update release and dev

1.8.0/_downloads/010b39bedbe86acef7710ea2f2054aab/combined_workflow_creation.py

@@ -5,20 +5,17 @@
 
 A ``CombinedWorkflow`` is a series of DIPY_ workflows organized together in a
 way that the output of a workflow serves as input for the next one.
-"""
-
-###############################################################################
-# First create your ``CombinedWorkflow`` class. Your ``CombinedWorkflow`` class
-# file is usually located in the ``dipy/workflows`` directory.
 
+First create your ``CombinedWorkflow`` class. Your ``CombinedWorkflow`` class
+file is usually located in the ``dipy/workflows`` directory.
+"""
 
 from dipy.workflows.combined_workflow import CombinedWorkflow
 
 ###############################################################################
 # ``CombinedWorkflow`` is the base class that will be extended to create our
 # combined workflow.
 
-
 from dipy.workflows.denoise import NLMeansFlow
 from dipy.workflows.segment import MedianOtsuFlow
 
@@ -27,7 +24,6 @@
 # processing section.
 
 
-
 class DenoiseAndSegment(CombinedWorkflow):
 
     """
@@ -42,8 +38,8 @@ def _get_sub_flows(self):
         ]
 
         """
-        It is mandatory to implement this method if you want to make all the sub
-        workflows parameters available in commandline.
+        It is mandatory to implement this method if you want to make all the
+        sub workflows parameters available in commandline.
         """
 
     def run(self, input_files, out_dir='', out_file='processed.nii.gz'):
@@ -84,59 +80,46 @@ def run(self, input_files, out_dir='', out_file='processed.nii.gz'):
 
 ###############################################################################
 # Use ``self.get_io_iterator()`` in every workflow you create. This creates
-# an ``IOIterator`` object that create output file names and directory structure
-# based on the inputs and some other advanced output strategy parameters.
-# 
+# an ``IOIterator`` object that create output file names and directory
+# structure based on the inputs and some other advanced output strategy
+# parameters.
+#
 # Iterating on the ``IOIterator`` object you created previously you
 # conveniently get all input and output paths for every input file
 # found when globbin the input parameters.
-# 
-# In the ``IOIterator`` loop you can see how we create a new ``NLMeans`` workflow
-# then run it using ``self.run_sub_flow``. Running it this way will pass any
-# workflow specific parameter that was retrieved from the command line and will
-# append the ones you specify as optional parameters (``out_dir`` in this case).
-# 
+#
+# In the ``IOIterator`` loop you can see how we create a new ``NLMeans``
+# workflow then run it using ``self.run_sub_flow``. Running it this way will
+# pass any workflow specific parameter that was retrieved from the command line
+# and will append the ones you specify as optional parameters (``out_dir``
+# in this case).
+#
 # Lastly, the outputs paths are retrieved using
 # ``workflow.last_generated_outputs``. This allows to use ``denoise`` as the
 # input for the ``MedianOtsuFlow``.
-
-
-###############################################################################
-# 
-# This is it for the combined workflow class! Now to be able to call it easily via
-# command line, you need this last bit of code. It is usually in an executable
-# file located in ``bin``.
-
-
-from dipy.workflows.flow_runner import run_flow
-###############################################################################
-# This is the method that will wrap everything that is needed to make a workflow
-# ready then run it.
-
-
-# if __name__ == "__main__":
-#     run_flow(DenoiseAndSegment())
-###############################################################################
-# This is the only thing needed to make your workflow available through command
-# line.
-# 
-# Now just call the script you just made with ``-h`` to see the argparser help
+#
+#
+# This is it for the combined workflow class! Now to be able to call it easily
+# via command line, you need to add this workflow in 2 different files:
+# - ``<dipy_root>/pyproject.toml``: open this file and add the following line
+#   to the ``[project.scripts]`` section:
+#   ``dipy_denoise_segment = "dipy.workflows.cli:run"``
+# - ``<dipy_root>/dipy/workflows/cli.py``: open this file and add the workflow
+#   information to the ``cli_flows`` dictionary. The key is the name of the
+#   command line command and the value is a tuple with the module name and the
+#   workflow class name. In this case it would be:
+#   ``"dipy_denoise_segment": ("dipy.workflows.my_combined_workflow",
+#                              "DenoiseAndSegment")``
+#
+# That`s it! Now you can call your workflow from anywhere with the command line.
+# Let's just call the script you just made with ``-h`` to see the argparser help
 # text::
-# 
-#    python combined_workflow_creation.py --help
-# 
-# You should see all your parameters available along with some extra common ones
-# like logging file and force overwrite. Also all the documentation you wrote
-# about each parameter is there. Also note that every sub workflow optional
-# parameter is available.
-# 
-# Now call it for real with a nifti file to see the results. Experiment
-# with the parameters and see the results::
-# 
-#    python combined_workflow_creation.py volume.nii.gz
-# 
-# .. include:: ../links_names.inc
-# 
+#
+#    dipy_denoise_segment --help
+#
+# You should see all your parameters available along with some extra common
+# ones like logging file and force overwrite. Also all the documentation you
+# wrote about each parameter is there.
 
 ###############################################################################
 # .. include:: ../../links_names.inc