1 files changed, 106 insertions, 0 deletions
diff --git a/core/bootstrap.cpp b/core/bootstrap.cpp
new file mode 100644
index 0000000..092d0f2
--- /dev/null
+++ b/core/bootstrap.cpp
@@ -0,0 +1,106 @@
+#include <boost/mpl/list.hpp>
+#include <boost/mpl/pair.hpp>
+#include <iostream>
+#include <inttypes.h>
+
+#include "index.hpp"
+#include "index_spike.hpp"
+#include "pla_get.hpp"
+#include "property_composition.hpp"
+#include "pla_init_default.hpp"
+#include "pla_set.hpp"
+#include "sim_loop.hpp"
+
+#include "model.hpp"
+
+using namespace boost;
+
+const Time startTime(0.1);
+
+struct FakeSim {
+  FakeSim()
+    : indices(),
+      queues()
+  {
+    using boost::make_tuple;
+  }
+
+  Ptr<GlobalMsg> addGlobalMsg(RNG::seed_t seed) {
+    const Time gmStartTime(ModelConsts::TrainerInitialDelay);
+    // create an discrete quant instance
+    Ptr<GlobalMsg> res(indices.get<Index<GlobalMsg>>().add
+		       (Time(0), gmStartTime, Ptr<Global>()));
+    // and a corresponding event occuring at time 0.1, stored in start
+    // interval (t=0)
+    queues.insert<GlobalMsg>(Time(0), gmStartTime, Event<GlobalMsg>(res));
+    pc.cast(PLA_Set<NextTrainer>(res, TrainerT(seed)));
+    return res;
+  }
+  
+  Ptr<Spike> addSpike(Ptr<Neuron> src) {
+    Time eventTime = startTime + TopologicalTimeOffset<Neuron, Spike>()(topo, src);
+    Ptr<Spike> res(indices.get<Index<Spike>>().add(startTime, eventTime, src));
+    queues.insert<Spike>(Time(0), eventTime, Event<Spike>(startTime, src, res));
+    return res;
+  }
+
+  Ptr<RandomSpike> addRandomSpike(Ptr<Neuron> src, RNG::seed_t seed) {
+    Time eventTime = startTime + RNG::expo(seed, 1 / ModelConsts::RandomFreq);
+    Ptr<RandomSpike> res(indices.get<Index<RandomSpike>>().add
+			 (startTime, eventTime, src));
+    queues.insert<RandomSpike>(Time(0), eventTime,
+			       Event<RandomSpike>(eventTime, src, res));
+    return res;
+  }
+
+  // data structs
+  typedef SimLoop<Lists::all> sim_t;
+  sim_t::indices_t indices;
+  sim_t::queues_t queues;
+  sim_t::pc_t pc;
+  Topology topo;
+};
+
+using namespace std;
+
+int main(int argc, char **argv) {
+  using boost::mpl::pair;
+  using boost::mpl::list;
+  FakeSim data;
+
+  // read cmd line arg
+  if (argc > 2) {
+    cout << "Usage: " << argv[0] << " [random-seed=0]";
+  }
+  char *tail;
+  RNG::seed_t rng(0);
+  if (argc == 2) {
+    rng = RNG::seed_t(strtoll(argv[1], &tail, 10));
+    assert(*tail == 0);
+  }
+
+  // init values (except weight)
+  data.pc.cast(PLA_Init_Default());
+
+  // init random seed (different one for every neuron)
+  for (Ptr<Neuron> i : Ptr<Global>().childs()) {
+    data.pc.cast(PLA_Set<RandomSeed>(Time(0), i, RNG::split(rng)));
+    rng = RNG::next(rng, 40);
+  }
+
+  // TODO: add a global event to start trainer
+  PLA_Get<NextTrainer> get(Ptr<GlobalMsg>(0));
+  data.addGlobalMsg(RNG::split(rng));
+  rng = RNG::next(rng, 40);
+
+  // add a random noise source for every neuron
+  for (Ptr<Neuron> i : Ptr<Global>().childs())
+    if (i() < ModelConsts::NumExcitatory) { // exclude special neurons
+      data.addRandomSpike(i,  RNG::split(rng));
+      rng = RNG::next(rng, 40);
+    }
+
+  // TODO: add discrete properties to the created events
+
+  return 0;
+}