/*

chronyd/chronyc - Programs for keeping computer clocks accurate.

**********************************************************************

* Copyright (C) Richard P. Curnow 1997-2003

* Copyright (C) Miroslav Lichvar 2011-2014

*

* 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.

*

**********************************************************************

=======================================================================

This file contains the routines that do the statistical

analysis on the samples obtained from the sources,

to determined frequencies and error bounds. */

#include "config.h"

#include "sysincl.h"

#include "sourcestats.h"

#include "memory.h"

#include "regress.h"

#include "util.h"

#include "conf.h"

#include "logging.h"

#include "local.h"

/* ================================================== */

/* Define the maxumum number of samples that we want

to store per source */

#define MAX_SAMPLES 64

/* User defined maximum and minimum number of samples */

int max_samples;

int min_samples;

/* This is the assumed worst case bound on an unknown frequency,

2000ppm, which would be pretty bad */

#define WORST_CASE_FREQ_BOUND (2000.0/1.0e6)

/* The minimum allowed skew */

#define MIN_SKEW 1.0e-12

/* ================================================== */

static LOG_FileID logfileid;

/* ================================================== */

/* This data structure is used to hold the history of data from the

source */

struct SST_Stats_Record {

};

/* ================================================== */

static void find_min_delay_sample(SST_Stats inst);

static int get_buf_index(SST_Stats inst, int i);

/* ================================================== */

void

SST_Initialise(void)

{

logfileid = CNF_GetLogStatistics() ? LOG_FileOpen("statistics",

" Date (UTC) Time IP Address Std dev'n Est offset Offset sd Diff freq Est skew Stress Ns Bs Nr")

: -1;

max_samples = CNF_GetMaxSamples();

min_samples = CNF_GetMinSamples();

}

/* ================================================== */

void

SST_Finalise(void)

{

}

/* ================================================== */

/* This function creates a new instance of the statistics handler */

SST_Stats

SST_CreateInstance(uint32_t refid, IPAddr *addr)

{

SST_Stats inst;

inst = MallocNew(struct SST_Stats_Record);

inst->refid = refid;

inst->ip_addr = addr;

SST_ResetInstance(inst);

return inst;

}

/* ================================================== */

/* This function deletes an instance of the statistics handler. */

void

SST_DeleteInstance(SST_Stats inst)

{

Free(inst);

}

/* ================================================== */

void

SST_ResetInstance(SST_Stats inst)

{

inst->n_samples = 0;

inst->runs_samples = 0;

inst->last_sample = 0;

inst->regression_ok = 0;

inst->best_single_sample = 0;

inst->min_delay_sample = 0;

inst->estimated_frequency = 0;

inst->skew = 2000.0e-6;

inst->skew_dirn = SST_Skew_Nochange;

inst->estimated_offset = 0.0;

inst->estimated_offset_sd = 86400.0; /* Assume it's at least within a day! */

inst->offset_time.tv_sec = 0;

inst->offset_time.tv_usec = 0;

inst->variance = 16.0;

inst->nruns = 0;

}

/* ================================================== */

/* This function is called to prune the register down when it is full.

For now, just discard the oldest sample. */

static void

prune_register(SST_Stats inst, int new_oldest)

{

if (!new_oldest)

return;

assert(inst->n_samples >= new_oldest);

inst->n_samples -= new_oldest;

inst->runs_samples += new_oldest;

if (inst->runs_samples > inst->n_samples * (REGRESS_RUNS_RATIO - 1))

inst->runs_samples = inst->n_samples * (REGRESS_RUNS_RATIO - 1);

assert(inst->n_samples + inst->runs_samples <= MAX_SAMPLES * REGRESS_RUNS_RATIO);

find_min_delay_sample(inst);

}

/* ================================================== */

void

SST_AccumulateSample(SST_Stats inst, struct timeval *sample_time,

int stratum)

{

int n, m;

/* Make room for the new sample */

if (inst->n_samples > 0 &&

(inst->n_samples == MAX_SAMPLES || inst->n_samples == max_samples)) {

prune_register(inst, 1);

