This function finds all the TP values of the models given (e.g. 0,1,2,3),
generates every pairwise combination (e.g. the group matchings: (0,1), (1,3),
etc.) and uses the get_avg_activity_diff_based_on_tp_predictions
function on each generated classification group matching, comparing thus all
groups of models with different true positive (TP) values.
get_avg_activity_diff_mat_based_on_tp_predictions(models,
models.synergies.tp, models.stable.state)character vector. The model names.
an integer vector of TP values. The names
attribute holds the models' names and have to be in the same order as in the
models parameter.
a matrix (nxm) with n models and m nodes. The row
names of the matrix specify the models' names (same order as in the models
parameter) whereas the column names specify the name of the network nodes
(gene, proteins, etc.). Possible values for each model-node element
are either 0 (inactive node) or 1 (active node).
a matrix whose rows are vectors of average node activity state differences between two groups of models where the classification was based on the number of true positive predictions. Rows represent the different classification group matchings, e.g. (1,2) means the models that predicted 1 TP synergy vs the models that predicted 2 TP synergies and the columns represent the network's node names. Values are in the [-1,1] interval.
Other average data difference functions: get_avg_activity_diff_based_on_mcc_clustering,
get_avg_activity_diff_based_on_specific_synergy_prediction,
get_avg_activity_diff_based_on_synergy_set_cmp,
get_avg_activity_diff_based_on_tp_predictions,
get_avg_activity_diff_mat_based_on_mcc_clustering,
get_avg_activity_diff_mat_based_on_specific_synergy_prediction,
get_avg_link_operator_diff_mat_based_on_mcc_clustering,
get_avg_link_operator_diff_mat_based_on_specific_synergy_prediction,
get_avg_link_operator_diff_mat_based_on_tp_predictions