136 lines
3.8 KiB
C++
136 lines
3.8 KiB
C++
/*+
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ARES/HADES/BORG Package -- ./libLSS/tests/test_messenger3.cpp
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Copyright (C) 2014-2020 Guilhem Lavaux <guilhem.lavaux@iap.fr>
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Copyright (C) 2009-2020 Jens Jasche <jens.jasche@fysik.su.se>
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Additional contributions from:
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Guilhem Lavaux <guilhem.lavaux@iap.fr> (2023)
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+*/
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#include "libLSS/mpi/generic_mpi.hpp"
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#include "libLSS/tools/static_init.hpp"
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#include "libLSS/mcmc/global_state.hpp"
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#include "libLSS/samplers/rgen/gsl_random_number.hpp"
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#include "libLSS/samplers/core/types_samplers.hpp"
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#include "libLSS/samplers/ares/gibbs_messenger.hpp"
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#include "libLSS/samplers/core/powerspec_tools.hpp"
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#include "libLSS/samplers/ares/powerspectrum_a_sampler.hpp"
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using namespace LibLSS;
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typedef GSL_RandomNumber RGenType;
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int main(int argc, char **argv)
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{
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StaticInit::execute();
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MPI_Communication *mpi_world = setupMPI(argc, argv);
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Console::instance().setVerboseLevel<LOG_DEBUG>();
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MarkovState state;
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SLong *N0, *N1, *N2, *N2_HC, *NUM_MODES, *localN0, *startN0, *fourierLocalSize;
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SDouble *L0, *L1, *L2, *K_MIN, *K_MAX;
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RGenType randgen;
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ArrayType1d *ps;
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IArrayType *k_keys;
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state.newElement("random_generator", new RandomGen(&randgen));
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state.newElement("fourierLocalSize", fourierLocalSize = new SLong());
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state.newElement("localN0", localN0 = new SLong());
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state.newElement("startN0", startN0 = new SLong());
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state.newElement("N0", N0 = new SLong());
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state.newElement("N1", N1 = new SLong());
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state.newElement("N2", N2 = new SLong());
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state.newElement("N2_HC", N2_HC = new SLong());
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state.newSyScalar("messenger_signal_blocked", false);
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state.newSyScalar("power_sampler_a_blocked", false);
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state.newSyScalar("power_sampler_b_blocked", false);
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state.newElement("NUM_MODES", NUM_MODES = new SLong());
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state.newElement("K_MIN", K_MIN = new SDouble());
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state.newElement("K_MAX", K_MAX = new SDouble());
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NUM_MODES->value = 100;
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K_MIN->value = 0;
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K_MAX->value = 2.;
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state.newElement("L0", L0 = new SDouble());
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state.newElement("L1", L1 = new SDouble());
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state.newElement("L2", L2 = new SDouble());
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localN0->value = 64;
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startN0->value = 0;
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N0->value = 64;
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N1->value = 64;
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N2->value = 64;
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N2_HC->value = 33;
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fourierLocalSize->value = 64*64*33;
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L0->value = 200;
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L1->value = 200;
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L2->value = 200;
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MessengerSampler s(mpi_world);
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MessengerSignalSampler s2(mpi_world);
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PowerSpectrumSampler_a p(mpi_world);
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// Initialize (data,s)->t sampler
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s.init_markov(state);
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s2.init_markov(state);
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p.init_markov(state);
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ArrayType1d::ArrayType& k_val = *state.get<ArrayType1d>("k_modes")->array;
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int Nk = NUM_MODES->value;
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s2.setMockGeneration(true);
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// Fill up powerspectrum
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ps = state.get<ArrayType1d>("powerspectrum");
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for (int k = 1; k < Nk; k++) {
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(*ps->array)[k] = pow(k_val[k], -2);
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}
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// Build some mock field
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ArrayType *field = state.get<ArrayType>("data_field");
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field->eigen().fill(0);
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// Setup messenger parameters
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ArrayType *mmask = state.get<ArrayType>("messenger_mask");
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mmask->eigen().fill(-1);
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(*mmask->array)[16][16][16] = 0;
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state.get<SDouble>("messenger_tau")->value = 1.; // Remove any sign of data. I should add a mechanism to generate unconstrained realizations
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// First round is unconstrained
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s2.sample(state);
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s2.setMockGeneration(false);
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field->eigen() = state.get<ArrayType>("s_field")->eigen();
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s.sample(state);
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s2.sample(state);
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p.sample(state);
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s.sample(state);
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s2.sample(state);
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p.sample(state);
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s.sample(state);
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s2.sample(state);
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p.sample(state);
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{
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H5::H5File f("dump.h5", H5F_ACC_TRUNC);
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state.saveState(f);
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}
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StaticInit::finalize();
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doneMPI();
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return 0;
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}
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