Adding a new test that executes a new directive

docs/source/pipelines/yaml.rst

@@ -10,62 +10,74 @@ HTTomo mainly targets GPU computations, therefore the use of :ref:`tutorials_pl_
 preferable. However, when the GPU device is not available or a GPU method is not implemented, the use of 
 :ref:`tutorials_pl_templates_cpu` is possible. 
 
-.. note:: The combination of both GPU and CPU methods is possible. If one expects to achieve the faster performance, please use the GPU methods provided, where possible.
-
 .. _tutorials_pl_templates_gpu:
 
-GPU Pipeline templates
------------------------
+Pipelines using HTTomo libraries
+--------------------------------
 
-The GPU-pipelines consist of methods from httomolibgpu (GPU) and httomolib (CPU) backend :ref:`backends_list`. Those libraries are supported directly by the HTTomo development team.
+Those pipelines consist of methods from HTTomolibgpu (GPU) and HTTomolib (CPU) backends :ref:`backends_list`. Those libraries are supported directly by the HTTomo development team and pipelines are built in computationally efficient way. 
 
-.. dropdown:: GPU pipeline with auto-centering and the `FBP3d_tomobar` reconstruction method.
+.. dropdown:: Using :code:`find_center_vo` auto-centering and :code:`FBP3d_tomobar` reconstruction method, then save the result into images.
 
     .. literalinclude:: ../pipelines_full/FBP3d_tomobar.yaml
         :language: yaml
 
-.. dropdown:: GPU pipeline as above and Total Variation denoising on the result of the FBP reconstruction.
+.. dropdown:: Using :code:`find_center_pc` auto-centering, FBP reconstruction and downsampling the result before saving the images.
+
+    .. literalinclude:: ../pipelines_full/titaren_center_pc_FBP3d_resample.yaml
+        :language: yaml
+
+.. dropdown:: Using :code:`find_center_pc` auto-centering, FBP reconstruction and downsampling the result before saving the images.
+
+    .. literalinclude:: ../pipelines_full/titaren_center_pc_FBP3d_resample.yaml
+        :language: yaml
+
+.. dropdown:: Using :code:`LPRec3d_tomobar` reconstruction, which is the fastest from all available reconstruction methods.
+
+    .. literalinclude:: ../pipelines_full/LPRec3d_tomobar.yaml
+        :language: yaml
+
+.. dropdown:: Applying Total Variation denoising :code:`total_variation_PD` to the result of the FBP reconstruction.
 
     .. literalinclude:: ../pipelines_full/FBP3d_tomobar_denoising.yaml
         :language: yaml
 
 .. _tutorials_pl_templates_cpu:
 
-CPU Pipeline templates
------------------------
+Pipelines using TomoPy library
+------------------------------
 
-The CPU-pipelines mostly use TomoPy methods. They are executed solely on the CPU and therefore expected to be slower than the GPU pipelines.
+One can build CPU-only pipelines by using mostly TomoPy methods. They are expected to be slower than the pipelines above.
 
-.. dropdown:: CPU pipeline using auto-centering and the gridrec reconstruction method on the CPU (TomoPy).
+.. dropdown:: CPU pipeline using auto-centering and the gridrec reconstruction method from TomoPy.
 
     .. literalinclude:: ../pipelines_full/tomopy_gridrec.yaml
         :language: yaml
 
 
 .. _tutorials_pl_templates_dls:
 
-DLS-specific templates
+DLS-specific pipelines
 ----------------------
 
 These pipelines are specific to Diamond Light Source processing strategies and can vary between different tomographic beamlines. 
 
-.. dropdown:: Pipeline for 360-degrees data with automatic CoR/overlap finding and stitching to 180-degrees data. Paganin filter is applied to the data.
+.. dropdown:: Reconstructing 360-degrees data with automatic CoR/overlap finding and stitching to 180-degrees data. Paganin filter is applied to the data.
 
     .. literalinclude:: ../pipelines_full/deg360_paganin_FBP3d_tomobar.yaml
         :language: yaml
 
-.. dropdown:: Using a distortion correction module as a part of the pipeline with the 360-degrees data. 
+.. dropdown:: Using distortion correction module as a part of the pipeline with 360-degrees data. 
 
