dynare/mex/sources/k_order_perturbation/dynamic_m.cc

207 lines
7.0 KiB
C++

/*
* Copyright © 2010-2022 Dynare Team
*
* This file is part of Dynare.
*
* Dynare is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Dynare is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with Dynare. If not, see <https://www.gnu.org/licenses/>.
*/
#include <algorithm>
#include <cassert>
#include "dynare_exception.hh"
#include "dynamic_m.hh"
DynamicModelMFile::DynamicModelMFile(const std::string &modName, int ntt_arg) :
DynamicModelAC(ntt_arg),
DynamicMFilename{modName + ".dynamic"}
{
}
/* NB: This is a duplicate of DynamicModelMatlabCaller::cmplxToReal() in
perfect_foresight_problem MEX */
mxArray *
DynamicModelMFile::cmplxToReal(mxArray *cmplx_mx)
{
mxArray *real_mx = mxCreateDoubleMatrix(mxGetM(cmplx_mx), mxGetN(cmplx_mx), mxREAL);
#if MX_HAS_INTERLEAVED_COMPLEX
mxComplexDouble *cmplx = mxGetComplexDoubles(cmplx_mx);
#else
double *cmplx_real = mxGetPr(cmplx_mx);
double *cmplx_imag = mxGetPi(cmplx_mx);
#endif
double *real = mxGetPr(real_mx);
for (size_t i = 0; i < mxGetNumberOfElements(cmplx_mx); i++)
#if MX_HAS_INTERLEAVED_COMPLEX
if (cmplx[i].imag == 0.0)
real[i] = cmplx[i].real;
#else
if (cmplx_imag[i] == 0.0)
real[i] = cmplx_real[i];
#endif
else
real[i] = std::numeric_limits<double>::quiet_NaN();
mxDestroyArray(cmplx_mx);
return real_mx;
}
void
DynamicModelMFile::unpackSparseMatrixAndCopyIntoTwoDMatData(mxArray *sparseMat, TwoDMatrix &tdm)
{
int totalCols = mxGetN(sparseMat);
mwIndex *rowIdxVector = mxGetIr(sparseMat);
mwIndex *colIdxVector = mxGetJc(sparseMat);
assert(tdm.ncols() == 3);
/* Under MATLAB, the following check always holds at equality; under Octave,
there may be an inequality, because Octave diminishes nzmax if one gives
zeros in the values vector when calling sparse(). */
assert(tdm.nrows() >= mxGetNzmax(sparseMat));
int rind = 0;
int output_row = 0;
for (int i = 0; i < totalCols; i++)
for (int j = 0; j < static_cast<int>((colIdxVector[i+1]-colIdxVector[i])); j++, rind++)
{
tdm.get(output_row, 0) = rowIdxVector[rind] + 1;
tdm.get(output_row, 1) = i + 1;
if (!mxIsComplex(sparseMat))
tdm.get(output_row, 2) = mxGetPr(sparseMat)[rind];
else
{
double real, imag;
#if MX_HAS_INTERLEAVED_COMPLEX
mxComplexDouble cmplx = mxGetComplexDoubles(sparseMat)[rind];
real = cmplx.real;
imag = cmplx.imag;
#else
real = mxGetPr(sparseMat)[rind];
imag = mxGetPi(sparseMat)[rind];
#endif
tdm.get(output_row, 2) = imag == 0.0 ? real : std::numeric_limits<double>::quiet_NaN();
}
output_row++;
}
/* If there are less elements than expected (that might happen if some
derivative is symbolically not zero but numerically zero at the evaluation
point), then fill in the matrix with empty entries, that will be
recognized as such by KordpDynare::populateDerivativesContainer() */
while (output_row < tdm.nrows())
{
tdm.get(output_row, 0) = 0;
tdm.get(output_row, 1) = 0;
tdm.get(output_row, 2) = 0;
output_row++;
}
}
void
DynamicModelMFile::eval(const Vector &y, const Vector &x, const Vector &modParams, const Vector &ySteady,
