Java Code Examples for org.apache.commons.math.exception.util.LocalizedFormats#NUMBER_OF_POINTS

/**
 * Computes a linear interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 2.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 2) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 2, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Slope of the lines between the datapoints.
    final double m[] = new double[n];
    for (int i = 0; i < n; i++) {
        m[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    final double coefficients[] = new double[2];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = m[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes a linear interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 2.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 2) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 2, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Slope of the lines between the datapoints.
    final double m[] = new double[n];
    for (int i = 0; i < n; i++) {
        m[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    final double coefficients[] = new double[2];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = m[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes a linear interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 2.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 2) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 2, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Slope of the lines between the datapoints.
    final double m[] = new double[n];
    for (int i = 0; i < n; i++) {
        m[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    final double coefficients[] = new double[2];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = m[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes a linear interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 2.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 2) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 2, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Slope of the lines between the datapoints.
    final double m[] = new double[n];
    for (int i = 0; i < n; i++) {
        m[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    final double coefficients[] = new double[2];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = m[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes an interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 3.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 3) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 3, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Differences between knot points
    double h[] = new double[n];
    for (int i = 0; i < n; i++) {
        h[i] = x[i + 1] - x[i];
    }

    double mu[] = new double[n];
    double z[] = new double[n + 1];
    mu[0] = 0d;
    z[0] = 0d;
    double g = 0;
    for (int i = 1; i < n; i++) {
        g = 2d * (x[i+1]  - x[i - 1]) - h[i - 1] * mu[i -1];
        mu[i] = h[i] / g;
        z[i] = (3d * (y[i + 1] * h[i - 1] - y[i] * (x[i + 1] - x[i - 1])+ y[i - 1] * h[i]) /
                (h[i - 1] * h[i]) - h[i - 1] * z[i - 1]) / g;
    }

    // cubic spline coefficients --  b is linear, c quadratic, d is cubic (original y's are constants)
    double b[] = new double[n];
    double c[] = new double[n + 1];
    double d[] = new double[n];

    z[n] = 0d;
    c[n] = 0d;

    for (int j = n -1; j >=0; j--) {
        c[j] = z[j] - mu[j] * c[j + 1];
        b[j] = (y[j + 1] - y[j]) / h[j] - h[j] * (c[j + 1] + 2d * c[j]) / 3d;
        d[j] = (c[j + 1] - c[j]) / (3d * h[j]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    double coefficients[] = new double[4];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = b[i];
        coefficients[2] = c[i];
        coefficients[3] = d[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes an interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 3.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 3) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 3, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Differences between knot points
    double h[] = new double[n];
    for (int i = 0; i < n; i++) {
        h[i] = x[i + 1] - x[i];
    }

    double mu[] = new double[n];
    double z[] = new double[n + 1];
    mu[0] = 0d;
    z[0] = 0d;
    double g = 0;
    for (int i = 1; i < n; i++) {
        g = 2d * (x[i+1]  - x[i - 1]) - h[i - 1] * mu[i -1];
        mu[i] = h[i] / g;
        z[i] = (3d * (y[i + 1] * h[i - 1] - y[i] * (x[i + 1] - x[i - 1])+ y[i - 1] * h[i]) /
                (h[i - 1] * h[i]) - h[i - 1] * z[i - 1]) / g;
    }

    // cubic spline coefficients --  b is linear, c quadratic, d is cubic (original y's are constants)
    double b[] = new double[n];
    double c[] = new double[n + 1];
    double d[] = new double[n];

    z[n] = 0d;
    c[n] = 0d;

    for (int j = n -1; j >=0; j--) {
        c[j] = z[j] - mu[j] * c[j + 1];
        b[j] = (y[j + 1] - y[j]) / h[j] - h[j] * (c[j + 1] + 2d * c[j]) / 3d;
        d[j] = (c[j + 1] - c[j]) / (3d * h[j]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    double coefficients[] = new double[4];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = b[i];
        coefficients[2] = c[i];
        coefficients[3] = d[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes an interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 3.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 3) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 3, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Differences between knot points
    double h[] = new double[n];
    for (int i = 0; i < n; i++) {
        h[i] = x[i + 1] - x[i];
    }