}

/* Make sure it's newer than the last sample */

if (inst->n_samples &&

UTI_CompareTimevals(&inst->sample_times[inst->last_sample], sample_time) >= 0) {

LOG(LOGS_WARN, LOGF_SourceStats, "Out of order sample detected, discarding history for %s",

inst->ip_addr ? UTI_IPToString(inst->ip_addr) : UTI_RefidToString(inst->refid));

SST_ResetInstance(inst);

}

n = inst->last_sample = (inst->last_sample + 1) %

(MAX_SAMPLES * REGRESS_RUNS_RATIO);

m = n % MAX_SAMPLES;

inst->sample_times[n] = *sample_time;

inst->offsets[n] = offset;

inst->orig_offsets[m] = offset;

inst->peer_delays[m] = peer_delay;

inst->peer_dispersions[m] = peer_dispersion;

inst->root_delays[m] = root_delay;

inst->root_dispersions[m] = root_dispersion;

inst->strata[m] = stratum;

if (!inst->n_samples || inst->peer_delays[m] < inst->peer_delays[inst->min_delay_sample])

inst->min_delay_sample = m;

++inst->n_samples;

}

/* ================================================== */

/* Return index of the i-th sample in the sample_times and offset buffers,

i can be negative down to -runs_samples */

static int

get_runsbuf_index(SST_Stats inst, int i)

{

return (unsigned int)(inst->last_sample + 2 * MAX_SAMPLES * REGRESS_RUNS_RATIO -

inst->n_samples + i + 1) % (MAX_SAMPLES * REGRESS_RUNS_RATIO);

}

/* ================================================== */

/* Return index of the i-th sample in the other buffers */

static int

get_buf_index(SST_Stats inst, int i)

{

return (unsigned int)(inst->last_sample + MAX_SAMPLES * REGRESS_RUNS_RATIO -

inst->n_samples + i + 1) % MAX_SAMPLES;

}

/* ================================================== */

/* This function is used by both the regression routines to find the

time interval between each historical sample and the most recent

one */

static void

convert_to_intervals(SST_Stats inst, double *times_back)

{

struct timeval *newest_tv;

int i;

newest_tv = &(inst->sample_times[inst->last_sample]);

for (i = -inst->runs_samples; i < inst->n_samples; i++) {

/* The entries in times_back[] should end up negative */

UTI_DiffTimevalsToDouble(&times_back[i],

&inst->sample_times[get_runsbuf_index(inst, i)], newest_tv);

}

}

/* ================================================== */

static void

find_best_sample_index(SST_Stats inst, double *times_back)

{

/* With the value of skew that has been computed, see which of the

samples offers the tightest bound on root distance */

double root_distance, best_root_distance;

double elapsed;

int i, j, best_index;

if (!inst->n_samples)

return;

best_index = -1;

best_root_distance = DBL_MAX;

for (i = 0; i < inst->n_samples; i++) {

j = get_buf_index(inst, i);

elapsed = -times_back[i];

assert(elapsed >= 0.0);

root_distance = inst->root_dispersions[j] + elapsed * inst->skew + 0.5 * inst->root_delays[j];

if (root_distance < best_root_distance) {

best_root_distance = root_distance;

best_index = i;

}

}

assert(best_index >= 0);

inst->best_single_sample = best_index;

}

/* ================================================== */

static void

find_min_delay_sample(SST_Stats inst)

{

int i, index;

inst->min_delay_sample = get_buf_index(inst, 0);

for (i = 1; i < inst->n_samples; i++) {

index = get_buf_index(inst, i);

if (inst->peer_delays[index] < inst->peer_delays[inst->min_delay_sample])

inst->min_delay_sample = index;

}

}

/* ================================================== */

/* This defines the assumed ratio between the standard deviation of

the samples and the peer distance as measured from the round trip

time. E.g. a value of 4 means that we think the standard deviation

is four times the fluctuation of the peer distance */

#define SD_TO_DIST_RATIO 1.0

/* ================================================== */

/* This function runs the linear regression operation on the data. It

finds the set of most recent samples that give the tightest

confidence interval for the frequency, and truncates the register

down to that number of samples */

void

SST_DoNewRegression(SST_Stats inst)

