sl2pm.pmt module

sl2pm.pmt.gain(alpha)

PMT gain, where alpha is the inverse scale parameter of the distribution describing single-photon output of a PMT.

sl2pm.pmt.nll_q_mean(s, e, a, sigma, n_aver, mu=0)

Negative log-likelihood of probability density of an average of ‘n’ PMT outputs with expected photon count ‘e’ based on the Central Limit Theorem. Used for tracking capillaries.

sl2pm.pmt.pmt_output(expect_val, alpha)

PMT output given expected count ‘expect_val’.

sl2pm.pmt.pmt_output_var(e, alpha, sigma)

Variance of PMT output given expected count ‘e’.

sl2pm.pmt.q(s, e, a, mu, sigma, delta_s=1, s_max=1024)

Probability density of PMT output ‘s’, given the expected photon count ‘e’, convolved with the Gaussian PMT noise. Used for tracking QDs and RBCs.