     .. literalinclude:: ../pipelines_full/deg360_distortion_FBP3d_tomobar.yaml
         :language: yaml
 
 .. _tutorials_pl_templates_sweeps:
 
-Parameter Sweeps templates
---------------------------
+Pipelines with parameter sweeps
+-------------------------------
 
-Here we demonstrate how to perform a sweep across multiple values of a
-single parameter (see :ref:`parameter_sweeping` for more details).
+Here we demonstrate how to perform a sweep across multiple values of a single parameter (see :ref:`parameter_sweeping` for more details).
 
 .. note::  There is no need to add image saving plugin for sweep runs as it will be added automatically. It is also preferable to keep the `preview` small as the time of computation can be substantial.
 

tests/conftest.py

@@ -228,6 +228,11 @@ def FBP3d_tomobar_denoising():
     return "docs/source/pipelines_full/FBP3d_tomobar_denoising.yaml"
 
 
+@pytest.fixture
+def titaren_center_pc_FBP3d_resample():
+    return "docs/source/pipelines_full/titaren_center_pc_FBP3d_resample.yaml"
+
+
 @pytest.fixture
 def deg360_paganin_FBP3d_tomobar():
     return "docs/source/pipelines_full/deg360_paganin_FBP3d_tomobar.yaml"
@@ -378,6 +383,12 @@ def pipeline_paganin_sweep_recon_images_i12_119647_tiffs():
     return "tests/test_data/raw_data/i12/sweep/images_sweep_FBP3d_tomobar16bit_tif/"
 
 
+@pytest.fixture
+def pipeline_parallel_titaren_center_pc_FBP3d_resample_i12_119647_tiffs():
+    # 200 downsampled to 512 x 512 tiff files from reconstruction of i12_119647
+    return "tests/test_data/raw_data/i12/tiffs/images8bit_tif/"
+
+
 # ---------------------END------------------------#
 
 # TODO: deprecate when loader is generalised

tests/test_parallel_pipeline_big.py

@@ -452,6 +452,59 @@ def test_parallel_pipe_360deg_distortion_FBP3d_tomobar_i13_179623_preview(
     assert res_norm < 1e-4
 
 
+# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
+@pytest.mark.full_data_parallel
+def test_parallel_pipe_titaren_center_pc_FBP3d_resample_i12_119647_preview(
+    get_files: Callable,
+    cmd_mpirun,
+    i12_119647,
+    titaren_center_pc_FBP3d_resample,
+    pipeline_parallel_titaren_center_pc_FBP3d_resample_i12_119647_tiffs,
+    output_folder,
+):
+    change_value_parameters_method_pipeline(
+        titaren_center_pc_FBP3d_resample,
+        method=[
+            "standard_tomo",
+            "data_resampler",
+            "remove_stripe_ti",
+        ],
+        key=[
+            "preview",
+            "newshape",
+            "beta",
+        ],
+        value=[
+            {"detector_y": {"start": 900, "stop": 1100}},
+            [512, 512],
+            0.01,
+        ],
+    )
+
+    cmd_mpirun.insert(9, i12_119647)
+    cmd_mpirun.insert(10, titaren_center_pc_FBP3d_resample)
+    cmd_mpirun.insert(11, output_folder)
+
+    process = Popen(
+        cmd_mpirun, env=os.environ, shell=False, stdin=PIPE, stdout=PIPE, stderr=PIPE
+    )
+    output, error = process.communicate()
+    print(output)
+
+    files = get_files(output_folder)
+    files_references = get_files(
+        pipeline_parallel_titaren_center_pc_FBP3d_resample_i12_119647_tiffs
+    )
+
+    # recurse through output_dir and check that all files are there
+    files = get_files(output_folder)
+    assert len(files) == 204
+
+    #: check the number of the resulting tif files
+    check_tif(files, 200, (512, 512))
+    compare_tif(files, files_references)
+
+
 # ########################################################################
 @pytest.mark.full_data_parallel
 def test_parallel_pipe_sweep_FBP3d_tomobar_i13_177906(