Created
December 12, 2021 21:04
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Generate simplest documentation possible
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# HERE import all functions/classes to generate documentation for | |
from covidseg.dataset_reduction import reduce_dataset | |
from covidseg.inference import inference | |
# Generate docstrings | |
def __docs(m): | |
""" | |
Generates simple docstring for python module. | |
""" | |
file = f"\nFILE: {m.__file__}" if hasattr(m, '__file__') else "" | |
d = f"{m.__module__}.{m.__name__}\n{m.__doc__}{file}\n" | |
return d | |
# HERE insert all modules to generate documentation for | |
mods = [ | |
reduce_dataset, | |
inference, | |
] | |
for mod in mods: | |
d = __docs(mod) | |
print(f"{d}\n") | |
# EXAMPLE OUTPUT | |
""" | |
covidseg.dataset_reduction.reduce_dataset | |
Reduce dataset within data_folder with help of lungseg_model. | |
:param lungseg_model: lung segmentation model Pytorch nn.Module | |
:param data_folder: path to inference images | |
:param output_folder: path where to store output volumes | |
covidseg.inference.inference | |
Performs inference on input volume with reducing the volume in the process. | |
:param volume_path: path to volume to perform inference on | |
:param lungseg_model: instance of lung segmentation model | |
:param covidseg_model: instance of covid segmentation model | |
:output_filename: output file name path | |
""" |
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