Method run

src/modules/regress/marginal.cpp:208–263

* @brief Perform the marginal effects transition step */

 * @brief Perform the marginal effects transition step
 */
AnyType
margins_linregr_int_transition::run(AnyType &args) {
    // Early return because of an exception has been "thrown"
    // (actually "warning") in the previous invocations
    if (args[0].isNull())
        return Null();
    MarginsLinregrInteractionState<MutableArrayHandle<double> > state = args[0];
    if (args[1].isNull() || args[2].isNull() ||
            args[3].isNull() || args[4].isNull()) {
        return args[0];
    }
    MappedColumnVector x;
    try {
        // an exception is raised in the backend if args[2] contains nulls
        MappedColumnVector xx = args[1].getAs<MappedColumnVector>();
        // x is a const reference, we can only rebind to change its pointer
        x.rebind(xx.memoryHandle(), xx.size());
    } catch (const ArrayWithNullException &e) {
        return args[0];
    }

    // The following check was added with MADLIB-138.
    if (!dbal::eigen_integration::isfinite(x)) {
        //throw std::domain_error("Design matrix is not finite.");
        warning("Design matrix is not finite.");
        return Null();
     }

    MappedColumnVector beta = args[2].getAs<MappedColumnVector>();

    Matrix J_trans = args[4].getAs<MappedMatrix>();
    J_trans.transposeInPlace(); // we actually pass-in J but transpose since
                                // we only require J^T in our equations

    if (state.numRows == 0) {
        if (x.size() > std::numeric_limits<uint16_t>::max()) {
            //throw std::domain_error("Number of independent variables cannot be "
            //                        "larger than 65535.");
            warning("Number of independent variables cannot be larger than 65535.");
            return Null();
        }
        state.initialize(*this,
                         static_cast<uint16_t>(beta.size()),
                         static_cast<uint16_t>(J_trans.rows()));
        Matrix training_data_vcov = args[3].getAs<MappedMatrix>();
        state.training_data_vcov = training_data_vcov;
    }

    // Now do the transition step
    state.numRows++;

    // compute marginal effects and delta using 1st and 2nd derivatives
    state.marginal_effects += J_trans * beta;
    state.delta += J_trans;
    return state;
}