tests/testthat/test_excess_entropy.R

In ELIFE-ASU/rinform: An R Wrapper of the 'Inform' C Library for Information Analysis of Complex Systems

################################################################################
# Copyright 2017-2018 Gabriele Valentini, Douglas G. Moore. All rights reserved.
# Use of this source code is governed by a MIT license that can be found in the
# LICENSE file.
################################################################################
library(rinform)
context("Excess Entropy")

test_that("excess_entropy checks parameters", {
  xs <- sample(0:1, 10, T)
  expect_error(excess_entropy("series", k = 1, local = !T))
  expect_error(excess_entropy(NULL,     k = 1, local = !T))
  expect_error(excess_entropy(NA,       k = 1, local = !T))
  
  expect_error(excess_entropy(xs, k = "k",  local = !T))
  expect_error(excess_entropy(xs, k = NULL, local = !T))
  expect_error(excess_entropy(xs, k = NA,   local = !T))  
  expect_error(excess_entropy(xs, k = 0,    local = !T))
  expect_error(excess_entropy(xs, k = -1,   local = !T))
  
  expect_error(excess_entropy(xs, k = 1, local = "TRUE"))
  expect_error(excess_entropy(xs, k = 1, local = NULL))
  expect_error(excess_entropy(xs, k = 1, local = NA))  
})

test_that("excess_entropy on single series", {
  expect_equal(excess_entropy(c(1, 1, 0, 0, 1, 0, 0, 1), k = 2, local = !T),
               1.521928, tolerance = 1e-6)
  expect_equal(excess_entropy(c(1, 0, 0, 0, 0, 0, 0, 0, 0), k = 2, local = !T),
               0.000000, tolerance = 1e-6)
  expect_equal(excess_entropy(c(0, 0, 1, 1, 1, 1, 0, 0, 0), k = 2, local = !T),
               0.666667, tolerance = 1e-6)

  expect_equal(excess_entropy(c(1, 1, 0, 0, 1, 0, 0, 1), k = 3, local = !T),
               1.584963, tolerance = 1e-6)
  expect_equal(excess_entropy(c(1, 0, 0, 0, 0, 0, 0, 0, 0), k = 3, local = !T),
               0.000000, tolerance = 1e-6)
  expect_equal(excess_entropy(c(0, 0, 1, 1, 1, 1, 0, 0, 0), k = 3, local = !T),
               1.500000, tolerance = 1e-6)

  expect_equal(excess_entropy(c(3, 3, 3, 2, 1, 0, 0, 0, 1), k = 2, local = !T),
               1.918296, tolerance = 1e-6)
  expect_equal(excess_entropy(c(2, 2, 3, 3, 3, 3, 2, 1, 0), k = 2, local = !T),
               1.000000, tolerance = 1e-6)
  expect_equal(excess_entropy(c(2, 2, 2, 2, 2, 2, 1, 1, 1), k = 2, local = !T),
               0.316689, tolerance = 1e-6)

  expect_equal(excess_entropy(c(3, 3, 3, 2, 1, 0, 0, 0, 1), k = 3, local = !T),
               2.000000, tolerance = 1e-6)
  expect_equal(excess_entropy(c(2, 2, 3, 3, 3, 3, 2, 1, 0), k = 3, local = !T),
               1.500000, tolerance = 1e-6)
  expect_equal(excess_entropy(c(2, 2, 2, 2, 2, 2, 1, 1, 1), k = 3, local = !T),
               0.000000, tolerance = 1e-6)
})

test_that("excess_entropy on ensemble of series", {
  series      <- matrix(0, nrow = 8, ncol = 2)
  series[, 1] <- c(1, 1, 0, 0, 1, 0, 0, 1)
  series[, 2] <- c(0, 0, 0, 1, 0, 0, 0, 1)
  expect_equal(excess_entropy(series, k = 2, local = !T), 0.846439, tolerance = 1e-6)
  expect_equal(excess_entropy(series, k = 3, local = !T), 1.584963, tolerance = 1e-6)

  series      <- matrix(0, nrow = 9, ncol = 9)
  series[, 1] <- c(1, 0, 0, 0, 0, 0, 0, 0, 0)
  series[, 2] <- c(0, 0, 1, 1, 1, 1, 0, 0, 0)
  series[, 3] <- c(1, 0, 0, 0, 0, 0, 0, 1, 1)
  series[, 4] <- c(1, 0, 0, 0, 0, 0, 0, 1, 1)
  series[, 5] <- c(0, 0, 0, 0, 0, 1, 1, 0, 0)
  series[, 6] <- c(0, 0, 0, 0, 1, 1, 0, 0, 0)
  series[, 7] <- c(1, 1, 1, 0, 0, 0, 0, 1, 1)
  series[, 8] <- c(0, 0, 0, 1, 1, 1, 1, 0, 0)
  series[, 9] <- c(0, 0, 0, 0, 0, 0, 1, 1, 0)  
  expect_equal(excess_entropy(series, k = 2, local = !T), 0.448839, tolerance = 1e-6)
  expect_equal(excess_entropy(series, k = 3, local = !T), 0.829542, tolerance = 1e-6)

