/*
chronyd/chronyc - Programs for keeping computer clocks accurate.
**********************************************************************
* Copyright (C) Miroslav Lichvar 2009-2011, 2014, 2016, 2018
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of version 2 of the GNU General Public License as
* published by the Free Software Foundation.
*
* 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, write to the Free Software Foundation, Inc.,
* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*
**********************************************************************
=======================================================================
Routines implementing a median sample filter.
*/
#include "config.h"
#include "local.h"
#include "logging.h"
#include "memory.h"
#include "regress.h"
#include "samplefilt.h"
#include "util.h"
#define MIN_SAMPLES 1
#define MAX_SAMPLES 256
struct SPF_Instance_Record {
int min_samples;
int max_samples;
int index;
int used;
int last;
int avg_var_n;
double avg_var;
double max_var;
double combine_ratio;
NTP_Sample *samples;
int *selected;
double *x_data;
double *y_data;
double *w_data;
};
/* ================================================== */
SPF_Instance
SPF_CreateInstance(int min_samples, int max_samples, double max_dispersion, double combine_ratio)
{
SPF_Instance filter;
filter = MallocNew(struct SPF_Instance_Record);
min_samples = CLAMP(MIN_SAMPLES, min_samples, MAX_SAMPLES);
max_samples = CLAMP(MIN_SAMPLES, max_samples, MAX_SAMPLES);
max_samples = MAX(min_samples, max_samples);
combine_ratio = CLAMP(0.0, combine_ratio, 1.0);
filter->min_samples = min_samples;
filter->max_samples = max_samples;
filter->index = -1;
filter->used = 0;
filter->last = -1;
/* Set the first estimate to the system precision */
filter->avg_var_n = 0;
filter->avg_var = SQUARE(LCL_GetSysPrecisionAsQuantum());
filter->max_var = SQUARE(max_dispersion);
filter->combine_ratio = combine_ratio;
filter->samples = MallocArray(NTP_Sample, filter->max_samples);
filter->selected = MallocArray(int, filter->max_samples);
filter->x_data = MallocArray(double, filter->max_samples);
filter->y_data = MallocArray(double, filter->max_samples);
filter->w_data = MallocArray(double, filter->max_samples);
return filter;
}
/* ================================================== */
void
SPF_DestroyInstance(SPF_Instance filter)
{
Free(filter->samples);
Free(filter->selected);
Free(filter->x_data);
Free(filter->y_data);
Free(filter->w_data);
Free(filter);
}
/* ================================================== */
/* Check that samples times are strictly increasing */
static int
check_sample(SPF_Instance filter, NTP_Sample *sample)
{
if (filter->used <= 0)
return 1;
if (UTI_CompareTimespecs(&filter->samples[filter->last].time, &sample->time) >= 0) {
DEBUG_LOG("filter non-increasing sample time %s", UTI_TimespecToString(&sample->time));
return 0;
}
return 1;
}
/* ================================================== */
int
SPF_AccumulateSample(SPF_Instance filter, NTP_Sample *sample)
{
if (!check_sample(filter, sample))
return 0;
filter->index++;
filter->index %= filter->max_samples;
filter->last = filter->index;
if (filter->used < filter->max_samples)
filter->used++;
filter->samples[filter->index] = *sample;
DEBUG_LOG("filter sample %d t=%s offset=%.9f peer_disp=%.9f",
filter->index, UTI_TimespecToString(&sample->time),
sample->offset, sample->peer_dispersion);
return 1;
}
/* ================================================== */
int
