/* * 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 <algorithm> #include <vector> #include "include/core/SkString.h" #include "include/private/SkFloatingPoint.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, bool want_plot) { 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 = sk_ieee_double_divide(err, n-1); std::vector<double> sorted(samples.begin(), samples.end()); std::sort(sorted.begin(), sorted.end()); median = sorted[n/2]; // Normalize samples to [min, max] in as many quanta as we have distinct bars to print. for (int i = 0; want_plot && 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