diff options
| author | Katelyn Gadd <kg@luminance.org> | 2020-02-26 05:24:10 +0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2020-02-26 05:24:10 +0300 |
| commit | 5c8da9e28456a8fca32bf4f5104d85c467e002bf (patch) | |
| tree | 57b8e2016b8c54a62b2b2de893d12ab404184ce7 /sdks | |
| parent | 3cba804069fc27f1cfdb944a64caa409039705fc (diff) | |
Add basic set of standalone benchmarks for wasm (#18977)
Adds a basic set of standalone benchmarks from multiple sources, along with simple infrastructure for running them in mono, netcore and node.js wasm. A couple of them also have original JS versions you can run from a JS shell.
Diffstat (limited to 'sdks')
25 files changed, 2767 insertions, 0 deletions
diff --git a/sdks/wasm/standalone-benchmarks/.gitignore b/sdks/wasm/standalone-benchmarks/.gitignore new file mode 100755 index 00000000000..cbc0889bdd0 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/.gitignore @@ -0,0 +1,8 @@ +.vs +obj +bin +*.log +wasm +!./wasm/BLANK +wasm-aot +!./wasm-aot/BLANK
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/Compat.cs b/sdks/wasm/standalone-benchmarks/Compat.cs new file mode 100755 index 00000000000..44a5dddc359 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/Compat.cs @@ -0,0 +1,65 @@ +using System; +using System.Collections.Generic; +using System.Text; +using System.Text.RegularExpressions; + +namespace Jetstream { + public static class Compat { + public static readonly Random Random = new Random (); + + public static double random () { + return Random.NextDouble (); + } + + public static void push<T> (this List<T> list, T item) { + list.Add (item); + } + + public static T shift<T> (this List<T> list) { + var result = list[0]; + list.RemoveAt (0); + return result; + } + + public static string slice (this string s, int startIndex) { + return s.Substring (startIndex); + } + + public static string slice (this string s, int startIndex, int endIndex) { + return s.Substring (startIndex, endIndex - startIndex); + } + + public static int codePointAt (this string s, int index) { + return char.ConvertToUtf32 (s, index); + } + + public static Match match (this string s, Regex regex) { + return regex.Match (s); + } + + public static T[] slice<T> (this T[] array, int begin, int end) { + if (begin < 0) + throw new ArgumentOutOfRangeException ("begin"); + else if (end < 0) + throw new ArgumentOutOfRangeException ("end"); + + if (end > array.Length) + end = array.Length; + + int count = end - begin; + var result = new T[count]; + for (int i = 0; i < count; i++) + result[i] = array[begin + i]; + + return result; + } + + public static string join<T> (this IEnumerable<T> values, string separator) { + return string.Join (separator, values); + } + + public static double log1p (double v) { + return Math.Log (v + 1); + } + } +} diff --git a/sdks/wasm/standalone-benchmarks/Program.cs b/sdks/wasm/standalone-benchmarks/Program.cs new file mode 100755 index 00000000000..3bf3f89db4a --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/Program.cs @@ -0,0 +1,51 @@ +using System; +using System.Diagnostics; +using System.Linq; + +class Program { + static void Main () { + const int iterations = Benchmark.IterationCount, + warming_iterations = Benchmark.WarmingIterationCount; + + WakeUp (); + + Console.WriteLine ($">>> Warming with {warming_iterations} iterations..."); + + var b = new Benchmark (); + var timings = new TimeSpan[iterations]; + + for (var i = 0; i < warming_iterations; i++) + b.runIteration (); + + b.reset (); + + Console.WriteLine ($">>> Running {iterations} iterations..."); + + var sw = new Stopwatch (); + for (int i = 0; i < iterations; i++) { + sw.Restart (); + b.Step (); + timings[i] = sw.Elapsed; + } + + Console.WriteLine ($">>> Elapsed {timings.Sum (t => t.TotalMilliseconds)}ms"); + Console.WriteLine ($">>> ms/iter avg = {timings.Average (t => t.TotalMilliseconds)}"); + Console.WriteLine ($">>> min = {timings.Min (t => t.TotalMilliseconds)}"); + Console.WriteLine ($">>> max = {timings.Max (t => t.TotalMilliseconds)}"); + + if (Debugger.IsAttached) { + Console.WriteLine (">>> Press enter to exit."); + Console.ReadLine (); + } + } + + static void WakeUp () { + } +} + +public partial class Benchmark { + public void Step () { + for (int i = 0; i < InnerIterationCount; i++) + runIteration (); + } +}
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/README.md b/sdks/wasm/standalone-benchmarks/README.md new file mode 100755 index 00000000000..2a92cd16896 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/README.md @@ -0,0 +1,29 @@ +# WASM standalone benchmarks
+
+This folder contains stand-alone benchmarks from various sources. Each folder contains one or more .cs files for the benchmark, and if the benchmark was ported from JavaScript the source benchmark is in the folder as well in JS form.
+
+# Running benchmarks
+
+All commands should be run from within the standalone-benchmarks directory.
+
+## .NET Core
+```dotnet run --project benchmarkname``` to build & run a benchmark using .NET Core.
+
+## Mono
+Use ```./run-benchmark-mono.sh benchmarkname``` to automatically build, package and run the benchmark, or manually:
+
+```dotnet build benchmarkname``` to build the debug-mode assembly for the benchmark, then:
+
+```mono benchmarkname/bin/Debug/netcoreapp2.1/benchmarkname.dll``` to run the benchmark in Mono.
+
+Use ```./run-benchmark-mono-aot.sh benchmarkname``` to run using full AOT,
+ and use ```./run-benchmark-mono-interpreter.sh benchmarkname``` to run in interpreter-only mode.
+
+## node.js
+Use ```./run-benchmark-wasm.sh benchmarkname``` to automatically build, package and run the benchmark, or manually:
+
+```dotnet build benchmarkname``` to build the debug-mode assembly for the benchmark, then:
+
+```mono ../packager.exe --out=wasm/benchmarkname benchmarkname/bin/Debug/netcoreapp2.1/benchmarkname.dll``` to generate the WASM output, then finally:
+
+```node test-runner.js benchmarkname wasm/benchmarkname``` to run the benchmark.
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/bilinear/bilinear.cs b/sdks/wasm/standalone-benchmarks/bilinear/bilinear.cs new file mode 100755 index 00000000000..943d46d5c40 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/bilinear/bilinear.cs @@ -0,0 +1,328 @@ +// Licensed to the .NET Foundation under one or more agreements. +// The .NET Foundation licenses this file to you under the MIT license. +// See the LICENSE file in the project root for more information. +// + +using System; +using System.Linq; +using System.Numerics; + +// HW Intrinsic APIs are available only in .NET Core 3.0+ +#if !NETCOREAPP2_1 && !NETFRAMEWORK +using System.Runtime.Intrinsics; +using System.Runtime.Intrinsics.X86; +#endif + +public partial class Benchmark +{ + public const int WarmingIterationCount = 3; + public const int IterationCount = 10; + public const int InnerIterationCount = 100; + + // These must be a multiple of the largest available vector of doubles. + const int inputVectorSize = 1024; + const int outputVectorSize = 1024; + const double minXA = 0.0; + const double maxXA = Math.PI; + const int lengthA = 500; + const double deltaA = (maxXA - minXA) / (double)(lengthA - 1); + + const double minXB = minXA + 2.0 * deltaA; + const double maxXB = maxXA - 2.0 * deltaA; + const double weightB = 0.15; + const int lengthB = 500; + const double deltaB = (maxXB - minXB) / (double)(lengthB - 1); + + //ref values + double[] A, B, input, output; + + public Benchmark() + { + reset(); + } + + public void reset() + { + A = new double[lengthA]; + B = new double[lengthB]; + for (int i = 0; i < lengthA; i++) A[i] = Math.Cos(i * deltaA + minXA); + for (int i = 0; i < lengthB; i++) B[i] = Math.Cos(i * deltaB + minXB); + + //Init X values + input = new double[inputVectorSize]; + double incr = (maxXA - minXA) / (double)(inputVectorSize - 3); + for (int i = 0; i < inputVectorSize; i++) input[i] = minXA + (i - 1) * incr; + } + + private static double[] BilinearInterpol(double[] x, + double[] z, + double[] A, + double minXA, + double maxXA, + double[] B, + double minXB, + double maxXB, + double weightB) + { + var weightA = 1.0 - weightB; + + var deltaA = (maxXA - minXA) / (double)(A.Length - 1); + var deltaB = (maxXB - minXB) / (double)(B.Length - 1); + + var invDeltaA = 1.0 / deltaA; + var invDeltaB = 1.0 / deltaB; + + for (var i = 0; i < x.Length; i++) + { + var currentX = x[i]; + + // Determine the largest a, such that A[i] = f(xA) and xA <= x[i]. + // This involves casting from double to int. + var a = (int)((currentX - minXA) * invDeltaA); + // We must ensure that it lies within our available range. + a = Math.Max(0, Math.Min(a, A.Length - 1)); + var aPlusOne = Math.Min(a + 1, A.Length - 1); + + // Now, get the reference input, xA, for our index a. + // This involves casting from int to double. + var xA = (a * deltaA) + minXA; + + // Now, compute the lambda for our A reference point. + var currentXNormA = Math.Max(minXA, Math.Min(currentX, maxXA)); + var lambdaA = (currentXNormA - xA) * invDeltaA; + + // Finally, get our A reference points. + var refALower = A[a]; + var refAUpper = A[aPlusOne]; + + // Now, do the all of the above for our B reference point. + var b = (int)((currentX - minXB) * invDeltaB); + b = Math.Max(0, Math.Min(b, B.Length - 1)); + var bPlusOne = Math.Min(b + 1, B.Length - 1); + var xB = (b * deltaB) + minXB; + var currentXNormB = Math.Max(minXB, Math.Min(currentX, maxXB)); + var lambdaB = (currentXNormB - xB) * invDeltaB; + var refBLower = B[b]; + var refBUpper = B[bPlusOne]; + + // Finally, compute our result. + z[i] = weightA * (refALower + lambdaA * (refAUpper - refALower)) + + weightB * (refBLower + lambdaB * (refBUpper - refBLower)); + } + return z; + } + + private double[] BilinearInterpol_Vector( + double[] x, + double[] A, + double minXA, + double maxXA, + double[] B, + double minXB, + double maxXB, + double weightB) + { + double[] z = new double[outputVectorSize]; + + var vWeightB = new Vector<double>(weightB); + var vWeightA = new Vector<double>(1 - weightB); + + var vMinXA = new Vector<double>(minXA); + var vMaxXA = new Vector<double>(maxXA); + var vMinXB = new Vector<double>(minXB); + var vMaxXB = new Vector<double>(maxXB); + + var deltaA = (maxXA - minXA) / (double)(A.Length - 1); + var deltaB = (maxXB - minXB) / (double)(B.Length - 1); + var vDeltaA = new Vector<double>(deltaA); + var vDeltaB = new Vector<double>(deltaB); + + var vInvDeltaA = Vector<double>.One / vDeltaA; + var vInvDeltaB = Vector<double>.One / vDeltaB; + + var ALengthMinusOne = new Vector<int>(A.Length - 1); + var BLengthMinusOne = new Vector<int>(B.Length - 1); + + double[] doubleTemp = new double[Vector<double>.Count]; + for (var i = 0; i < x.Length; i += Vector<double>.Count) + { + var currentX = new Vector<double>(x, i); + + // Determine the largest a, such that A[i] = f(xA) and xA <= x[i]. + // This involves casting from double to int; here we use two Vector conversions. + Vector<int> a = Vector.ConvertToInt32(Vector.Narrow((currentX - vMinXA) * vInvDeltaA, Vector<double>.Zero)); + a = Vector.Min(Vector.Max(a, Vector<int>.Zero), ALengthMinusOne); + Vector<int> aPlusOne = Vector.Min(a + Vector<int>.One, ALengthMinusOne); + + // Now, get the reference input, xA, for our index a. + // This involves casting from int to double. + Vector<double> tALeft; + Vector<double> tADummy; + Vector.Widen(Vector.ConvertToSingle(a), out tALeft, out tADummy); + Vector<double> xA = (tALeft * vDeltaA) + vMinXA; + + // Now, compute the lambda for our A reference point. + Vector<double> currentXNormA = Vector.Max(vMinXA, Vector.Min(currentX, vMaxXA)); + Vector<double> lambdaA = (currentXNormA - xA) * vInvDeltaA; + + // Now, we need to load up our reference points. + // This is basically a "gather" operation, for which we use a temporary double array. + for (var j = 0; j < Vector<double>.Count; j++) doubleTemp[j] = A[a[j]]; + Vector<double> AVector = new Vector<double>(doubleTemp); + for (var j = 0; j < Vector<double>.Count; j++) doubleTemp[j] = A[aPlusOne[j]]; + Vector<double> AVectorPlusOne = new Vector<double>(doubleTemp); + + // Now, do the all of the above for our B reference point. + Vector<int> b = Vector.ConvertToInt32(Vector.Narrow((currentX - vMinXB) * vInvDeltaB, Vector<double>.Zero)); + b = Vector.Min(Vector.Max(b, Vector<int>.Zero), BLengthMinusOne); + Vector<int> bPlusOne = Vector.Min(b + Vector<int>.One, BLengthMinusOne); + + Vector<double> tBLeft; + Vector<double> tBDummy; + Vector.Widen(Vector.ConvertToSingle(b), out tBLeft, out tBDummy); + Vector<double> xB = (tBLeft * vDeltaB) + vMinXB; + + Vector<double> currentXNormB = Vector.Max(vMinXB, Vector.Min(currentX, vMaxXB)); + Vector<double> lambdaB = (currentXNormB - xB) * vInvDeltaB; + + for (var j = 0; j < Vector<double>.Count; j++) doubleTemp[j] = B[b[j]]; + Vector<double> BVector = new Vector<double>(doubleTemp); + for (var j = 0; j < Vector<double>.Count; j++) doubleTemp[j] = B[bPlusOne[j]]; + Vector<double> BVectorPlusOne = new Vector<double>(doubleTemp); + + Vector<double> newZ = vWeightA * (AVector + lambdaA * (AVectorPlusOne - AVector)) + + vWeightB * (BVector + lambdaB * (BVectorPlusOne - BVector)); + newZ.CopyTo(z, i); + } + return z; + } + +#if !NETCOREAPP2_1 && !NETFRAMEWORK + private static unsafe double[] BilinearInterpol_AVX( + double[] x, + double[] A, + double minXA, + double maxXA, + double[] B, + double minXB, + double maxXB, + double weightB) + { + double[] z = new double[outputVectorSize]; + + fixed (double* pX = &x[0], pA = &A[0], pB = &B[0], pZ = &z[0]) + { + Vector256<double> vWeightB = Vector256.Create(weightB); + Vector256<double> vWeightA = Vector256.Create(1 - weightB); + + Vector256<double> vMinXA = Vector256.Create(minXA); + Vector256<double> vMaxXA = Vector256.Create(maxXA); + Vector256<double> vMinXB = Vector256.Create(minXB); + Vector256<double> vMaxXB = Vector256.Create(maxXB); + + double deltaA = (maxXA - minXA) / (double)(A.Length - 1); + double deltaB = (maxXB - minXB) / (double)(B.Length - 1); + Vector256<double> vDeltaA = Vector256.Create(deltaA); + Vector256<double> vDeltaB = Vector256.Create(deltaB); + + double invDeltaA = 1.0 / deltaA; + double invDeltaB = 1.0 / deltaB; + Vector256<double> vInvDeltaA = Vector256.Create(invDeltaA); + Vector256<double> vInvDeltaB = Vector256.Create(invDeltaB); + + Vector128<int> ALengthMinusOne = Vector128.Create(A.Length - 1); + Vector128<int> BLengthMinusOne = Vector128.Create(B.Length - 1); + Vector128<int> One = Vector128.Create(1); + + for (var i = 0; i < x.Length; i += Vector256<double>.Count) + { + Vector256<double> currentX = Avx.LoadVector256(pX + i); + + // Determine the largest a, such that A[i] = f(xA) and xA <= x[i]. + // This involves casting from double to int; here we use a Vector conversion. + Vector256<double> aDouble = Avx.Multiply(Avx.Subtract(currentX, vMinXA), vInvDeltaA); + Vector128<int> a = Avx.ConvertToVector128Int32WithTruncation(aDouble); + a = Sse41.Min(Sse41.Max(a, Vector128<int>.Zero), ALengthMinusOne); + Vector128<int> aPlusOne = Sse41.Min(Sse2.Add(a, One), ALengthMinusOne); + + // Now, get the reference input, xA, for our index a. + // This involves casting from int to double. + Vector256<double> xA = Avx.Add(Avx.Multiply(Avx.ConvertToVector256Double(a), vDeltaA), vMinXA); + + // Now, compute the lambda for our A reference point. + Vector256<double> currentXNormA = Avx.Max(vMinXA, Avx.Min(currentX, vMaxXA)); + Vector256<double> lambdaA = Avx.Multiply(Avx.Subtract(currentXNormA, xA), vInvDeltaA); + + // Now, we need to load up our reference points using Vector Gather operations. + Vector256<double> AVector = Avx2.GatherVector256(pA, a, 8); + Vector256<double> AVectorPlusOne = Avx2.GatherVector256(pA, aPlusOne, 8); + + // Now, do the all of the above for our B reference point. + Vector256<double> bDouble = Avx.Multiply(Avx.Subtract(currentX, vMinXB), vInvDeltaB); + Vector128<int> b = Avx.ConvertToVector128Int32WithTruncation(bDouble); + b = Sse41.Min(Sse41.Max(b, Vector128<int>.Zero), BLengthMinusOne); + Vector128<int> bPlusOne = Sse41.Min(Sse2.Add(b, One), BLengthMinusOne); + + Vector256<double> xB = Avx.Add(Avx.Multiply(Avx.ConvertToVector256Double(b), vDeltaB), vMinXB); + Vector256<double> currentXNormB = Avx.Max(vMinXB, Avx.Min(currentX, vMaxXB)); + Vector256<double> lambdaB = Avx.Multiply(Avx.Subtract(currentXNormB, xB), vInvDeltaB); + + Vector256<double> BVector = Avx2.GatherVector256(pB, b, 8); + Vector256<double> BVectorPlusOne = Avx2.GatherVector256(pB, bPlusOne, 8); + + Vector256<double> newZ = Avx.Add(Avx.Multiply(vWeightA, Avx.Add(AVector, Avx.Multiply(lambdaA, Avx.Subtract(AVectorPlusOne, AVector)))), + Avx.Multiply(vWeightB, Avx.Add(BVector, Avx.Multiply(lambdaB, Avx.Subtract(BVectorPlusOne, BVector))))); + Avx.Store(pZ + i, newZ); + } + } + return z; + } +#endif // !NETCOREAPP2_1 && !NETFRAMEWORK + + // This method is currently unused. It is useful, when generating a new vectorized version + // of the benchmark (e.g. with a different set of HW intrinsics), to ensure that it is + // correct (i.e. produces the same result as the scalar version). + // + public static bool CheckResult(double[] output, double[] vectorOutput) + { + double eps = 1e-16; + for (int i = 0; i < output.Length; i++) + { + if (Math.Abs(output[i] - vectorOutput[i]) > eps) + { + Console.WriteLine("Failed at " + i + ": output is " + output[i] + ", vectorOutput is " + vectorOutput[i]); + return false; + } + } + return true; + } + + public double[] runIteration() + { + var output = new double[outputVectorSize]; + + for (int i = 0; i < InnerIterationCount; i++) + BilinearInterpol(input, output, A, minXA, maxXA, B, minXB, maxXB, weightB); + + return output; + } + + public double[] Interpol_Vector() + { + double[] vectorOutput = BilinearInterpol_Vector(input, A, minXA, maxXA, B, minXB, maxXB, weightB); + return vectorOutput; + } + +#if !NETCOREAPP2_1 && !NETFRAMEWORK + public double[] Interpol_AVX() + { + if (Avx2.IsSupported) + { + double[] vectorOutput; + vectorOutput = BilinearInterpol_AVX(input, A, minXA, maxXA, B, minXB, maxXB, weightB); + return vectorOutput; + } + return null; + } +#endif +} diff --git a/sdks/wasm/standalone-benchmarks/bilinear/bilinear.csproj b/sdks/wasm/standalone-benchmarks/bilinear/bilinear.csproj new file mode 100755 index 00000000000..f57cff9f75d --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/bilinear/bilinear.csproj @@ -0,0 +1,13 @@ +<Project Sdk="Microsoft.NET.Sdk"> + + <PropertyGroup> + <OutputType>Exe</OutputType> + <TargetFramework>netcoreapp2.1</TargetFramework> + </PropertyGroup> + + <ItemGroup> + <Compile Include="..\Compat.cs" Link="Compat.cs" /> + <Compile Include="..\Program.cs" Link="Program.cs" /> + </ItemGroup> + +</Project> diff --git a/sdks/wasm/standalone-benchmarks/dotnet_LICENSE.TXT b/sdks/wasm/standalone-benchmarks/dotnet_LICENSE.TXT new file mode 100755 index 00000000000..984713a4962 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/dotnet_LICENSE.TXT @@ -0,0 +1,23 @@ +The MIT License (MIT) + +Copyright (c) .NET Foundation and Contributors + +All rights reserved. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/sdks/wasm/standalone-benchmarks/exceptions/exceptions.cs b/sdks/wasm/standalone-benchmarks/exceptions/exceptions.cs new file mode 100755 index 00000000000..36098df938f --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/exceptions/exceptions.cs @@ -0,0 +1,21 @@ +using System; + +public partial class Benchmark +{ + public const int WarmingIterationCount = 300; + public const int IterationCount = 300; + public const int InnerIterationCount = 500; + + public Benchmark() + { + reset(); + } + + public void reset() + { + } + + public void runIteration() + { + } +} diff --git a/sdks/wasm/standalone-benchmarks/exceptions/exceptions.csproj b/sdks/wasm/standalone-benchmarks/exceptions/exceptions.csproj new file mode 100755 index 00000000000..f57cff9f75d --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/exceptions/exceptions.csproj @@ -0,0 +1,13 @@ +<Project Sdk="Microsoft.NET.Sdk"> + + <PropertyGroup> + <OutputType>Exe</OutputType> + <TargetFramework>netcoreapp2.1</TargetFramework> + </PropertyGroup> + + <ItemGroup> + <Compile Include="..\Compat.cs" Link="Compat.cs" /> + <Compile Include="..