ggseg 0.1
Python module for ggseg-like visualizations
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).