Metadata-Version: 2.1
Name: ggseg
Version: 0.1
Summary: Python module for ggseg-like visualizations
Home-page: https://github.com/ggseg/python-ggseg
Author: Greg Operto
Author-email: goperto@barcelonabeta.org
License: MIT
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        # python-ggseg
        
        Python module for ggseg-like visualizations. 
        
        ## Dependencies
        
        Requires `matplotlib>=3.4` and `numpy>=1.21`.
        
        ## Install
        
        ```pip install ggseg```
        
        ## Usage
        
        In order to work with `python-ggseg`, the data should be prepared as a
        dictionary where each item is one region of a given atlas assigned with some
        numeric value. The current version includes three atlases: the
        [Desikan-Killiany (DK) atlas](https://pubmed.ncbi.nlm.nih.gov/16530430/)
        , the [Johns Hopkins University (JHU) white-matter atlas](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases) and the [FreeSurfer `aseg` atlas](https://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferVersion3).
        
        ### Cortical ROIs (Desikan-Killiany)
        
        Cortical ROI data such as using the DK atlas may be
        structured as follows:
        > ```
        > {'bankssts_left': 1.1,
        >  'caudalanteriorcingulate_left': 1.0,
        >  'caudalmiddlefrontal_left': 2.6,
        >  'cuneus_left': 2.6,
        >  'entorhinal_left': 0.6,
        >  ...}
        
        Then be passed to the `ggseg.plot_dk` function:
        
        ```python
        import ggseg
        ggseg.plot_dk(data, cmap='Spectral', figsize=(15,15),
                      background='k', edgecolor='w', bordercolor='gray',
                      ylabel='Cortical thickness (mm)', title='Title of the figure')
        ```
        
        ![DK](https://raw.githubusercontent.com/ggseg/python-ggseg/main/doc/dk01.jpg)
        
        The comprehensive list of applicable regions can be found in this [folder](https://github.com/ggseg/python-ggseg/tree/main/ggseg/data/dk).
        
        ### Subcortical regions (FreeSurfer `aseg` atlas)
        
        ```python
        data = {'Left-Lateral-Ventricle': 12289.6,
                'Left-Thalamus': 8158.3,
                'Left-Caudate': 3463.3,
                'Left-Putamen': 4265.3,
                'Left-Pallidum': 1620.9,
                '3rd-Ventricle': 1635.6,
                '4th-Ventricle': 1115.6,
                ...}
        ```
        
        ```python
        ggseg.plot_aseg(data, cmap='Spectral',
                        background='k', edgecolor='w', bordercolor='gray',
                        ylabel='Volume (mm3)', title='Title of the figure')
        ```
        
        ![aseg](https://raw.githubusercontent.com/ggseg/python-ggseg/main/doc/aseg.png)
        
        The comprehensive list of applicable regions can be found in this [folder](https://github.com/ggseg/python-ggseg/tree/main/ggseg/data/aseg).
        
        ### White-matter fiber tracts (Johns Hopkins University)
        
        ```python
        data = {'Anterior thalamic radiation L': 0.3004812598228455,
                'Anterior thalamic radiation R': 0.2909256815910339,
                'Corticospinal tract L': 0.3517134189605713,
                'Corticospinal tract R': 0.3606771230697632,
                'Cingulum (cingulate gyrus) L': 0.3149917721748352,
                'Cingulum (cingulate gyrus) R': 0.3126821517944336,
                ...}
        ```
        
        ```python
        ggseg.plot_jhu(data_jhu, background='k', edgecolor='w', cmap='Spectral',
                       bordercolor='gray', ylabel='Mean Fractional Anisotropy',
                       title='Title of the figure')
        ```
        
        ![JHU](https://raw.githubusercontent.com/ggseg/python-ggseg/main/doc/jhu.png)
        
        The comprehensive list of applicable regions can be found in this [folder](https://github.com/ggseg/python-ggseg/tree/main/ggseg/data/jhu).
        
        ## Tests
        
        The current development version of `python-ggseg` has a coverage rate close to 100%.
        The corresponding tests can be found in this [folder](https://github.com/ggseg/python-ggseg/tree/main/ggseg/tests).
        
        ## Examples
        
        A Jupyter Notebook with examples can be found [there](https://github.com/ggseg/python-ggseg/blob/main/doc/ggseg.ipynb).
        
Platform: any
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
