def _take_next(phases: tfs.TfsDataFrame, shift: int = 1):
"""
Takes the following BPM for momentum reconstruction by a given shift.
Args:
phases (tfs.TfsDataFrame): Dataframe matrix of phase advances, as calculated in phase.py.
shift (int): Value to determine the BPM pairing. If ``0`` is given,
tries to find the best candidate. If a value ``n>=1`` is given,
then takes the n-th following BPM downstream for the pairing.
"""
indices = np.roll(np.arange(phases.to_numpy().shape[0]), shift)
return indices, phases.to_numpy()[np.arange(phases.to_numpy().shape[0]),
indices] - 0.25
def _find_candidate(phases: tfs.TfsDataFrame) -> Tuple[np.ndarray, np.ndarray]:
"""
Finds the best candidate for momentum reconstruction.
Args:
phases (tfs.TfsDataFrame): Dataframe matrix of phase advances, as calculated in phase.py.
bd (int): beam direction, will be negative for beam 2.
Returns:
The indices of best candidates, and the corresponding phase advances between these indices.
"""
slice_ = _tilt_slice_matrix(
phases.to_numpy(), 0,
2 * CUTOFF) - 0.25 # do not overwrite built-in 'slice'
indices = np.argmin(abs(slice_), axis=0)
deltas = slice_[indices, range(len(indices))]
indices = (indices + np.arange(len(indices))) % len(indices)
return np.array(indices), deltas