\Program.cs" Link="Program.cs" /> + </ItemGroup> + +</Project> diff --git a/sdks/wasm/standalone-benchmarks/poker/poker.cs b/sdks/wasm/standalone-benchmarks/poker/poker.cs new file mode 100755 index 00000000000..2c95703471c --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/poker/poker.cs @@ -0,0 +1,429 @@ +using System; +using System.Collections.Generic; +using System.Diagnostics; +using System.Linq; +using System.Text; +using System.Threading.Tasks; +using System.Text.RegularExpressions; +using Jetstream; + +// copyright notice from jetstream benchmark: + +/* + * Copyright (C) 2017 Apple Inc. All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY APPLE INC. ``AS IS'' AND ANY + * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR + * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE INC. OR + * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY + * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + */ + +public class CardDeck +{ + public static readonly string[] _newDeck = new[] { + // Spades + "\x1f0a1", "\x1f0a2", "\x1f0a3", "\x1f0a4", "\x1f0a5", + "\x1f0a6", "\x1f0a7", "\x1f0a8", "\x1f0a9", "\x1f0aa", + "\x1f0ab", "\x1f0ad", "\x1f0ae", + // Hearts + "\x1f0b1", "\x1f0b2", "\x1f0b3", "\x1f0b4", "\x1f0b5", + "\x1f0b6", "\x1f0b7", "\x1f0b8", "\x1f0b9", "\x1f0ba", + "\x1f0bb", "\x1f0bd", "\x1f0be", + // Clubs + "\x1f0d1", "\x1f0d2", "\x1f0d3", "\x1f0d4", "\x1f0d5", + "\x1f0d6", "\x1f0d7", "\x1f0d8", "\x1f0d9", "\x1f0da", + "\x1f0db", "\x1f0dd", "\x1f0de", + // Diamonds + "\x1f0c1", "\x1f0c2", "\x1f0c3", "\x1f0c4", "\x1f0c5", + "\x1f0c6", "\x1f0c7", "\x1f0c8", "\x1f0c9", "\x1f0ca", + "\x1f0cb", "\x1f0cd", "\x1f0ce" + }; + + public static readonly string[] _rankNames = new[] { + "", "Ace", "2", "3", "4", "5", "6", "7", "8", "9", "10", "Jack", "", "Queen", "King" + }; + + public List<string> _cards; + + public CardDeck () + { + this.newDeck(); + } + + public void newDeck() + { + // Make a shallow copy of a new deck + this._cards = new List<string>(_newDeck); + } + + public void shuffle() + { + this.newDeck(); + + for (int index = 52; index != 0;) { + // Select a random card + var randomIndex = (int)Math.Floor(Compat.random() * index); + index--; + + // Swap the current card with the random card + var tempCard = this._cards[index]; + this._cards[index] = this._cards[randomIndex]; + this._cards[randomIndex] = tempCard; + } + } + + public string dealOneCard () + { + return this._cards.shift(); + } + + public static int cardRank (string card) + { + // This returns a numeric value for a card. + // Ace is highest. + + var rankOfCard = card.codePointAt(0) & 0xf; + if (rankOfCard == 0x1) // Make Aces higher than Kings + rankOfCard = 0xf; + + return rankOfCard; + } + + public static string cardName(string card) + { + return cardName(card.codePointAt(0)); + } + + public static string cardName(int card) + { + return _rankNames[card & 0xf]; + } +} + +public class Hand +{ + public static readonly Regex FlushRegExp = new Regex( + "([\x1f0a1-\x1f0ae]{5})|([\x1f0b1-\x1f0be]{5})|([\x1f0c1-\x1f0ce]{5})|([\x1f0d1-\x1f0de]{5})", + RegexOptions.ECMAScript | RegexOptions.Compiled + ), + StraightRegExp = new Regex( + "([\x1f0a1\x1f0b1\x1f0d1\x1f0c1][\x1f0ae\x1f0be\x1f0de\x1f0ce][\x1f0ad\x1f0bd\x1f0dd\x1f0cd][\x1f0ab\x1f0bb\x1f0db\x1f0cb][\x1f0aa\x1f0ba\x1f0da\x1f0ca])|[\x1f0ae\x1f0be\x1f0de\x1f0ce][\x1f0ad\x1f0bd\x1f0dd\x1f0cd][\x1f0ab\x1f0bb\x1f0db\x1f0cb][\x1f0aa\x1f0ba\x1f0da\x1f0ca][\x1f0a9\x1f0b9\x1f0d9\x1f0c9]|[\x1f0ad\x1f0bd\x1f0dd\x1f0cd][\x1f0ab\x1f0bb\x1f0db\x1f0cb][\x1f0aa\x1f0ba\x1f0da\x1f0ca][\x1f0a9\x1f0b9\x1f0d9\x1f0c9][\x1f0a8\x1f0b8\x1f0d8\x1f0c8]|[\x1f0ab\x1f0bb\x1f0db\x1f0cb][\x1f0aa\x1f0ba\x1f0da\x1f0ca][\x1f0a9\x1f0b9\x1f0d9\x1f0c9][\x1f0a8\x1f0b8\x1f0d8\x1f0c8][\x1f0a7\x1f0b7\x1f0d7\x1f0c7]|[\x1f0aa\x1f0ba\x1f0da\x1f0ca][\x1f0a9\x1f0b9\x1f0d9\x1f0c9][\x1f0a8\x1f0b8\x1f0d8\x1f0c8][\x1f0a7\x1f0b7\x1f0d7\x1f0c7][\x1f0a6\x1f0b6\x1f0d6\x1f0c6]|[\x1f0a9\x1f0b9\x1f0d9\x1f0c9][\x1f0a8\x1f0b8\x1f0d8\x1f0c8][\x1f0a7\x1f0b7\x1f0d7\x1f0c7][\x1f0a6\x1f0b6\x1f0d6\x1f0c6][\x1f0a5\x1f0b5\x1f0d5\x1f0c5]|[\x1f0a8\x1f0b8\x1f0d8\x1f0c8][\x1f0a7\x1f0b7\x1f0d7\x1f0c7][\x1f0a6\x1f0b6\x1f0d6\x1f0c6][\x1f0a5\x1f0b5\x1f0d5\x1f0c5][\x1f0a4\x1f0b4\x1f0d4\x1f0c4]|[\x1f0a7\x1f0b7\x1f0d7\x1f0c7][\x1f0a6\x1f0b6\x1f0d6\x1f0c6][\x1f0a5\x1f0b5\x1f0d5\x1f0c5][\x1f0a4\x1f0b4\x1f0d4\x1f0c4][\x1f0a3\x1f0b3\x1f0d3\x1f0c3]|[\x1f0a6\x1f0b6\x1f0d6\x1f0c6][\x1f0a5\x1f0b5\x1f0d5\x1f0c5][\x1f0a4\x1f0b4\x1f0d4\x1f0c4][\x1f0a3\x1f0b3\x1f0d3\x1f0c3][\x1f0a2\x1f0b2\x1f0d2\x1f0c2]|[\x1f0a1\x1f0b1\x1f0d1\x1f0c1][\x1f0a5\x1f0b5\x1f0d5\x1f0c5][\x1f0a4\x1f0b4\x1f0d4\x1f0c4][\x1f0a3\x1f0b3\x1f0d3\x1f0c3][\x1f0a2\x1f0b2\x1f0d2\x1f0c2]", + RegexOptions.ECMAScript | RegexOptions.Compiled + ), + OfAKindRegExp = new Regex( + "(?:[\x1f0a1\x1f0b1\x1f0d1\x1f0c1]{2,4})|(?:[\x1f0ae\x1f0be\x1f0de\x1f0ce]{2,4})|(?:[\x1f0ad\x1f0bd\x1f0dd\x1f0cd]{2,4})|(?:[\x1f0ab\x1f0bb\x1f0db\x1f0cb]{2,4})|(?:[\x1f0aa\x1f0ba\x1f0da\x1f0ca]{2,4})|(?:[\x1f0a9\x1f0b9\x1f0d9\x1f0c9]{2,4})|(?:[\x1f0a8\x1f0b8\x1f0d8\x1f0c8]{2,4})|(?:[\x1f0a7\x1f0b7\x1f0d7\x1f0c7]{2,4})|(?:[\x1f0a6\x1f0b6\x1f0d6\x1f0c6]{2,4})|(?:[\x1f0a5\x1f0b5\x1f0d5\x1f0c5]{2,4})|(?:[\x1f0a4\x1f0b4\x1f0d4\x1f0c4]{2,4})|(?:[\x1f0a3\x1f0b3\x1f0d3\x1f0c3]{2,4})|(?:[\x1f0a2\x1f0b2\x1f0d2\x1f0c2]{2,4})", + RegexOptions.ECMAScript | RegexOptions.Compiled + ); + + public const int RoyalFlush = 0x900000; + public const int StraightFlush = 0x800000; + public const int FourOfAKind = 0x700000; + public const int FullHouse = 0x600000; + public const int Flush = 0x500000; + public const int Straight = 0x400000; + public const int ThreeOfAKind = 0x300000; + public const int TwoPair = 0x200000; + public const int Pair = 0x100000; + + public List<string> _cards = new List<string>(); + public int _rank; + + public Hand () { + this.clear(); + } + + public void clear() + { + this._cards.Clear(); + this._rank = 0; + } + + public void takeCard(string card) + { + this._cards.push(card); + } + + public void score() + { + // Sort highest rank to lowest + this._cards.Sort((a, b) => { + return CardDeck.cardRank(b) - CardDeck.cardRank(a); + }); + + var handString = this._cards.join(""); + + var flushResult = handString.match(Hand.FlushRegExp); + var straightResult = handString.match(Hand.StraightRegExp); + var ofAKindResult = handString.match(Hand.OfAKindRegExp); + + if (flushResult.Success) { + if (straightResult.Success) { + if (straightResult.Groups[1].Success) + this._rank = Hand.RoyalFlush; + else + this._rank = Hand.StraightFlush; + } else + this._rank = Hand.Flush; + + this._rank |= CardDeck.cardRank(this._cards[0]) << 16 | CardDeck.cardRank(this._cards[1]) << 12; + } else if (straightResult.Success) + this._rank = Hand.Straight | CardDeck.cardRank(this._cards[0]) << 16 | CardDeck.cardRank(this._cards[1]) << 12; + else if (ofAKindResult.Success) { + // When comparing lengths, a matched unicode character has a length of 2. + // Therefore expected lengths are doubled, e.g a pair will have a match length of 4. + if (ofAKindResult.Groups[0].Length == 8) + this._rank = Hand.FourOfAKind | CardDeck.cardRank(this._cards[0]); + else { + // Found pair or three of a kind. Check for two pair or full house. + var firstOfAKind = ofAKindResult.Groups[0].Value; + var remainingCardsIndex = handString.IndexOf(firstOfAKind) + firstOfAKind.Length; + Match secondOfAKindResult = null; + if (remainingCardsIndex <= 6 + && (secondOfAKindResult = Hand.OfAKindRegExp.Match(handString.slice(remainingCardsIndex))).Success) { + if ((firstOfAKind.Length == 6 && secondOfAKindResult.Groups[0].Length == 4) + || (firstOfAKind.Length == 4 && secondOfAKindResult.Groups[0].Length == 6)) { + int threeOfAKindCardRank, twoOfAKindCardRank; + if (firstOfAKind.Length == 6) { + threeOfAKindCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + twoOfAKindCardRank = CardDeck.cardRank(secondOfAKindResult.Groups[0].Value.slice(0,2)); + } else { + threeOfAKindCardRank = CardDeck.cardRank(secondOfAKindResult.Groups[0].Value.slice(0,2)); + twoOfAKindCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + } + // Nice typo, jetstream + this._rank = Hand.FullHouse | threeOfAKindCardRank << 16 | ((threeOfAKindCardRank < 12) ? 1 : 0) | threeOfAKindCardRank << 8 | twoOfAKindCardRank << 4 | twoOfAKindCardRank; + } else if (firstOfAKind.Length == 4 && secondOfAKindResult.Groups[0].Length == 4) { + var firstPairCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + var SecondPairCardRank = CardDeck.cardRank(secondOfAKindResult.Groups[0].Value.slice(0,2)); + int otherCardRank = 0; + // Due to sorting, the other card is at index 0, 4 or 8 + if (firstOfAKind.codePointAt(0) == handString.codePointAt(0)) { + if (secondOfAKindResult.Groups[0].Value.codePointAt(0) == handString.codePointAt(4)) + otherCardRank = CardDeck.cardRank(handString.slice(8,10)); + else + otherCardRank = CardDeck.cardRank(handString.slice(4,6)); + } else + otherCardRank = CardDeck.cardRank(handString.slice(0,2)); + + this._rank = Hand.TwoPair | firstPairCardRank << 16 | firstPairCardRank << 12 | SecondPairCardRank << 8 | SecondPairCardRank << 4 | otherCardRank; + } + } else { + var ofAKindCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + var otherCardsRank = 0; + foreach (var card in this._cards) { + var cardRank = CardDeck.cardRank(card); + if (cardRank != ofAKindCardRank) + otherCardsRank = (otherCardsRank << 4) | cardRank; + } + + if (firstOfAKind.Length == 6) + this._rank = Hand.ThreeOfAKind | ofAKindCardRank << 16 | ofAKindCardRank << 12 | ofAKindCardRank << 8 | otherCardsRank; + else + this._rank = Hand.Pair | ofAKindCardRank << 16 | ofAKindCardRank << 12 | otherCardsRank; + } + } + } else { + this._rank = 0; + foreach (var card in _cards) { + var cardRank = CardDeck.cardRank(card); + this._rank = (this._rank << 4) | cardRank; + } + } + } + + public int rank { + get { + return _rank; + } + } + + public override string ToString () { + return this._cards.join(""); + } +} + +public class Player : Hand { + public string _name; + public int _wins; + public int[] _handTypeCounts; + + public Player (string name) + : base () { + this._name = name; + this._wins = 0; + this._handTypeCounts = new int[] { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; + } + + public void scoreHand() { + this.score(); + var handType = this.rank >> 20; + this._handTypeCounts[handType]++; + } + + public void wonHand() { + this._wins++; + } + + public string name { + get { + return this._name; + } + } + + public string hand { + get { + return base.ToString(); + } + } + + public int wins { + get { + return this._wins; + } + } + + public int[] handTypeCounts { + get { + return this._handTypeCounts; + } + } +} + +public static class Hands { + public static void playHands (List<Player> players) + { + var cardDeck = new CardDeck(); + var handsPlayed = 0; + var highestRank = 0; + + do { + cardDeck.shuffle(); + + foreach (var player in players) + player.clear(); + + for (var i = 0; i < 5; i++) { + foreach (var player in players) + player.takeCard(cardDeck.dealOneCard()); + } + + foreach (var player in players) + player.scoreHand(); + + handsPlayed++; + + highestRank = 0; + + foreach (var player in players) + if (player.rank > highestRank) + highestRank = player.rank; + + foreach (var player in players) + // We count ties as wins for each player. + if (player.rank == highestRank) + player.wonHand(); + + } while (handsPlayed < 2000); + } +} + +public class PlayerExpectation +{ + public static readonly string[] _handTypes = new [] { + "High Cards", + "Pairs", + "Two