| /*** | |
| This file is part of PulseAudio. | |
| Copyright 2007 Lennart Poettering | |
| PulseAudio is free software; you can redistribute it and/or modify | |
| it under the terms of the GNU Lesser General Public License as | |
| published by the Free Software Foundation; either version 2.1 of the | |
| License, or (at your option) any later version. | |
| PulseAudio 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 | |
| Lesser General Public License for more details. | |
| You should have received a copy of the GNU Lesser General Public | |
| License along with PulseAudio; if not, see <http://www.gnu.org/licenses/>. | |
| ***/ | |
| #ifdef HAVE_CONFIG_H | |
| #include <config.h> | |
| #endif | |
| #include <stdio.h> | |
| #include <math.h> | |
| #include <pulse/sample.h> | |
| #include <pulse/xmalloc.h> | |
| #include <pulsecore/macro.h> | |
| #include "time-smoother.h" | |
| #define HISTORY_MAX 64 | |
| /* | |
| * Implementation of a time smoothing algorithm to synchronize remote | |
| * clocks to a local one. Evens out noise, adjusts to clock skew and | |
| * allows cheap estimations of the remote time while clock updates may | |
| * be seldom and received in non-equidistant intervals. | |
| * | |
| * Basically, we estimate the gradient of received clock samples in a | |
| * certain history window (of size 'history_time') with linear | |
| * regression. With that info we estimate the remote time in | |
| * 'adjust_time' ahead and smoothen our current estimation function | |
| * towards that point with a 3rd order polynomial interpolation with | |
| * fitting derivatives. (more or less a b-spline) | |
| * | |
| * The larger 'history_time' is chosen the better we will suppress | |
| * noise -- but we'll adjust to clock skew slower.. | |
| * | |
| * The larger 'adjust_time' is chosen the smoother our estimation | |
| * function will be -- but we'll adjust to clock skew slower, too. | |
| * | |
| * If 'monotonic' is true the resulting estimation function is | |
| * guaranteed to be monotonic. | |
| */ | |
| struct pa_smoother { | |
| pa_usec_t adjust_time, history_time; | |
| pa_usec_t time_offset; | |
| pa_usec_t px, py; /* Point p, where we want to reach stability */ | |
| double dp; /* Gradient we want at point p */ | |
| pa_usec_t ex, ey; /* Point e, which we estimated before and need to smooth to */ | |
| double de; /* Gradient we estimated for point e */ | |
| pa_usec_t ry; /* The original y value for ex */ | |
| /* History of last measurements */ | |
| pa_usec_t history_x[HISTORY_MAX], history_y[HISTORY_MAX]; | |
| unsigned history_idx, n_history; | |
| /* To even out for monotonicity */ | |
| pa_usec_t last_y, last_x; | |
| /* Cached parameters for our interpolation polynomial y=ax^3+b^2+cx */ | |
| double a, b, c; | |
| bool abc_valid:1; | |
| bool monotonic:1; | |
| bool paused:1; | |
| bool smoothing:1; /* If false we skip the polynomial interpolation step */ | |
| pa_usec_t pause_time; | |
| unsigned min_history; | |
| }; | |
| pa_smoother* pa_smoother_new( | |
| pa_usec_t adjust_time, | |
| pa_usec_t history_time, | |
| bool monotonic, | |
| bool smoothing, | |
| unsigned min_history, | |
| pa_usec_t time_offset, | |
| bool paused) { | |
| pa_smoother *s; | |
| pa_assert(adjust_time > 0); | |
| pa_assert(history_time > 0); | |
