def test_logsumexp_converged_geometric_series():
data = np.ascontiguousarray(np.arange(10000)[::-1].astype(np.float64))
assert_almost_equal(util.logsumexp(-data,
inplace=False,
sort_array=False,
use_kahan=False),
0.45867514538708193,
decimal=15)
assert_almost_equal(util.logsumexp(-data,
inplace=False,
sort_array=False,
use_kahan=True),
0.45867514538708193,
decimal=15)
assert_almost_equal(util.logsumexp(-data,
inplace=False,
sort_array=True,
use_kahan=False),
0.45867514538708193,
decimal=15)
assert_almost_equal(util.logsumexp(-data,
inplace=False,
sort_array=True,
use_kahan=True),
0.45867514538708193,
decimal=15)
assert_almost_equal(util.logsumexp(-data,
inplace=True,
sort_array=True,
use_kahan=True),
0.45867514538708193,
decimal=15)
def test_logsumexp_truncated_diverging_geometric_series():
data = np.ascontiguousarray(np.arange(10000)[::-1].astype(np.float64))
assert_almost_equal(util.logsumexp(data,
inplace=False,
sort_array=False,
use_kahan=False),
9999.4586751453862,
decimal=15)
assert_almost_equal(util.logsumexp(data,
inplace=False,
sort_array=False,
use_kahan=True),
9999.4586751453862,
decimal=15)
assert_almost_equal(util.logsumexp(data,
inplace=False,
sort_array=True,
use_kahan=False),
9999.4586751453862,
decimal=15)
assert_almost_equal(util.logsumexp(data,
inplace=False,
sort_array=True,
use_kahan=True),
9999.4586751453862,
decimal=15)
assert_almost_equal(util.logsumexp(data,
inplace=True,
sort_array=True,
use_kahan=True),
9999.4586751453862,
decimal=15)
def test_logsumexp_zeros():
N = 10000
data = np.zeros(shape=(N, ), dtype=np.float64)
assert_almost_equal(util.logsumexp(data, inplace=False),
np.log(N),
decimal=15)
assert_almost_equal(util.logsumexp(-data, inplace=False),
np.log(N),
decimal=15)
def test_logsumexp_truncated_diverging_geometric_series():
data = np.ascontiguousarray(np.arange(10000)[::-1].astype(np.float64))
assert_almost_equal(
util.logsumexp(data, inplace=False, sort_array=False, use_kahan=False),
9999.4586751453862, decimal=15)
assert_almost_equal(
util.logsumexp(data, inplace=False, sort_array=False, use_kahan=True),
9999.4586751453862, decimal=15)
assert_almost_equal(
util.logsumexp(data, inplace=False, sort_array=True, use_kahan=False),
9999.4586751453862, decimal=15)
assert_almost_equal(
util.logsumexp(data, inplace=False, sort_array=True, use_kahan=True),
9999.4586751453862, decimal=15)
assert_almost_equal(
util.logsumexp(data, inplace=True, sort_array=True, use_kahan=True),
9999.4586751453862, decimal=15)
def test_logsumexp_converged_geometric_series():
data = np.ascontiguousarray(np.arange(10000)[::-1].astype(np.float64))
assert_almost_equal(
util.logsumexp(-data, inplace=False, sort_array=False, use_kahan=False),
0.45867514538708193, decimal=15)
assert_almost_equal(
util.logsumexp(-data, inplace=False, sort_array=False, use_kahan=True),
0.45867514538708193, decimal=15)
assert_almost_equal(
util.logsumexp(-data, inplace=False, sort_array=True, use_kahan=False),
0.45867514538708193, decimal=15)
assert_almost_equal(
util.logsumexp(-data, inplace=False, sort_array=True, use_kahan=True),
0.45867514538708193, decimal=15)
assert_almost_equal(
util.logsumexp(-data, inplace=True, sort_array=True, use_kahan=True),
0.45867514538708193, decimal=15)
def validate_thermodynamics(obj, estimator, strict=True):
pi = [estimator.pi_full_state[s].sum() for s in obj.metastable_sets]
f = [-logsumexp((-1.0) * estimator.f_full_state[s]) for s in obj.metastable_sets]
if strict:
npt.assert_allclose(pi, obj.pi, rtol=0.1, atol=0.2)
npt.assert_allclose(f, obj.f, rtol=0.3, atol=0.5)
else:
npt.assert_allclose(pi, obj.pi, rtol=0.3, atol=0.4)
npt.assert_allclose(f, obj.f, rtol=0.5, atol=0.7)
def test_logsumexp_zeros():
N = 10000
data = np.zeros(shape=(N,), dtype=np.float64)
assert_almost_equal(util.logsumexp(data, inplace=False), np.log(N), decimal=15)
assert_almost_equal(util.logsumexp(-data, inplace=False), np.log(N), decimal=15)