Vector &residual, std::vector<TwoDMatrix> &md) noexcept(false)
{
mxArray *T_m = mxCreateDoubleMatrix(ntt, 1, mxREAL);
mxArray *y_m = mxCreateDoubleMatrix(y.length(), 1, mxREAL);
std::copy_n(y.base(), y.length(), mxGetPr(y_m));
mxArray *x_m = mxCreateDoubleMatrix(1, x.length(), mxREAL);
std::copy_n(x.base(), x.length(), mxGetPr(x_m));
mxArray *params_m = mxCreateDoubleMatrix(modParams.length(), 1, mxREAL);
std::copy_n(modParams.base(), modParams.length(), mxGetPr(params_m));
mxArray *steady_state_m = mxCreateDoubleMatrix(ySteady.length(), 1, mxREAL);
std::copy_n(ySteady.base(), ySteady.length(), mxGetPr(steady_state_m));
mxArray *it_m = mxCreateDoubleScalar(1.0);
mxArray *T_flag_m = mxCreateLogicalScalar(false);
{
// Compute temporary terms (for all orders)
std::string funcname = DynamicMFilename + "_g" + std::to_string(md.size()) + "_tt";
mxArray *plhs[1], *prhs[] = { T_m, y_m, x_m, params_m, steady_state_m, it_m };
int retVal = mexCallMATLAB(1, plhs, 6, prhs, funcname.c_str());
if (retVal != 0)
throw DynareException(__FILE__, __LINE__, "Trouble calling " + funcname);
mxDestroyArray(T_m);
T_m = plhs[0];
}
{
// Compute residuals
std::string funcname = DynamicMFilename + "_resid";
mxArray *plhs[1], *prhs[] = { T_m, y_m, x_m, params_m, steady_state_m, it_m, T_flag_m };
int retVal = mexCallMATLAB(1, plhs, 7, prhs, funcname.c_str());
if (retVal != 0)
throw DynareException(__FILE__, __LINE__, "Trouble calling " + funcname);
if (!mxIsDouble(plhs[0]) || mxIsSparse(plhs[0]))
throw DynareException(__FILE__, __LINE__, "Residual should be a dense array of double floats");
if (mxIsComplex(plhs[0]))
plhs[0] = cmplxToReal(plhs[0]);
residual = Vector{plhs[0]};
mxDestroyArray(plhs[0]);
}
for (size_t i = 1; i <= md.size(); i++)
{
// Compute model derivatives
std::string funcname = DynamicMFilename + "_g" + std::to_string(i);
mxArray *plhs[1], *prhs[] = { T_m, y_m, x_m, params_m, steady_state_m, it_m, T_flag_m };
int retVal = mexCallMATLAB(1, plhs, 7, prhs, funcname.c_str());
if (retVal != 0)
throw DynareException(__FILE__, __LINE__, "Trouble calling " + funcname);
if (!mxIsDouble(plhs[0]))
throw DynareException(__FILE__, __LINE__, "Derivatives matrix at order " + std::to_string(i) + "should be an array of double floats");
if (i == 1)
{
if (mxIsSparse(plhs[0]))
throw DynareException(__FILE__, __LINE__, "Derivatives matrix at order " + std::to_string(i) + " should be dense");
assert(static_cast<int>(mxGetM(plhs[0])) == md[i-1].nrows());
assert(static_cast<int>(mxGetN(plhs[0])) == md[i-1].ncols());
std::copy_n(mxGetPr(plhs[0]), mxGetM(plhs[0])*mxGetN(plhs[0]), md[i-1].base());
}
else
{
if (!mxIsSparse(plhs[0]))
throw DynareException(__FILE__, __LINE__, "Derivatives matrix at order " + std::to_string(i) + " should be sparse");
unpackSparseMatrixAndCopyIntoTwoDMatData(plhs[0], md[i-1]);
}
mxDestroyArray(plhs[0]);
}
mxDestroyArray(T_m);
mxDestroyArray(y_m);
mxDestroyArray(x_m);
mxDestroyArray(params_m);
mxDestroyArray(steady_state_m);
mxDestroyArray(it_m);
mxDestroyArray(T_flag_m);
}