Metadata-Version: 2.1
Name: nsdcode
Version: 1.1.dev260054000
Summary: NSD map data from various spaces
Home-page: https://github.com/kendrickkay/nsdcode
Author: Ian Charest and Kendrick Kay
Author-email: charest.ian@gmail.com
Maintainer: Ian Charest
Maintainer-email: charest.ian@gmail.com
License: UNKNOWN
Description: # nsdcode
        
        This repository contains nsd_mapdata.{m,py}, a light-weight utility that
        allows the user to map data between different reference spaces
        (e.g. anatomical, functional, volume-based, surface-based) in the NSD dataset.
        Both MATLAB and Python versions of the utility are provided.
        
        For more information on the NSD dataset, please see http://naturalscenesdataset.org.
        
        For examples of how to use nsd_mapdata, please take a look at examples_nsdmapdata.{m,py}.
        
        Known issues:
        * Note that the MATLAB and Python implementations give extremely similar but not
        numerically identical results due to differences in interpolation implementation.
        Also, voxels near the edges of valid locations are also handled slightly differently
        in the Python version.
        * The Python version does not yet implement the anat-to-anat case.
        
        
        ## MATLAB
        
        The MATLAB implementation relies on a few external toolboxes that are provided
        in the matlab/external directory.
        
        To install, unzip the matlab/external/*.zip files in place, and then
        
        ```matlab
        addpath(genpath('/path/to/nsdcode/matlab/'));
        ```
        
        Because the utility relies on transformation files provided with the NSD dataset,
        the user must edit **nsd_datalocation.m** with the location of your local copy
        of the NSD dataset.
        
        
        ## Python
        
        To install: 
        
        ```bash
        cd python
        python setup.py develop
        ```
        
        Code dependencies:
        
        There are some external dependencies which are listed in requirements.txt
        These are installed automatically when you run the setup above.
        These dependencies include:
        
          1. nibabel
          2. scipy
          3. numpy
          4. tqdm
        
        
        ## Change history
        
        * Version 1.0 (Dec 20, 2020). This is the first official release of the software.
        
Platform: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
