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 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))