def test_poisson_conf_array_rootn0_zero():
n = np.zeros((3, 4, 5))
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n-0'),
funcs.poisson_conf_interval(n[0, 0, 0], interval='root-n-0')[:, None, None, None] * np.ones_like(n)) # noqa: E501
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='root-n-0')))
def test_poisson_conf_list_rootn0_zero():
n = [0, 0, 0]
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n-0'),
[[0, 0, 0], [1, 1, 1]])
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='root-n-0')))
def test_poisson_conf_kbn_value_errors():
with pytest.raises(ValueError, match='number between 0 and 1'):
funcs.poisson_conf_interval(5,
'kraft-burrows-nousek',
background=2.5,
confidence_level=99)
with pytest.raises(ValueError, match='Set confidence_level for method'):
funcs.poisson_conf_interval(5, 'kraft-burrows-nousek', background=2.5)
with pytest.raises(ValueError, match='Background must be'):
funcs.poisson_conf_interval(5,
'kraft-burrows-nousek',
background=-2.5,
confidence_level=.99)
with pytest.raises(TypeError, match='Number of counts must be integer'):
funcs.poisson_conf_interval(5.,
'kraft-burrows-nousek',
background=2.5,
confidence_level=.99)
with pytest.raises(TypeError, match='Number of counts must be integer'):
funcs.poisson_conf_interval([5., 6.],
'kraft-burrows-nousek',
background=[2.5, 2.],
confidence_level=[.99, .9])
def test_poisson_conf_list_rootn0_zero():
n = [0, 0, 0]
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n-0'),
[[0, 0, 0], [1, 1, 1]])
assert not np.any(
np.isnan(funcs.poisson_conf_interval(n, interval='root-n-0')))
def test_poisson_limit_nodependencies():
with pytest.raises(ImportError):
with pytest.warns(AstropyDeprecationWarning):
funcs.poisson_conf_interval(20.,
interval='kraft-burrows-nousek',
background=10.,
conflevel=.95)
def test_poisson_conf_array_rootn0_zero():
n = np.zeros((3, 4, 5))
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n-0'),
funcs.poisson_conf_interval(n[0, 0, 0], interval='root-n-0')[:, None, None, None] * np.ones_like(n))
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='root-n-0')))
def test_poisson_conf_array_frequentist_confidence_zero():
n = np.zeros((3, 4, 5))
assert_allclose(
funcs.poisson_conf_interval(n, interval='frequentist-confidence'),
funcs.poisson_conf_interval(n[0, 0, 0], interval='frequentist-confidence')[:, None, None, None] * np.ones_like(n))
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='root-n-0')))
def test_poisson_conf_array_rootn0():
n = 7 * np.ones((3, 4, 5))
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n-0'),
funcs.poisson_conf_interval(n[0, 0, 0], interval='root-n-0')[:, None, None, None] * np.ones_like(n))
n[1, 2, 3] = 0
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='root-n-0')))
def test_poisson_conf_array_fc():
n = 7 * np.ones((3, 4, 5))
assert_allclose(
funcs.poisson_conf_interval(n, interval='frequentist-confidence'),
funcs.poisson_conf_interval(n[0, 0, 0], interval='frequentist-confidence')[:, None, None, None] * np.ones_like(n))
n[1, 2, 3] = 0
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='frequentist-confidence')))
def test_poisson_conf_array_fc():
n = 7 * np.ones((3, 4, 5))
assert_allclose(
funcs.poisson_conf_interval(n, interval='frequentist-confidence'),
funcs.poisson_conf_interval(n[0, 0, 0], interval='frequentist-confidence')[:, None, None, None] * np.ones_like(n)) # noqa: E501
n[1, 2, 3] = 0
assert not np.any(np.isnan(
funcs.poisson_conf_interval(n, interval='frequentist-confidence')))
def test_mpmath_poisson_limit():
assert_allclose(funcs._mpmath_kraft_burrows_nousek(1., .1, .99),
(0.00, 6.54), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(1., .5, .95),
(0.00, 4.36), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(5., 0., .99),
(1.17, 13.32), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(5., 2.5, .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(np.int32(6), 2., .9),
(0.81, 8.99), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(np.int64(6), 2., .9),
(0.81, 8.99), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., np.float32(2.), .9),
(0.81, 8.99), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., np.float64(2.), .9),
(0.81, 8.99), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., 2., np.float32(.9)),
(0.81, 8.99), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., 2., np.float64(.9)),
(0.81, 8.99), rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(5., 2.5, .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs.poisson_conf_interval(
n=160, background=154.543,
confidence_level=.95, interval='kraft-burrows-nousek')[:, 0], (0, 30.30454909))
# For this one we do not have the "true" answer from the publication,
# but we want to make sure that it at least runs without error
# see https://github.com/astropy/astropy/issues/9596
_ = funcs._mpmath_kraft_burrows_nousek(1000., 900., .9)
def test_scipy_poisson_limit():
'''Test that the lower-level routine gives the snae number.
