Metadata-Version: 2.1
Name: neuroquery
Version: 1.0.2
Summary: Meta-analysis of neuroimaging studies
Home-page: https://github.com/neuroquery/neuroquery
Maintainer: Jerome Dockes
Maintainer-email: jerome@dockes.org
License: BSD 3-Clause License
Description: [![Build Status](https://dev.azure.com/neuroquery/neuroquery/_apis/build/status/neuroquery.neuroquery?branchName=master)](https://dev.azure.com/neuroquery/neuroquery/_build/latest?definitionId=1&branchName=master) [![codecov](https://codecov.io/gh/neuroquery/neuroquery/branch/master/graph/badge.svg)](https://codecov.io/gh/neuroquery/neuroquery) 
        
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/neuroquery/neuroquery.git/master?filepath=examples)
        
        # NeuroQuery
        
        NeuroQuery is a tool and a statistical model for meta-analysis of the functional
        neuroimaging literature.
        
        Given a text query, it can produce a brain map of the most relevant anatomical
        structures according to the current scientific literature.
        
        It can be used through a web interface: https://neuroquery.org
        
        Technical details and extensive validation are provided in [this paper](https://elifesciences.org/articles/53385).
        
        This Python package permits using NeuroQuery offline or integrating it in other
        applications. 
        
        ## Getting started
        
        [Quick demo](https://nbviewer.jupyter.org/github/neuroquery/neuroquery/blob/master/examples/minimal_example.ipynb)
        
        ### Dependencies
        
        NeuroQuery requires Python 3, numpy, scipy, scikit-learn, nilearn, pandas,
        regex, lxml, and requests.
        
        nltk is an optional dependency needed only if you use stemming or lemmatization
        for tokenization of input text.
        
        python-Levenshtein is an optional dependency used only in some parts of
        tokenization. If you use the vocabulary lists provided with `neuroquery` or in
        `neuroquery_data` it is not needed.
        
        ### Installation
        
        `neuroquery` can be installed with
        
        ```
        pip install neuroquery
        ```
        
        ### Usage
        
        In the `examples` folder, 
        [`minimal_example.ipynb`](https://nbviewer.jupyter.org/github/neuroquery/neuroquery/blob/master/examples/minimal_example.ipynb)
        shows basic usage of `neuroquery`.
        
        `neuroquery` has a function to download a trained model so that users can get
        started right away:
        
        ```python
        from neuroquery import fetch_neuroquery_model, NeuroQueryModel
        from nilearn.plotting import view_img
        
        encoder = NeuroQueryModel.from_data_dir(fetch_neuroquery_model())
        # encoder returns a dictionary containing a brain map and more,
        # see examples or documentation for details
        view_img(
            encoder("Parkinson's disease")["brain_map"], threshold=3.).open_in_browser()
        ```
        
        `neuroquery` also provides classes to train new models from scientific
        publications' text and stereotactic peak activation coordinates (see
        [`training_neuroquery.ipynb`](https://nbviewer.jupyter.org/github/neuroquery/neuroquery/blob/master/examples/training_neuroquery.ipynb)
        in the examples).
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3
Description-Content-Type: text/markdown
