aquakin.PredictiveBand#

class aquakin.PredictiveBand(t, median, lo, hi, percentiles, n_valid, species=None)[source]#

Bases: object

Posterior-predictive band from CalibrationResult.predictive_band().

Variables:

  • t (np.ndarray) – Output time grid, shape (n_t,) (the t_eval passed in).

  • median (np.ndarray) – Pointwise median over the posterior draws, shape (n_t, n_species) (or (n_t, n_observed) if observed_species was given).

  • hi (lo,) – Lower / upper percentile envelopes, same shape as median.

  • percentiles (tuple[float, float]) – The (lo, hi) percentiles used.

  • n_valid (int) – Number of posterior draws that solved to a finite trajectory and were included in the percentiles.

  • species (list[str] or None) – Observed-species labels for the columns, or None for all species.

Parameters:

  • t (ndarray)

  • median (ndarray)

  • lo (ndarray)

  • hi (ndarray)

  • percentiles (tuple[float, float])

  • n_valid (int)

  • species (list[str] | None)

__init__(t, median, lo, hi, percentiles, n_valid, species=None)#
Parameters:

  • t (ndarray)

  • median (ndarray)

  • lo (ndarray)

  • hi (ndarray)

  • percentiles (tuple[float, float])

  • n_valid (int)

  • species (list[str] | None)

Return type:

None

Methods

__init__(t, median, lo, hi, percentiles, n_valid)

Attributes

species

t

median

lo

hi

percentiles

n_valid