fitfractions

class FitFractions(amp, res)

Bases: object

append_int(mcdata, *args, weight=None, no_grad=False, **kwargs)

get_frac(error_matrix=None, sum_diag=True)

get_frac_diag_sum(error_matrix=None)

get_frac_grad(sum_diag=True)

init_res_table()

integral(mcdata, *args, batch=None, no_grad=False, **kwargs)

cal_fitfractions(amp, mcdata, res=None, batch=None, args=(), kwargs=None)

defination:

\[FF_{i} = \frac{\int |A_i|^2 d\Omega }{ \int |\sum_{i}A_i|^2 d\Omega } \approx \frac{\sum |A_i|^2 }{\sum|\sum_{i} A_{i}|^2}\]

interference fitfraction:

\[FF_{i,j} = \frac{\int 2Re(A_i A_j*) d\Omega }{ \int |\sum_{i}A_i|^2 d\Omega } = \frac{\int |A_i +A_j|^2 d\Omega }{ \int |\sum_{i}A_i|^2 d\Omega } - FF_{i} - FF_{j}\]

gradients (for error transfer):

\[\frac{\partial }{\partial \theta_i }\frac{f(\theta_i)}{g(\theta_i)} = \frac{\partial f(\theta_i)}{\partial \theta_i} \frac{1}{g(\theta_i)} - \frac{\partial g(\theta_i)}{\partial \theta_i} \frac{f(\theta_i)}{g^2(\theta_i)}\]

cal_fitfractions_no_grad(amp, mcdata, res=None, batch=None, args=(), kwargs=None)

calculate fit fractions without gradients.

eval_integral(f, data, var, weight=None, args=(), no_grad=False, kwargs=None)

nll_grad(f, var, args=(), kwargs=None, options=None)

sum_gradient(amp, data, var, weight=1.0, func=<function <lambda>>, grad=True, args=(), kwargs=None)

sum_no_gradient(amp, data, var, weight=1.0, func=<function <lambda>>, *, grad=False, args=(), kwargs=None)