Fix a few Clang warnings.

[nageru] / resampling_queue.cpp

// Parts of the code is adapted from Adriaensen's project Zita-ajbridge
// (as of November 2015), although it has been heavily reworked for this use
// case. Original copyright follows:
//
//  Copyright (C) 2012-2015 Fons Adriaensen <fons@linuxaudio.org>
//    
//  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 "resampling_queue.h"

#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <zita-resampler/vresampler.h>
#include <algorithm>
#include <cmath>

using namespace std;
using namespace std::chrono;

ResamplingQueue::ResamplingQueue(unsigned card_num, unsigned freq_in, unsigned freq_out, unsigned num_channels, double expected_delay_seconds)
        : card_num(card_num), freq_in(freq_in), freq_out(freq_out), num_channels(num_channels),
          current_estimated_freq_in(freq_in),
          ratio(double(freq_out) / double(freq_in)), expected_delay(expected_delay_seconds * OUTPUT_FREQUENCY)
{
        vresampler.setup(ratio, num_channels, /*hlen=*/32);

        // Prime the resampler so there's no more delay.
        vresampler.inp_count = vresampler.inpsize() / 2 - 1;
        vresampler.out_count = 1048576;
        vresampler.process ();
}

void ResamplingQueue::add_input_samples(steady_clock::time_point ts, const float *samples, ssize_t num_samples, ResamplingQueue::RateAdjustmentPolicy rate_adjustment_policy)
{
        if (num_samples == 0) {
                return;
        }

        assert(duration<double>(ts.time_since_epoch()).count() >= 0.0);

        bool good_sample = (rate_adjustment_policy == ADJUST_RATE);
        if (good_sample && a1.good_sample) {
                a0 = a1;
        }
        a1.ts = ts;
        a1.input_samples_received += num_samples;
        a1.good_sample = good_sample;
        if (a0.good_sample && a1.good_sample) {
                current_estimated_freq_in = (a1.input_samples_received - a0.input_samples_received) / duration<double>(a1.ts - a0.ts).count();
                assert(current_estimated_freq_in >= 0.0);

                // Bound the frequency, so that a single wild result won't throw the filter off guard.
                current_estimated_freq_in = min(current_estimated_freq_in, 1.2 * freq_in);
                current_estimated_freq_in = max(current_estimated_freq_in, 0.8 * freq_in);
        }

        buffer.insert(buffer.end(), samples, samples + num_samples * num_channels);
}

bool ResamplingQueue::get_output_samples(steady_clock::time_point ts, float *samples, ssize_t num_samples, ResamplingQueue::RateAdjustmentPolicy rate_adjustment_policy)
{
        assert(num_samples > 0);
        if (a1.input_samples_received == 0) {
                // No data yet, just return zeros.
                memset(samples, 0, num_samples * num_channels * sizeof(float));
                return true;
        }

        // This can happen when we get dropped frames on the master card.
        if (duration<double>(ts.time_since_epoch()).count() <= 0.0) {
                rate_adjustment_policy = DO_NOT_ADJUST_RATE;
        }

        if (rate_adjustment_policy == ADJUST_RATE && (a0.good_sample || a1.good_sample)) {
                // Estimate the current number of input samples produced at
                // this instant in time, by extrapolating from the last known
                // good point. Note that we could be extrapolating backward or
                // forward, depending on the timing of the calls.
                const InputPoint &base_point = a1.good_sample ? a1 : a0;
                assert(duration<double>(base_point.ts.time_since_epoch()).count() >= 0.0);

                // NOTE: Due to extrapolation, input_samples_received can
                // actually go negative here the few first calls (ie., we asked
                // about a timestamp where we hadn't actually started producing
                // samples yet), but that is harmless.
                const double input_samples_received = base_point.input_samples_received +
                        current_estimated_freq_in * duration<double>(ts - base_point.ts).count();

