Nothing
library(nonlinearTseries)
context("Maximal Lyapunov exponent")
test_that("estimates equal theoretical results", {
skip_on_cran()
set.seed(10)
tolerance = 5e-2
# Henon system
ts = henon(n.sample = 5000, n.transient = 100, a = 1.4, b = 0.3,
start = c(0.63954883, 0.04772637),
do.plot = FALSE
)$x
x = maxLyapunov(
time.series = ts,
min.embedding.dim = 2,
time.lag = 1,
radius = 0.001,
theiler.window = 4,
min.neighs = 2,
min.ref.points = 500,
max.time.steps = 10,
number.boxes = NULL,
do.plot = FALSE
)
expect_equal(estimate(x), 0.41, tolerance = tolerance)
# Lorenz
ts = lorenz(
sigma = 16,
rho = 40,
beta = 4,
start = c(-10, -11, 47),
time = seq(0, 100, by = 0.01),
do.plot = FALSE
)$x
x = maxLyapunov(
time.series = ts,
min.embedding.dim = 4,
max.embedding.dim = 6,
time.lag = 8,
radius = 0.40,
theiler.window = 200,
min.neighs = 5,
min.ref.points = length(ts),
max.time.steps = 400,
number.boxes = NULL,
sampling.period = 0.01,
do.plot = FALSE
)
expected = 1.37
expect_equal(estimate(x, c(0, 2.7), FALSE), expected, tolerance = tolerance,
scale = expected)
# lorenz
ts = lorenz(
sigma = 10,
rho = 45.92,
beta = 4,
start = c(-10, -11, 47),
time = seq(0, 70, by = 0.01),
do.plot = FALSE
)$x
x = maxLyapunov(
time.series = ts,
min.embedding.dim = 5,
time.lag = 8,
radius = 0.5,
theiler.window = 30,
min.neighs = 5,
min.ref.points = length(ts),
max.time.steps = 200,
number.boxes = NULL,
sampling.period = 0.01,
do.plot = FALSE
)
expect_equal(estimate(x), 1.50, tolerance = tolerance)
# rossler
ts = rossler(
a = 0.15,
b = 0.2,
w = 10,
start = c(0, 0, 0),
time = seq(0, 3000, 0.1),
do.plot = FALSE
)$x
x = maxLyapunov(
time.series = ts,
min.embedding.dim = 5,
time.lag = 12,
radius = 0.05,
theiler.window = 50,
min.neighs = 10,
min.ref.points = 1000,
max.time.steps = 300,
number.boxes = NULL,
sampling.period = 0.1,
do.plot = FALSE
)
expect_equal(estimate(x), 0.065, tolerance = tolerance)
# logistic map
logmap = nonlinearTseries::logisticMap(do.plot = FALSE, n.sample = 10000, start = 0.3)
x = maxLyapunov(
time.series = logmap,
min.embedding.dim = 2,
time.lag = 1,
radius = 0.01,
theiler.window = 100,
min.neighs = 10,
min.ref.points = 10000,
max.time.steps = 5,
number.boxes = NULL,
sampling.period = 1,
do.plot = FALSE
)
expect_equal(estimate(x), 0.693, tolerance = tolerance)
})
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