Metadata-Version: 2.1
Name: niwidgets
Version: 0.2.1
Summary: A package that provides ipywidgets for standard neuroimaging plotting
Home-page: https://github.com/nipy/niwidgets
Author: Bjoern Soergel & Jan Freyberg
Author-email: jan.freyberg@gmail.com
License: UNKNOWN
Download-URL: https://github.com/nipy/niwidgets/archive/0.2.1.tar.gz
Description: # Neuroimaging Widgets (`niwidgets`)
        
        This repository is supposed to provide easy and general wrappers to display
        interactive widgets that visualise standard-format neuroimaging data, using new
        functions and standard functions from other libraries. It looks like this:
        
        ![](https://thumbs.gfycat.com/ExcitableReflectingLcont-size_restricted.gif)
        
        Install via:
        
        ```
        pip install niwidgets
        ```
        
        Or, to get the most up-to-date development version from github:
        
        ```
        pip install git+git://github.com/nipy/niwidgets/
        ```
        
        It requires nibabel and nilearn:
        
        ```
        pip install nibabel nilearn
        ```
        
        Check out the examples using the code in this notebook here:
        https://github.com/nipy/niwidgets/blob/master/index.ipynb (you need to run the
        notebook on your local machine to use the interactive features).
        
        or using binder here:
        https://mybinder.org/v2/gh/nipy/niwidgets/master?filepath=index.ipynb
        
        ### Usage:
        
        There are currently three supported widgets:
        
        1. Volume widgets. This widget is primarily designed to mimic existing tools
        such as <add tool here>, but it also allows you to wrap plots from the `nilearn`
        plotting library to make them interactive.
        
        2. Surface widgets. This widget takes freesurfer-generated volume files and
        turns them into widgets using the `ipyvolume` library. It allows you to add
        different overlays for the surface files.
        
        3. Streamline widgets. This widget accepts `.trk` files and displays the tracts
        using `ipyvolume`.
        
        To see how to use these widgets, please check the
        [documentation](nipy.org/niwidgets).
        
        As an example of how you might generate a Volume widget:
        
        ```
        from niwidgets import NiftiWidget
        
        my_widget = NiftiWidget('./path/to/file.nii')
        ```
        
        You can then create a plot either with the default nifti plotter:
        
        ```
        my_widget.nifti_plotter()
        ```
        
        This will give you sliders to slice through the image, and an option to set the
        colormap.
        
        You can also provide your own plotting function:
        
        ```
        import nilearn.plotting as nip
        
        my_widget.nifti_plotter(plotting_func=nip.plot_glass_brain)
        ```
        
        By default, this will give you the following interactive features: -
        selecting a colormap - if supported by the plotting function, x-y-x
        sliders (e.g. for `nip.plot_img`)
        
        
        You can, however, always provide features you would like to have interactive
        yourself. This follows the normal ipywidgets format. For example, if you provide
        a list of strings for a keyword argument, this becomes a drop-down menu. If you
        provide a tuple of two numbers, this becomes a slider. Take a look at some
        examples we have in [this
        notebook](https://github.com/janfreyberg/niwidgets/blob/master/visualisation_wrapper.ipynb)
        (you need to run the notebook on your local machine to use the interactive
        features).
        
        Hopefully we will be able to add more default interactive features in the
        future, as well as plotting of other data (such as surface projections). If you
        have any suggestions for plot features to be added, please let us know - or add
        them yourself and create a pull request!
        
        ## Development
        
        ![](https://travis-ci.org/nipy/niwidgets.svg?branch=master)
        
        ### Contributing
        
        Please contribute! When writing new widgets, please make sure you include
        example data that allows users to try a widget without having to munge their
        data into the right format first.
        
        Please also make sure you write a test for your new widget. It's hard to test
        jupyter widgets, but it would be great if you could at least write a test that
        "instantiates" a widget. This allows us to maintain a stable release.
        
        ### Development installation
        
        As always with pip packages, you can install a _"development"_ version of this
        package by cloning the git repository and installing it via `pip install -e
        /path/to/package`.
        
        ### Updating the documentation
        
        To update the documentation, you can do the following things:
        
        - Make your changes on a separate branch, such as DOC/update-api-documentation.
        - Merge your branch into master Make sure you have the packages in
        - `doc-requirements.txt` installed Run `make gh-pages` in the root directory of
        - the repository
        
        This should run sphinx to generate the documentation, push it to the gh-pages
        branch, and then revert to master.
        
        ---
        
        _Developed by [Jan Freyberg](http://www.twitter.com/janfreyberg), [Bjoern
        Soergel](http://www.ast.cam.ac.uk/~bs538/), [Satrajit
        Ghosh](https://github.com/satra), [Melanie
        Ganz](https://github.com/melanieganz), [Murat
        Bilgel](https://github.com/bilgelm), [Ariel Rokem](https://github.com/arokem),
        and [elyb01](https://github.com/elyb01)._
        
Keywords: widgets,neuroimaging
Platform: UNKNOWN
Description-Content-Type: text/markdown