Pairs", + "Three of a Kinds", + "Straights", + "Flushes", + "Full Houses", + "Four of a Kinds", + "Straight Flushes", + "Royal Flushes" + }; + + public int _wins; + public int[] _handTypeCounts; + + public PlayerExpectation (int wins, int[] handTypeCounts) + { + this._wins = wins; + this._handTypeCounts = handTypeCounts; + } + + public void validate (Player player) + { + if (player.wins != this._wins) + throw new Exception("Expected " + player.name + " to have " + this._wins + ", but they have " + player.wins); + + var actualHandTypeCounts = player.handTypeCounts; + if (this._handTypeCounts.Length != actualHandTypeCounts.Length) + throw new Exception("Expected " + player.name + " to have " + this._handTypeCounts.Length + " hand types, but they have " + actualHandTypeCounts.Length); + + for (var handTypeIdx = 0; handTypeIdx < this._handTypeCounts.Length; handTypeIdx++) { + if (this._handTypeCounts[handTypeIdx] != actualHandTypeCounts[handTypeIdx]) { + throw new Exception("Expected " + player.name + " to have " + this._handTypeCounts[handTypeIdx] + " " + PlayerExpectation._handTypes[handTypeIdx] + " hands, but they have " + actualHandTypeCounts[handTypeIdx]); + } + + } + } +} + + + +public partial class Benchmark { + public const int WarmingIterationCount = 3; + public const int IterationCount = 10; + public const int InnerIterationCount = 1; + + public List<Player> _players = new List<Player> { + new Player("Player 1"), + new Player("Player 2"), + new Player("Player 3"), + new Player("Player 4") + }; + + public static readonly PlayerExpectation[] playerExpectations = new[] { + new PlayerExpectation(59864, new[] { 120476, 101226, 11359, 5083, 982, 456, 370, 45, 3, 0 }), + new PlayerExpectation(60020, new[] { 120166, 101440, 11452, 5096, 942, 496, 333, 67, 8, 0 }), + new PlayerExpectation(60065, new[] { 120262, 101345, 11473, 5093, 941, 472, 335, 76, 3, 0 }), + new PlayerExpectation(60064, new[] { 120463, 101218, 11445, 5065, 938, 446, 364, 58, 3, 0 }) + }; + + public Benchmark () { + } + + public void runIteration() + { + Hands.playHands(this._players); + } + + public void validate() + { + if (this._players.Count != playerExpectations.Length) + throw new Exception("Expect " + playerExpectations.Length + ", but actually have " + this._players.Count); + + for (var playerIdx = 0; playerIdx < playerExpectations.Length; playerIdx++) + playerExpectations[playerIdx].validate(this._players[playerIdx]); + } + + public void reset() + { + } +}
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/poker/poker.csproj b/sdks/wasm/standalone-benchmarks/poker/poker.csproj new file mode 100755 index 00000000000..5eca76261ac --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/poker/poker.csproj @@ -0,0 +1,17 @@ +<Project Sdk="Microsoft.NET.Sdk"> + + <PropertyGroup> + <OutputType>Exe</OutputType> + <TargetFramework>netcoreapp2.1</TargetFramework> + </PropertyGroup> + + <ItemGroup> + <Compile Remove="Program.cs" /> + </ItemGroup> + + <ItemGroup> + <Compile Include="..\Compat.cs" Link="Compat.cs" /> + <Compile Include="..\Program.cs" Link="Program.cs" /> + </ItemGroup> + +</Project> diff --git a/sdks/wasm/standalone-benchmarks/poker/poker.js b/sdks/wasm/standalone-benchmarks/poker/poker.js new file mode 100755 index 00000000000..8fbd29dd50f --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/poker/poker.js @@ -0,0 +1,439 @@ +/* + * Copyright (C) 2017 Apple Inc. All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY APPLE INC. ``AS IS'' AND ANY + * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR + * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE INC. OR + * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY + * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + */ +"use strict"; + + +class CardDeck +{ + constructor() + { + this.newDeck(); + } + + newDeck() + { + // Make a shallow copy of a new deck + this._cards = CardDeck._newDeck.slice(0); + } + + shuffle() + { + this.newDeck(); + + for (let index = 52; index !== 0;) { + // Select a random card + let randomIndex = Math.floor(Math.random() * index); + index--; + + // Swap the current card with the random card + let tempCard = this._cards[index]; + this._cards[index] = this._cards[randomIndex]; + this._cards[randomIndex] = tempCard; + } + } + + dealOneCard() + { + return this._cards.shift(); + } + + static cardRank(card) + { + // This returns a numeric value for a card. + // Ace is highest. + + let rankOfCard = card.codePointAt(0) & 0xf; + if (rankOfCard == 0x1) // Make Aces higher than Kings + rankOfCard = 0xf; + + return rankOfCard; + } + + static cardName(card) + { + if (typeof(card) == "string") + card = card.codePointAt(0); + return this._rankNames[card & 0xf]; + } +} + +CardDeck._rankNames = [ + "", "Ace", "2", "3", "4", "5", "6", "7", "8", "9", "10", "Jack", "", "Queen", "King" +]; + +CardDeck._newDeck = [ + // Spades + "\u{1f0a1}", "\u{1f0a2}", "\u{1f0a3}", "\u{1f0a4}", "\u{1f0a5}", + "\u{1f0a6}", "\u{1f0a7}", "\u{1f0a8}", "\u{1f0a9}", "\u{1f0aa}", + "\u{1f0ab}", "\u{1f0ad}", "\u{1f0ae}", + // Hearts + "\u{1f0b1}", "\u{1f0b2}", "\u{1f0b3}", "\u{1f0b4}", "\u{1f0b5}", + "\u{1f0b6}", "\u{1f0b7}", "\u{1f0b8}", "\u{1f0b9}", "\u{1f0ba}", + "\u{1f0bb}", "\u{1f0bd}", "\u{1f0be}", + // Clubs + "\u{1f0d1}", "\u{1f0d2}", "\u{1f0d3}", "\u{1f0d4}", "\u{1f0d5}", + "\u{1f0d6}", "\u{1f0d7}", "\u{1f0d8}", "\u{1f0d9}", "\u{1f0da}", + "\u{1f0db}", "\u{1f0dd}", "\u{1f0de}", + // Diamonds + "\u{1f0c1}", "\u{1f0c2}", "\u{1f0c3}", "\u{1f0c4}", "\u{1f0c5}", + "\u{1f0c6}", "\u{1f0c7}", "\u{1f0c8}", "\u{1f0c9}", "\u{1f0ca}", + "\u{1f0cb}", "\u{1f0cd}", "\u{1f0ce}" +]; + +class Hand +{ + constructor() + { + this.clear(); + } + + clear() + { + this._cards = []; + this._rank = 0; + } + + takeCard(card) + { + this._cards.push(card); + } + + score() + { + // Sort highest rank to lowest + this._cards.sort((a, b) => { + return CardDeck.cardRank(b) - CardDeck.cardRank(a); + }); + + let handString = this._cards.join(""); + + let flushResult = handString.match(Hand.FlushRegExp); + let straightResult = handString.match(Hand.StraightRegExp); + let ofAKindResult = handString.match(Hand.OfAKindRegExp); + + if (flushResult) { + if (straightResult) { + if (straightResult[1]) + this._rank = Hand.RoyalFlush; + else + this._rank = Hand.StraightFlush + } else + this._rank = Hand.Flush; + + this._rank |= CardDeck.cardRank(this._cards[0]) << 16 | CardDeck.cardRank(this._cards[1]) << 12; + } else if (straightResult) + this._rank = Hand.Straight | CardDeck.cardRank(this._cards[0]) << 16 | CardDeck.cardRank(this._cards[1]) << 12; + else if (ofAKindResult) { + // When comparing lengths, a matched unicode character has a length of 2. + // Therefore expected lengths are doubled, e.g a pair will have a match length of 4. + if (ofAKindResult[0].length == 8) + this._rank = Hand.FourOfAKind | CardDeck.cardRank(this._cards[0]); + else { + // Found pair or three of a kind. Check for two pair or full house. + let firstOfAKind = ofAKindResult[0]; + let remainingCardsIndex = handString.indexOf(firstOfAKind) + firstOfAKind.length; + let secondOfAKindResult; + if (remainingCardsIndex <= 6 + && (secondOfAKindResult = handString.slice(remainingCardsIndex).match(Hand.OfAKindRegExp))) { + if ((firstOfAKind.length == 6 && secondOfAKindResult[0].length == 4) + || (firstOfAKind.length == 4 && secondOfAKindResult[0].length == 6)) { + let threeOfAKindCardRank; + let twoOfAKindCardRank; + if (firstOfAKind.length == 6) { + threeOfAKindCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + twoOfAKindCardRank = CardDeck.cardRank(secondOfAKindResult[0].slice(0,2)); + } else { + threeOfAKindCardRank = CardDeck.cardRank(secondOfAKindResult[0].slice(0,2)); + twoOfAKindCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + } + this._rank = Hand.FullHouse | threeOfAKindCardRank << 16 | threeOfAKindCardRank < 12 | threeOfAKindCardRank << 8 | twoOfAKindCardRank << 4 | twoOfAKindCardRank; + } else if (firstOfAKind.length == 4 && secondOfAKindResult[0].length == 4) { + let firstPairCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + let SecondPairCardRank = CardDeck.cardRank(secondOfAKindResult[0].slice(0,2)); + let otherCardRank; + // Due to sorting, the other card is at index 0, 4 or 8 + if (firstOfAKind.codePointAt(0) == handString.codePointAt(0)) { + if (secondOfAKindResult[0].codePointAt(0) == handString.codePointAt(4)) + otherCardRank = CardDeck.cardRank(handString.slice(8,10)); + else + otherCardRank = CardDeck.cardRank(handString.slice(4,6)); + } else + otherCardRank = CardDeck.cardRank(handString.slice(0,2)); + + this._rank = Hand.TwoPair | firstPairCardRank << 16 | firstPairCardRank << 12 | SecondPairCardRank << 8 | SecondPairCardRank << 4 | otherCardRank; + } + } else { + let ofAKindCardRank = CardDeck.cardRank(firstOfAKind.slice(0,2)); + let otherCardsRank = 0; + for (let card of this._cards) { + let cardRank = CardDeck.cardRank(card); + if (cardRank != ofAKindCardRank) + otherCardsRank = (otherCardsRank << 4) | cardRank; + } + + if (firstOfAKind.length == 6) + this._rank = Hand.ThreeOfAKind | ofAKindCardRank << 16 | ofAKindCardRank << 12 | ofAKindCardRank << 8 | otherCardsRank; + else + this._rank = Hand.Pair | ofAKindCardRank << 16 | ofAKindCardRank << 12 | otherCardsRank; + } + } + } else { + this._rank = 0; + for (let card of this._cards) { + let cardRank = CardDeck.cardRank(card); + this._rank = (this._rank << 4) | cardRank; + } + } + } + + get rank() + { + return this._rank; + } + + toString() + { + return this._cards.join(""); + } +} + +Hand.FlushRegExp = new RegExp("([\u{1f0a1}-\u{1f0ae}]{5})|([\u{1f0b1}-\u{1f0be}]{5})|([\u{1f0c1}-\u{1f0ce}]{5})|([\u{1f0d1}-\u{1f0de}]{5})", "u"); + +Hand.StraightRegExp = new