| pa_assert(min_history >= 2); | |
| pa_assert(min_history <= HISTORY_MAX); | |
| s = pa_xnew(pa_smoother, 1); | |
| s->adjust_time = adjust_time; | |
| s->history_time = history_time; | |
| s->min_history = min_history; | |
| s->monotonic = monotonic; | |
| s->smoothing = smoothing; | |
| pa_smoother_reset(s, time_offset, paused); | |
| return s; | |
| } | |
| void pa_smoother_free(pa_smoother* s) { | |
| pa_assert(s); | |
| pa_xfree(s); | |
| } | |
| #define REDUCE(x) \ | |
| do { \ | |
| x = (x) % HISTORY_MAX; \ | |
| } while(false) | |
| #define REDUCE_INC(x) \ | |
| do { \ | |
| x = ((x)+1) % HISTORY_MAX; \ | |
| } while(false) | |
| static void drop_old(pa_smoother *s, pa_usec_t x) { | |
| /* Drop items from history which are too old, but make sure to | |
| * always keep min_history in the history */ | |
| while (s->n_history > s->min_history) { | |
| if (s->history_x[s->history_idx] + s->history_time >= x) | |
| /* This item is still valid, and thus all following ones | |
| * are too, so let's quit this loop */ | |
| break; | |
| /* Item is too old, let's drop it */ | |
| REDUCE_INC(s->history_idx); | |
| s->n_history --; | |
| } | |
| } | |
| static void add_to_history(pa_smoother *s, pa_usec_t x, pa_usec_t y) { | |
| unsigned j, i; | |
| pa_assert(s); | |
| /* First try to update an existing history entry */ | |
| i = s->history_idx; | |
| for (j = s->n_history; j > 0; j--) { | |
| if (s->history_x[i] == x) { | |
| s->history_y[i] = y; | |
| return; | |
| } | |
| REDUCE_INC(i); | |
| } | |
| /* Drop old entries */ | |
| drop_old(s, x); | |
| /* Calculate position for new entry */ | |
| j = s->history_idx + s->n_history; | |
| REDUCE(j); | |
| /* Fill in entry */ | |
| s->history_x[j] = x; | |
| s->history_y[j] = y; | |
| /* Adjust counter */ | |
| s->n_history ++; | |
| /* And make sure we don't store more entries than fit in */ | |
| if (s->n_history > HISTORY_MAX) { | |
| s->history_idx += s->n_history - HISTORY_MAX; | |
| REDUCE(s->history_idx); | |
| s->n_history = HISTORY_MAX; | |
| } | |
| } | |
| static double avg_gradient(pa_smoother *s, pa_usec_t x) { | |
| unsigned i, j, c = 0; | |
| int64_t ax = 0, ay = 0, k, t; | |
| double r; | |
| /* FIXME: Optimization: Jason Newton suggested that instead of | |
| * going through the history on each iteration we could calculated | |
| * avg_gradient() as we go. | |
| * | |
| * Second idea: it might make sense to weight history entries: | |
| * more recent entries should matter more than old ones. */ | |
| /* Too few measurements, assume gradient of 1 */ | |
| if (s->n_history < s->min_history) | |
| return 1; | |
| /* First, calculate average of all measurements */ | |
| i = s->history_idx; | |
| for (j = s->n_history; j > 0; j--) { | |
| ax += (int64_t) s->history_x[i]; | |
| ay += (int64_t) s->history_y[i]; | |
| c++; | |
| REDUCE_INC(i); | |
| } | |
| pa_assert(c >= s->min_history); | |
| ax /= c; | |
| ay /= c; | |
| /* Now, do linear regression */ | |
| k = t = 0; | |
| i = s->history_idx; | |
| for (j = s->n_history; j > 0; j--) { | |
| int64_t dx, dy; | |
| dx = (int64_t) s->history_x[i] - ax; | |
| dy = (int64_t) s->history_y[i] - ay; | |
| k += dx*dy; | |
| t += dx*dx; | |
| REDUCE_INC(i); | |
| } | |
| r = (double) k / (double) t; | |
| return (s->monotonic && r < 0) ? 0 : r; | |
| } | |
| static void calc_abc(pa_smoother *s) { | |
