| /* |
| * 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 |