克里金插值代码java

以下是Java语言实现的克里金插值算法代码：

import java.util.ArrayList;

public class KrigingInterpolation {

    // 计算两点之间的欧式距离
    private static double euclideanDistance(double[] point1, double[] point2) {
        double sum = 0.0;
        for (int i = 0; i < point1.length; i++) {
            double diff = point1[i] - point2[i];
            sum += diff * diff;
        }
        return Math.sqrt(sum);
    }

    // 计算半方差函数
    private static double semiVariance(double[] point1, double[] point2, double nugget, double range, double sill) {
        double h = euclideanDistance(point1, point2);
        if (h == 0) {
            return 0;
        }
        if (h > range) {
            return sill;
        }
        return nugget + ((sill - nugget) / range) * h;
    }

    // 计算克里金权重
    private static double[] krigingWeights(double[] point, ArrayList<double[]> dataPoints, double nugget, double range, double sill) {
        int n = dataPoints.size();
        double[][] covariances = new double[n][n];
        double[] distances = new double[n];
        double[] weights = new double[n];

        // 计算半方差函数矩阵
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < n; j++) {
                double covariance = semiVariance(dataPoints.get(i), dataPoints.get(j), nugget, range, sill);
                covariances[i][j] = covariance;
                covariances[j][i] = covariance;
            }
            distances[i] = euclideanDistance(point, dataPoints.get(i));
        }

        // 计算权重
        double[][] inverse = Matrix.invert(covariances);
        double sum = 0;
        for (int i = 0; i < n; i++) {
            weights[i] = 0;
            for (int j = 0; j < n; j++) {
                weights[i] += inverse[i][j] * (distances[j] > 0 ? distances[j] : 0.000001);
            }
            sum += weights[i];
        }
        for (int i = 0; i < n; i++) {
            weights[i] /= sum;
        }

        return weights;
    }

    // 计算克里金插值
    public static double kriging(double[] point, ArrayList<double[]> dataPoints, ArrayList<Double> dataValues, double nugget, double range, double sill) {
        double[] weights = krigingWeights(point, dataPoints, nugget, range, sill);
        double value = 0;
        for (int i = 0; i < dataPoints.size(); i++) {
            value += weights[i] * dataValues.get(i);
        }
        return value;
    }
}

其中，`euclideanDistance` 方法计算两点之间的欧式距离，`semiVariance` 方法计算半方差函数，`krigingWeights` 方法计算克里金权重，`kriging` 方法计算克里金插值。这里用到了矩阵求逆的方法，可以使用 `Matrix` 类实现。