adding working jenkins test

Author: dkazanc

tests/conftest.py

@@ -228,6 +228,7 @@ def FBP2d_astra():
 def FBP3d_tomobar_denoising():
     return "docs/source/pipelines_full/FBP3d_tomobar_denoising.yaml"
 
+
 @pytest.fixture
 def angles_averaging():
     return "docs/source/pipelines_full/angles_averaging.yaml"
@@ -343,6 +344,12 @@ def FBP2d_astra_i12_119647_npz():
     return np.load("tests/test_data/raw_data/i12/FBP2d_astra_i12_119647.npz")
 
 
+@pytest.fixture
+def angle_average_LPrec_i12_119647_npz():
+    # 10 slices numpy array
+    return np.load("tests/test_data/raw_data/i12/angle_average_LPrec_i12_119647.npz")
+
+
 @pytest.fixture
 def FBP3d_tomobar_TVdenoising_i13_177906_npz():
     # 10 slices numpy array

tests/test_parallel_pipeline_big.py

@@ -183,7 +183,7 @@ def test_angles_averaging_LPRec_i12_119647_preview(
     cmd_mpirun,
     i12_119647,
     angles_averaging,
-    FBP3d_tomobar_k11_38730_npz,
+    angle_average_LPrec_i12_119647_npz,
     output_folder,
 ):
 
@@ -213,38 +213,39 @@ def test_angles_averaging_LPRec_i12_119647_preview(
     output, error = process.communicate()
     print(output)
 
-    # files = get_files(output_folder)
-
-    # #: check the generated reconstruction (hdf5 file)
-    # h5_files = list(filter(lambda x: ".h5" in x, files))
-    # assert len(h5_files) == 1
-
-    # # load the pre-saved numpy array for comparison bellow
-    # data_gt = FBP3d_tomobar_k11_38730_npz["data"]
-    # axis_slice = FBP3d_tomobar_k11_38730_npz["axis_slice"]
-    # slices, sizeX, sizeY = np.shape(data_gt)
-
-    # step = axis_slice // (slices + 2)
-    # # store for the result
-    # data_result = np.zeros((slices, sizeX, sizeY), dtype=np.float32)
-
-    # path_to_data = "data/"
-    # h5_file_name = "FBP3d_tomobar"
-    # for file_to_open in h5_files:
-    #     if h5_file_name in file_to_open:
-    #         h5f = h5py.File(file_to_open, "r")
-    #         index_prog = step
-    #         for i in range(slices):
-    #             data_result[i, :, :] = h5f[path_to_data][:, index_prog, :]
-    #             index_prog += step
-    #         h5f.close()
-    #     else:
-    #         message_str = f"File name with {h5_file_name} string cannot be found."
-    #         raise FileNotFoundError(message_str)
-
-    # residual_im = data_gt - data_result
-    # res_norm = np.linalg.norm(residual_im.flatten()).astype("float32")
-    # assert res_norm < 1e-6
+    files = get_files(output_folder)
+
+    #: check the generated reconstruction (hdf5 file)
+    h5_files = list(filter(lambda x: ".h5" in x, files))
+    assert len(h5_files) == 1
+
+    # load the pre-saved numpy array for comparison bellow
+    data_gt = angle_average_LPrec_i12_119647_npz["data"]
+    axis_slice = angle_average_LPrec_i12_119647_npz["axis_slice"]
+    slices, sizeX, sizeY = np.shape(data_gt)
+
+    step = axis_slice // (slices + 2)
+    # store for the result
+    data_result = np.zeros((slices, sizeX, sizeY), dtype=np.float32)
+
+    path_to_data = "data/"
+    h5_file_name = "FBP3d_tomobar"
+    for file_to_open in h5_files:
+        if h5_file_name in file_to_open:
+            h5f = h5py.File(file_to_open, "r")
+            index_prog = step
+            for i in range(slices):
+                data_result[i, :, :] = h5f[path_to_data][:, index_prog, :]
+                index_prog += step
+            h5f.close()
+        else:
+            message_str = f"File name with {h5_file_name} string cannot be found."
+            raise FileNotFoundError(message_str)
+
+    residual_im = data_gt - data_result
+    res_norm = np.linalg.norm(residual_im.flatten()).astype("float32")
+    assert res_norm < 1e-6
+
 
 # ########################################################################