RegExp("([\u{1f0a1}\u{1f0b1}\u{1f0d1}\u{1f0c1}][\u{1f0ae}\u{1f0be}\u{1f0de}\u{1f0ce}][\u{1f0ad}\u{1f0bd}\u{1f0dd}\u{1f0cd}][\u{1f0ab}\u{1f0bb}\u{1f0db}\u{1f0cb}][\u{1f0aa}\u{1f0ba}\u{1f0da}\u{1f0ca}])|[\u{1f0ae}\u{1f0be}\u{1f0de}\u{1f0ce}][\u{1f0ad}\u{1f0bd}\u{1f0dd}\u{1f0cd}][\u{1f0ab}\u{1f0bb}\u{1f0db}\u{1f0cb}][\u{1f0aa}\u{1f0ba}\u{1f0da}\u{1f0ca}][\u{1f0a9}\u{1f0b9}\u{1f0d9}\u{1f0c9}]|[\u{1f0ad}\u{1f0bd}\u{1f0dd}\u{1f0cd}][\u{1f0ab}\u{1f0bb}\u{1f0db}\u{1f0cb}][\u{1f0aa}\u{1f0ba}\u{1f0da}\u{1f0ca}][\u{1f0a9}\u{1f0b9}\u{1f0d9}\u{1f0c9}][\u{1f0a8}\u{1f0b8}\u{1f0d8}\u{1f0c8}]|[\u{1f0ab}\u{1f0bb}\u{1f0db}\u{1f0cb}][\u{1f0aa}\u{1f0ba}\u{1f0da}\u{1f0ca}][\u{1f0a9}\u{1f0b9}\u{1f0d9}\u{1f0c9}][\u{1f0a8}\u{1f0b8}\u{1f0d8}\u{1f0c8}][\u{1f0a7}\u{1f0b7}\u{1f0d7}\u{1f0c7}]|[\u{1f0aa}\u{1f0ba}\u{1f0da}\u{1f0ca}][\u{1f0a9}\u{1f0b9}\u{1f0d9}\u{1f0c9}][\u{1f0a8}\u{1f0b8}\u{1f0d8}\u{1f0c8}][\u{1f0a7}\u{1f0b7}\u{1f0d7}\u{1f0c7}][\u{1f0a6}\u{1f0b6}\u{1f0d6}\u{1f0c6}]|[\u{1f0a9}\u{1f0b9}\u{1f0d9}\u{1f0c9}][\u{1f0a8}\u{1f0b8}\u{1f0d8}\u{1f0c8}][\u{1f0a7}\u{1f0b7}\u{1f0d7}\u{1f0c7}][\u{1f0a6}\u{1f0b6}\u{1f0d6}\u{1f0c6}][\u{1f0a5}\u{1f0b5}\u{1f0d5}\u{1f0c5}]|[\u{1f0a8}\u{1f0b8}\u{1f0d8}\u{1f0c8}][\u{1f0a7}\u{1f0b7}\u{1f0d7}\u{1f0c7}][\u{1f0a6}\u{1f0b6}\u{1f0d6}\u{1f0c6}][\u{1f0a5}\u{1f0b5}\u{1f0d5}\u{1f0c5}][\u{1f0a4}\u{1f0b4}\u{1f0d4}\u{1f0c4}]|[\u{1f0a7}\u{1f0b7}\u{1f0d7}\u{1f0c7}][\u{1f0a6}\u{1f0b6}\u{1f0d6}\u{1f0c6}][\u{1f0a5}\u{1f0b5}\u{1f0d5}\u{1f0c5}][\u{1f0a4}\u{1f0b4}\u{1f0d4}\u{1f0c4}][\u{1f0a3}\u{1f0b3}\u{1f0d3}\u{1f0c3}]|[\u{1f0a6}\u{1f0b6}\u{1f0d6}\u{1f0c6}][\u{1f0a5}\u{1f0b5}\u{1f0d5}\u{1f0c5}][\u{1f0a4}\u{1f0b4}\u{1f0d4}\u{1f0c4}][\u{1f0a3}\u{1f0b3}\u{1f0d3}\u{1f0c3}][\u{1f0a2}\u{1f0b2}\u{1f0d2}\u{1f0c2}]|[\u{1f0a1}\u{1f0b1}\u{1f0d1}\u{1f0c1}][\u{1f0a5}\u{1f0b5}\u{1f0d5}\u{1f0c5}][\u{1f0a4}\u{1f0b4}\u{1f0d4}\u{1f0c4}][\u{1f0a3}\u{1f0b3}\u{1f0d3}\u{1f0c3}][\u{1f0a2}\u{1f0b2}\u{1f0d2}\u{1f0c2}]", "u"); + +Hand.OfAKindRegExp = new RegExp("(?:[\u{1f0a1}\u{1f0b1}\u{1f0d1}\u{1f0c1}]{2,4})|(?:[\u{1f0ae}\u{1f0be}\u{1f0de}\u{1f0ce}]{2,4})|(?:[\u{1f0ad}\u{1f0bd}\u{1f0dd}\u{1f0cd}]{2,4})|(?:[\u{1f0ab}\u{1f0bb}\u{1f0db}\u{1f0cb}]{2,4})|(?:[\u{1f0aa}\u{1f0ba}\u{1f0da}\u{1f0ca}]{2,4})|(?:[\u{1f0a9}\u{1f0b9}\u{1f0d9}\u{1f0c9}]{2,4})|(?:[\u{1f0a8}\u{1f0b8}\u{1f0d8}\u{1f0c8}]{2,4})|(?:[\u{1f0a7}\u{1f0b7}\u{1f0d7}\u{1f0c7}]{2,4})|(?:[\u{1f0a6}\u{1f0b6}\u{1f0d6}\u{1f0c6}]{2,4})|(?:[\u{1f0a5}\u{1f0b5}\u{1f0d5}\u{1f0c5}]{2,4})|(?:[\u{1f0a4}\u{1f0b4}\u{1f0d4}\u{1f0c4}]{2,4})|(?:[\u{1f0a3}\u{1f0b3}\u{1f0d3}\u{1f0c3}]{2,4})|(?:[\u{1f0a2}\u{1f0b2}\u{1f0d2}\u{1f0c2}]{2,4})", "u"); + +Hand.RoyalFlush = 0x900000; +Hand.StraightFlush = 0x800000; +Hand.FourOfAKind = 0x700000; +Hand.FullHouse = 0x600000; +Hand.Flush = 0x500000; +Hand.Straight = 0x400000; +Hand.ThreeOfAKind = 0x300000; +Hand.TwoPair = 0x200000; +Hand.Pair = 0x100000; + +class Player extends Hand +{ + constructor(name) + { + super(); + this._name = name; + this._wins = 0; + this._handTypeCounts = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]; + } + + scoreHand() + { + this.score(); + let handType = this.rank >> 20; + this._handTypeCounts[handType]++; + } + + wonHand() + { + this._wins++ + } + + get name() + { + return this._name; + } + + get hand() + { + return super.toString(); + } + + get wins() + { + return this._wins; + } + + get handTypeCounts() + { + return this._handTypeCounts; + } +} + +function playHands(players) +{ + let cardDeck = new CardDeck(); + let handsPlayed = 0; + let highestRank = 0; + + do { + cardDeck.shuffle(); + + for (let player of players) + player.clear(); + + for (let i = 0; i < 5; i++) { + for (let player of players) + player.takeCard(cardDeck.dealOneCard()); + } + + for (let player of players) + player.scoreHand(); + + handsPlayed++; + + highestRank = 0; + + for (let player of players) { + if (player.rank > highestRank) + highestRank = player.rank; + } + + for (let player of players) { + // We count ties as wins for each player. + if (player.rank == highestRank) + player.wonHand(); + } + } while (handsPlayed < 2000); +} + + + +class PlayerExpectation +{ + constructor(wins, handTypeCounts) + { + this._wins = wins; + this._handTypeCounts = handTypeCounts; + } + + validate(player) + { + if (player.wins != this._wins) + throw "Expected " + player.name + " to have " + this._wins + ", but they have " + player.wins; + + let actualHandTypeCounts = player.handTypeCounts; + if (this._handTypeCounts.length != actualHandTypeCounts.length) + throw "Expected " + player.name + " to have " + this._handTypeCounts.length + " hand types, but they have " + actualHandTypeCounts.length; + + for (let handTypeIdx = 0; handTypeIdx < this._handTypeCounts.length; handTypeIdx++) { + if (this._handTypeCounts[handTypeIdx] != actualHandTypeCounts[handTypeIdx]) { + throw "Expected " + player.name + " to have " + this._handTypeCounts[handTypeIdx] + " " + PlayerExpectation._handTypes[handTypeIdx] + " hands, but they have " + actualHandTypeCounts[handTypeIdx]; + } + + } + } +} + +PlayerExpectation._handTypes = [ + "High Cards", + "Pairs", + "Two Pairs", + "Three of a Kinds", + "Straights", + "Flushes", + "Full Houses", + "Four of a Kinds", + "Straight Flushes", + "Royal Flushes" +]; + +var playerExpectations = []; + +playerExpectations.push(new PlayerExpectation(59864, [ 120476, 101226, 11359, 5083, 982, 456, 370, 45, 3, 0])); +playerExpectations.push(new PlayerExpectation(60020, [ 120166, 101440, 11452, 5096, 942, 496, 333, 67, 8, 0])); +playerExpectations.push(new PlayerExpectation(60065, [ 120262, 101345, 11473, 5093, 941, 472, 335, 76, 3, 0])); +playerExpectations.push(new PlayerExpectation(60064, [ 120463, 101218, 11445, 5065, 938, 446, 364, 58, 3, 0])); + + + +class Benchmark { + constructor() + { + this._players = []; + this._players.push(new Player("Player 1")); + this._players.push(new Player("Player 2")); + this._players.push(new Player("Player 3")); + this._players.push(new Player("Player 4")); + } + + runIteration() + { + playHands(this._players); + } + + validate() + { + if (this._players.length != playerExpectations.length) + throw "Expect " + playerExpectations.length + ", but actually have " + this._players.length; + + for (let playerIdx = 0; playerIdx < playerExpectations.length; playerIdx++) + playerExpectations[playerIdx].validate(this._players[playerIdx]); + } + + reset() + { + } +} + + + +function main () { + const iterations = 300, warming_iterations = 60; + + console.log("Initializing..."); + + var b = new Benchmark(); + var timings = new Array(iterations); + + for (var i = 0; i < warming_iterations; i++) + b.runIteration(); + + b.reset(); + + console.log("Running", iterations, "times..."); + + var started = Date.now(); + + for (var i = 0; i < iterations; i++) { + var substarted = Date.now(); + b.runIteration(); + timings[i] = Date.now() - substarted; + + // FIXME: These expectations are assuming some weird unstated set of conditions? + // b.validate(); + } + + console.log("Elapsed", Date.now() - started); + var tsum = 0, tmin = 999999999, tmax = 0; + + for (var i = 0; i < iterations; i++) { + tsum += timings[i]; + tmin = Math.min(tmin, timings[i]); + tmax = Math.max(tmax, timings[i]); + } + + console.log("ms/iter avg =", tsum / iterations); + console.log("min =", tmin); + console.log("max =", tmax); +} + +main();
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/run-benchmark-all.sh b/sdks/wasm/standalone-benchmarks/run-benchmark-all.sh new file mode 100755 index 00000000000..d5cae3a3b1f --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/run-benchmark-all.sh @@ -0,0 +1,40 @@ +#!/bin/bash +set -e +set -u + +# &>> is used to pipe both stdout and stderr to a file in append mode +# Tee is used to both append full stdout to a log file and then print filtered stdout. +# Before that we need to merge stdout and stderr using 2>&1. +# Grep ^\>\>\> is used to only print result messages from the benchmark. + +LOGFILE=$(realpath run-benchmark-all.$1.log) +PACKAGER=$(realpath ../packager.exe) +SRC_DIR=$(realpath $1/bin/Debug/netcoreapp2.1) +OUT_DIR=$(realpath wasm/$1) +AOT_OUT_DIR=$(realpath wasm-aot/$1) +MONO_SDK_DIR=$(realpath ../../out) +EMSCRIPTEN_SDK_DIR=$(realpath ../../builds/toolchains/emsdk) +TEMPLATE_PATH=$(realpath ../runtime.js) + +echo \# Building benchmark $1... +rm -f $LOGFILE +dotnet build $1 &>>$LOGFILE +rm -f SRC_DIR/*.so +echo \# Running benchmark $1... | tee -a $LOGFILE +echo \# .NET Core | tee -a $LOGFILE +dotnet run --project=$1 | tee -a $LOGFILE | grep ^\>\>\> +echo \# Mono \(JIT\) | tee -a $LOGFILE +mono $SRC_DIR/$1.dll 2>&1 | tee -a $LOGFILE | grep ^\>\>\> +echo \# Mono \(interpreter\) | tee -a $LOGFILE +mono --interpreter --interp=interp-only $SRC_DIR/$1.dll 2>&1 | tee -a $LOGFILE | grep ^\>\>\> +echo \# Mono \(full AOT\) | tee -a $LOGFILE +mono --aot=full $SRC_DIR/$1.dll &>>$LOGFILE +mono $SRC_DIR/$1.dll 2>&1 | tee -a $LOGFILE | grep ^\>\>\> +echo \# WebAssembly \(interpreter, node.js\) | tee -a $LOGFILE +mono --debug $PACKAGER --out=$OUT_DIR $SRC_DIR/$1.dll --template=$TEMPLATE_PATH &>>$LOGFILE +node test-runner.js $1 wasm/$1 2>&1 | tee -a $LOGFILE | grep \>\>\> +echo \# WebAssembly \(AOT, node.js\) | tee -a $LOGFILE +mono --debug $PACKAGER --linker --aot --builddir=$AOT_OUT_DIR/obj --appdir=$AOT_OUT_DIR $SRC_DIR/$1.dll --mono-sdkdir=$MONO_SDK_DIR --emscripten-sdkdir=$EMSCRIPTEN_SDK_DIR --template=$TEMPLATE_PATH +ninja -v -C $AOT_OUT_DIR/obj &>>$LOGFILE +node test-runner.js $1 $AOT_OUT_DIR 2>&1 | tee -a $LOGFILE | grep \>\>\> +echo \# Test run complete. Check $LOGFILE for any errors. diff --git a/sdks/wasm/standalone-benchmarks/run-benchmark-mono-aot.sh b/sdks/wasm/standalone-benchmarks/run-benchmark-mono-aot.sh new file mode 100755 index 00000000000..418862991aa --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/run-benchmark-mono-aot.sh @@ -0,0 +1,9 @@ +#!/bin/bash +set -e +set -x +set -u + +dotnet build $1 +rm -f $1/bin/Debug/netcoreapp2.1/*.so +mono --aot=full $1/bin/Debug/netcoreapp2.1/$1.dll +mono $1/bin/Debug/netcoreapp2.1/$1.dll diff --git a/sdks/wasm/standalone-benchmarks/run-benchmark-mono-interpreter.sh b/sdks/wasm/standalone-benchmarks/run-benchmark-mono-interpreter.sh new file mode 100755 index 00000000000..ed975bcd8b2 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/run-benchmark-mono-interpreter.sh @@ -0,0 +1,8 @@ +#!/bin/bash +set -e +set -x +set -u + +dotnet build $1 +rm -f $1/bin/Debug/netcoreapp2.1/*.so +mono --interpreter --interp=interp-only $1/bin/Debug/netcoreapp2.1/$1.dll diff --git a/sdks/wasm/standalone-benchmarks/run-benchmark-mono.sh b/sdks/wasm/standalone-benchmarks/run-benchmark-mono.sh new file mode 100755 index 00000000000..88f97debf66 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/run-benchmark-mono.sh @@ -0,0 +1,8 @@ +#!/bin/bash +set -e +set -x +set -u + +dotnet build $1 +rm -f $1/bin/Debug/netcoreapp2.1/*.so +mono $1/bin/Debug/netcoreapp2.1/$1.dll diff --git a/sdks/wasm/standalone-benchmarks/run-benchmark-wasm-aot.sh b/sdks/wasm/standalone-benchmarks/run-benchmark-wasm-aot.sh new file mode 100755 index 00000000000..9d121242d79 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/run-benchmark-wasm-aot.sh @@ -0,0 +1,16 @@ +#!