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# nipype.interfaces.cmtk.convert module

## CFFConverter

Link to code

> Bases: CFFBaseInterface

> Creates a Connectome File Format (CFF) file from input networks, surfaces, volumes, tracts, etcetera….

> Example

>     >>> import nipype.interfaces.cmtk as cmtk
>     >>> cvt = cmtk.CFFConverter()
>     >>> cvt.inputs.title = 'subject 1'
>     >>> cvt.inputs.gifti_surfaces = ['lh.pial_converted.gii', 'rh.pial_converted.gii']
>     >>> cvt.inputs.tract_files = ['streamlines.trk']
>     >>> cvt.inputs.gpickled_networks = ['network0.gpickle']
>     >>> cvt.run()

> creatora unicode string

>   Creator.

> data_filesa list of items which are a pathlike object or string representing an existing file

>   List of external data files (i.e. Numpy, HD5, XML) .

> descriptiona unicode string

>   Description. (Nipype default value: `Created with the Nipype CFF converter`)

> emaila unicode string

>   Email address.

> gifti_labelsa list of items which are a pathlike object or string representing an existing file

>   List of GIFTI labels.

> gifti_surfacesa list of items which are a pathlike object or string representing an existing file

>   List of GIFTI surfaces.

> gpickled_networksa list of items which are a pathlike object or string representing an existing file

>   List of gpickled Networkx graphs.

> graphml_networksa list of items which are a pathlike object or string representing an existing file

>   List of graphML networks.

> licensea unicode string

>   License.

> nifti_volumesa list of items which are a pathlike object or string representing an existing file

>   List of NIFTI volumes.

> out_filea pathlike object or string representing a file

>   Output connectome file. (Nipype default value: `connectome.cff`)

> publishera unicode string

>   Publisher.

> referencesa unicode string

>   References.

> relationa unicode string

>   Relation.

> rightsa unicode string

>   Rights.

> script_filesa list of items which are a pathlike object or string representing an existing file

>   List of script files to include.

> speciesa unicode string

>   Species. (Nipype default value: `Homo sapiens`)

> timeseries_filesa list of items which are a pathlike object or string representing an existing file

>   List of HDF5 timeseries files.

> titlea unicode string

>   Connectome Title.

> tract_filesa list of items which are a pathlike object or string representing an existing file

>   List of Trackvis fiber files.

> connectome_filea pathlike object or string representing an existing file

>   Output connectome file.

## MergeCNetworks

Link to code

> Bases: CFFBaseInterface

> Merges networks from multiple CFF files into one new CFF file.

> Example

>     >>> import nipype.interfaces.cmtk as cmtk
>     >>> mrg = cmtk.MergeCNetworks()
>     >>> mrg.inputs.in_files = ['subj1.cff','subj2.cff']
>     >>> mrg.run()

> in_filesa list of items which are a pathlike object or string representing an existing file

>   List of CFF files to extract networks from.

> out_filea pathlike object or string representing a file

>   Output CFF file with all the networks added. (Nipype default value: `merged_network_connectome.cff`)

> connectome_filea pathlike object or string representing an existing file

>   Output CFF file with all the networks added.