Awesome
BdPy
Python package for brain decoding analysis
Requirements
- Python 3.8 or later
- numpy
- scipy
- scikit-learn
- pandas
- h5py
- hdf5storage
- pyyaml
Optional requirements
dataform
module- pandas
dl.caffe
module- Caffe
- Pillow
- tqdm
dl.torch
module- PyTorch
- Pillow
fig
module- matplotlib
- Pillow
bdpy.ml
module- tqdm
mri
module- nipy
- nibabel
- pandas
recon.torch
module- PyTorch
- Pillow
Optional requirements for testing
- fastl2lir
Installation
Latest stable release:
$ pip install bdpy
To install the latest development version ("master" branch of the repository), please run the following command.
$ pip install git+https://github.com/KamitaniLab/bdpy.git
Packages
- bdata: BdPy data format (BData) core package
- dataform: Utilities for various data format
- distcomp: Distributed computation utilities
- dl: Deep learning utilities
- feature: Utilities for DNN features
- fig: Utilities for figure creation
- ml: Machine learning utilities
- mri: MRI utilities
- opendata: Open data utilities
- preproc: Utilities for preprocessing
- recon: Reconstruction methods
- stats: Utilities for statistics
- util: Miscellaneous utilities
BdPy data format
BdPy data format (or BrainDecoderToolbox2 data format; BData) consists of two variables: dataset and metadata. dataset stores brain activity data (e.g., voxel signal value for fMRI data), target variables (e.g., ID of stimuli for vision experiments), and additional information specifying experimental design (e.g., run and block numbers for fMRI experiments). Each row corresponds to a single 'sample', and each column representes either single feature (voxel), target, or experiment design information. metadata contains data describing meta-information for each column in dataset.
See BData API examples for useage of BData.
Developers
- Shuntaro C. Aoki (Kyoto Univ)