/bin/bash +set -e +set -x +set -u + +PACKAGER=$(realpath ../packager.exe) +SRC_DIR=$(realpath $1/bin/Debug/netcoreapp2.1) +AOT_OUT_DIR=$(realpath wasm-aot/$1) +MONO_SDK_DIR=$(realpath ../../out) +EMSCRIPTEN_SDK_DIR=$(realpath ../../builds/toolchains/emsdk) +TEMPLATE_PATH=$(realpath ../runtime.js) + +dotnet build $1 +mono --debug $PACKAGER --linker --aot --builddir=$AOT_OUT_DIR/obj --appdir=$AOT_OUT_DIR $SRC_DIR/$1.dll --mono-sdkdir=$MONO_SDK_DIR --emscripten-sdkdir=$EMSCRIPTEN_SDK_DIR --template=$TEMPLATE_PATH +ninja -v -C $AOT_OUT_DIR/obj +node test-runner.js $1 $AOT_OUT_DIR diff --git a/sdks/wasm/standalone-benchmarks/run-benchmark-wasm.sh b/sdks/wasm/standalone-benchmarks/run-benchmark-wasm.sh new file mode 100755 index 00000000000..6ba4513b219 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/run-benchmark-wasm.sh @@ -0,0 +1,12 @@ +#!/bin/bash +set -e +set -x +set -u + +PACKAGER=$(realpath ../packager.exe) +SRC_DIR=$(realpath $1/bin/Debug/netcoreapp2.1) +TEMPLATE_PATH=$(realpath ../runtime.js) + +dotnet build $1 +mono --debug $PACKAGER --out=wasm/$1 $SRC_DIR/$1.dll --template=$TEMPLATE_PATH +node test-runner.js $1 wasm/$1 diff --git a/sdks/wasm/standalone-benchmarks/segmentation/segmentation.cs b/sdks/wasm/standalone-benchmarks/segmentation/segmentation.cs new file mode 100755 index 00000000000..de48cf7165b --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/segmentation/segmentation.cs @@ -0,0 +1,559 @@ +using System; +using System.Collections.Generic; +using System.Diagnostics; +using System.Linq; +using System.Text; +using System.Threading.Tasks; +using Jetstream; + +// copyright notice from jetstream benchmark: +/* + * Copyright (C) 2018 Apple Inc. All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY APPLE INC. ``AS IS'' AND ANY + * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR + * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE INC. OR + * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY + * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + */ + + +public static class Statistics { + public static readonly Dictionary<double, double[]> tDistributionByOneSidedProbability = + new Dictionary<double, double[]> { + { 0.9, new [] { + 3.077684, 1.885618, 1.637744, 1.533206, 1.475884, 1.439756, 1.414924, 1.396815, 1.383029, 1.372184, + 1.363430, 1.356217, 1.350171, 1.345030, 1.340606, 1.336757, 1.333379, 1.330391, 1.327728, 1.325341, + 1.323188, 1.321237, 1.319460, 1.317836, 1.316345, 1.314972, 1.313703, 1.312527, 1.311434, 1.310415, + 1.309464, 1.308573, 1.307737, 1.306952, 1.306212, 1.305514, 1.304854, 1.304230, 1.303639, 1.303077, + 1.302543, 1.302035, 1.301552, 1.301090, 1.300649, 1.300228, 1.299825, 1.299439, 1.299069, 1.298714, + + 1.298373, 1.298045, 1.297730, 1.297426, 1.297134, 1.296853, 1.296581, 1.296319, 1.296066, 1.295821, + 1.295585, 1.295356, 1.295134, 1.294920, 1.294712, 1.294511, 1.294315, 1.294126, 1.293942, 1.293763, + 1.293589, 1.293421, 1.293256, 1.293097, 1.292941, 1.292790, 1.292643, 1.292500, 1.292360, 1.292224, + 1.292091, 1.291961, 1.291835, 1.291711, 1.291591, 1.291473, 1.291358, 1.291246, 1.291136, 1.291029, + 1.290924, 1.290821, 1.290721, 1.290623, 1.290527, 1.290432, 1.290340, 1.290250, 1.290161, 1.290075 } }, + { 0.95, new [] { + 6.313752, 2.919986, 2.353363, 2.131847, 2.015048, 1.943180, 1.894579, 1.859548, 1.833113, 1.812461, + 1.795885, 1.782288, 1.770933, 1.761310, 1.753050, 1.745884, 1.739607, 1.734064, 1.729133, 1.724718, + 1.720743, 1.717144, 1.713872, 1.710882, 1.708141, 1.705618, 1.703288, 1.701131, 1.699127, 1.697261, + 1.695519, 1.693889, 1.692360, 1.690924, 1.689572, 1.688298, 1.687094, 1.685954, 1.684875, 1.683851, + 1.682878, 1.681952, 1.681071, 1.680230, 1.679427, 1.678660, 1.677927, 1.677224, 1.676551, 1.675905, + + 1.675285, 1.674689, 1.674116, 1.673565, 1.673034, 1.672522, 1.672029, 1.671553, 1.671093, 1.670649, + 1.670219, 1.669804, 1.669402, 1.669013, 1.668636, 1.668271, 1.667916, 1.667572, 1.667239, 1.666914, + 1.666600, 1.666294, 1.665996, 1.665707, 1.665425, 1.665151, 1.664885, 1.664625, 1.664371, 1.664125, + 1.663884, 1.663649, 1.663420, 1.663197, 1.662978, 1.662765, 1.662557, 1.662354, 1.662155, 1.661961, + 1.661771, 1.661585, 1.661404, 1.661226, 1.661052, 1.660881, 1.660715, 1.660551, 1.660391, 1.660234 } }, + { 0.975, new [] { + 12.706205, 4.302653, 3.182446, 2.776445, 2.570582, 2.446912, 2.364624, 2.306004, 2.262157, 2.228139, + 2.200985, 2.178813, 2.160369, 2.144787, 2.131450, 2.119905, 2.109816, 2.100922, 2.093024, 2.085963, + 2.079614, 2.073873, 2.068658, 2.063899, 2.059539, 2.055529, 2.051831, 2.048407, 2.045230, 2.042272, + 2.039513, 2.036933, 2.034515, 2.032245, 2.030108, 2.028094, 2.026192, 2.024394, 2.022691, 2.021075, + 2.019541, 2.018082, 2.016692, 2.015368, 2.014103, 2.012896, 2.011741, 2.010635, 2.009575, 2.008559, + + 2.007584, 2.006647, 2.005746, 2.004879, 2.004045, 2.003241, 2.002465, 2.001717, 2.000995, 2.000298, + 1.999624, 1.998972, 1.998341, 1.997730, 1.997138, 1.996564, 1.996008, 1.995469, 1.994945, 1.994437, + 1.993943, 1.993464, 1.992997, 1.992543, 1.992102, 1.991673, 1.991254, 1.990847, 1.990450, 1.990063, + 1.989686, 1.989319, 1.988960, 1.988610, 1.988268, 1.987934, 1.987608, 1.987290, 1.986979, 1.986675, + 1.986377, 1.986086, 1.985802, 1.985523, 1.985251, 1.984984, 1.984723, 1.984467, 1.984217, 1.983972 } }, + { 0.99, new [] { + 31.820516, 6.964557, 4.540703, 3.746947, 3.364930, 3.142668, 2.997952, 2.896459, 2.821438, 2.763769, + 2.718079, 2.680998, 2.650309, 2.624494, 2.602480, 2.583487, 2.566934, 2.552380, 2.539483, 2.527977, + 2.517648, 2.508325, 2.499867, 2.492159, 2.485107, 2.478630, 2.472660, 2.467140, 2.462021, 2.457262, + 2.452824, 2.448678, 2.444794, 2.441150, 2.437723, 2.434494, 2.431447, 2.428568, 2.425841, 2.423257, + 2.420803, 2.418470, 2.416250, 2.414134, 2.412116, 2.410188, 2.408345, 2.406581, 2.404892, 2.403272, + + 2.401718, 2.400225, 2.398790, 2.397410, 2.396081, 2.394801, 2.393568, 2.392377, 2.391229, 2.390119, + 2.389047, 2.388011, 2.387008, 2.386037, 2.385097, 2.384186, 2.383302, 2.382446, 2.381615, 2.380807, + 2.380024, 2.379262, 2.378522, 2.377802, 2.377102, 2.376420, 2.375757, 2.375111, 2.374482, 2.373868, + 2.373270, 2.372687, 2.372119, 2.371564, 2.371022, 2.370493, 2.369977, 2.369472, 2.368979, 2.368497, + 2.368026, 2.367566, 2.367115, 2.366674, 2.366243, 2.365821, 2.365407, 2.365002, 2.364606, 2.364217 } }, + }; + + public const bool debuggingSegmentation = false; + public const bool debuggingTestingRangeNomination = false; + + public static double oneSidedToTwoSidedProbability (double probability) { return 2 * probability - 1; } + public static double twoSidedToOneSidedProbability (double probability) { return (1 - (1 - probability) / 2); } + + public static double min (double[] values) { + var result = values[0]; + for (int i = 1; i < values.Length; i++) + result = Math.Min(result, values[i]); + return result; + } + + public static double max (double[] values) { + var result = values[0]; + for (int i = 1; i < values.Length; i++) + result = Math.Max(result, values[i]); + return result; + } + + public static double sum (double[] values) { + double result = 0; + foreach (var v in values) + result += v; + return result; + } + + public static double mean (double[] values) { + return sum(values) / values.Length; + } + + public static double median (double[] values) { + Array.Sort(values, (a, b) => a.CompareTo(b)); + return values[values.Length / 2]; + } + + public static double squareSum (double[] values) { + double result = 0; + foreach (var v in values) + result += (v * v); + return result; + } + + // With sum and sum of squares, we can compute the sample standard deviation in O(1). + // See https://rniwa.com/2012-11-10/sample-standard-deviation-in-terms-of-sum-and-square-sum-of-samples/ + public static double sampleStandardDeviation (double numberOfSamples, double sum, double squareSum) { + if (numberOfSamples < 2) + return 0; + return Math.Sqrt(squareSum / (numberOfSamples - 1) - sum * sum / (numberOfSamples - 1) / numberOfSamples); + } + + // FIXME + public static double[] supportedConfidenceIntervalProbabilities () { + var supportedProbabilities = new List<double>(); + foreach (var probability in tDistributionByOneSidedProbability.Keys) { + var p = oneSidedToTwoSidedProbability(probability); + supportedProbabilities.Add(Math.Round(p, 2)); + } + return supportedProbabilities.ToArray(); + } + + // FIXME + public static double[] supportedOneSideTTestProbabilities () { + return tDistributionByOneSidedProbability.Keys.ToArray(); + } + + // Computes the delta d s.t. (mean - d, mean + d) is the confidence interval with the specified probability in O(1). + public static double confidenceIntervalDelta (double probability, int numberOfSamples, double sum, double squareSum) { + var oneSidedProbability = twoSidedToOneSidedProbability(probability); + + if (!tDistributionByOneSidedProbability.ContainsKey(oneSidedProbability)) + throw new Exception("Confidence interval not supported"); + if (numberOfSamples - 2 < 0) + return double.NaN; + var deltas = tDistributionByOneSidedProbability[oneSidedProbability]; + var degreesOfFreedom = numberOfSamples - 1; + if (degreesOfFreedom > deltas.Length) + throw new Exception("We only support up to " + deltas.Length + " degrees of freedom"); + + // d = c * S/sqrt(numberOfSamples) where c ~ t-distribution(degreesOfFreedom) and S is the sample standard deviation. + return deltas[degreesOfFreedom - 1] * sampleStandardDeviation(numberOfSamples, sum, squareSum) / Math.Sqrt(numberOfSamples); + } + + public static double[] confidenceInterval (double[] values, double probability = 0.95) { + var sum = Statistics.sum(values); + var mean = sum / values.Length; + var delta = confidenceIntervalDelta(probability, values.Length, sum, squareSum(values)); + return new double[] { mean - delta, mean + delta }; + } + + // Welch's t-test (http://en.wikipedia.org/wiki/Welch%27s_t_test) + public static object testWelchsT (double[] values1, double[] values2, double probability) { + return computeWelchsT(values1, 0, values1.Length, values2, 0, values2.Length, probability).significantlyDifferent; + } + + public class ProbabilityRangeForWelchsT { + public double t; + public double degreesOfFreedom; + public double?[] range; + } + + public static ProbabilityRangeForWelchsT probabilityRangeForWelchsT (double[] values1, double[] values2) { + var result = computeWelchsT(values1, 0, values1.Length, values2, 0, values2.Length); + if (Double.IsNaN(result.t) || Double.IsNaN(result.degreesOfFreedom)) + return new ProbabilityRangeForWelchsT {t = Double.NaN, degreesOfFreedom = Double.NaN, range = new double?