pls100_device::pls100_device(const machine_config &mconfig, const char *tag, device_t *owner, uint32_t clock)
: pla_device(mconfig, PLS100, tag, owner, clock)
{
set_num_inputs(16);
set_num_outputs(8);
set_num_terms(48);
}
mos8721_device::mos8721_device(const machine_config &mconfig, const char *tag, device_t *owner, uint32_t clock)
: pla_device(mconfig, MOS8721, tag, owner, clock)
{
// TODO: actual number of terms is unknown
set_num_inputs(27);
set_num_outputs(18);
set_num_terms(379);
}
t_CKBOOL miniAudicle::set_adc( t_CKUINT adc )
{
#ifndef __CHIP_MODE__
// sanity check
if( adc > interfaces.size() )
return FALSE;
else
vm_options.adc = adc;
// set parameters to a reasonable value, if necessary
set_num_inputs( get_num_inputs() );
#endif // __CHIP_MODE__
return TRUE;
}
void ann::add(int argc, const t_atom *argv)
{
if (get_data_type() != data_type::LABELLED_CLASSIFICATION)
{
ml::add(argc, argv);
return;
}
// work around a bug in GRT where class labels must be contigious
if (argc < 2)
{
flext::error("invalid input length, must contain at least 2 values");
return;
}
GRT::UINT numInputDimensions = classification_data.getNumDimensions();
GRT::UINT numOutputDimensions = 1;
GRT::UINT combinedVectorSize = numInputDimensions + numOutputDimensions;
if ((unsigned)argc != combinedVectorSize)
{
numInputDimensions = argc - numOutputDimensions;
if (numInputDimensions < 1)
{
flext::error(std::string("invalid input length, expected at least " + std::to_string(numOutputDimensions + 1)).c_str());
return;
}
post("new input vector size, adjusting num_inputs to " + std::to_string(numInputDimensions));
set_num_inputs(numInputDimensions);
}
GRT::VectorDouble inputVector(numInputDimensions);
GRT::VectorDouble targetVector(numOutputDimensions);
for (uint32_t index = 0; index < (unsigned)argc; ++index)
{
float value = GetAFloat(argv[index]);
if (index < numOutputDimensions)
{
targetVector[index] = value;
}
else
{
inputVector[index - numOutputDimensions] = value;
}
}
GRT::UINT label = get_index_for_class((GRT::UINT)targetVector[0]);
assert(label > 0);
// if ((double)label != targetVector[0])
// {
// flext::error("class label must be a positive integer");
// return;
// }
//
// if (label == 0)
// {
// flext::error("class label must be non-zero");
// return;
// }
classification_data.addSample(label, inputVector);
}
