Function get_csp

src/data_handler/data_handler.cpp:662–748

}

int get_csp (const double *data, const double *labels, int n_epochs, int n_channels, int n_times,
    double *output_w, double *output_d)
{
    if ((!data) || (!labels) || n_epochs <= 0 || n_channels <= 0 || n_times <= 0)
    {
        data_logger->error ("Invalid function arguments provided. Please verify that all integer "
                            "arguments are positive and data and labels arrays aren't empty.");
        return (int)BrainFlowExitCodes::INVALID_ARGUMENTS_ERROR;
    }
    try
    {
        Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> sum1 (
            n_channels, n_channels);
        Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> sum2 (
            n_channels, n_channels);

        sum1.setZero ();
        sum2.setZero ();

        int n_class1 = 0;
        int n_class2 = 0;

        // Compute an averaged covariance matrix for each class
        for (int e = 0; e < n_epochs; e++)
        {
            Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> X (
                n_channels, n_times);
            for (int c = 0; c < n_channels; c++)
            {
                for (int t = 0; t < n_times; t++)
                {
                    X (c, t) = data[e * n_channels * n_times + c * n_times + t];
                }
            }

            // center data
            for (int i = 0; i < n_channels; i++)
            {
                double ctr = X.row (i).mean ();
                for (int j = 0; j < n_times; j++)
                {
                    X (i, j) -= ctr;
                }
            }

            // For centered data cov(X) = (X * X_T) / n
            switch (int (labels[e]))
            {
                case 0:
                    sum1 += ((X * X.transpose ()).eval ()) / double (n_times);
                    n_class1++;
                    break;
                case 1:
                    sum2 += ((X * X.transpose ()).eval ()) / double (n_times);
                    n_class2++;
                    break;
                default:
                    data_logger->error ("Invalid class label. Current class label: {}", labels[e]);