Test numbers are from table1 1, 3 in
Kraft, Burrows and Nousek in
`ApJ 374, 344 (1991) <https://ui.adsabs.harvard.edu/abs/1991ApJ...374..344K>`_
'''
assert_allclose(funcs._scipy_kraft_burrows_nousek(5, 2.5, .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._scipy_kraft_burrows_nousek(np.int32(5.), 2.5, .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._scipy_kraft_burrows_nousek(np.int64(5.), 2.5, .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._scipy_kraft_burrows_nousek(5, np.float32(2.5), .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._scipy_kraft_burrows_nousek(5, np.float64(2.5), .99),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._scipy_kraft_burrows_nousek(5, 2.5, np.float32(.99)),
(0, 10.67), rtol=1e-3)
assert_allclose(funcs._scipy_kraft_burrows_nousek(5, 2.5, np.float64(.99)),
(0, 10.67), rtol=1e-3)
conf = funcs.poisson_conf_interval([5, 6], 'kraft-burrows-nousek',
background=[2.5, 2.],
confidence_level=[.99, .9])
assert_allclose(conf[:, 0], (0, 10.67), rtol=1e-3)
assert_allclose(conf[:, 1], (0.81, 8.99), rtol=5e-3)
def test_mpmath_poisson_limit():
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., 2., .9),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(5., 2.5, .99),
(0, 10.67),
rtol=1e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(np.int32(6), 2., .9),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(np.int64(6), 2., .9),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., np.float32(2.), .9),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., np.float64(2.), .9),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., 2., np.float32(.9)),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(6., 2., np.float64(.9)),
(0.81, 8.99),
rtol=5e-3)
assert_allclose(funcs._mpmath_kraft_burrows_nousek(5., 2.5, .99),
(0, 10.67),
rtol=1e-3)
assert_allclose(
funcs.poisson_conf_interval(n=160,
background=154.543,
confidence_level=.95,
interval='kraft-burrows-nousek')[:, 0],
(0, 30.30454909))
def test_poisson_conf_value_errors():
with pytest.raises(ValueError, match='Only sigma=1 supported'):
funcs.poisson_conf_interval([5, 6], 'root-n', sigma=2)
with pytest.raises(ValueError, match='background not supported'):
funcs.poisson_conf_interval([5, 6], 'pearson', background=[2.5, 2.])
with pytest.raises(ValueError, match='confidence_level not supported'):
funcs.poisson_conf_interval([5, 6], 'sherpagehrels',
confidence_level=[2.5, 2.])
with pytest.raises(ValueError, match='Invalid method'):
funcs.poisson_conf_interval(1, 'foo')
def test_scipy_poisson_limit():
'''Test that the lower-level routine gives the snae number.
Test numbers are from table1 1, 3 in
Kraft, Burrows and Nousek in
`ApJ 374, 344 (1991) <http://adsabs.harvard.edu/abs/1991ApJ...374..344K>`_
'''
assert_allclose(funcs._scipy_kraft_burrows_nousek(5., 2.5, .99),
(0, 10.67), rtol=1e-3)
conf = funcs.poisson_conf_interval([5., 6.], 'kraft-burrows-nousek',
background=[2.5, 2.],
conflevel=[.99, .9])
assert_allclose(conf[:, 0], (0, 10.67), rtol=1e-3)
assert_allclose(conf[:, 1], (0.81, 8.99), rtol=5e-3)
def test_poisson_conf_value_errors():
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval([5, 6], 'root-n', sigma=2)
assert 'Only sigma=1 supported' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval([5, 6], 'pearson', background=[2.5, 2.])
