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/*
* Copyright 2015 Google Inc.
*
* Use of this source code is governed by a BSD-style license that can be
* found in the LICENSE file.
*/
#ifndef Stats_DEFINED
#define Stats_DEFINED
#include "SkString.h"
#include "SkTSort.h"
#ifdef SK_BUILD_FOR_WIN
static const char* kBars[] = { ".", "o", "O" };
#else
static const char* kBars[] = { "▁", "▂", "▃", "▄", "▅", "▆", "▇", "█" };
#endif
struct Stats {
Stats(const SkTArray<double>& samples) {
int n = samples.count();
if (!n) {
min = max = mean = var = median = 0;
return;
}
min = samples[0];
max = samples[0];
for (int i = 0; i < n; i++) {
if (samples[i] < min) { min = samples[i]; }
if (samples[i] > max) { max = samples[i]; }
}
double sum = 0.0;
for (int i = 0 ; i < n; i++) {
sum += samples[i];
}
mean = sum / n;
double err = 0.0;
for (int i = 0 ; i < n; i++) {
err += (samples[i] - mean) * (samples[i] - mean);
}
var = err / (n-1);
SkAutoTMalloc<double> sorted(n);
memcpy(sorted.get(), samples.begin(), n * sizeof(double));
SkTQSort(sorted.get(), sorted.get() + n - 1);
median = sorted[n/2];
// Normalize samples to [min, max] in as many quanta as we have distinct bars to print.
for (int i = 0; i < n; i++) {
if (min == max) {
// All samples are the same value. Don't divide by zero.
plot.append(kBars[0]);
continue;
}
double s = samples[i];
s -= min;
s /= (max - min);
s *= (SK_ARRAY_COUNT(kBars) - 1);
const size_t bar = (size_t)(s + 0.5);
SkASSERT_RELEASE(bar < SK_ARRAY_COUNT(kBars));
plot.append(kBars[bar]);
}
}
double min;
double max;
double mean; // Estimate of population mean.
double var; // Estimate of population variance.
double median;
SkString plot; // A single-line bar chart (_not_ histogram) of the samples.
};
#endif//Stats_DEFINED
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