#!/usr/bin/env Rscript
library(grangers)
library(RcppCNPy)

signal_mat <- npyLoad('../data/time_series_small.npy')
x <- signal_mat[1, ]
y <- signal_mat[2, ]

GC <- Granger.unconditional(x, y, ic.chosen='AIC', max.lag=4, plot=F)
frequency <- GC$frequency
gc_x_y <- GC$Unconditional_causality_x.to.y
gc_y_x <- GC$Unconditional_causality_y.to.x
result_df <- data.frame(frequency, gc_x_y, gc_y_x)

gc_matrix <- as.matrix(result_df)

npySave("../data/gc_matrix.npy", gc_matrix)