def test_dfts4():
"""
Test inferring a distribution from a time-series.
"""
gm = golden_mean()
ts = np.array([next(gm) for _ in range(1000000)]).reshape(1000000, 1)
d1 = dist_from_timeseries(ts)
d2 = Distribution([((0,), 0), ((0,), 1), ((1,), 0)], [1 / 3, 1 / 3, 1 / 3])
assert d1.is_approx_equal(d2, atol=1e-3)
def test_dfts3():
"""
Test inferring a distribution from a time-series.
"""
gm = golden_mean()
ts = [next(gm) for _ in range(1000000)]
d1 = dist_from_timeseries(ts, history_length=0)
d2 = Distribution([(0,), (1,)], [2 / 3, 1 / 3])
assert d1.is_approx_equal(d2, atol=1e-3)
def test_dfts2():
"""
Test inferring a distribution from a time-series.
"""
gm = golden_mean()
ts = [next(gm) for _ in range(1000000)]
d1 = dist_from_timeseries(ts, base=None)
d2 = Distribution([((0,), 0), ((0,), 1), ((1,), 0)], [np.log2(1 / 3)] * 3, base=2)
assert d1.is_approx_equal(d2, atol=1e-2)
def test_dfts4():
"""
Test inferring a distribution from a time-series.
"""
gm = golden_mean()
ts = np.array([next(gm) for _ in range(1000000)]).reshape(1000000, 1)
d1 = dist_from_timeseries(ts)
d2 = Distribution([((0,), 0), ((0,), 1), ((1,), 0)], [1/3, 1/3, 1/3])
assert d1.is_approx_equal(d2, atol=1e-3)
def test_dfts3():
"""
Test inferring a distribution from a time-series.
"""
gm = golden_mean()
ts = [next(gm) for _ in range(1000000)]
d1 = dist_from_timeseries(ts, history_length=0)
d2 = Distribution([(0,), (1,)], [2/3, 1/3])
assert d1.is_approx_equal(d2, atol=1e-3)
def test_dfts2():
"""
Test inferring a distribution from a time-series.
"""
gm = golden_mean()
ts = [next(gm) for _ in range(1000000)]
d1 = dist_from_timeseries(ts, base=None)
d2 = Distribution([((0,), 0), ((0,), 1), ((1,), 0)], [np.log2(1/3)]*3, base=2)
assert d1.is_approx_equal(d2, atol=1e-2)
