autoActivation FFNet_Categories_to_Activation (FFNet me, Categories thee) {
try {
autoCategories uniq = Categories_selectUniqueItems (thee);
if (! my outputCategories) {
Melder_throw (U"The FFNet does not have categories.");
}
long nl = OrderedOfString_isSubsetOf (uniq.get(), my outputCategories.get(), 0);
if (nl == 0) {
Melder_throw (U"The Categories do not match the categories of the FFNet.");
}
autoActivation him = Activation_create (thy size, my nOutputs);
for (long i = 1; i <= thy size; i ++) {
const char32 *citem = OrderedOfString_itemAtIndex_c (thee, i);
long pos = OrderedOfString_indexOfItem_c (my outputCategories.get(), citem);
if (pos < 1) {
Melder_throw (U"The FFNet doesn't know the category ", citem, U".");
}
his z [i] [pos] = 1.0;
}
return him;
} catch (MelderError) {
Melder_throw (me, U": no Activation created.");
}
}
Any Matrix_to_Activation (I)
{
iam (Matrix);
Activation thee = Activation_create (my ny, my nx);
if (! thee) return NULL;
NUMdmatrix_copyElements (my z, thy z, 1, my ny, 1, my nx);
return thee;
}
autoActivation Matrix_to_Activation (Matrix me) {
try {
autoActivation thee = Activation_create (my ny, my nx);
NUMmatrix_copyElements (my z, thy z, 1, my ny, 1, my nx);
return thee;
} catch (MelderError) {
Melder_throw (me, U": not converted to Activation.");
}
}
Activation FFNet_Categories_to_Activation (FFNet me, Categories thee)
{
Activation him = NULL;
Categories uniq;
long i, nl, cSize = thy size, hasCategories = 1;
uniq = Categories_selectUniqueItems (thee, 1);
if (uniq == NULL) Melder_error1 (L"There is not enough memory to create a Categories.");
if (my outputCategories == NULL)
{
if (my nUnitsInLayer[my nLayers] == uniq -> size)
{
my outputCategories = uniq;
hasCategories = 0;
}
else
{
(void) Melder_error1 (L"");
goto end;
}
}
else if (! ( (nl = OrderedOfString_isSubsetOf (uniq, my outputCategories, NULL)) &&
nl == uniq -> size && my nOutputs >= uniq -> size))
{
(void) Melder_error1 (L"The Categories do not match the categories of the FFNet.");
goto end;
}
him = Activation_create (cSize, my nOutputs);
if (him == NULL) goto end;
for (i=1; i <= cSize; i++)
{
long pos = OrderedOfString_indexOfItem_c (my outputCategories, OrderedOfString_itemAtIndex_c (thee, i));
if (pos < 1)
{
(void) Melder_error3 (L"The FFNet doesn't know the category ", OrderedOfString_itemAtIndex_c (thee, i), L" from Categories.");
goto end;
}
his z[i][pos] = 1.0;
}
end:
if (hasCategories) forget (uniq);
if (Melder_hasError ()) forget (him);
return him;
}
Activation FFNet_Pattern_to_Activation (FFNet me, Pattern p, long layer) {
try {
if (layer < 1 || layer > my nLayers) {
layer = my nLayers;
}
if (my nInputs != p -> nx) Melder_throw (U"The Pattern and the FFNet do not match. "
U"The number of colums in the Pattern (", p -> nx, U") should equal the number of inputs "
U"in the FFNet (", my nInputs, U").");
if (! _Pattern_checkElements (p)) Melder_throw
(U"The elements in the Activation are not all in the interval [0, 1].\n"
U"The output units of the neural net can only process values that are between 0 and 1.\n"
U"You could use \"Formula...\" to scale the Activation values first.");
long nPatterns = p -> ny;
autoActivation thee = Activation_create (nPatterns, my nUnitsInLayer[layer]);
for (long i = 1; i <= nPatterns; i++) {
FFNet_propagateToLayer (me, p -> z[i], thy z[i], layer);
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, U": no Activation created.");
}
}
