SumModel.cpp

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#include "SumModel.hpp"
 
#include <jse/jse.h>
 
// #include <polyfem/basis/Basis.hpp>
// #include <polyfem/autogen/auto_elasticity_rhs.hpp>
 
// #include <igl/Timer.h>
 
namespace polyfem::assembler
{
    void SumModel::add_multimaterial(const int index, const json &params, const Units &units)
    {
        assert(size() == 2 || size() == 3);
        if (params.count("models") == 0)
            return;
 
        auto models = params["models"];
 
        for (const auto &model : models)
        {
            const std::string model_name = model["type"];
 
            const auto assembler = AssemblerUtils::make_assembler(model_name);
            // cast assembler to elasticity assembler
            assemblers_.emplace_back(std::dynamic_pointer_cast<NLAssembler>(assembler));
            assert(assemblers_.back() != nullptr);
            assemblers_.back()->set_size(size());
            assemblers_.back()->add_multimaterial(index, model, units);
        }
    }
 
    Eigen::Matrix<double, Eigen::Dynamic, 1, 0, 3, 1>
    SumModel::compute_rhs(const AutodiffHessianPt &pt) const
    {
        assert(pt.size() == size());
        Eigen::Matrix<double, Eigen::Dynamic, 1, 0, 3, 1> res;
        assert(false);
 
        return res;
    }
 
    Eigen::VectorXd
    SumModel::assemble_gradient(const NonLinearAssemblerData &data) const
    {
        Eigen::VectorXd gradient = assemblers_.front()->assemble_gradient(data);
        for (size_t i = 1; i < assemblers_.size(); ++i)
        {
            const auto assembler = assemblers_[i];
            gradient += assembler->assemble_gradient(data);
        }
        return gradient;
    }
 
    Eigen::MatrixXd
    SumModel::assemble_hessian(const NonLinearAssemblerData &data) const
    {
        Eigen::MatrixXd hessian = assemblers_.front()->assemble_hessian(data);
        for (size_t i = 1; i < assemblers_.size(); ++i)
        {
            const auto assembler = assemblers_[i];
            hessian += assembler->assemble_hessian(data);
        }
        return hessian;
    }
 
    double SumModel::compute_energy(const NonLinearAssemblerData &data) const
    {
        double energy = assemblers_.front()->compute_energy(data);
        for (size_t i = 1; i < assemblers_.size(); ++i)
        {
            const auto assembler = assemblers_[i];
            energy += assembler->compute_energy(data);
        }
        return energy;
    }
 
    void SumModel::assign_stress_tensor(
        const OutputData &data,
        const int all_size,
        const ElasticityTensorType &type,
        Eigen::MatrixXd &all,
        const std::function<Eigen::MatrixXd(const Eigen::MatrixXd &)> &fun) const
    {
        all.resize(data.local_pts.rows(), all_size);
        all.setZero();
 
        Eigen::MatrixXd tmp;
 
        for (const auto &assembler : assemblers_)
        {
            std::dynamic_pointer_cast<assembler::ElasticityNLAssembler>(assembler)->assign_stress_tensor(data, all_size, type, tmp, fun);
            all += tmp;
        }
    }
 
    std::map<std::string, Assembler::ParamFunc> SumModel::parameters() const
    {
        std::map<std::string, Assembler::ParamFunc> params;
        for (const auto &a : assemblers_)
        {
            auto p = a->parameters();
            for (auto &it : p)
            {
                params[a->name() + "/" + it.first] = it.second;
            }
        }
        return params;
    }
} // namespace polyfem::assembler