[] { null, null } }; + + double? lowerBound = null; + double? upperBound = null; + foreach (var probability in tDistributionByOneSidedProbability.Keys) { + var twoSidedProbability = oneSidedToTwoSidedProbability(probability); + var idx = (int)Math.Round(result.degreesOfFreedom - 1); + if (result.t > tDistributionByOneSidedProbability[probability][idx]) + lowerBound = twoSidedProbability; + else if (lowerBound.HasValue) { + upperBound = twoSidedProbability; + break; + } + } + return new ProbabilityRangeForWelchsT {t = result.t, degreesOfFreedom = result.degreesOfFreedom, range = new [] { lowerBound, upperBound } }; + } + + public class ComputedWelchsT { + public double t; + public double degreesOfFreedom; + public bool significantlyDifferent; + } + + public static ComputedWelchsT computeWelchsT (double[] values1, int startIndex1, int length1, double[] values2, int startIndex2, int length2, double probability = 0.8) { + var stat1 = sampleMeanAndVarianceForValues(values1, startIndex1, length1); + var stat2 = sampleMeanAndVarianceForValues(values2, startIndex2, length2); + var sumOfSampleVarianceOverSampleSize = stat1.variance / stat1.size + stat2.variance / stat2.size; + var t = Math.Abs((stat1.mean - stat2.mean) / Math.Sqrt(sumOfSampleVarianceOverSampleSize)); + + // http://en.wikipedia.org/wiki/Welch–Satterthwaite_equation + var degreesOfFreedom = sumOfSampleVarianceOverSampleSize * sumOfSampleVarianceOverSampleSize + / (stat1.variance * stat1.variance / stat1.size / stat1.size / stat1.degreesOfFreedom + + stat2.variance * stat2.variance / stat2.size / stat2.size / stat2.degreesOfFreedom); + var idx = (int)Math.Round(degreesOfFreedom - 1); + var minT = tDistributionByOneSidedProbability[twoSidedToOneSidedProbability(probability)][idx]; + return new ComputedWelchsT { + t = t, + degreesOfFreedom = degreesOfFreedom, + significantlyDifferent = t > minT, + }; + } + + public class MeanAndVariance { + public double mean, variance; + public double size; + public double degreesOfFreedom; + } + + public static MeanAndVariance sampleMeanAndVarianceForValues (double[] values, int startIndex, int length) { + double sum = 0; + for (var i = 0; i < length; i++) + sum += values[startIndex + i]; + double squareSum = 0; + for (var i = 0; i < length; i++) + squareSum += values[startIndex + i] * values[startIndex + i]; + var sampleMean = sum / length; + // FIXME: Maybe we should be using the biased sample variance. + var unbiasedSampleVariance = (squareSum - sum * sum / length) / (length - 1); + return new MeanAndVariance { + mean = sampleMean, + variance = unbiasedSampleVariance, + size = length, + degreesOfFreedom = length - 1, + }; + } + + public static double[] movingAverage (double[] values, int backwardWindowSize, int forwardWindowSize) { + var averages = new double[values.Length]; + // We use naive O(n^2) algorithm for simplicy as well as to avoid accumulating round-off errors. + for (var i = 0; i < values.Length; i++) { + double sum = 0; + double count = 0; + for (var j = i - backwardWindowSize; j <= i + forwardWindowSize; j++) { + if (j >= 0 && j < values.Length) { + sum += values[j]; + count++; + } + } + averages[i] = sum / count; + } + return averages; + } + + public static double[] cumulativeMovingAverage (double[] values) { + var averages = new double[values.Length]; + double sum = 0; + for (var i = 0; i < values.Length; i++) { + sum += values[i]; + averages[i] = sum / (double)(i + 1); + } + return averages; + } + + public static object exponentialMovingAverage (double[] values, double smoothingFactor) { + var averages = new double[values.Length]; + var movingAverage = values[0]; + averages[0] = movingAverage; + for (var i = 1; i < values.Length; i++) { + movingAverage = smoothingFactor * values[i] + (1 - smoothingFactor) * movingAverage; + averages[i] = movingAverage; + } + return averages; + } + + // The return value is the starting indices of each segment. + public static int[] segmentTimeSeriesGreedyWithStudentsTTest (double[] values, int minLength) { + if (values.Length < 2) + return new int[] { 0 }; + var segments = new List<int>(); + recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, 0, values.Length, minLength, segments); + segments.Add(values.Length); + return segments.ToArray(); + } + + public static int[] segmentTimeSeriesByMaximizingSchwarzCriterion (double[] values, double segmentCountWeight, int gridLength = 500) { + // Split the time series into grids since splitIntoSegmentsUntilGoodEnough is O(n^2). + var totalSegmentation = new List<int> { 0 }; + for (int gridCount = 0, l = (int)Math.Ceiling(values.Length / (double)gridLength); gridCount < l; gridCount++) { + + var gridValues = values.slice(gridCount * gridLength, (gridCount + 1) * gridLength); + var segmentation = splitIntoSegmentsUntilGoodEnough(gridValues, segmentCountWeight); + + if (Statistics.debuggingSegmentation) + Console.WriteLine($"grid={gridCount}, {segmentation}"); + + for (var i = 1; i < segmentation.Length - 1; i++) + totalSegmentation.Add(gridCount * gridLength + segmentation[i]); + } + + if (Statistics.debuggingSegmentation) + Console.WriteLine($"Final segmentation {totalSegmentation}"); + + totalSegmentation.Add(values.Length); + + return totalSegmentation.ToArray(); + } + + public static void recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent (double[] values, int startIndex, int length, int minLength, List<int> segments) { + double tMax = 0; + int? argTMax = null; + for (var i = 1; i < length - 1; i++) { + var firstLength = i; + var secondLength = length - i; + if (firstLength < minLength || secondLength < minLength) + continue; + var result = Statistics.computeWelchsT(values, startIndex, firstLength, values, startIndex + i, secondLength, 0.9); + if (result.significantlyDifferent && result.t > tMax) { + tMax = result.t; + argTMax = i; + } + } + if (tMax <= 0) { + segments.Add(startIndex); + return; + } + recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, startIndex, argTMax.Value, minLength, segments); + recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, startIndex + argTMax.Value, length - argTMax.Value, minLength, segments); + } + + public static int[] splitIntoSegmentsUntilGoodEnough(double[] values, double BirgeAndMassartC = 2.5) { + if (values.Length < 2) + return new[] { 0, values.Length }; + + var matrix = new SampleVarianceUpperTriangularMatrix(values); + + var SchwarzCriterionBeta = Compat.log1p(values.Length - 1) / values.Length; + + var BirgeAndMassartPenalization = (Func<int, double>)((segmentCount) => + segmentCount * (1 + BirgeAndMassartC * Compat.log1p(values.Length / (double)segmentCount - 1)) + ); + + int[] segmentation = null; + var minTotalCost = double.PositiveInfinity; + var maxK = Math.Min(50, values.Length); + + for (var k = 1; k < maxK; k++) { + // var start = Date.now(); + var result = findOptimalSegmentation(values, matrix, k); + var cost = result.cost / (double)values.Length; + var penalty = SchwarzCriterionBeta * BirgeAndMassartPenalization(k); + if (cost + penalty < minTotalCost) { + minTotalCost = cost + penalty; + segmentation = result.segmentation; + } else + maxK = Math.Min(maxK, k + 3); + /* + if (Statistics.debuggingSegmentation) + console.log('splitIntoSegmentsUntilGoodEnough', k, Date.now() - start, cost + penalty); + */ + } + + return segmentation; + } + + public static float[][] allocateCostUpperTriangularForSegmentation (double[] values, int segmentCount) + { + // Dynamic programming. cost[i][k] = The cost to segmenting values up to i into k segments. + var cost = new float[values.Length][]; + for (var segmentEnd = 0; segmentEnd < values.Length; segmentEnd++) + cost[segmentEnd] = new float[segmentCount + 1]; + return cost; + } + + public static int[][] allocatePreviousNodeForSegmentation(double[] values, int segmentCount) + { + // previousNode[i][k] = The start of the last segment in an optimal segmentation that ends at i with k segments. + var previousNode = new int[values.Length][]; + for (var i = 0; i < values.Length; i++) + previousNode[i] = new int[segmentCount + 1]; + return previousNode; + } + + public static bool IsInRange<T> (T[] arr, int index) { + if (index < 0) + return false; + if (index >= arr.Length) + return false; + return true; + } + + public static void findOptimalSegmentationInternal(float[][] cost, int[][] previousNode, double[] values, SampleVarianceUpperTriangularMatrix costMatrix, int segmentCount) + { + // The cost of segmenting single value is always 0. + for (int i = 0; i < cost[0].Length; i++) + cost[0][i] = 0; + for (int i = 0; i < previousNode[0].Length; i++) + previousNode[0][i] = -1; + + for (var segmentStart = 0; segmentStart < values.Length; segmentStart++) { + var costOfOptimalSegmentationThatEndAtCurrentStart = cost[segmentStart]; + for (var k = 0; k < segmentCount; k++) { + var noSegmentationOfLenghtKEndsAtCurrentStart = !IsInRange(previousNode[segmentStart], k); + if (noSegmentationOfLenghtKEndsAtCurrentStart) + continue; + for (var segmentEnd = segmentStart + 1; segmentEnd < values.Length; segmentEnd++) { + var costOfOptimalSegmentationOfLengthK = costOfOptimalSegmentationThatEndAtCurrentStart[k]; + var costOfCurrentSegment = costMatrix.costBetween(segmentStart, segmentEnd); + var totalCost = costOfOptimalSegmentationOfLengthK + costOfCurrentSegment; + if (!IsInRange(previousNode[segmentEnd], k + 1) || totalCost < cost[segmentEnd][k + 1]) { + cost[segmentEnd][k + 1] = (float)totalCost; + previousNode[segmentEnd][k + 1] = segmentStart; + } + } + } + } + } + + public class OptimalSegmentation { + public int[] segmentation; + public float cost; + } + + public static OptimalSegmentation findOptimalSegmentation (double[] values, SampleVarianceUpperTriangularMatrix costMatrix, int segmentCount) { + var cost = allocateCostUpperTriangularForSegmentation(values, segmentCount); + var previousNode = allocatePreviousNodeForSegmentation(values, segmentCount); + + findOptimalSegmentationInternal(cost, previousNode, values, costMatrix, segmentCount); + + if (Statistics.debuggingSegmentation) { + /* + console.log('findOptimalSegmentation with', segmentCount, 'segments'); + for (var end = 0; end < values.length; end++) { + for (var k = 0; k <= segmentCount; k++) { + var start = previousNode[end][k]; + if (start === undefined) + continue; + console.log(`C(segment=[${start}, ${end + 1}], segmentCount=${k})=${cost[end][k]}`); + } + } + */ + } + + var segmentEnd = values.Length - 1; + var segmentation = new int[segmentCount + 1]; + segmentation[segmentCount] = values.Length; + + for (var k = segmentCount; k > 0; k--) { + if (segmentEnd < 0) + break; + + segmentEnd = previousNode[segmentEnd][k]; + segmentation[k - 1] = segmentEnd; + } + + var costOfOptimalSegmentation = cost[values.Length - 1][segmentCount]; + + if (Statistics.debuggingSegmentation) + Console.WriteLine($"Optimal