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//
// Copyright 2010-2011,2014 Ettus Research LLC
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
//
#include <uhd/utils/gain_group.hpp>
#include <uhd/utils/log.hpp>
#include <uhd/types/dict.hpp>
#include <uhd/utils/algorithm.hpp>
#include <uhd/exception.hpp>
#include <boost/bind.hpp>
#include <algorithm>
#include <vector>
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();
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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