SPF_GetLastSample(SPF_Instance filter, NTP_Sample *sample)
{
if (filter->last < 0)
return 0;
*sample = filter->samples[filter->last];
return 1;
}
/* ================================================== */
int
SPF_GetNumberOfSamples(SPF_Instance filter)
{
return filter->used;
}
/* ================================================== */
double
SPF_GetAvgSampleDispersion(SPF_Instance filter)
{
return sqrt(filter->avg_var);
}
/* ================================================== */
void
SPF_DropSamples(SPF_Instance filter)
{
filter->index = -1;
filter->used = 0;
}
/* ================================================== */
static const NTP_Sample *tmp_sort_samples;
static int
compare_samples(const void *a, const void *b)
{
const NTP_Sample *s1, *s2;
s1 = &tmp_sort_samples[*(int *)a];
s2 = &tmp_sort_samples[*(int *)b];
if (s1->offset < s2->offset)
return -1;
else if (s1->offset > s2->offset)
return 1;
return 0;
}
/* ================================================== */
static int
select_samples(SPF_Instance filter)
{
int i, j, k, o, from, to, *selected;
double min_dispersion;
if (filter->used < filter->min_samples)
return 0;
selected = filter->selected;
/* With 4 or more samples, select those that have peer dispersion smaller
than 1.5x of the minimum dispersion */
if (filter->used > 4) {
for (i = 1, min_dispersion = filter->samples[0].peer_dispersion; i < filter->used; i++) {
if (min_dispersion > filter->samples[i].peer_dispersion)
min_dispersion = filter->samples[i].peer_dispersion;
}
for (i = j = 0; i < filter->used; i++) {
if (filter->samples[i].peer_dispersion <= 1.5 * min_dispersion)
selected[j++] = i;
}
} else {
j = 0;
}
if (j < 4) {
/* Select all samples */
for (j = 0; j < filter->used; j++)
selected[j] = j;
}
/* And sort their indices by offset */
tmp_sort_samples = filter->samples;
qsort(selected, j, sizeof (int), compare_samples);
/* Select samples closest to the median */
if (j > 2) {
from = j * (1.0 - filter->combine_ratio) / 2.0;
from = CLAMP(1, from, (j - 1) / 2);
} else {
from = 0;
}
to = j - from;
/* Mark unused samples and sort the rest by their time */
o = filter->used - filter->index - 1;
for (i = 0; i < from; i++)
selected[i] = -1;
for (; i < to; i++)
selected[i] = (selected[i] + o) % filter->used;
for (; i < filter->used; i++)
selected[i] = -1;
for (i = from; i < to; i++) {
j = selected[i];
selected[i] = -1;
while (j != -1 && selected[j] != j) {
k = selected[j];
selected[j] = j;
j = k;
}
}
for (i = j = 0, k = -1; i < filter->used; i++) {
if (selected[i] != -1)
selected[j++] = (selected[i] + filter->used - o) % filter->used;
}
assert(j > 0 && j <= filter->max_samples);
return j;
}
/* ================================================== */
static int
combine_selected_samples(SPF_Instance filter, int n, NTP_Sample *result)
{
double mean_peer_dispersion, mean_root_dispersion, mean_peer_delay, mean_root_delay;
double mean_x, mean_y, disp, var, prev_avg_var;
NTP_Sample *sample, *last_sample;
int i, dof;
last_sample = &filter->samples[filter->selected[n - 1]];
/* Prepare data */
for (i = 0; i < n; i++) {
sample = &filter->samples[filter->selected[i]];
filter->x_data[i] = UTI_DiffTimespecsToDouble(&sample->time, &last_sample->time);
filter->y_data[i] = sample->offset;
filter->w_data[i] = sample->peer_dispersion;
}
/* Calculate mean offset and interval since the last sample */
for (i = 0, mean_x = mean_y = 0.0; i < n; i++) {
mean_x += filter->x_data[i];
mean_y += filter->y_data[i];
}
mean_x /= n;
mean_y /= n;
if (n >= 4) {
double b0, b1, s2, sb0, sb1;
