     kernel_args = "raven_filter<{0}>".format(
-        "float" if input_type == "float32" else "double"
+        "float" if calc_type == "complex64" else "double"
     )
 
     # setting grid/block parameters

tests/test_prep/test_stripe.py

@@ -155,23 +155,23 @@ def test_raven_filter_performance(ensure_clean_memory):
 
     assert "performance in ms" == duration_ms
 
-@pytest.mark.perf
-def test_raven_filter_cpu_performance(ensure_clean_memory):
-    data_host = (
-        np.random.random_sample(size=(1801, 5, 2560)).astype(np.float32) * 2.0 + 0.001
-    )
-    data = cp.asarray(data_host, dtype=np.float32)
-
-    # do a cold run first
-    raven_filter_cpu(cp.copy(data).get())
-
-    start = time.perf_counter_ns()
-    for _ in range(10):
-        raven_filter_cpu(cp.copy(data).get())
-
-    duration_ms = float(time.perf_counter_ns() - start) * 1e-6 / 10
-
-    assert "performance in ms" == duration_ms
+# @pytest.mark.perf
+# def test_raven_filter_cpu_performance(ensure_clean_memory):
+#     data_host = (
+#         np.random.random_sample(size=(1801, 5, 2560)).astype(np.float32) * 2.0 + 0.001
+#     )
+#     data = cp.asarray(data_host, dtype=np.float32)
+# 
+#     # do a cold run first
+#     raven_filter_cpu(cp.copy(data).get())
+# 
+#     start = time.perf_counter_ns()
+#     for _ in range(10):
+#         raven_filter_cpu(cp.copy(data).get())
+# 
+#     duration_ms = float(time.perf_counter_ns() - start) * 1e-6 / 10
+# 
+#     assert "performance in ms" == duration_ms
 
 
 def test_remove_all_stripe_on_data(data, flats, darks):