NWB conversion scripts and tutorials.
Project description
axel-lab-to-nwb
NWB conversion scripts and tutorials. A collaboration with Axel Lab.
Install
To clone the repository and set up a conda environment, do:
$ git clone https://github.com/ben-dichter-consulting/axel-lab-to-nwb.git
$ conda env create -f axel-lab-to-nwb/make_env.yml
$ source activate convert_to_nwb
Alternatively, to install directly in an existing environment:
$ pip install axel-lab-to-nwb
Use
After activating the correct environment, the conversion function can be used in different forms:
1. Imported and run from a python script:
Here's an example: we'll grab the data from the same experiment but stored in different .npz
files and save it to a single .nwb
file.
from axel_lab_to_nwb import conversion_function
source_paths = {}
source_paths['processed data'] = {'type': 'file', 'path': PATH_TO_FILE}
source_paths['sparse matrix'] = {'type': 'file', 'path': PATH_TO_FILE}
source_paths['ref image'] = {'type': 'file', 'path': PATH_TO_FILE}
f_nwb = 'fly2.nwb'
metafile = 'metafile.yml'
conversion_function(source_paths=source_paths,
f_nwb=f_nwb,
metafile=metafile,
plot_rois=False)
2. Command line:
Similarly, the conversion function can be called from the command line in terminal:
$ python conversion_module.py [processed_data_file] [sparse_matrix_file] [ref_image_file]
[output_file] [metadata_file]
3. Graphical User Interface:
To use the GUI, just run the auxiliary function nwb_gui.py
from terminal:
$ python nwb_gui.py
4. Tutorial:
At tutorials you can also find Jupyter notebooks with the step-by-step process of conversion.
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