{

double times_back[MAX_SAMPLES * REGRESS_RUNS_RATIO];

double offsets[MAX_SAMPLES * REGRESS_RUNS_RATIO];

double peer_distances[MAX_SAMPLES];

double weights[MAX_SAMPLES];

int degrees_of_freedom;

int best_start, times_back_start;

double est_intercept, est_slope, est_var, est_intercept_sd, est_slope_sd;

int i, j, nruns;

double min_distance, mean_distance;

double sd_weight, sd;

double old_skew, old_freq, stress;

convert_to_intervals(inst, times_back + inst->runs_samples);

if (inst->n_samples > 0) {

for (i = -inst->runs_samples; i < inst->n_samples; i++) {

offsets[i + inst->runs_samples] = inst->offsets[get_runsbuf_index(inst, i)];

}

for (i = 0, mean_distance = 0.0, min_distance = DBL_MAX; i < inst->n_samples; i++) {

j = get_buf_index(inst, i);

peer_distances[i] = 0.5 * inst->peer_delays[j] + inst->peer_dispersions[j];

mean_distance += peer_distances[i];

if (peer_distances[i] < min_distance) {

min_distance = peer_distances[i];

}

}

mean_distance /= inst->n_samples;

/* And now, work out the weight vector */

sd = mean_distance - min_distance;

if (sd > min_distance || sd <= 0.0)

sd = min_distance;

for (i=0; i<inst->n_samples; i++) {

sd_weight = 1.0 + SD_TO_DIST_RATIO * (peer_distances[i] - min_distance) / sd;

weights[i] = sd_weight * sd_weight;

}

}

inst->regression_ok = RGR_FindBestRegression(times_back + inst->runs_samples,

offsets + inst->runs_samples, weights,

inst->n_samples, inst->runs_samples,

min_samples,

&est_intercept, &est_slope, &est_var,

&est_intercept_sd, &est_slope_sd,

&best_start, &nruns, &degrees_of_freedom);

if (inst->regression_ok) {

old_skew = inst->skew;

old_freq = inst->estimated_frequency;

inst->estimated_frequency = est_slope;

inst->skew = est_slope_sd * RGR_GetTCoef(degrees_of_freedom);

inst->estimated_offset = est_intercept;

inst->offset_time = inst->sample_times[inst->last_sample];

inst->estimated_offset_sd = est_intercept_sd;

inst->variance = est_var;

inst->nruns = nruns;

if (inst->skew < MIN_SKEW)

inst->skew = MIN_SKEW;

stress = fabs(old_freq - inst->estimated_frequency) / old_skew;

if (best_start > 0) {

/* If we are throwing old data away, retain the current

assumptions about the skew */

inst->skew_dirn = SST_Skew_Nochange;

} else {

if (inst->skew < old_skew) {

inst->skew_dirn = SST_Skew_Decrease;

} else {

inst->skew_dirn = SST_Skew_Increase;

}

}

if (logfileid != -1) {

LOG_FileWrite(logfileid, "%s %-15s %10.3e %10.3e %10.3e %10.3e %10.3e %7.1e %3d %3d %3d",

UTI_TimeToLogForm(inst->offset_time.tv_sec),

inst->ip_addr ? UTI_IPToString(inst->ip_addr) : UTI_RefidToString(inst->refid),

sqrt(inst->variance),

inst->estimated_offset,

inst->estimated_offset_sd,

inst->estimated_frequency,

inst->skew,

stress,

inst->n_samples,

best_start, nruns);

}

times_back_start = inst->runs_samples + best_start;

prune_register(inst, best_start);

} else {

inst->estimated_frequency = 0.0;

inst->skew = WORST_CASE_FREQ_BOUND;

times_back_start = 0;

}

find_best_sample_index(inst, times_back + times_back_start);

}

/* ================================================== */

/* Return the assumed worst case range of values that this source's

frequency lies within. Frequency is defined as the amount of time

the local clock gains relative to the source per unit local clock

time. */

void

SST_GetFrequencyRange(SST_Stats inst,

double *lo, double *hi)

{

double freq, skew;

freq = inst->estimated_frequency;

skew = inst->skew;

*lo = freq - skew;

*hi = freq + skew;

/* This function is currently used only to determine the values of delta

and epsilon in the ntp_core module. Limit the skew to a reasonable maximum

to avoid failing the dispersion test too easily. */

if (skew > WORST_CASE_FREQ_BOUND) {

*lo = -WORST_CASE_FREQ_BOUND;

