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import numpy as np
from numpy.testing import assert_array_equal, assert_almost_equal, \
assert_array_almost_equal
from scipy.misc import pade, logsumexp
def test_pade_trivial():
nump, denomp = pade([1.0], 0)
assert_array_equal(nump.c, [1.0])
assert_array_equal(denomp.c, [1.0])
def test_pade_4term_exp():
# First four Taylor coefficients of exp(x).
# Unlike poly1d, the first array element is the zero-order term.
an = [1.0, 1.0, 0.5, 1.0/6]
nump, denomp = pade(an, 0)
assert_array_almost_equal(nump.c, [1.0/6, 0.5, 1.0, 1.0])
assert_array_almost_equal(denomp.c, [1.0])
nump, denomp = pade(an, 1)
assert_array_almost_equal(nump.c, [1.0/6, 2.0/3, 1.0])
assert_array_almost_equal(denomp.c, [-1.0/3, 1.0])
nump, denomp = pade(an, 2)
assert_array_almost_equal(nump.c, [1.0/3, 1.0])
assert_array_almost_equal(denomp.c, [1.0/6, -2.0/3, 1.0])
nump, denomp = pade(an, 3)
assert_array_almost_equal(nump.c, [1.0])
assert_array_almost_equal(denomp.c, [-1.0/6, 0.5, -1.0, 1.0])
def test_logsumexp():
"""Test whether logsumexp() function correctly handles large inputs."""
a = np.arange(200)
desired = np.log(np.sum(np.exp(a)))
assert_almost_equal(logsumexp(a), desired)
# Now test with large numbers
b = [1000,1000]
desired = 1000.0 + np.log(2.0)
assert_almost_equal(logsumexp(b), desired)
n = 1000
b = np.ones(n)*10000
desired = 10000.0 + np.log(n)
assert_almost_equal(logsumexp(b), desired)
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