assert 'background not supported' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval([5, 6], 'sherpagehrels',
conflevel=[2.5, 2.])
assert 'conflevel not supported' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(1, 'foo')
assert 'Invalid method' in str(e.value)
def test_poisson_conf_value_errors():
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval([5, 6], 'root-n', sigma=2)
assert 'Only sigma=1 supported' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval([5, 6], 'pearson', background=[2.5, 2.])
assert 'background not supported' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval([5, 6],
'sherpagehrels',
conflevel=[2.5, 2.])
assert 'conflevel not supported' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(1, 'foo')
assert 'Invalid method' in str(e.value)
def test_poisson_conf_frequentist_confidence_gehrels_2sigma():
"""Test intervals against those published in Gehrels 1986
Note: I think there's a typo (transposition of digits) in Gehrels 1986,
specifically for the two-sigma lower limit for 3 events; they claim
0.569 but this function returns 0.59623...
"""
nlh = np.array([(0, 2, 0, 3.783), (1, 2, 2.30e-2, 5.683),
(2, 2, 0.230, 7.348), (3, 2, 0.596, 8.902),
(4, 2, 1.058, 10.39), (5, 2, 1.583, 11.82),
(6, 2, 2.153, 13.22), (7, 2, 2.758, 14.59),
(8, 2, 3.391, 15.94), (9, 2, 4.046, 17.27),
(10, 2, 4.719, 18.58)])
assert_allclose(funcs.poisson_conf_interval(
nlh[:, 0], sigma=2, interval='frequentist-confidence').T,
nlh[:, 2:],
rtol=0.01)
def test_poisson_conf_frequentist_confidence_gehrels():
"""Test intervals against those published in Gehrels 1986"""
nlh = np.array([(0, 0, 1.841),
(1, 0.173, 3.300),
(2, 0.708, 4.638),
(3, 1.367, 5.918),
(4, 2.086, 7.163),
(5, 2.840, 8.382),
(6, 3.620, 9.584),
(7, 4.419, 10.77),
(8, 5.232, 11.95),
(9, 6.057, 13.11),
(10, 6.891, 14.27),
])
assert_allclose(
funcs.poisson_conf_interval(nlh[:, 0],
interval='frequentist-confidence'),
nlh[:, 1:].T, rtol=0.001, atol=0.001)
def test_poisson_conf_frequentist_confidence_gehrels_3sigma():
"""Test intervals against those published in Gehrels 1986"""
nlh = np.array([(0, 3, 0, 6.608),
(1, 3, 1.35e-3, 8.900),
(2, 3, 5.29e-2, 10.87),
(3, 3, 0.212, 12.68),
(4, 3, 0.465, 14.39),
(5, 3, 0.792, 16.03),
(6, 3, 1.175, 17.62),
(7, 3, 1.603, 19.17),
(8, 3, 2.068, 20.69),
(9, 3, 2.563, 22.18),
(10, 3, 3.084, 23.64),
])
assert_allclose(
funcs.poisson_conf_interval(nlh[:, 0], sigma=3,
interval='frequentist-confidence').T,
nlh[:, 2:], rtol=0.01, verbose=True)
def test_poisson_conf_frequentist_confidence_gehrels_3sigma():
"""Test intervals against those published in Gehrels 1986"""
nlh = np.array([(0, 3, 0, 6.608),
(1, 3, 1.35e-3, 8.900),
(2, 3, 5.29e-2, 10.87),
(3, 3, 0.212, 12.68),
(4, 3, 0.465, 14.39),
(5, 3, 0.792, 16.03),
(6, 3, 1.175, 17.62),
(7, 3, 1.603, 19.17),
(8, 3, 2.068, 20.69),
(9, 3, 2.563, 22.18),
(10, 3, 3.084, 23.64),
])
assert_allclose(
funcs.poisson_conf_interval(nlh[:, 0], sigma=3,
interval='frequentist-confidence').T,
nlh[:, 2:], rtol=0.01, verbose=True)
def test_poisson_conf_frequentist_confidence_gehrels():
"""Test intervals against those published in Gehrels 1986"""
nlh = np.array([(0, 0, 1.841),
(1, 0.173, 3.300),
(2, 0.708, 4.638),
(3, 1.367, 5.918),
(4, 2.086, 7.163),
