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# interfaces.cmtk.nbs

## NetworkBasedStatistic

Link to code

Calculates and outputs the average network given a set of input NetworkX gpickle files

For documentation of Network-based statistic parameters:

> https://github.com/LTS5/connectomeviewer/blob/master/cviewer/libs/pyconto/groupstatistics/nbs/_nbs.py

### Example

    >>> import nipype.interfaces.cmtk as cmtk
    >>> nbs = cmtk.NetworkBasedStatistic()
    >>> nbs.inputs.in_group1 = ['subj1.pck', 'subj2.pck']
    >>> nbs.inputs.in_group2 = ['pat1.pck', 'pat2.pck']
    >>> nbs.run()

Inputs:

    [Mandatory]
    in_group1: (an existing file name)
            Networks for the first group of subjects
    in_group2: (an existing file name)
            Networks for the second group of subjects

    [Optional]
    edge_key: (a string, nipype default value: number_of_fibers)
            Usually "number_of_fibers, "fiber_length_mean", "fiber_length_std"
            for matrices made with CMTKSometimes "weight" or "value" for
            functional networks.
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    in_group1: (an existing file name)
            Networks for the first group of subjects
    in_group2: (an existing file name)
            Networks for the second group of subjects
    node_position_network: (a file name)
            An optional network used to position the nodes for the output
            networks
    number_of_permutations: (an integer, nipype default value: 1000)
            Number of permutations to perform
    out_nbs_network: (a file name)
            Output network with edges identified by the NBS
    out_nbs_pval_network: (a file name)
            Output network with p-values to weight the edges identified by the
            NBS
    t_tail: ('left' or 'right' or 'both', nipype default value: left)
            Can be one of "left", "right", or "both"
    threshold: (a float, nipype default value: 3)
            T-statistic threshold

Outputs:

    nbs_network: (an existing file name)
            Output network with edges identified by the NBS
    nbs_pval_network: (an existing file name)
            Output network with p-values to weight the edges identified by the
            NBS
    network_files: (an existing file name)
            Output network with edges identified by the NBS

## `ntwks_to_matrices()`

Link to code