// fold functor example
static bool fun(const char *& acc, const data_t& data, const store_t& store,
pos_t begin, pos_t end, bool has_next) {
if (data.empty())
return true;
acc = data.str(store);
std::cout << begin << ":" << end << ":" << has_next << ":" << acc << "\n";
return true;
}
// fold functor example
static bool fun(const char *& acc, const data_t& data, const store_t& store,
pos_t, bool) {
if (data.empty())
return true;
acc = data.str(store);
std::cout << acc << std::endl;
return true;
}
/** Sets a new filter. However, the filter partitions are updated
* cycle by cycle one after the other. Note: With the current implementation
* the number of partitions of the new filter does not matter as long as it is
* equal or higher than the number of partitions of the current filter! If you
* set a filter which has less partitions than the current one, some of the
* partitions of the old filter will remain in the chain. So don't do that.
* @param filter vector holding the transfer functions of the zero padded
* filter partitions in halfcomplex format (see also fftw3 documentation).
* First element of \b filter is the first partition etc.
*/
void Convolver::set_filter_f(data_t& filter)
{
if (filter.empty())
return;
// if more filter updates than convolutions happen
if (!_waiting_queue.empty() && _waiting_queue.back().second == 0u)
{
_waiting_queue.pop_back();
}
_waiting_queue.push_back(std::pair<data_t, unsigned int>(filter, 0u));
}
/** Sets the filter.
* The length of the impulse response is arbitrary. It automatically
* performs zero padding if necessary and creates the required number of
* partitions. It is not very efficient since it calls
* \b Convolver::prepare_impulse_response(). It is provided for convenience.
* If you have the filter's transfer function in halfcomplex format use
* \b Convolver::set_filter_f() instead.
* @param filter impulse response of the filter
*/
void Convolver::set_filter_t(const data_t& filter)
{
if (filter.empty())
{
WARNING("You are trying to use an empty filter.");
return;
}
data_t buffer;
// TODO: It would be more efficient to use _fft_plan and _fft_buffer etc.
prepare_impulse_response(buffer, &filter[0], filter.size(), _frame_size);
set_filter_f(buffer);
}
secure_comparator_t(const data_t& shared_secret)
: comparator_(NULL)
{
if (shared_secret.empty()) {
throw themispp::exception_t("Secure Comparator must have non-empty shared secret");
}
res_.reserve(512);
comparator_ = secure_comparator_create();
if (!comparator_) {
throw themispp::exception_t("Secure Comparator construction failed");
}
themis_status_t status = secure_comparator_append_secret(comparator_,
&shared_secret[0],
shared_secret.size());
if (THEMIS_SUCCESS != status) {
throw themispp::exception_t("Secure Comparator failed to append secret", status);
}
}
bool isEmpty() const
{
return m_verts.empty();
}