Note
Go to the end to download the full example code.
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 thecli_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.
Total running time of the script: (0 minutes 0.001 seconds)