*hi = WORST_CASE_FREQ_BOUND;

}

}

/* ================================================== */

void

SST_GetSelectionData(SST_Stats inst, struct timeval *now,

double *variance, int *select_ok)

{

double offset, sample_elapsed;

int i, j;

i = get_runsbuf_index(inst, inst->best_single_sample);

j = get_buf_index(inst, inst->best_single_sample);

*stratum = inst->strata[get_buf_index(inst, inst->n_samples - 1)];

*variance = inst->variance;

UTI_DiffTimevalsToDouble(&sample_elapsed, now, &inst->sample_times[i]);

offset = inst->offsets[i] + sample_elapsed * inst->estimated_frequency;

*root_distance = 0.5 * inst->root_delays[j] +

inst->root_dispersions[j] + sample_elapsed * inst->skew;

*offset_lo_limit = offset - *root_distance;

*offset_hi_limit = offset + *root_distance;

#if 0

double average_offset, elapsed;

int average_ok;

/* average_ok ignored for now */

UTI_DiffTimevalsToDouble(&elapsed, now, &(inst->offset_time));

average_offset = inst->estimated_offset + inst->estimated_frequency * elapsed;

if (fabs(average_offset - offset) <=

inst->peer_dispersions[j] + 0.5 * inst->peer_delays[j]) {

average_ok = 1;

} else {

average_ok = 0;

}

#endif

*select_ok = inst->regression_ok;

DEBUG_LOG(LOGF_SourceStats, "n=%d off=%f dist=%f var=%f selok=%d",

inst->n_samples, offset, *root_distance, *variance, *select_ok);

}

/* ================================================== */

void

SST_GetTrackingData(SST_Stats inst, struct timeval *ref_time,

double *average_offset, double *offset_sd,

double *frequency, double *skew,

double *root_delay, double *root_dispersion)

{

int i, j;

double elapsed_sample;

assert(inst->n_samples > 0);

i = get_runsbuf_index(inst, inst->best_single_sample);

j = get_buf_index(inst, inst->best_single_sample);

*ref_time = inst->offset_time;

*average_offset = inst->estimated_offset;

*offset_sd = inst->estimated_offset_sd;

*frequency = inst->estimated_frequency;

*skew = inst->skew;

*root_delay = inst->root_delays[j];

UTI_DiffTimevalsToDouble(&elapsed_sample, &inst->offset_time, &inst->sample_times[i]);

*root_dispersion = inst->root_dispersions[j] + inst->skew * elapsed_sample;

DEBUG_LOG(LOGF_SourceStats, "n=%d freq=%f (%.3fppm) skew=%f (%.3fppm) avoff=%f offsd=%f disp=%f",

inst->n_samples, *frequency, 1.0e6* *frequency, *skew, 1.0e6* *skew, *average_offset, *offset_sd, *root_dispersion);

}

/* ================================================== */

void

SST_SlewSamples(SST_Stats inst, struct timeval *when, double dfreq, double doffset)

{

int m, i;

double delta_time;

struct timeval *sample, prev;

double prev_offset, prev_freq;

if (!inst->n_samples)

return;

for (m = -inst->runs_samples; m < inst->n_samples; m++) {

i = get_runsbuf_index(inst, m);

sample = &(inst->sample_times[i]);

prev = *sample;

UTI_AdjustTimeval(sample, when, sample, &delta_time, dfreq, doffset);

prev_offset = inst->offsets[i];

inst->offsets[i] += delta_time;

DEBUG_LOG(LOGF_SourceStats, "i=%d old_st=[%s] new_st=[%s] old_off=%f new_off=%f",

i, UTI_TimevalToString(&prev), UTI_TimevalToString(sample),

prev_offset, inst->offsets[i]);

}

/* Do a half-baked update to the regression estimates */

prev = inst->offset_time;

prev_offset = inst->estimated_offset;

prev_freq = inst->estimated_frequency;

UTI_AdjustTimeval(&(inst->offset_time), when, &(inst->offset_time),

&delta_time, dfreq, doffset);

inst->estimated_offset += delta_time;

inst->estimated_frequency -= dfreq;

