Examples with ObjectiveFunction org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction used on opensource projects

Example 11 with ObjectiveFunction

use of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction in project vcell by virtualcell.

the class FitBleachSpotOp method fitToGaussian.

static GaussianFitResults fitToGaussian(double init_center_i, double init_center_j, double init_radius2, FloatImage image) {
    // 
    // do some optimization on the image (fitting to a Gaussian)
    // set initial guesses from ROI operation.
    // 
    ISize imageSize = image.getISize();
    final int num_i = imageSize.getX();
    final int num_j = imageSize.getY();
    final float[] floatPixels = image.getFloatPixels();
    // 
    // initial guess based on previous fit of ROI
    // do gaussian fit in index space for center and standard deviation (later to translate it back to world coordinates)
    // 
    final int window_size = (int) Math.sqrt(init_radius2) * 4;
    // final int window_min_i = 0;       // (int) Math.max(0, Math.floor(init_center_i - window_size/2));
    // final int window_max_i = num_i-1; // (int) Math.min(num_i-1, Math.ceil(init_center_i + window_size/2));
    // final int window_min_j = 0;       // (int) Math.max(0, Math.floor(init_center_j - window_size/2));
    // final int window_max_j = num_j-1; // (int) Math.min(num_j-1, Math.ceil(init_center_j + window_size/2));
    final int window_min_i = (int) Math.max(0, Math.floor(init_center_i - window_size / 2));
    final int window_max_i = (int) Math.min(num_i - 1, Math.ceil(init_center_i + window_size / 2));
    final int window_min_j = (int) Math.max(0, Math.floor(init_center_j - window_size / 2));
    final int window_max_j = (int) Math.min(num_j - 1, Math.ceil(init_center_j + window_size / 2));
    final int PARAM_INDEX_CENTER_I = 0;
    final int PARAM_INDEX_CENTER_J = 1;
    final int PARAM_INDEX_K = 2;
    final int PARAM_INDEX_HIGH = 3;
    final int PARAM_INDEX_RADIUS_SQUARED = 4;
    final int NUM_PARAMETERS = 5;
    double[] initParameters = new double[NUM_PARAMETERS];
    initParameters[PARAM_INDEX_CENTER_I] = init_center_i;
    initParameters[PARAM_INDEX_CENTER_J] = init_center_j;
    initParameters[PARAM_INDEX_HIGH] = 1.0;
    initParameters[PARAM_INDEX_K] = 10;
    initParameters[PARAM_INDEX_RADIUS_SQUARED] = init_radius2;
    PowellOptimizer optimizer = new PowellOptimizer(1e-4, 1e-1);
    MultivariateFunction func = new MultivariateFunction() {

        @Override
        public double value(double[] point) {
            double center_i = point[PARAM_INDEX_CENTER_I];
            double center_j = point[PARAM_INDEX_CENTER_J];
            double high = point[PARAM_INDEX_HIGH];
            double K = point[PARAM_INDEX_K];
            double radius2 = point[PARAM_INDEX_RADIUS_SQUARED];
            double error2 = 0;
            for (int j = window_min_j; j <= window_max_j; j++) {
                // double y = j - center_j;
                double y = j;
                for (int i = window_min_i; i <= window_max_i; i++) {
                    // double x = i - center_i;
                    double x = i;
                    double modelValue = high - FastMath.exp(-K * FastMath.exp(-2 * (x * x + y * y) / radius2));
                    double imageValue = floatPixels[j * num_i + i];
                    double error = modelValue - imageValue;
                    error2 += error * error;
                }
            }
            System.out.println(new GaussianFitResults(center_i, center_j, radius2, K, high, error2));
            return error2;
        }
    };
    PointValuePair pvp = optimizer.optimize(new ObjectiveFunction(func), new InitialGuess(initParameters), new MaxEval(100000), GoalType.MINIMIZE);
    double[] fittedParamValues = pvp.getPoint();
    double fitted_center_i = fittedParamValues[PARAM_INDEX_CENTER_I];
    double fitted_center_j = fittedParamValues[PARAM_INDEX_CENTER_J];
    double fitted_radius2 = fittedParamValues[PARAM_INDEX_RADIUS_SQUARED];
    double fitted_K = fittedParamValues[PARAM_INDEX_K];
    double fitted_high = fittedParamValues[PARAM_INDEX_HIGH];
    double objectiveFunctionValue = pvp.getValue();
    return new GaussianFitResults(fitted_center_i, fitted_center_j, fitted_radius2, fitted_K, fitted_high, objectiveFunctionValue);
}