torchref.base.metrics.rfactor module
R-factor calculation functions.
Functions for computing crystallographic R-factors and related metrics.
- torchref.base.metrics.rfactor.get_rfactor_torch(F_obs, F_calc)[source]
Calculate R-factor between observed and calculated structure factors (PyTorch version).
- Parameters:
F_obs (torch.Tensor) – Observed structure factor amplitudes.
F_calc (torch.Tensor) – Calculated structure factor amplitudes.
- Returns:
R-factor value.
- Return type:
- torchref.base.metrics.rfactor.get_rfactor(F_obs, F_calc)[source]
Calculate the R-factor between observed and calculated structure factors (NumPy version).
The R-factor is a measure of agreement between observed and calculated structure factor amplitudes, defined as sum(|F_obs - F_calc|) / sum(F_obs).
- Parameters:
F_obs (numpy.ndarray) – Observed structure factor amplitudes.
F_calc (numpy.ndarray) – Calculated structure factor amplitudes.
- Returns:
R-factor value between 0 and 1.
- Return type:
- torchref.base.metrics.rfactor.rfactor(F_obs, F_calc)[source]
Calculate R-factor between observed and calculated structure factors.
- Parameters:
F_obs (torch.Tensor) – Observed structure factor amplitudes of shape (N,).
F_calc (torch.Tensor) – Calculated structure factor amplitudes of shape (N,).
- Returns:
R-factor value.
- Return type:
- torchref.base.metrics.rfactor.get_rfactors(F_obs, F_calc, rfree)[source]
Get R-factors for working and test sets.
- Parameters:
F_obs (torch.Tensor) – Observed structure factor amplitudes of shape (N,).
F_calc (torch.Tensor) – Calculated structure factor amplitudes of shape (N,).
rfree (torch.Tensor) – Boolean mask indicating R-free reflections of shape (N,). 1 is Working set, 0 is Test set.
- Returns:
(r_work, r_test) where r_work is the R-factor for the working set and r_test is the R-factor for the test set.
- Return type:
- torchref.base.metrics.rfactor.bin_wise_rfactors(F_obs, F_calc, rfree, bins)[source]
Calculate bin-wise R-factors between observed and calculated structure factors.
- Parameters:
F_obs (torch.Tensor) – Observed structure factors.
F_calc (torch.Tensor) – Calculated structure factors.
rfree (torch.Tensor) – R-free mask.
bins (torch.Tensor) – Bin indices for each reflection.
- Returns:
r_work_bins (torch.Tensor) – R-factors for working set (per bin).
r_test_bins (torch.Tensor) – R-factors for test set (per bin).
- Return type:
- torchref.base.metrics.rfactor.calc_outliers(F_obs, F_calc, z)[source]
Identify outlier reflections based on deviation from expected values (PyTorch version).
- Parameters:
F_obs (torch.Tensor) – Observed structure factor amplitudes.
F_calc (torch.Tensor) – Calculated structure factor amplitudes.
z (float) – Number of standard deviations for outlier threshold.
- Returns:
Boolean mask where True indicates outlier reflections.
- Return type:
- torchref.base.metrics.rfactor.calc_outliers_numpy(F_obs, F_calc, z)[source]
Identify outlier reflections based on structure factor differences (NumPy version).
Detects reflections where the normalized difference between observed and calculated structure factors exceeds z standard deviations.
- Parameters:
F_obs (numpy.ndarray) – Observed structure factor amplitudes.
F_calc (numpy.ndarray) – Calculated structure factor amplitudes.
z (float) – Number of standard deviations for outlier threshold.
- Returns:
Boolean array where True indicates an outlier reflection.
- Return type: