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import numpy as np
import numpy.testing as npt
import nitime.algorithms as tsa
np.random.seed(1945)
def test_entropy():
x = np.random.randint(0, 2, size=1000)
e1 = tsa.entropy(x)
npt.assert_almost_equal(e1, 1, decimal=2)
# The joint entropy of the variable with itself is the same:
e2 = tsa.entropy(x, x)
npt.assert_almost_equal(e1, e2)
y = np.random.randint(0, 2, size=1000)
# Joint entropy with another random variable is 2:
e3 = tsa.entropy(x, y)
npt.assert_almost_equal(e3, 2, decimal=2)
def test_conditional_entropy():
x = np.random.randint(0, 2, size=1000)
y = np.random.randint(0, 2, size=1000)
e1 = tsa.conditional_entropy(x, x)
npt.assert_almost_equal(e1, 0)
e2 = tsa.conditional_entropy(x, y)
npt.assert_almost_equal(e2, 1, decimal=2)
def test_mutual_information():
x = np.random.randint(0, 2, size=1000)
y = np.random.randint(0, 2, size=1000)
e1 = tsa.mutual_information(x, x)
npt.assert_almost_equal(e1, 1, decimal=2)
e2 = tsa.mutual_information(x, y)
npt.assert_almost_equal(e2, 0, decimal=2)
def test_entropy_cc():
x = np.random.randint(0, 2, size=1000)
e1 = tsa.entropy_cc(x, x)
npt.assert_almost_equal(e1, 1, decimal=2)
def test_transfer_entropy():
x = np.random.randint(0, 4, size=1000)
y = np.roll(x, -1)
e1 = tsa.transfer_entropy(x, y, lag=1)
npt.assert_almost_equal(e1, 2, decimal=1)
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