  series      <- matrix(0, nrow = 9, ncol = 4)
  series[, 1] <- c(3, 3, 3, 2, 1, 0, 0, 0, 1)
  series[, 2] <- c(2, 2, 3, 3, 3, 3, 2, 1, 0)
  series[, 3] <- c(0, 0, 0, 0, 1, 1, 0, 0, 0)
  series[, 4] <- c(1, 1, 0, 0, 0, 1, 1, 2, 2)
  expect_equal(excess_entropy(series, k = 2, local = !T), 2.041814, tolerance = 1e-6)
  expect_equal(excess_entropy(series, k = 3, local = !T), 2.780639, tolerance = 1e-6)  
})

test_that("excess_entropy local on single series", {
  expect_equal(mean(excess_entropy(c(1, 1, 0, 0, 1, 0, 0, 1), k = 2, local = T)),
               1.521928, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(1, 0, 0, 0, 0, 0, 0, 0, 0), k = 2, local = T)),
               0.000000, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(0, 0, 1, 1, 1, 1, 0, 0, 0), k = 2, local = T)),
               0.666667, tolerance = 1e-6)

  expect_equal(mean(excess_entropy(c(1, 1, 0, 0, 1, 0, 0, 1), k = 3, local = T)),
               1.584963, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(1, 0, 0, 0, 0, 0, 0, 0, 0), k = 3, local = T)),
               0.000000, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(0, 0, 1, 1, 1, 1, 0, 0, 0), k = 3, local = T)),
               1.500000, tolerance = 1e-6)

  expect_equal(mean(excess_entropy(c(3, 3, 3, 2, 1, 0, 0, 0, 1), k = 2, local = T)),
               1.918296, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(2, 2, 3, 3, 3, 3, 2, 1, 0), k = 2, local = T)),
               1.000000, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(2, 2, 2, 2, 2, 2, 1, 1, 1), k = 2, local = T)),
               0.316689, tolerance = 1e-6)

  expect_equal(mean(excess_entropy(c(3, 3, 3, 2, 1, 0, 0, 0, 1), k = 3, local = T)),
               2.000000, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(2, 2, 3, 3, 3, 3, 2, 1, 0), k = 3, local = T)),
               1.500000, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(c(2, 2, 2, 2, 2, 2, 1, 1, 1), k = 3, local = T)),
               0.000000, tolerance = 1e-6)
})

test_that("excess_entropy local on ensemble of series", {
  series      <- matrix(0, nrow = 8, ncol = 2)
  series[, 1] <- c(1, 1, 0, 0, 1, 0, 0, 1)
  series[, 2] <- c(0, 0, 0, 1, 0, 0, 0, 1)
  expect_equal(mean(excess_entropy(series, k = 2, local = T)), 0.846439, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(series, k = 3, local = T)), 1.584963, tolerance = 1e-6)

  series      <- matrix(0, nrow = 9, ncol = 9)
  series[, 1] <- c(1, 0, 0, 0, 0, 0, 0, 0, 0)
  series[, 2] <- c(0, 0, 1, 1, 1, 1, 0, 0, 0)
  series[, 3] <- c(1, 0, 0, 0, 0, 0, 0, 1, 1)
  series[, 4] <- c(1, 0, 0, 0, 0, 0, 0, 1, 1)
  series[, 5] <- c(0, 0, 0, 0, 0, 1, 1, 0, 0)
  series[, 6] <- c(0, 0, 0, 0, 1, 1, 0, 0, 0)
  series[, 7] <- c(1, 1, 1, 0, 0, 0, 0, 1, 1)
  series[, 8] <- c(0, 0, 0, 1, 1, 1, 1, 0, 0)
  series[, 9] <- c(0, 0, 0, 0, 0, 0, 1, 1, 0)  
  expect_equal(mean(excess_entropy(series, k = 2, local = T)), 0.448839, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(series, k = 3, local = T)), 0.829542, tolerance = 1e-6)

  series      <- matrix(0, nrow = 9, ncol = 4)
  series[, 1] <- c(3, 3, 3, 2, 1, 0, 0, 0, 1)
  series[, 2] <- c(2, 2, 3, 3, 3, 3, 2, 1, 0)
  series[, 3] <- c(0, 0, 0, 0, 1, 1, 0, 0, 0)
  series[, 4] <- c(1, 1, 0, 0, 0, 1, 1, 2, 2)
  expect_equal(mean(excess_entropy(series, k = 2, local = T)), 2.041814, tolerance = 1e-6)
  expect_equal(mean(excess_entropy(series, k = 3, local = T)), 2.780639, tolerance = 1e-6)
})