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pynv

Python library for interfacing with http://neurovault.org API

Installation

  1. Method 1 (Recommended)

    pip install pynv

  2. Method 2 (Latest Development Version)

    git clone https://github.com/neurolearn/pynv.git
cd pynv
python setup.py install

Example Usage

Initialize a Client instance

First, we need to create an instance of the Client class. This requires adding your NeuroVault personal access token which can be found under “Personal Access tokens” tab in the Account Settings.

from pynv import Client

api = Client(access_token='your_neurovault_personal_access_token')

Create a Collection

To create a new collection in NeuroVault you need to pass a dictionary of all of the metadata you would like to specify in the collection. At a minimum you must specify a collection name.

collection = api.create_collection('a name of a new collection')

Add an image to a collection

Once a collection is created you can add images to it using the add_image() method. You need to pass a string indicating the path to the file you would like to upload. You also need to pass a few mandatory parameters, which include the image name, the image modality, and the map type.

Here are tables containing the corresponding to the values required by Neurovault for various image parameters.

Map Type Neurovault Value
T map T
Z map Z
F map F
Chi squared map X2
P map (given null hypothesis) P
Multivariate-beta map M
Univariate-beta map U
ROI/Mask R
Parcellation Pa
Anatomical A
Other OTHER
Analysis Level Neurovault Value
Single-Subject S
Group G
Meta-Analysis M
Other OTHER
Image Modality Neurovault Value
fMRI-BOLD fMRI_BOLD
fMRI-CBF fMRI_CBF
fMRI-CBV fMRI_CBV
Diffusion MRI Diffusion_MRI
Structural MRI Structural_MRI
PET FDG PET_FDG
PET [15O]-water PET_15O
PET Other PET_OTHER
MEG MEG
EEG EEG
Other OTHER 
image_file_path = 'path/to/image/file.nii.gz'

image = api.add_image(
    collection['id'],
    image_file_path,
    name='Parcellation_k25',
    modality='Other',
    map_type='Pa'
)

You can also annotate an image with custom metadata:

image = api.add_image(
    collection['id'],
    image_file_path,
    name='Parcellation_k25',
    modality='Other',
    map_type='Pa',
    custom_metadata_field=42
)

Update an image

api.update_image(
    image['id'], 
    map_type='T',
    custom_metadata_field=42
)

Delete an image

api.delete_image(image['id'])

Delete a collection

To delete a collection you can simply run the delete_collection() method. You can delete any collection that you own. Be careful with this as you will be unable to recover any collections that you delete!

api.delete_collection(collection.id)

Get a collection

You can get information about a collection using the get_collection() method.

c = api.get_collection(collection_id=collection)

Get Collection images

To get information about images within a collection, use the get_collection_images() method. You can use the limit and offset keywords to set the pagination. Here is an example using pagination to get information about collection images into a pandas data frame.

import pandas as pd

offset = 0
limit = 10
i = api.get_collection_images(collection_id=collection, limit=limit,offset=offset)
dat = pd.DataFrame(columns=i['results'][0].keys())
while int(offset) < int(i['count']):
    for x in i['results']:
        dat = dat.append(x,ignore_index=True)
    offset = offset + limit
    i = api.get_collection_images(collection_id=collection, limit=limit, offset=offset)