nanshe.learner module

The module learner provides the ability to run the segmentation algorithm.

Overview

The main function actually starts the algorithm and can be called externally. The module allows for running multiple jobs through subprocess or drmaa. Configuration files for the learner are provided in the examples and are entitled learner.

API

nanshe.learner.generate_neurons(*args, **kwargs)

nanshe.learner.generate_neurons_a_block(*args, **kwargs)

Uses generate_neurons to process a input_filename (HDF5 dataset) and outputs results to an output_filename (HDF5 dataset).

Parameters:

• HDF5 filename to read from (should be a (input_filename) – path to a h5py.Dataset)
• HDF5 filename to write to (should be a path (output_filename) – to a h5py.Group)
• how the run should be configured. (parameters) –

nanshe.learner.generate_neurons_blocks(*args, **kwargs)

nanshe.learner.generate_neurons_io_handler(*args, **kwargs)

Uses generate_neurons to process a input_filename (HDF5 dataset) and outputs results to an output_filename (HDF5 dataset). Also,

Parameters:

• HDF5 filename to read from (should be a (input_filename) – path to a h5py.Dataset)
• HDF5 filename to write to (should be a path (output_filename) – to a h5py.Group)
• JSON filename with parameters. (parameters_filename) –

nanshe.learner.main(*args, **kwargs)

Simple main function (like in C). Takes all arguments (as from sys.argv) and returns an exit status.

Parameters:argv (list) – arguments (includes command line call). Returns:exit code (0 if success) Return type:int