def poisson_sf(n, mu):
"""Calculate the upper-tail probability for a Poisson distribution.
The calculated probability is:
.. math::
SF(n) = P(N > n) = 1 - CDF(n)
Parameters
----------
n : int
Quantile.
mu :
The expectation value of the Poisson distribution.
Returns
-------
"""
return special.pdtrc(n, mu)
def _sf(self, x, mu):
k = floor(x)
return special.pdtrc(k, mu)
def _sf(self, x, mu):
k = floor(x)
return special.pdtrc(k, mu)
def test_domain(self):
val = sc.pdtrc(-1.1, 1.0)
assert np.isnan(val)
def test_inf(self):
val = sc.pdtrc(np.inf, 1.0)
assert_almost_equal(val, 0.0)
def test_rounding(self):
double_val = sc.pdtrc([0.1, 1.1, 2.1], 1.0)
int_val = sc.pdtrc([0, 1, 2], 1.0)
assert_array_equal(double_val, int_val)
def test_m_zero(self):
val = sc.pdtrc([0, 1, 2], 0.0)
assert_array_equal(val, [0, 0, 0])
def test_value(self):
val = sc.pdtrc(0, 1)
assert_almost_equal(val, 1 - np.exp(-1))
def _coincrate2(mincount, tcoinc, rate):
"""cross check of coincrate"""
mu = rate * tcoinc
mink = np.ceil(mincount)
return rate * np.where(mink < 2, mu > 0, special.pdtrc(mink - 2, mu))
