sccala.interplib.interpolators
Classes
Module Contents
- class sccala.interplib.interpolators.Interpolator
- get_toe_rnd(tkde, toe_samples, toe=0.0)
- sample_posterior(num_live_points=800)
- log_likelihood(params)
- reject_invalid(data_int, dint, no_reject)
- check_sample_size(size, toe_samples)
- predict_from_posterior(t_pred, tkde=None, toe=0.0, size=100, no_reject=False, toe_samples=25)
- _print_predicting()
- class sccala.interplib.interpolators.LC_Interpolator(data, data_error, t_grid, num_live_points=800, disable_mean_fit=False, disable_white_noise_fit=False)
Bases:
Interpolator- data
- data_error
- t_grid
- num_live_points = 800
- disable_mean_fit = False
- disable_white_noise_fit = False
- parameters = []
- gp
- prior_transform(cube)
- _print_predicting()
- class sccala.interplib.interpolators.AKS_Interpolator(data, t_grid, uncertainty=0.004, num_live_points=400, disable_mean_fit=False)
Bases:
Interpolator- data
- t_grid
- uncertainty = 0.004
- num_live_points = 400
- disable_mean_fit = False
- parameters = []
- gp
- prior_transform(cube)
- _print_predicting()
- predict_from_posterior(t_pred, size=1000)
- class sccala.interplib.interpolators.Vel_Interpolator(data, data_error, t_grid, num_live_points=800, disable_mean_fit=True, disable_white_noise_fit=True)
Bases:
Interpolator- data
- data_error
- t_grid
- num_live_points = 800
- disable_mean_fit = True
- disable_white_noise_fit = True
- parameters = []
- gp
- prior_transform(cube)
- reject_invalid(data_int, dint, no_reject)
- _print_predicting()
- class sccala.interplib.interpolators.AE_Interpolator(data, data_error, t_grid, num_live_points=800, disable_mean_fit=True, disable_white_noise_fit=True)
Bases:
Interpolator- data
- data_error
- t_grid
- num_live_points = 800
- disable_mean_fit = True
- disable_white_noise_fit = True
- parameters = []
- gp
- reject_invalid(data_int, dint, no_reject)
- prior_transform(cube)
- _print_predicting()