(5, 2.840, 8.382),
(6, 3.620, 9.584),
(7, 4.419, 10.77),
(8, 5.232, 11.95),
(9, 6.057, 13.11),
(10, 6.891, 14.27),
])
assert_allclose(
funcs.poisson_conf_interval(nlh[:, 0],
interval='frequentist-confidence'),
nlh[:, 1:].T, rtol=0.001, atol=0.001)
def test_poisson_conf_kbn_value_errors():
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(5., 'kraft-burrows-nousek',
background=2.5,
confidence_level=99)
assert 'number between 0 and 1' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(5., 'kraft-burrows-nousek',
background=2.5)
assert 'Set confidence_level for method' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(5., 'kraft-burrows-nousek',
background=-2.5,
confidence_level=.99)
assert 'Background must be' in str(e.value)
def test_poisson_conf_kbn_value_errors():
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(5., 'kraft-burrows-nousek',
background=2.5,
conflevel=99)
assert 'number between 0 and 1' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(5., 'kraft-burrows-nousek',
background=2.5)
assert 'Set conflevel for method' in str(e.value)
with pytest.raises(ValueError) as e:
funcs.poisson_conf_interval(5., 'kraft-burrows-nousek',
background=-2.5,
conflevel=.99)
assert 'Background must be' in str(e.value)
def test_poisson_conf_frequentist_confidence_gehrels_2sigma():
"""Test intervals against those published in Gehrels 1986
Note: I think there's a typo (transposition of digits) in Gehrels 1986,
specifically for the two-sigma lower limit for 3 events; they claim
0.569 but this function returns 0.59623...
"""
nlh = np.array([(0, 2, 0, 3.783),
(1, 2, 2.30e-2, 5.683),
(2, 2, 0.230, 7.348),
(3, 2, 0.596, 8.902),
(4, 2, 1.058, 10.39),
(5, 2, 1.583, 11.82),
(6, 2, 2.153, 13.22),
(7, 2, 2.758, 14.59),
(8, 2, 3.391, 15.94),
(9, 2, 4.046, 17.27),
(10, 2, 4.719, 18.58)])
assert_allclose(
funcs.poisson_conf_interval(nlh[:, 0], sigma=2,
interval='frequentist-confidence').T,
nlh[:, 2:], rtol=0.01)
def test_poisson_conf_gehrels86(n):
assert_allclose(
funcs.poisson_conf_interval(n, interval='sherpagehrels')[1],
funcs.poisson_conf_interval(n, interval='frequentist-confidence')[1],
rtol=0.02)
def test_poisson_conf_large(interval):
n = 100
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n'),
funcs.poisson_conf_interval(n, interval=interval),
rtol=2e-2)
def test_poisson_conf_interval_rootn():
assert_allclose(funcs.poisson_conf_interval(16, interval='root-n'),
(12, 20))
def test_poisson_limit_nodependencies():
with pytest.raises(ImportError):
funcs.poisson_conf_interval(20., interval='kraft-burrows-nousek',
background=10., conflevel=.95)
def test_poisson_conf_gehrels86(n):
assert_allclose(
funcs.poisson_conf_interval(n, interval='sherpagehrels')[1],
funcs.poisson_conf_interval(n, interval='frequentist-confidence')[1],
rtol=0.02)
def test_poisson_conf_interval_rootn():
assert_allclose(funcs.poisson_conf_interval(16, interval='root-n'),
(12, 20))
def test_poisson_conf_large(interval):
n = 100
assert_allclose(funcs.poisson_conf_interval(n, interval='root-n'),
funcs.poisson_conf_interval(n, interval=interval),
rtol=2e-2)
def test_poisson_limit_nodependencies():
with pytest.raises(ImportError):
funcs.poisson_conf_interval(20,
interval='kraft-burrows-nousek',
background=10.,
confidence_level=.95)