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# nipype.interfaces.cmtk.nx module

## AverageNetworks

Link to code

> Bases: BaseInterface

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

> This interface will only keep an edge in the averaged network if that edge is present in at least half of the input networks.

> Example

>     >>> import nipype.interfaces.cmtk as cmtk
>     >>> avg = cmtk.AverageNetworks()
>     >>> avg.inputs.in_files = ['subj1.pck', 'subj2.pck']
>     >>> avg.run()

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

>   Networks for a group of subjects.

> group_ida string

>   ID for group. (Nipype default value: `group1`)

> out_gexf_groupavga pathlike object or string representing a file

>   Average network saved as a .gexf file.

> out_gpickled_groupavga pathlike object or string representing a file

>   Average network saved as a NetworkX .pck.

> resolution_network_filea pathlike object or string representing an existing file

>   Parcellation files from Connectome Mapping Toolkit. This is not necessary, but if included, the interface will output the statistical maps as networkx graphs.

> gexf_groupavga pathlike object or string representing a file

>   Average network saved as a .gexf file.

> gpickled_groupavga pathlike object or string representing a file

>   Average network saved as a NetworkX .pck.

> matlab_groupavgs : a list of items which are a pathlike object or string representing a file

## NetworkXMetrics

Link to code

> Bases: BaseInterface

> Calculates and outputs NetworkX-based measures for an input network

> Example

>     >>> import nipype.interfaces.cmtk as cmtk
>     >>> nxmetrics = cmtk.NetworkXMetrics()
>     >>> nxmetrics.inputs.in_file = 'subj1.pck'
>     >>> nxmetrics.run()

> in_filea pathlike object or string representing an existing file

>   Input network.

> compute_clique_related_measuresa boolean

>   Computing clique-related measures (e.g. node clique number) can be very time consuming. (Nipype default value: `False`)

> out_edge_metrics_matlaba pathlike object or string representing a file

>   Output edge metrics in MATLAB .mat format.

> out_global_metrics_matlaba pathlike object or string representing a file

>   Output node metrics in MATLAB .mat format.

> out_k_corea pathlike object or string representing a file

>   Computed k-core network stored as a NetworkX pickle. (Nipype default value: `k_core`)

> out_k_crusta pathlike object or string representing a file

>   Computed k-crust network stored as a NetworkX pickle. (Nipype default value: `k_crust`)

> out_k_shella pathlike object or string representing a file

>   Computed k-shell network stored as a NetworkX pickle. (Nipype default value: `k_shell`)

> out_node_metrics_matlaba pathlike object or string representing a file

>   Output node metrics in MATLAB .mat format.

> out_pickled_extra_measuresa pathlike object or string representing a file

>   Network measures for group 1 that return dictionaries stored as a Pickle. (Nipype default value: `extra_measures`)

> treat_as_weighted_grapha boolean

>   Some network metrics can be calculated while considering only a binarized version of the graph. (Nipype default value: `True`)

> edge_measure_networks : a list of items which are a pathlike object or string representing a file edge_measures_matlab : a pathlike object or string representing a file

> > Output edge metrics in MATLAB .mat format.

> global_measures_matlaba pathlike object or string representing a file

>   Output global metrics in MATLAB .mat format.

> gpickled_network_files : a list of items which are a pathlike object or string representing a file k_core : a pathlike object or string representing a file

> > Computed k-core network stored as a NetworkX pickle.

> k_crusta pathlike object or string representing a file

>   Computed k-crust network stored as a NetworkX pickle.

> k_networks : a list of items which are a pathlike object or string representing a file k_shell : a pathlike object or string representing a file

> > Computed k-shell network stored as a NetworkX pickle.

> matlab_dict_measures : a list of items which are a pathlike object or string representing a file matlab_matrix_files : a list of items which are a pathlike object or string representing a file node_measure_networks : a list of items which are a pathlike object or string representing a file node_measures_matlab : a pathlike object or string representing a file

> > Output node metrics in MATLAB .mat format.

> pickled_extra_measuresa pathlike object or string representing a file

>   Network measures for the group that return dictionaries, stored as a Pickle.

nipype.interfaces.cmtk.nx.add_dicts_by_key(in_dict1, in_dict2)

  Combines two dictionaries and adds the values for those keys that are shared

nipype.interfaces.cmtk.nx.add_edge_data(edge_array, ntwk, above=0, below=0)

nipype.interfaces.cmtk.nx.add_node_data(node_array, ntwk)

nipype.interfaces.cmtk.nx.average_networks(in_files, ntwk_res_file, group_id)

  Sums the edges of input networks and divides by the number of networks Writes the average network as .pck and .gexf and returns the name of the written networks

nipype.interfaces.cmtk.nx.compute_dict_measures(ntwk)

  Returns a dictionary

nipype.interfaces.cmtk.nx.compute_edge_measures(ntwk)

  These return edge-based measures

nipype.interfaces.cmtk.nx.compute_network_measures(ntwk)

nipype.interfaces.cmtk.nx.compute_node_measures(ntwk, calculate_cliques=False)

  These return node-based measures

nipype.interfaces.cmtk.nx.compute_singlevalued_measures(ntwk, weighted=True, calculate_cliques=False)

  Returns a single value per network

nipype.interfaces.cmtk.nx.fix_keys_for_gexf(orig)

  GEXF Networks can be read in Gephi, however, the keys for the node and edge IDs must be converted to strings

nipype.interfaces.cmtk.nx.read_unknown_ntwk(ntwk)

nipype.interfaces.cmtk.nx.remove_all_edges(ntwk)