See also Fit framework
This module contains functions for direct fitting of burst populations (FRET peaks) without passing through a FRET histogram.
This module provides a standard interface for different fitting algorithms.
fretbursts.fret_fit.
fit_E_E_size
(nd, na, weights=None, gamma=1.0, gamma_correct=False)¶Fit the E with least-square minimization of errors on burst E values.
fretbursts.fret_fit.
fit_E_binom
(nd, na, noprint=False, method='c', **kwargs)¶Fit the E with MLE using binomial distribution. method (‘a’,’b’, or ‘c’) choose how to handle negative (nd,na) values.
fretbursts.fret_fit.
fit_E_cdf
(nd, na, gamma=1.0, **kwargs)¶Fit E using the CDF curve-fit (see gaussian_fit_cdf). No weights are possible with this method.
fretbursts.fret_fit.
fit_E_hist
(nd, na, gamma=1.0, **kwargs)¶Fit E using the histogram curve-fit (see gaussian_fit_hist).
You can specify weights
that will be passed to the histogram
function.
fretbursts.fret_fit.
fit_E_m
(nd, na, weights=None, gamma=1.0, gamma_correct=False)¶Fit the E with a weighted mean of burst E values.
fretbursts.fret_fit.
fit_E_poisson_na
(nd, na, bg_a, **kwargs)¶Fit the E using MLE with na extracted from a Poisson.
fretbursts.fret_fit.
fit_E_poisson_nd
(nd, na, bg_d, **kwargs)¶Fit the E using MLE with nd extracted from a Poisson.
fretbursts.fret_fit.
fit_E_poisson_nt
(nd, na, bg_a, **kwargs)¶Fit the E using MLE with na extracted from a Poisson.
fretbursts.fret_fit.
fit_E_slope
(nd, na, weights=None, gamma=1.0)¶Fit E with a least-squares fitting of slope on (nd,na) plane.
fretbursts.fret_fit.
get_dist_euclid
(nd, na, E_fit=None, slope=None)¶Returns the euclidean distance of (nd,na) from a fit line.
The fit line is specified by slope
or by E_fit
. Intercept is always 0.
fretbursts.fret_fit.
get_weights
(nd, na, weights, naa=0, gamma=1.0, widths=None)¶Return burst weights computed according to different criteria.
The burst size is computed as nd*gamma + na + naa
.
Parameters: |
|
---|---|
Returns: | 1D array of weights, one element per burst. |
fretbursts.fret_fit.
log_likelihood_binom
(E, nd, na)¶Likelihood function for (nd,na) to be from a binom with p=E (no BG).
fretbursts.fret_fit.
log_likelihood_poisson_na
(E, nd, na, bg_a)¶Likelihood function for na extracted from Poisson. nd, na BG corrected.
fretbursts.fret_fit.
log_likelihood_poisson_nd
(E, nd, na, bg_d)¶Likelihood function for nd extracted from Poisson. nd, na BG corrected.
fretbursts.fret_fit.
log_likelihood_poisson_nt
(E, nd, na, bg_a)¶Likelihood function for na extracted from Poisson. nd, na BG corrected.
fretbursts.fret_fit.
sim_nd_na
(E, N=1000, size_mean=100)¶Simulate an exponential-size burst distribution with binomial (nd,na)