krigekit.variogram_observation#

One variable’s observation and neighbour-search configuration.

ObservationSet carries everything krigekit.Kriging.set_obs() and set_obs_drift need, plus the per-variable search settings transferred by VariogramSystem.apply. It holds data only – the Python side does not perform neighbour selection; that stays in the Fortran engine.

Classes#

ObservationSet

Observation data and search configuration for one variable.

Module Contents#

class krigekit.variogram_observation.ObservationSet#

Observation data and search configuration for one variable.

property configured#: True once valid coordinates and values are present.

property nobs#: Number of observation rows (zero before set()).

property ndim#: Spatial dimension (zero before set()).

property ndrift#: Number of external-drift columns (zero when drift is absent).

set(coord, value, times=None, variance=None, sk_mean=None, drift=None)#

Set observation data, validating shapes.

coord/value are required. times, variance and drift are per-observation and replace any previous values (None clears them). sk_mean is updated only when provided, so it survives a data-only re-set().

set_search(nmax=None, maxdist=None, anis1=1.0, anis2=1.0, azimuth=0.0, dip=0.0, plunge=0.0, sector_search=False, time_at=None)#: Configure neighbour search (stored for transfer to the engine).

clear()#: Reset all data and search configuration to defaults.

validate(ndim=None)#: Validate configured data; optionally require a spatial dimension.

is_collocated_with(other)#: Return true when two variables share coordinates and times.

apply_to(kriging, ivar)#: Transfer observations (and drift) to a kriging object for ivar.