README
¶
go-kriging
Golang Multi-Goroutine spatial interpolation algorithm library for geospatial prediction and mapping via ordinary kriging.
Based on @oeo4b's kriging.js refactoring and optimized the algorithm and added some new features.
This is exponential grid output png examples.
Fitting a Model
The train method with the new ordinaryKriging fits your input to whatever variogram model you specify - gaussian, exponential or spherical - and returns a variogram variable.
import "github.com/lvisei/go-kriging/ordinarykriging"
func main() {
sigma2 := 0
alpha := 100
ordinaryKriging := ordinarykriging.NewOrdinary(values, x, y)
variogram = ordinaryKriging.Train(ordinarykriging.Spherical, sigma2, alpha)
}
Predicting New Values
Values can be predicted for new coordinate pairs by using the predict method with the new ordinaryKriging.
import "github.com/lvisei/go-kriging/ordinarykriging"
func main() {
// ...
// Pair of new coordinates to predict
xnew := 0.5481
ynew := 0.4455
tpredicted := ordinaryKriging.predict(xnew, ynew)
}
Variogram and Probability Model
According to sakitam-gis, the various variogram models can be interpreted as kernel functions for 2-dimensional coordinates a, b and parameters nugget, range, sill and A. Reparameterized as a linear function, with w = [nugget, (sill-nugget)/range], this becomes:
- Gaussian: k(a,b) = w[0] + w[1] * ( 1 - exp{ -( ||a-b|| / range )2 / A } )
- Exponential: k(a,b) = w[0] + w[1] * ( 1 - exp{ -( ||a-b|| / range ) / A } )
- Spherical: k(a,b) = w[0] + w[1] _ ( 1.5 _ ( ||a-b|| / range ) - 0.5 * ( ||a-b|| / range )3 )
The variance parameter α of the prior distribution for w should be manually set, according to:
- w ~ N(w|0, αI)
Using the fitted kernel function hyperparameters and setting K as the Gram matrix, the prior and likelihood for the gaussian process become:
- y ~ N(y|0, K)
- t|y ~ N(t|y, σ2I)
The variance parameter σ2 of the likelihood reflects the error in the gaussian process and should be manually set.
Other
kriging-wasm example - Test example used by wasm compiled with go-kriging algorithm code.
go-kriging-service - Call the REST service written by the go-kriging algorithm package, which supports concurrent calls by multiple users, and has a simple logging and fault-tolerant recovery mechanism.
License
This package implement @oeo4b's kriging.js, a JavaScript library that is also MIT-licensed.
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