                // Estimate the number of input samples _consumed_ after we've run the resampler.
                const double input_samples_consumed = total_consumed_samples +
                        num_samples / (ratio * rcorr);

                double actual_delay = input_samples_received - input_samples_consumed;
                actual_delay += vresampler.inpdist();    // Delay in the resampler itself.
                double err = actual_delay - expected_delay;
                if (first_output) {
                        // Before the very first block, insert artificial delay based on our initial estimate,
                        // so that we don't need a long period to stabilize at the beginning.
                        if (err < 0.0) {
                                int delay_samples_to_add = lrintf(-err);
                                for (ssize_t i = 0; i < delay_samples_to_add * num_channels; ++i) {
                                        buffer.push_front(0.0f);
                                }
                                total_consumed_samples -= delay_samples_to_add;  // Equivalent to increasing input_samples_received on a0 and a1.
                                err += delay_samples_to_add;
                        } else if (err > 0.0) {
                                int delay_samples_to_remove = min<int>(lrintf(err), buffer.size() / num_channels);
                                buffer.erase(buffer.begin(), buffer.begin() + delay_samples_to_remove * num_channels);
                                total_consumed_samples += delay_samples_to_remove;
                                err -= delay_samples_to_remove;
                        }
                }
                first_output = false;

                // Compute loop filter coefficients for the two filters. We need to compute them
                // every time, since they depend on the number of samples the user asked for.
                //
                // The loop bandwidth is at 0.02 Hz; our jitter is pretty large
                // since none of the threads involved run at real-time priority.
                // However, the first four seconds, we use a larger loop bandwidth (2 Hz),
                // because there's a lot going on during startup, and thus the
                // initial estimate might be tainted by jitter during that phase,
                // and we want to converge faster.
                //
                // NOTE: The above logic might only hold during Nageru startup
                // (we start ResamplingQueues also when we e.g. switch sound sources),
                // but in general, a little bit of increased timing jitter is acceptable
                // right after a setup change like this.
                double loop_bandwidth_hz = (total_consumed_samples < 4 * freq_in) ? 0.2 : 0.02;

                // Set filters. The first filter much wider than the first one (20x as wide).
                double w = (2.0 * M_PI) * loop_bandwidth_hz * num_samples / freq_out;
                double w0 = 1.0 - exp(-20.0 * w);
                double w1 = w * 1.5 / num_samples / ratio;
                double w2 = w / 1.5;

                // Filter <err> through the loop filter to find the correction ratio.
                z1 += w0 * (w1 * err - z1);
                z2 += w0 * (z1 - z2);
                z3 += w2 * z2;
                rcorr = 1.0 - z2 - z3;
                if (rcorr > 1.05) rcorr = 1.05;
                if (rcorr < 0.95) rcorr = 0.95;
                assert(!isnan(rcorr));
                vresampler.set_rratio(rcorr);
        }

        // Finally actually resample, producing exactly <num_samples> output samples.
        vresampler.out_data = samples;
        vresampler.out_count = num_samples;
        while (vresampler.out_count > 0) {
                if (buffer.empty()) {
                        // This should never happen unless delay is set way too low,
                        // or we're dropping a lot of data.
                        fprintf(stderr, "Card %u: PANIC: Out of input samples to resample, still need %d output samples! (correction factor is %f)\n",
                                card_num, int(vresampler.out_count), rcorr);
                        memset(vresampler.out_data, 0, vresampler.out_count * num_channels * sizeof(float));

                        // Reset the loop filter.
                        z1 = z2 = z3 = 0.0;

                        return false;
                }

                float inbuf[1024];
                size_t num_input_samples = sizeof(inbuf) / (sizeof(float) * num_channels);
                if (num_input_samples * num_channels > buffer.size()) {
                        num_input_samples = buffer.size() / num_channels;
                }
                copy(buffer.begin(), buffer.begin() + num_input_samples * num_channels, inbuf);

                vresampler.inp_count = num_input_samples;
                vresampler.inp_data = inbuf;

                int err = vresampler.process();
                assert(err == 0);

                size_t consumed_samples = num_input_samples - vresampler.inp_count;
                total_consumed_samples += consumed_samples;
                buffer.erase(buffer.begin(), buffer.begin() + consumed_samples * num_channels);
        }
        return true;
}