DEBUG_LOG(LOGF_SourceStats, "old_off_time=[%s] new=[%s] old_off=%f new_off=%f old_freq=%.3fppm new_freq=%.3fppm",

UTI_TimevalToString(&prev), UTI_TimevalToString(&(inst->offset_time)),

prev_offset, inst->estimated_offset,

1.0e6*prev_freq, 1.0e6*inst->estimated_frequency);

}

/* ================================================== */

void

SST_AddDispersion(SST_Stats inst, double dispersion)

{

int m, i;

for (m = 0; m < inst->n_samples; m++) {

i = get_buf_index(inst, m);

inst->root_dispersions[i] += dispersion;

inst->peer_dispersions[i] += dispersion;

}

}

/* ================================================== */

double

SST_PredictOffset(SST_Stats inst, struct timeval *when)

{

double elapsed;

if (inst->n_samples < 3) {

/* We don't have any useful statistics, and presumably the poll

interval is minimal. We can't do any useful prediction other

than use the latest sample or zero if we don't have any samples */

if (inst->n_samples > 0) {

return inst->offsets[inst->last_sample];

} else {

return 0.0;

}

} else {

UTI_DiffTimevalsToDouble(&elapsed, when, &inst->offset_time);

return inst->estimated_offset + elapsed * inst->estimated_frequency;

}

}

/* ================================================== */

double

SST_MinRoundTripDelay(SST_Stats inst)

{

if (!inst->n_samples)

return DBL_MAX;

return inst->peer_delays[inst->min_delay_sample];

}

/* ================================================== */

int

SST_IsGoodSample(SST_Stats inst, double offset, double delay,

double max_delay_dev_ratio, double clock_error, struct timeval *when)

{

double elapsed, allowed_increase, delay_increase;

if (inst->n_samples < 3)

return 1;

UTI_DiffTimevalsToDouble(&elapsed, when, &inst->offset_time);

/* Require that the ratio of the increase in delay from the minimum to the

standard deviation is less than max_delay_dev_ratio. In the allowed

increase in delay include also skew and clock_error. */

allowed_increase = sqrt(inst->variance) * max_delay_dev_ratio +

elapsed * (inst->skew + clock_error);

delay_increase = (delay - SST_MinRoundTripDelay(inst)) / 2.0;

if (delay_increase < allowed_increase)

return 1;

offset -= inst->estimated_offset + elapsed * inst->estimated_frequency;

/* Before we decide to drop the sample, make sure the difference between

measured offset and predicted offset is not significantly larger than

the increase in delay */

if (fabs(offset) - delay_increase > allowed_increase)

return 1;

DEBUG_LOG(LOGF_SourceStats, "Bad sample: offset=%f delay=%f incr_delay=%f allowed=%f",

offset, delay, allowed_increase, delay_increase);

return 0;

}

/* ================================================== */

/* This is used to save the register to a file, so that we can reload

it after restarting the daemon */

void

SST_SaveToFile(SST_Stats inst, FILE *out)

{

int m, i, j;

fprintf(out, "%d\n", inst->n_samples);

for(m = 0; m < inst->n_samples; m++) {

i = get_runsbuf_index(inst, m);

j = get_buf_index(inst, m);

fprintf(out, "%08lx %08lx %.6e %.6e %.6e %.6e %.6e %.6e %.6e %d\n",

(unsigned long) inst->sample_times[i].tv_sec,

(unsigned long) inst->sample_times[i].tv_usec,

inst->offsets[i],

inst->orig_offsets[j],

inst->peer_delays[j],

inst->peer_dispersions[j],

inst->root_delays[j],

inst->root_dispersions[j],

1.0, /* used to be inst->weights[i] */

inst->strata[j]);

}

}

/* ================================================== */

/* This is used to reload samples from a file */

int

SST_LoadFromFile(SST_Stats inst, FILE *in)