/* Set y axis to the mean sample time */
for (i = 0; i < n; i++)
filter->x_data[i] -= mean_x;
/* Make a linear fit and use the estimated standard deviation of the
intercept as dispersion */
RGR_WeightedRegression(filter->x_data, filter->y_data, filter->w_data, n,
&b0, &b1, &s2, &sb0, &sb1);
var = s2;
disp = sb0;
dof = n - 2;
} else if (n >= 2) {
for (i = 0, disp = 0.0; i < n; i++)
disp += (filter->y_data[i] - mean_y) * (filter->y_data[i] - mean_y);
var = disp / (n - 1);
disp = sqrt(var);
dof = n - 1;
} else {
var = filter->avg_var;
disp = sqrt(var);
dof = 1;
}
/* Avoid working with zero dispersion */
if (var < 1e-20) {
var = 1e-20;
disp = sqrt(var);
}
/* Drop the sample if the variance is larger than the maximum */
if (filter->max_var > 0.0 && var > filter->max_var) {
DEBUG_LOG("filter dispersion too large disp=%.9f max=%.9f",
sqrt(var), sqrt(filter->max_var));
return 0;
}
prev_avg_var = filter->avg_var;
/* Update the exponential moving average of the variance */
if (filter->avg_var_n > 50) {
filter->avg_var += dof / (dof + 50.0) * (var - filter->avg_var);
} else {
filter->avg_var = (filter->avg_var * filter->avg_var_n + var * dof) /
(dof + filter->avg_var_n);
if (filter->avg_var_n == 0)
prev_avg_var = filter->avg_var;
filter->avg_var_n += dof;
}
/* Use the long-term average of variance instead of the estimated value
unless it is significantly smaller in order to reduce the noise in
sourcestats weights */
if (var * dof / RGR_GetChi2Coef(dof) < prev_avg_var)
disp = sqrt(filter->avg_var) * disp / sqrt(var);
mean_peer_dispersion = mean_root_dispersion = mean_peer_delay = mean_root_delay = 0.0;
for (i = 0; i < n; i++) {
sample = &filter->samples[filter->selected[i]];
mean_peer_dispersion += sample->peer_dispersion;
mean_root_dispersion += sample->root_dispersion;
mean_peer_delay += sample->peer_delay;
mean_root_delay += sample->root_delay;
}
mean_peer_dispersion /= n;
mean_root_dispersion /= n;
mean_peer_delay /= n;
mean_root_delay /= n;
UTI_AddDoubleToTimespec(&last_sample->time, mean_x, &result->time);
result->offset = mean_y;
result->peer_dispersion = MAX(disp, mean_peer_dispersion);
result->root_dispersion = MAX(disp, mean_root_dispersion);
result->peer_delay = mean_peer_delay;
result->root_delay = mean_root_delay;
result->stratum = last_sample->stratum;
result->leap = last_sample->leap;
return 1;
}
/* ================================================== */
int
SPF_GetFilteredSample(SPF_Instance filter, NTP_Sample *sample)
{
int n;
n = select_samples(filter);
if (n < 1)
return 0;
if (!combine_selected_samples(filter, n, sample))
return 0;
SPF_DropSamples(filter);
return 1;
}
/* ================================================== */
void
SPF_SlewSamples(SPF_Instance filter, struct timespec *when, double dfreq, double doffset)
{
int i, first, last;
double delta_time;
if (filter->last < 0)
return;
/* Always slew the last sample as it may be returned even if no new
samples were accumulated */
if (filter->used > 0) {
first = 0;
last = filter->used - 1;
} else {
first = last = filter->last;
}
for (i = first; i <= last; i++) {
UTI_AdjustTimespec(&filter->samples[i].time, when, &filter->samples[i].time,
&delta_time, dfreq, doffset);
filter->samples[i].offset -= delta_time;
}
}
/* ================================================== */
void
SPF_AddDispersion(SPF_Instance filter, double dispersion)
{
int i;
for (i = 0; i < filter->used; i++) {
filter->samples[i].peer_dispersion += dispersion;
filter->samples[i].root_dispersion += dispersion;
}
}