CoClass

Functions used for the generation of coclassification matrices

PrepareCoclass

class neuropype_graph.nodes.coclass.PrepareCoclass(from_file=None, **inputs)

Prepare a list of coclassification matrices, in a similar reference given by a coord (resp label) file based on individual coords (resp labels) files

Inputs:

mod_files:

type = List of Files, exists=True, desc=’list of all files representing modularity assignement (in rada, lol files) for each subject’, mandatory=True

node_corres_files:

type = List of Files, exists=True, desc=’list of all Pajek files (in txt format) to extract correspondance between nodes in rada analysis and original subject coordinates for each subject (as obtained from PrepRada)’, mandatory=True

coords_files:

type = List of Files, exists=True, desc=’list of all coordinates in numpy space files (in txt format) for each subject (after removal of non void data)’, mandatory=True, xor = [‘labels_files’]

gm_mask_coords_file

type = File,exists=True, desc=’Coordinates in numpy space, corresponding to all possible nodes in the original space’, mandatory=False, xor = [‘gm_mask_labels_file’]

labels_files:

type = List of Files, exists=True, desc=’list of labels (in txt format) for each subject (after removal of non void data)’, mandatory=True, xor = [‘coords_files’]

gm_mask_labels_file:

type = File, exists=True, desc=’Labels for all possible nodes - in case coords are varying from one indiv to the other (source space for example)’, mandatory=False, xor = [‘gm_mask_coords_file’]

Outputs:

group_coclass_matrix_file:

type = File,exists=True, desc=”all coclass matrices of the group in .npy format”

sum_coclass_matrix_file:

type = File, exists=True, desc=”sum of coclass matrix of the group in .npy format”

sum_possible_edge_matrix_file:

type = File, exists=True, desc=”sum of possible edges matrices of the group in .npy format”

norm_coclass_matrix_file:

type = File, exists=True, desc=”sum of coclass matrix normalized by possible edges matrix of the group in .npy format”

DiffMatrices

class neuropype_graph.nodes.coclass.DiffMatrices(from_file=None, **inputs)

Description:

Compute difference between two matrices, should have same shape

Inputs:

mat_file1:

type = File,exists=True, desc=’Matrix in npy format’, mandatory=True

mat_file2:

type = File,exists=True, desc=’Matrix in npy format’, mandatory=True

Outputs:

diff_mat_file:

type = File, exists=True, desc=’Difference of Matrices (mat1 - mat2) in npy format’, mandatory=True

Comments:

Not sure where it is used ...

PlotCoclass

class neuropype_graph.nodes.coclass.PlotCoclass(from_file=None, **inputs)

Description :

Plot coclass matrix with matplotlib matshow

• labels are optional
• range values are optional (default is min and max values of the matrix)

Inputs:

coclass_matrix_file:

type = File, exists=True, desc=’coclass matrix in npy format’, mandatory=True

labels_file:

type = File, exists=True, desc=’labels of nodes’, mandatory=False

list_value_range

type = ListInt, desc=’force the range of the plot’, mandatory=False

Outputs:

plot_coclass_matrix_file:

type = File, exists=True, desc=”eps file with graphical representation”