pyinterp.RTree4DFloat64.packing

pyinterp.RTree4DFloat64.packing#

RTree4DFloat64.packing(self, coordinates: numpy.ndarray[dtype=float64, shape=(*, *), writable=False], values: numpy.ndarray[dtype=float64, shape=(*), writable=False], sigma2: numpy.ndarray[dtype=float64, shape=(*), writable=False]) None#

Bulk-load observations using STR packing.

Erases any existing data and rebuilds the index from the given (coordinates, values, sigma2) triple.

Parameters:
  • coordinates – Matrix of shape (n, 4) — the four Cartesian coordinates of each observation. The user is responsible for unit consistency.

  • values – Vector of length n with the observed values.

  • sigma2 – Vector of length n with the per-observation error variance. Must be strictly positive.