| pa_usec_t ex, ey, px, py; | |
| int64_t kx, ky; | |
| double de, dp; | |
| pa_assert(s); | |
| if (s->abc_valid) | |
| return; | |
| /* We have two points: (ex|ey) and (px|py) with two gradients at | |
| * these points de and dp. We do a polynomial | |
| * interpolation of degree 3 with these 6 values */ | |
| ex = s->ex; ey = s->ey; | |
| px = s->px; py = s->py; | |
| de = s->de; dp = s->dp; | |
| pa_assert(ex < px); | |
| /* To increase the dynamic range and simplify calculation, we | |
| * move these values to the origin */ | |
| kx = (int64_t) px - (int64_t) ex; | |
| ky = (int64_t) py - (int64_t) ey; | |
| /* Calculate a, b, c for y=ax^3+bx^2+cx */ | |
| s->c = de; | |
| s->b = (((double) (3*ky)/ (double) kx - dp - (double) (2*de))) / (double) kx; | |
| s->a = (dp/(double) kx - 2*s->b - de/(double) kx) / (double) (3*kx); | |
| s->abc_valid = true; | |
| } | |
| static void estimate(pa_smoother *s, pa_usec_t x, pa_usec_t *y, double *deriv) { | |
| pa_assert(s); | |
| pa_assert(y); | |
| if (x >= s->px) { | |
| /* Linear interpolation right from px */ | |
| int64_t t; | |
| /* The requested point is right of the point where we wanted | |
| * to be on track again, thus just linearly estimate */ | |
| t = (int64_t) s->py + (int64_t) llrint(s->dp * (double) (x - s->px)); | |
| if (t < 0) | |
| t = 0; | |
| *y = (pa_usec_t) t; | |
| if (deriv) | |
| *deriv = s->dp; | |
| } else if (x <= s->ex) { | |
| /* Linear interpolation left from ex */ | |
| int64_t t; | |
| t = (int64_t) s->ey - (int64_t) llrint(s->de * (double) (s->ex - x)); | |
| if (t < 0) | |
| t = 0; | |
| *y = (pa_usec_t) t; | |
| if (deriv) | |
| *deriv = s->de; | |
| } else { | |
| /* Spline interpolation between ex and px */ | |
| double tx, ty; | |
| /* Ok, we're not yet on track, thus let's interpolate, and | |
| * make sure that the first derivative is smooth */ | |
| calc_abc(s); | |
| /* Move to origin */ | |
| tx = (double) (x - s->ex); | |
| /* Horner scheme */ | |
| ty = (tx * (s->c + tx * (s->b + tx * s->a))); | |
| /* Move back from origin */ | |
| ty += (double) s->ey; | |
| *y = ty >= 0 ? (pa_usec_t) llrint(ty) : 0; | |
| /* Horner scheme */ | |
| if (deriv) | |
| *deriv = s->c + (tx * (s->b*2 + tx * s->a*3)); | |
| } | |
| /* Guarantee monotonicity */ | |
| if (s->monotonic) { | |
| if (deriv && *deriv < 0) | |
| *deriv = 0; | |
| } | |
| } | |
| void pa_smoother_put(pa_smoother *s, pa_usec_t x, pa_usec_t y) { | |
| pa_usec_t ney; | |
| double nde; | |
| bool is_new; | |
| pa_assert(s); | |
| /* Fix up x value */ | |
| if (s->paused) | |
| x = s->pause_time; | |
| x = PA_LIKELY(x >= s->time_offset) ? x - s->time_offset : 0; | |
| is_new = x >= s->ex; | |
| if (is_new) { | |
| /* First, we calculate the position we'd estimate for x, so that | |
| * we can adjust our position smoothly from this one */ | |
| estimate(s, x, &ney, &nde); | |
| s->ex = x; s->ey = ney; s->de = nde; | |
| s->ry = y; | |
| } | |
| /* Then, we add the new measurement to our history */ | |
| add_to_history(s, x, y); | |
| /* And determine the average gradient of the history */ | |
| s->dp = avg_gradient(s, x); | |
| /* And calculate when we want to be on track again */ | |
| if (s->smoothing) { | |
| s->px = s->ex + s->adjust_time; | |
| s->py = s->ry + (pa_usec_t) llrint(s->dp * (double) s->adjust_time); | |
