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/*
* Copyright © 2006 Red Hat, Inc.
*
* Permission to use, copy, modify, distribute, and sell this software
* and its documentation for any purpose is hereby granted without
* fee, provided that the above copyright notice appear in all copies
* and that both that copyright notice and this permission notice
* appear in supporting documentation, and that the name of
* the authors not be used in advertising or publicity pertaining to
* distribution of the software without specific, written prior
* permission. The authors make no representations about the
* suitability of this software for any purpose. It is provided "as
* is" without express or implied warranty.
*
* THE AUTHORS DISCLAIM ALL WARRANTIES WITH REGARD TO THIS
* SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
* FITNESS, IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY SPECIAL,
* INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER
* RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION
* OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR
* IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
*
* Authors: Carl Worth <cworth@cworth.org>
*/
#include "cairo-stats.h"
static int
_cairo_perf_ticks_cmp (const void *_a, const void *_b)
{
const cairo_perf_ticks_t *a = _a;
const cairo_perf_ticks_t *b = _b;
if (*a > *b)
return 1;
if (*a < *b)
return -1;
return 0;
}
void
_cairo_stats_compute (cairo_stats_t *stats,
cairo_perf_ticks_t *values,
int num_values)
{
int i;
double sum, mean, delta, q1, q3, iqr;
double outlier_min, outlier_max;
int min_valid, num_valid;
/* First, identify any outliers, using the definition of "mild
* outliers" from:
*
* http://en.wikipedia.org/wiki/Outliers
*
* Which is that outliers are any values less than Q1 - 1.5 * IQR
* or greater than Q3 + 1.5 * IQR where Q1 and Q3 are the first
* and third quartiles and IQR is the inter-quartile range (Q3 -
* Q1).
*/
qsort (values, num_values,
sizeof (cairo_perf_ticks_t), _cairo_perf_ticks_cmp);
q1 = values[(1*num_values)/4];
q3 = values[(3*num_values)/4];
iqr = q3 - q1;
outlier_min = q1 - 1.5 * iqr;
outlier_max = q3 + 1.5 * iqr;
min_valid = 0;
while (min_valid < num_values && values[min_valid] < outlier_min)
min_valid++;
i = min_valid;
num_valid = 0;
while (i + num_valid < num_values && values[i+num_valid] <= outlier_max)
num_valid++;
stats->iterations = num_valid;
stats->min_ticks = values[min_valid];
sum = 0.0;
for (i = min_valid; i < min_valid + num_valid; i++) {
sum += values[i];
if (values[i] < stats->min_ticks)
stats->min_ticks = values[i];
}
mean = sum / num_valid;
stats->median_ticks = values[min_valid + num_valid / 2];
sum = 0.0;
for (i = min_valid; i < min_valid + num_valid; i++) {
delta = values[i] - mean;
sum += delta * delta;
}
/* Let's use a std. deviation normalized to the mean for easier
* comparison. */
stats->std_dev = sqrt(sum / num_valid) / mean;
}
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