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from gudhi.point_cloud.timedelay import TimeDelayEmbedding
import numpy as np
def test_normal():
# Sample array
ts = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
# Normal case.
prep = TimeDelayEmbedding()
attractor = prep(ts)
assert (attractor[0] == np.array([1, 2, 3]))
assert (attractor[1] == np.array([2, 3, 4]))
assert (attractor[2] == np.array([3, 4, 5]))
assert (attractor[3] == np.array([4, 5, 6]))
assert (attractor[4] == np.array([5, 6, 7]))
assert (attractor[5] == np.array([6, 7, 8]))
assert (attractor[6] == np.array([7, 8, 9]))
assert (attractor[7] == np.array([8, 9, 10]))
# Delay = 3
prep = TimeDelayEmbedding(delay=3)
attractor = prep(ts)
assert (attractor[0] == np.array([1, 4, 7]))
assert (attractor[1] == np.array([2, 5, 8]))
assert (attractor[2] == np.array([3, 6, 9]))
assert (attractor[3] == np.array([4, 7, 10]))
# Skip = 3
prep = TimeDelayEmbedding(skip=3)
attractor = prep(ts)
assert (attractor[0] == np.array([1, 2, 3]))
assert (attractor[1] == np.array([4, 5, 6]))
assert (attractor[2] == np.array([7, 8, 9]))
# Delay = 2 / Skip = 2
prep = TimeDelayEmbedding(delay=2, skip=2)
attractor = prep(ts)
assert (attractor[0] == np.array([1, 3, 5]))
assert (attractor[1] == np.array([3, 5, 7]))
assert (attractor[2] == np.array([5, 7, 9]))
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