{

int i, line_number;

char line[1024];

unsigned long sec, usec;

double weight;

assert(!inst->n_samples);

if (fgets(line, sizeof(line), in) &&

sscanf(line, "%d", &inst->n_samples) == 1 &&

inst->n_samples > 0 && inst->n_samples <= MAX_SAMPLES) {

line_number = 2;

for (i=0; i<inst->n_samples; i++) {

if (!fgets(line, sizeof(line), in) ||

(sscanf(line, "%lx%lx%lf%lf%lf%lf%lf%lf%lf%d\n",

&(sec), &(usec),

&(inst->offsets[i]),

&(inst->orig_offsets[i]),

&(inst->peer_delays[i]),

&(inst->peer_dispersions[i]),

&(inst->root_delays[i]),

&(inst->root_dispersions[i]),

&weight, /* not used anymore */

&(inst->strata[i])) != 10)) {

/* This is the branch taken if the read FAILED */

LOG(LOGS_WARN, LOGF_SourceStats, "Failed to read data from line %d of dump file", line_number);

inst->n_samples = 0; /* Load abandoned if any sign of corruption */

return 0;

} else {

/* This is the branch taken if the read is SUCCESSFUL */

inst->sample_times[i].tv_sec = sec;

inst->sample_times[i].tv_usec = usec;

line_number++;

}

}

} else {

LOG(LOGS_WARN, LOGF_SourceStats, "Could not read number of samples from dump file");

inst->n_samples = 0; /* Load abandoned if any sign of corruption */

return 0;

}

inst->last_sample = inst->n_samples - 1;

inst->runs_samples = 0;

find_min_delay_sample(inst);

return 1;

}

/* ================================================== */

void

SST_DoSourceReport(SST_Stats inst, RPT_SourceReport *report, struct timeval *now)

{

int i, j;

struct timeval ago;

if (inst->n_samples > 0) {

i = get_runsbuf_index(inst, inst->n_samples - 1);

j = get_buf_index(inst, inst->n_samples - 1);

report->orig_latest_meas = inst->orig_offsets[j];

report->latest_meas = inst->offsets[i];

report->latest_meas_err = 0.5*inst->root_delays[j] + inst->root_dispersions[j];

report->stratum = inst->strata[j];

UTI_DiffTimevals(&ago, now, &inst->sample_times[i]);

report->latest_meas_ago = ago.tv_sec;

} else {

report->latest_meas_ago = 86400 * 365 * 10;

report->orig_latest_meas = 0;

report->latest_meas = 0;

report->latest_meas_err = 0;

report->stratum = 0;

}

}

/* ================================================== */

SST_Skew_Direction SST_LastSkewChange(SST_Stats inst)

{

return inst->skew_dirn;

}

/* ================================================== */

int

SST_Samples(SST_Stats inst)

{

return inst->n_samples;

}

/* ================================================== */

void

SST_DoSourcestatsReport(SST_Stats inst, RPT_SourcestatsReport *report, struct timeval *now)

{

double dspan;

double elapsed, sample_elapsed;

int li, lj, bi, bj;

report->n_samples = inst->n_samples;

report->n_runs = inst->nruns;

if (inst->n_samples > 1) {

li = get_runsbuf_index(inst, inst->n_samples - 1);

lj = get_buf_index(inst, inst->n_samples - 1);

UTI_DiffTimevalsToDouble(&dspan, &inst->sample_times[li],

&inst->sample_times[get_runsbuf_index(inst, 0)]);

report->span_seconds = (unsigned long) (dspan + 0.5);

if (inst->n_samples > 3) {

UTI_DiffTimevalsToDouble(&elapsed, now, &inst->offset_time);

bi = get_runsbuf_index(inst, inst->best_single_sample);

bj = get_buf_index(inst, inst->best_single_sample);

UTI_DiffTimevalsToDouble(&sample_elapsed, now, &inst->sample_times[bi]);

report->est_offset = inst->estimated_offset + elapsed * inst->estimated_frequency;

report->est_offset_err = (inst->estimated_offset_sd +

sample_elapsed * inst->skew +

(0.5*inst->root_delays[bj] + inst->root_dispersions[bj]));

} else {

report->est_offset = inst->offsets[li];

report->est_offset_err = 0.5*inst->root_delays[lj] + inst->root_dispersions[lj];

}

} else {

report->span_seconds = 0;

report->est_offset = 0;

report->est_offset_err = 0;

}

report->resid_freq_ppm = 1.0e6 * inst->estimated_frequency;

report->skew_ppm = 1.0e6 * inst->skew;

report->sd = sqrt(inst->variance);

}

/* ================================================== */