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"""
============================================================
Creating a new workflow.
============================================================
A workflow is a series of DIPY_ operations with fixed inputs and outputs
that is callable via command line or another interface.
For example, after installing DIPY_, you can call anywhere from your command
line::
dipy_nlmeans t1.nii.gz t1_denoised.nii.gz
First create your workflow (let's name this workflow file as my_workflow.py).
Usually this is a python file in the ``<../dipy/workflows>`` directory.
"""
import shutil
###############################################################################
# ``shutil`` Will be used for sample file manipulation.
from dipy.workflows.workflow import Workflow
###############################################################################
# ``Workflow`` is the base class that will be extended to create our workflow.
class AppendTextFlow(Workflow):
def run(
self, input_files, text_to_append="dipy", out_dir="", out_file="append.txt"
):
"""
Parameters
----------
input_files : string
Path to the input files. This path may contain wildcards to
process multiple inputs at once.
text_to_append : string, optional
Text that will be appended to the file. (default 'dipy')
out_dir : string, optional
Where the resulting file will be saved. (default '')
out_file : string, optional
Name of the result file to be saved. (default 'append.txt')
"""
"""
``AppendTextFlow`` is the name of our workflow. Note that it needs
to extend Workflow for everything to work properly. It will append
text to a file.
It is mandatory to have out_dir as a parameter. It is also mandatory
to put `out_` in front of every parameter that is going to be an
output. Lastly, all `out_` params needs to be at the end of the params
list.
The ``run`` docstring is very important, you need to document every
parameter as they will be used with inspection to build the command line
argument parser.
"""
io_it = self.get_io_iterator()
for in_file, out_file in io_it:
shutil.copy(in_file, out_file)
with open(out_file, "a") as myfile:
myfile.write(text_to_append)
###############################################################################
# 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.
#
# By iterating on the ``IOIterator`` object you created previously you
# conveniently get all input and output paths for every input file
# found when globbing the input parameters.
#
# The code in the loop is the actual workflow processing code. It can be
# anything. For example, it just appends text to an input file.
#
# This is it for the workflow! 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_append_text = "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_append_text": ("dipy.workflows.my_workflow", "AppendTextFlow")``
#
# 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::
#
# dipy_append_text --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.
|