| } else { | |
| s->px = s->ex; | |
| s->py = s->ry; | |
| } | |
| s->abc_valid = false; | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("%p, put(%llu | %llu) = %llu", s, (unsigned long long) (x + s->time_offset), (unsigned long long) x, (unsigned long long) y); | |
| #endif | |
| } | |
| pa_usec_t pa_smoother_get(pa_smoother *s, pa_usec_t x) { | |
| pa_usec_t y; | |
| pa_assert(s); | |
| /* Fix up x value */ | |
| if (s->paused) | |
| x = s->pause_time; | |
| x = PA_LIKELY(x >= s->time_offset) ? x - s->time_offset : 0; | |
| if (s->monotonic) | |
| if (x <= s->last_x) | |
| x = s->last_x; | |
| estimate(s, x, &y, NULL); | |
| if (s->monotonic) { | |
| /* Make sure the querier doesn't jump forth and back. */ | |
| s->last_x = x; | |
| if (y < s->last_y) | |
| y = s->last_y; | |
| else | |
| s->last_y = y; | |
| } | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("%p, get(%llu | %llu) = %llu", s, (unsigned long long) (x + s->time_offset), (unsigned long long) x, (unsigned long long) y); | |
| #endif | |
| return y; | |
| } | |
| void pa_smoother_set_time_offset(pa_smoother *s, pa_usec_t offset) { | |
| pa_assert(s); | |
| s->time_offset = offset; | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("offset(%llu)", (unsigned long long) offset); | |
| #endif | |
| } | |
| void pa_smoother_pause(pa_smoother *s, pa_usec_t x) { | |
| pa_assert(s); | |
| if (s->paused) | |
| return; | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("pause(%llu)", (unsigned long long) x); | |
| #endif | |
| s->paused = true; | |
| s->pause_time = x; | |
| } | |
| void pa_smoother_resume(pa_smoother *s, pa_usec_t x, bool fix_now) { | |
| pa_assert(s); | |
| if (!s->paused) | |
| return; | |
| if (x < s->pause_time) | |
| x = s->pause_time; | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("resume(%llu)", (unsigned long long) x); | |
| #endif | |
| s->paused = false; | |
| s->time_offset += x - s->pause_time; | |
| if (fix_now) | |
| pa_smoother_fix_now(s); | |
| } | |
| void pa_smoother_fix_now(pa_smoother *s) { | |
| pa_assert(s); | |
| s->px = s->ex; | |
| s->py = s->ry; | |
| } | |
| pa_usec_t pa_smoother_translate(pa_smoother *s, pa_usec_t x, pa_usec_t y_delay) { | |
| pa_usec_t ney; | |
| double nde; | |
| pa_assert(s); | |
| /* Fix up x value */ | |
| if (s->paused) | |
| x = s->pause_time; | |
| x = PA_LIKELY(x >= s->time_offset) ? x - s->time_offset : 0; | |
| estimate(s, x, &ney, &nde); | |
| /* Play safe and take the larger gradient, so that we wakeup | |
| * earlier when this is used for sleeping */ | |
| if (s->dp > nde) | |
| nde = s->dp; | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("translate(%llu) = %llu (%0.2f)", (unsigned long long) y_delay, (unsigned long long) ((double) y_delay / nde), nde); | |
| #endif | |
| return (pa_usec_t) llrint((double) y_delay / nde); | |
| } | |
| void pa_smoother_reset(pa_smoother *s, pa_usec_t time_offset, bool paused) { | |
| pa_assert(s); | |
| s->px = s->py = 0; | |
| s->dp = 1; | |
| s->ex = s->ey = s->ry = 0; | |
| s->de = 1; | |
| s->history_idx = 0; | |
| s->n_history = 0; | |
| s->last_y = s->last_x = 0; | |
| s->abc_valid = false; | |
| s->paused = paused; | |
| s->time_offset = s->pause_time = time_offset; | |
| #ifdef DEBUG_DATA | |
| pa_log_debug("reset()"); | |
| #endif | |
| } |