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//
// Copyright 2010-2011,2014 Ettus Research LLC
// Copyright 2018 Ettus Research, a National Instruments Company
//
// SPDX-License-Identifier: GPL-3.0-or-later
//
#include <uhd/exception.hpp>
#include <uhd/types/dict.hpp>
#include <uhd/utils/algorithm.hpp>
#include <uhd/utils/gain_group.hpp>
#include <uhd/utils/log.hpp>
#include <boost/bind.hpp>
#include <algorithm>
#include <vector>
#if (BOOST_VERSION >= 106000)
using namespace boost::placeholders;
#endif
using namespace uhd;
static bool compare_by_step_size(
const size_t& rhs, const size_t& lhs, std::vector<gain_fcns_t>& fcns)
{
return fcns.at(rhs).get_range().step() > fcns.at(lhs).get_range().step();
}
/*!
* Get a multiple of step with the following relation:
* result = step*floor(num/step)
*
* Due to small doubleing-point inaccuracies:
* num = n*step e, where e is a small inaccuracy.
* When e is negative, floor would yield (n-1)*step,
* despite that n*step is really the desired result.
* This function is designed to mitigate that issue.
*
* \param num the number to approximate
* \param step the step size to round with
* \param e the small inaccuracy to account for
* \return a multiple of step approximating num
*/
template <typename T>
static T floor_step(T num, T step, T e = T(0.001))
{
if (num < T(0)) {
return step * int(num / step - e);
} else {
return step * int(num / step e);
}
}
gain_group::~gain_group(void)
{
/* NOP */
}
/***********************************************************************
* gain group implementation
**********************************************************************/
class gain_group_impl : public gain_group
{
public:
gain_group_impl(void)
{
/*NOP*/
}
gain_range_t get_range(const std::string& name)
{
if (not name.empty())
return _name_to_fcns.get(name).get_range();
double overall_min = 0, overall_max = 0, overall_step = 0;
for (const gain_fcns_t& fcns : get_all_fcns()) {
const gain_range_t range = fcns.get_range();
overall_min = range.start();
overall_max = range.stop();
// the overall step is the min (zero is invalid, first run)
if (overall_step == 0) {
overall_step = range.step();
} else if (range.step()) {
overall_step = std::min(overall_step, range.step());
}
}
return gain_range_t(overall_min, overall_max, overall_step);
}
double get_value(const std::string& name)
{
if (not name.empty())
return _name_to_fcns.get(name).get_value();
double overall_gain = 0;
for (const gain_fcns_t& fcns : get_all_fcns()) {
overall_gain = fcns.get_value();
}
return overall_gain;
}
void set_value(double gain, const std::string& name)
{
if (not name.empty())
return _name_to_fcns.get(name).set_value(gain);
std::vector<gain_fcns_t> all_fcns = get_all_fcns();
if (all_fcns.size() == 0)
return; // nothing to set!
// get the max step size among the gains
double max_step = 0;
for (const gain_fcns_t& fcns : all_fcns) {
max_step = std::max(max_step, fcns.get_range().step());
}
// create gain bucket to distribute power
std::vector<double> gain_bucket;
// distribute power according to priority (round to max step)
double gain_left_to_distribute = gain;
for (const gain_fcns_t& fcns : all_fcns) {
const gain_range_t range = fcns.get_range();
gain_bucket.push_back(floor_step(
uhd::clip(gain_left_to_distribute, range.start(), range.stop()),
max_step));
gain_left_to_distribute -= gain_bucket.back();
}
// get a list of indexes sorted by step size large to small
std::vector<size_t> indexes_step_size_dec;
for (size_t i = 0; i < all_fcns.size(); i ) {
indexes_step_size_dec.push_back(i);
}
std::sort(indexes_step_size_dec.begin(),
indexes_step_size_dec.end(),
boost::bind(&compare_by_step_size, _1, _2, all_fcns));
UHD_ASSERT_THROW(all_fcns.at(indexes_step_size_dec.front()).get_range().step()
>= all_fcns.at(indexes_step_size_dec.back()).get_range().step());
// distribute the remainder (less than max step)
// fill in the largest step sizes first that are less than the remainder
for (size_t i : indexes_step_size_dec) {
const gain_range_t range = all_fcns.at(i).get_range();
double additional_gain =
floor_step(uhd::clip(gain_bucket.at(i) gain_left_to_distribute,
range.start(),
range.stop()),
range.step())
- gain_bucket.at(i);
gain_bucket.at(i) = additional_gain;
gain_left_to_distribute -= additional_gain;
}
UHD_LOGGER_DEBUG("UHD") << "gain_left_to_distribute " << gain_left_to_distribute;
// now write the bucket out to the individual gain values
for (size_t i = 0; i < gain_bucket.size(); i ) {
UHD_LOGGER_DEBUG("UHD") << i << ": " << gain_bucket.at(i);
all_fcns.at(i).set_value(gain_bucket.at(i));
}
}
const std::vector<std::string> get_names(void)
{
return _name_to_fcns.keys();
}
void register_fcns(
const std::string& name, const gain_fcns_t& gain_fcns, size_t priority)
{
if (name.empty() or _name_to_fcns.has_key(name)) {
// ensure the name name is unique and non-empty
return register_fcns(name "_", gain_fcns, priority);
}
_registry[priority].push_back(gain_fcns);
_name_to_fcns[name] = gain_fcns;
}
private:
//! get the gain function sets in order (highest priority first)
std::vector<gain_fcns_t> get_all_fcns(void)
{
std::vector<gain_fcns_t> all_fcns;
for (size_t key : uhd::sorted(_registry.keys())) {
const std::vector<gain_fcns_t>& fcns = _registry[key];
all_fcns.insert(all_fcns.begin(), fcns.begin(), fcns.end());
}
return all_fcns;
}
uhd::dict<size_t, std::vector<gain_fcns_t>> _registry;
uhd::dict<std::string, gain_fcns_t> _name_to_fcns;
};
/***********************************************************************
* gain group factory function
**********************************************************************/
gain_group::sptr gain_group::make(void)
{
return sptr(new gain_group_impl());
}
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