connectoviz.io.parsers

Functions

atlas_check(atlas[, index_col, label_col, ...])	Validate atlas format and infer index and label columns if not provided.
check_col_existence(cols_name)	Validate that at least one matching column was found.
check_layout_dict(layout_dict, comb_mat)	Check if the provided layout_dict is a valid dictionary.
check_layout_list_Multilayer(layers_list, ...)	Check if the provided layers_list is a valid list of dictionaries.
check_mapping([mapping, node_vec, label_vec])	Processes mapping information either from a DataFrame/dict or from two separate lists.
check_mask(mask)	Check if the mask is a valid binary 2D NumPy array.
check_metadata(metadata, atlas[, index_col, ...])	check if the metadata is in the correct format
check_namings(col_names, df)	Check if the given column names exist in the DataFrame.
compare_mapping(mapping, atlas)	Validate and match the mapping dictionary against the atlas DataFrame.
masking(mask, con_mat)	Apply a binary mask to a connectivity matrix.
merge_metadata(*metadata)	Merge multiple metadata DataFrames along columns with index alignment.
parse_matrix(data)	Parse a connectivity matrix from various supported formats.