    double mu[] = new double[n];
    double z[] = new double[n + 1];
    mu[0] = 0d;
    z[0] = 0d;
    double g = 0;
    for (int i = 1; i < n; i++) {
        g = 2d * (x[i+1]  - x[i - 1]) - h[i - 1] * mu[i -1];
        mu[i] = h[i] / g;
        z[i] = (3d * (y[i + 1] * h[i - 1] - y[i] * (x[i + 1] - x[i - 1])+ y[i - 1] * h[i]) /
                (h[i - 1] * h[i]) - h[i - 1] * z[i - 1]) / g;
    }

    // cubic spline coefficients --  b is linear, c quadratic, d is cubic (original y's are constants)
    double b[] = new double[n];
    double c[] = new double[n + 1];
    double d[] = new double[n];

    z[n] = 0d;
    c[n] = 0d;

    for (int j = n -1; j >=0; j--) {
        c[j] = z[j] - mu[j] * c[j + 1];
        b[j] = (y[j + 1] - y[j]) / h[j] - h[j] * (c[j + 1] + 2d * c[j]) / 3d;
        d[j] = (c[j + 1] - c[j]) / (3d * h[j]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    double coefficients[] = new double[4];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = b[i];
        coefficients[2] = c[i];
        coefficients[3] = d[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}
 

/**
 * Computes an interpolating function for the data set.
 * @param x the arguments for the interpolation points
 * @param y the values for the interpolation points
 * @return a function which interpolates the data set
 * @throws DimensionMismatchException if {@code x} and {@code y}
 * have different sizes.
 * @throws org.apache.commons.math.exception.NonMonotonousSequenceException
 * if {@code x} is not sorted in strict increasing order.
 * @throws NumberIsTooSmallException if the size of {@code x} is smaller
 * than 3.
 */
public PolynomialSplineFunction interpolate(double x[], double y[]) {
    if (x.length != y.length) {
        throw new DimensionMismatchException(x.length, y.length);
    }

    if (x.length < 3) {
        throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
                                            x.length, 3, true);
    }

    // Number of intervals.  The number of data points is n + 1.
    int n = x.length - 1;

    MathUtils.checkOrder(x);

    // Differences between knot points
    double h[] = new double[n];
    for (int i = 0; i < n; i++) {
        h[i] = x[i + 1] - x[i];
    }

    double mu[] = new double[n];
    double z[] = new double[n + 1];
    mu[0] = 0d;
    z[0] = 0d;
    double g = 0;
    for (int i = 1; i < n; i++) {
        g = 2d * (x[i+1]  - x[i - 1]) - h[i - 1] * mu[i -1];
        mu[i] = h[i] / g;
        z[i] = (3d * (y[i + 1] * h[i - 1] - y[i] * (x[i + 1] - x[i - 1])+ y[i - 1] * h[i]) /
                (h[i - 1] * h[i]) - h[i - 1] * z[i - 1]) / g;
    }

    // cubic spline coefficients --  b is linear, c quadratic, d is cubic (original y's are constants)
    double b[] = new double[n];
    double c[] = new double[n + 1];
    double d[] = new double[n];

    z[n] = 0d;
    c[n] = 0d;

    for (int j = n -1; j >=0; j--) {
        c[j] = z[j] - mu[j] * c[j + 1];
        b[j] = (y[j + 1] - y[j]) / h[j] - h[j] * (c[j + 1] + 2d * c[j]) / 3d;
        d[j] = (c[j + 1] - c[j]) / (3d * h[j]);
    }

    PolynomialFunction polynomials[] = new PolynomialFunction[n];
    double coefficients[] = new double[4];
    for (int i = 0; i < n; i++) {
        coefficients[0] = y[i];
        coefficients[1] = b[i];
        coefficients[2] = c[i];
        coefficients[3] = d[i];
        polynomials[i] = new PolynomialFunction(coefficients);
    }

    return new PolynomialSplineFunction(x, polynomials);
}