/*************************************************************************
Serializer: unserialization
-- ALGLIB --
Copyright 14.03.2011 by Bochkanov Sergey
*************************************************************************/
public static void mlpunserialize(alglib.serializer s,
multilayerperceptron network)
{
int i0 = 0;
int i1 = 0;
int i = 0;
int j = 0;
int k = 0;
int fkind = 0;
double threshold = 0;
double v0 = 0;
double v1 = 0;
int nin = 0;
int nout = 0;
bool issoftmax = new bool();
int[] layersizes = new int[0];
//
// check correctness of header
//
i0 = s.unserialize_int();
alglib.ap.assert(i0==scodes.getmlpserializationcode(), "MLPUnserialize: stream header corrupted");
i1 = s.unserialize_int();
alglib.ap.assert(i1==mlpfirstversion, "MLPUnserialize: stream header corrupted");
//
// Create network
//
issoftmax = s.unserialize_bool();
apserv.unserializeintegerarray(s, ref layersizes);
alglib.ap.assert((alglib.ap.len(layersizes)==2 || alglib.ap.len(layersizes)==3) || alglib.ap.len(layersizes)==4, "MLPUnserialize: too many hidden layers!");
nin = layersizes[0];
nout = layersizes[alglib.ap.len(layersizes)-1];
if( alglib.ap.len(layersizes)==2 )
{
if( issoftmax )
{
mlpcreatec0(layersizes[0], layersizes[1], network);
}
else
{
mlpcreate0(layersizes[0], layersizes[1], network);
}
}
if( alglib.ap.len(layersizes)==3 )
{
if( issoftmax )
{
mlpcreatec1(layersizes[0], layersizes[1], layersizes[2], network);
}
else
{
mlpcreate1(layersizes[0], layersizes[1], layersizes[2], network);
}
}
if( alglib.ap.len(layersizes)==4 )
{
if( issoftmax )
{
mlpcreatec2(layersizes[0], layersizes[1], layersizes[2], layersizes[3], network);
}
else
{
mlpcreate2(layersizes[0], layersizes[1], layersizes[2], layersizes[3], network);
}
}
//
// Load neurons and weights
//
for(i=1; i<=alglib.ap.len(layersizes)-1; i++)
{
for(j=0; j<=layersizes[i]-1; j++)
{
fkind = s.unserialize_int();
threshold = s.unserialize_double();
mlpsetneuroninfo(network, i, j, fkind, threshold);
for(k=0; k<=layersizes[i-1]-1; k++)
{
v0 = s.unserialize_double();
mlpsetweight(network, i-1, k, i, j, v0);
}
}
}
//
// Load standartizator
//
for(j=0; j<=nin-1; j++)
{
v0 = s.unserialize_double();
v1 = s.unserialize_double();
mlpsetinputscaling(network, j, v0, v1);
}
for(j=0; j<=nout-1; j++)
{
v0 = s.unserialize_double();
v1 = s.unserialize_double();
mlpsetoutputscaling(network, j, v0, v1);
}
}
public static void rec4serializationunserialize(alglib.serializer s,
rec4serialization v)
{
int i = 0;
int k = 0;
bool bv = new bool();
int iv = 0;
double rv = 0;
//
// boolean fields
//
k = s.unserialize_int();
if( k>0 )
{
v.b = new bool[k];
for(i=0; i<=k-1; i++)
{
bv = s.unserialize_bool();
v.b[i] = bv;
}
}
//
// integer fields
//
k = s.unserialize_int();
if( k>0 )
{
v.i = new int[k];
for(i=0; i<=k-1; i++)
{
iv = s.unserialize_int();
v.i[i] = iv;
}
}
//
// real fields
//
k = s.unserialize_int();
if( k>0 )
{
v.r = new double[k];
for(i=0; i<=k-1; i++)
{
rv = s.unserialize_double();
v.r[i] = rv;
}
}
}