config_loader
- class ConfigLoader(file_name, vm=None, share_dict=None)[source]
Bases:
tf_pwa.config_loader.base_config.BaseConfig
class for loading config.yml
- cal_bins_numbers(adapter, data, phsp, read_data, bg=None, bg_weight=None)
- cal_chi2(read_data=None, bins=[[2, 2], [2, 2], [2, 2]], mass=['R_BD', 'R_CD'])
- fit(data=None, phsp=None, bg=None, inmc=None, batch=65000, method='BFGS', check_grad=False, improve=False, reweight=False, maxiter=None)[source]
- generate_phsp(N=1000)
- generate_phsp_p(N=1000)
- generate_toy(N=1000, force=True, max_N=100000)
- generate_toy2(N=1000, force=True, gen=None, gen_p=None, max_N=100000, include_charge=False)
A more accurate method for generating toy data.
- Parameters
N – number of events.
force – if romove extra data generated.
gen – optional function for generate phase space, the return value is same as config.get_data.
gen_p – optional function for generate phase space, the return value is dict as
{B: pb, C: pc, D: pd}
.max_N – max number of events for every try.
- get_params_error(params=None, data=None, phsp=None, bg=None, inmc=None, batch=10000, using_cached=False, method=None, force_pos=True, correct_params=None)[source]
calculate parameters error
- plot_partial_wave(params=None, data=None, phsp=None, bg=None, prefix='figure/', res=None, save_root=False, **kwargs)