barnes_objective
Optimally interpolates data using Barnes objective analysis using a successive corrections scheme
Calling Sequence
import spatial_interpolators as spi
ZI = spi.barnes_objective(xs, ys, zs, XI, YI, XR, YR)
- spatial_interpolators.barnes_objective(xs, ys, zs, XI, YI, XR, YR, runs=3)[source]
Barnes objective analysis for the optimal interpolation of an input grid using a successive corrections scheme
- Parameters
- xs: float
input x-coordinates
- ys: float
input y-coordinates
- zs: float
input data
- XI: float
output x-coordinates for data grid
- YI: float
output y-coordinates for data grid
- XR: float
x-component of Barnes smoothing length scale
- YR: float
y-component of Barnes smoothing length scale
- runs: int, default 3
number of iterations
- Returns
- ZI: float
interpolated data grid
References
- Barnes1994a
S. L. Barnes, “Applications of the Barnes objective analysis scheme. Part I: Effects of undersampling, wave position, and station randomness,” Journal of Atmospheric and Oceanic Technology, 11(6), 1433–1448, (1994).
- Barnes1994b
S. L. Barnes, “Applications of the Barnes objective analysis scheme. Part II: Improving derivative estimates,” Journal of Atmospheric and Oceanic Technology, 11(6), 1449–1458, (1994).
- Barnes1994c
S. L. Barnes, “Applications of the Barnes objective analysis scheme. Part III: Tuning for minimum error,” Journal of Atmospheric and Oceanic Technology, 11(6), 1459–1479, (1994).
- Daley1991
R. Daley, Atmospheric data analysis, Cambridge Press, New York. (1991).