a4c277b07f
Change-Id: I9ba1caa4862bdf9ffc9c0e637bd69cce91fd8468 Reviewed-on: https://skia-review.googlesource.com/c/168740 Reviewed-by: Herb Derby <herb@google.com> Commit-Queue: Mike Klein <mtklein@google.com>
80 lines
2.2 KiB
C
80 lines
2.2 KiB
C
/*
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* Copyright 2015 Google Inc.
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*
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* Use of this source code is governed by a BSD-style license that can be
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* found in the LICENSE file.
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*/
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#ifndef Stats_DEFINED
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#define Stats_DEFINED
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#include "SkFloatingPoint.h"
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#include "SkString.h"
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#include "SkTSort.h"
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#ifdef SK_BUILD_FOR_WIN
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static const char* kBars[] = { ".", "o", "O" };
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#else
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static const char* kBars[] = { "▁", "▂", "▃", "▄", "▅", "▆", "▇", "█" };
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#endif
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struct Stats {
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Stats(const SkTArray<double>& samples, bool want_plot) {
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int n = samples.count();
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if (!n) {
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min = max = mean = var = median = 0;
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return;
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}
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min = samples[0];
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max = samples[0];
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for (int i = 0; i < n; i++) {
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if (samples[i] < min) { min = samples[i]; }
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if (samples[i] > max) { max = samples[i]; }
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}
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double sum = 0.0;
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for (int i = 0 ; i < n; i++) {
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sum += samples[i];
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}
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mean = sum / n;
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double err = 0.0;
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for (int i = 0 ; i < n; i++) {
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err += (samples[i] - mean) * (samples[i] - mean);
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}
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var = sk_ieee_double_divide(err, n-1);
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SkAutoTMalloc<double> sorted(n);
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memcpy(sorted.get(), samples.begin(), n * sizeof(double));
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SkTQSort(sorted.get(), sorted.get() + n - 1);
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median = sorted[n/2];
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// Normalize samples to [min, max] in as many quanta as we have distinct bars to print.
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for (int i = 0; want_plot && i < n; i++) {
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if (min == max) {
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// All samples are the same value. Don't divide by zero.
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plot.append(kBars[0]);
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continue;
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}
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double s = samples[i];
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s -= min;
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s /= (max - min);
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s *= (SK_ARRAY_COUNT(kBars) - 1);
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const size_t bar = (size_t)(s + 0.5);
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SkASSERT_RELEASE(bar < SK_ARRAY_COUNT(kBars));
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plot.append(kBars[bar]);
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}
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}
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double min;
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double max;
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double mean; // Estimate of population mean.
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double var; // Estimate of population variance.
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double median;
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SkString plot; // A single-line bar chart (_not_ histogram) of the samples.
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};
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#endif//Stats_DEFINED
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