segmentation: {segmentation} with cost = {costOfOptimalSegmentation}"); + + return new OptimalSegmentation {segmentation = segmentation, cost = costOfOptimalSegmentation}; + } +} + +public class SampleVarianceUpperTriangularMatrix { + public float[][] costMatrix; + + public SampleVarianceUpperTriangularMatrix (double[] values) { + // The cost of segment (i, j]. + costMatrix = new float[values.Length - 1][]; + for (var i = 0; i < values.Length - 1; i++) { + var remainingValueCount = values.Length - i - 1; + costMatrix[i] = new float[remainingValueCount]; + var sum = values[i]; + var squareSum = sum * sum; + costMatrix[i][0] = 0; + for (var j = i + 1; j < values.Length; j++) { + var currentValue = values[j]; + sum += currentValue; + squareSum += currentValue * currentValue; + var sampleSize = j - i + 1; + var stdev = Statistics.sampleStandardDeviation(sampleSize, sum, squareSum); + costMatrix[i][j - i - 1] = (float)(stdev > 0 ? sampleSize * Math.Log(stdev * stdev) : 0); + } + } + } + + public double costBetween (int from, int to) { + if (from >= this.costMatrix.Length || from == to) + return 0; // The cost of the segment that starts at the last data point is 0. + return this.costMatrix[from][to - from - 1]; + } +} + +public partial class Benchmark { + public const int WarmingIterationCount = 2; + public const int IterationCount = 7; + public const int InnerIterationCount = 1; + + public double[] d1, d2; + + public Benchmark () { + d1 = new double[] { 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}; + d2 = new double[] { 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}; + } + + public void runIteration() { + // var @params = new double[] { 2.5, 500 }; + const double segmentCountWeight = 2.5; + const int gridLength = 500; + var data = new [] { d1, d2 }; + + var promises = new List<int[]>(); + foreach (var d in data) { + // _invokeSegmentationAlgorithm (string segmentationName, object[] parameters, object[] timeSeriesValues) + // var args = [timeSeriesValues].concat(parameters || []); + // var promise = Task.Run(() => { + // return Statistics.segmentTimeSeriesByMaximizingSchwarzCriterion(d, segmentCountWeight, gridLength); + //}); + var result = Statistics.segmentTimeSeriesByMaximizingSchwarzCriterion(d, segmentCountWeight, gridLength); + promises.Add(result); + } + + var expectedResults = new[] { + new int [] { 0, 97, 174, 211, 301, 1270, 1278, 2696, 3613, 3700 }, + new int [] { 0, 175, 1194, 1237, 2310 } + }; + + for (var i = 0; i < promises.Count; ++i) { + var result = promises[i]; + if (result.ToString() != expectedResults[i].ToString()) + throw new Exception("Bad result"); + } + } + + public void reset() { + } +}; diff --git a/sdks/wasm/standalone-benchmarks/segmentation/segmentation.csproj b/sdks/wasm/standalone-benchmarks/segmentation/segmentation.csproj new file mode 100755 index 00000000000..f57cff9f75d --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/segmentation/segmentation.csproj @@ -0,0 +1,13 @@ +<Project Sdk="Microsoft.NET.Sdk"> + + <PropertyGroup> + <OutputType>Exe</OutputType> + <TargetFramework>netcoreapp2.1</TargetFramework> + </PropertyGroup> + + <ItemGroup> + <Compile Include="..\Compat.cs" Link="Compat.cs" /> + <Compile Include="..\Program.cs" Link="Program.cs" /> + </ItemGroup> + +</Project> diff --git a/sdks/wasm/standalone-benchmarks/segmentation/segmentation.js b/sdks/wasm/standalone-benchmarks/segmentation/segmentation.js new file mode 100755 index 00000000000..b7aa5a64915 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/segmentation/segmentation.js @@ -0,0 +1,553 @@ +"use strict"; +/* + * Copyright (C) 2018 Apple Inc. All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY APPLE INC. ``AS IS'' AND ANY + * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR + * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE INC. OR + * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY + * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + */ + +// Statistics.js +var Statistics = new (function () { + + this.min = function (values) { + return Math.min.apply(Math, values); + } + + this.max = function (values) { + return Math.max.apply(Math, values); + } + + this.sum = function (values) { + return values.length ? values.reduce(function (a, b) { return a + b; }) : 0; + } + + this.mean = function (values) { + return this.sum(values) / values.length; + } + + this.median = function (values) { + return values.sort(function (a, b) { return a - b; })[Math.floor(values.length / 2)]; + } + + this.squareSum = function (values) { + return values.length ? values.reduce(function (sum, value) { return sum + value * value;}, 0) : 0; + } + + // With sum and sum of squares, we can compute the sample standard deviation in O(1). + // See https://rniwa.com/2012-11-10/sample-standard-deviation-in-terms-of-sum-and-square-sum-of-samples/ + this.sampleStandardDeviation = function (numberOfSamples, sum, squareSum) { + if (numberOfSamples < 2) + return 0; + return Math.sqrt(squareSum / (numberOfSamples - 1) - sum * sum / (numberOfSamples - 1) / numberOfSamples); + } + + this.supportedConfidenceIntervalProbabilities = function () { + var supportedProbabilities = []; + for (var probability in tDistributionByOneSidedProbability) + supportedProbabilities.push(oneSidedToTwoSidedProbability(probability).toFixed(2)); + return supportedProbabilities + } + + this.supportedOneSideTTestProbabilities = function () { + return Object.keys(tDistributionByOneSidedProbability); + } + + // Computes the delta d s.t. (mean - d, mean + d) is the confidence interval with the specified probability in O(1). + this.confidenceIntervalDelta = function (probability, numberOfSamples, sum, squareSum) { + var oneSidedProbability = twoSidedToOneSidedProbability(probability); + if (!(oneSidedProbability in tDistributionByOneSidedProbability)) { + throw 'We only support ' + this.supportedConfidenceIntervalProbabilities().map(function (probability) + { return probability * 100 + '%'; } ).join(', ') + ' confidence intervals.'; + } + if (numberOfSamples - 2 < 0) + return NaN; + var deltas = tDistributionByOneSidedProbability[oneSidedProbability]; + var degreesOfFreedom = numberOfSamples - 1; + if (degreesOfFreedom > deltas.length) + throw 'We only support up to ' + deltas.length + ' degrees of freedom'; + + // d = c * S/sqrt(numberOfSamples) where c ~ t-distribution(degreesOfFreedom) and S is the sample standard deviation. + return deltas[degreesOfFreedom - 1] * this.sampleStandardDeviation(numberOfSamples, sum, squareSum) / Math.sqrt(numberOfSamples); + } + + this.confidenceInterval = function (values, probability) { + var sum = this.sum(values); + var mean = sum / values.length; + var delta = this.confidenceIntervalDelta(probability || 0.95, values.length, sum, this.squareSum(values)); + return [mean - delta, mean + delta]; + } + + // Welch's t-test (http://en.wikipedia.org/wiki/Welch%27s_t_test) + this.testWelchsT = function (values1, values2, probability) { + return this.computeWelchsT(values1, 0, values1.length, values2, 0, values2.length, probability).significantlyDifferent; + } + + this.probabilityRangeForWelchsT = function (values1, values2) { + var result = this.computeWelchsT(values1, 0, values1.length, values2, 0, values2.length); + if (isNaN(result.t) || isNaN(result.degreesOfFreedom)) + return {t: NaN, degreesOfFreedom:NaN, range: [null, null]}; + + var lowerBound = null; + var upperBound = null; + for (var probability in tDistributionByOneSidedProbability) { + var twoSidedProbability = oneSidedToTwoSidedProbability(probability); + if (result.t > tDistributionByOneSidedProbability[probability][Math.round(result.degreesOfFreedom - 1)]) + lowerBound = twoSidedProbability; + else if (lowerBound) { + upperBound = twoSidedProbability; + break; + } + } + return {t: result.t, degreesOfFreedom: result.degreesOfFreedom, range: [lowerBound, upperBound]}; + } + + this.computeWelchsT = function (values1, startIndex1, length1, values2, startIndex2, length2, probability) { + var stat1 = sampleMeanAndVarianceForValues(values1, startIndex1, length1); + var stat2 = sampleMeanAndVarianceForValues(values2, startIndex2, length2); + var sumOfSampleVarianceOverSampleSize = stat1.variance / stat1.size + stat2.variance / stat2.size; + var t = Math.abs((stat1.mean - stat2.mean) / Math.sqrt(sumOfSampleVarianceOverSampleSize)); + + // http://en.wikipedia.org/wiki/Welch–Satterthwaite_equation + var degreesOfFreedom = sumOfSampleVarianceOverSampleSize * sumOfSampleVarianceOverSampleSize + / (stat1.variance * stat1.variance / stat1.size / stat1.size / stat1.degreesOfFreedom + + stat2.variance * stat2.variance / stat2.size / stat2.size / stat2.degreesOfFreedom); + var minT = tDistributionByOneSidedProbability[twoSidedToOneSidedProbability(probability || 0.8)][Math.round(degreesOfFreedom - 1)]; + return { + t: t, + degreesOfFreedom: degreesOfFreedom, + significantlyDifferent: t > minT, + }; + } + + this.findRangesForChangeDetectionsWithWelchsTTest = function (values, segmentations, oneSidedPossibility=0.99) { + if (!values.length) + return []; + + const selectedRanges = []; + const twoSidedFromOneSidedPossibility = 2 * oneSidedPossibility - 1; + + for (let i = 1; i + 2 < segmentations.length; i += 2) { + let found = false; + const previousMean = segmentations[i].value; + const currentMean = segmentations[i + 1].value; + console.assert(currentMean != previousMean); + const currentChangePoint = segmentations[i].seriesIndex; + const start = segmentations[i - 1].seriesIndex; + const end = segmentations[i + 2].seriesIndex; + + for (let leftEdge = currentChangePoint - 2, rightEdge = currentChangePoint + 2; leftEdge >= start && rightEdge <= end; leftEdge--, rightEdge++) { + const result = this.computeWelchsT(values, leftEdge, currentChangePoint - leftEdge, values, currentChangePoint, rightEdge - currentChangePoint, twoSidedFromOneSidedPossibility); + if (result.significantlyDifferent) { + selectedRanges.push({ + startIndex: leftEdge, + endIndex: rightEdge - 1, + segmentationStartValue: previousMean, + segmentationEndValue: currentMean + }); + found = true; + break; + } + } + if (!found && Statistics.debuggingTestingRangeNomination) + console.log('Failed to find a testing range at', currentChangePoint, 'changing from', previousMean, 'to', currentMean); + } + + return selectedRanges; + }; + + function sampleMeanAndVarianceForValues(values, startIndex, length) { + var sum = 0; + for (var i = 0; i < length; i++) + sum += values[startIndex + i]; + var squareSum = 0; + for (var i = 0; i < length; i++) + squareSum += values[startIndex + i] * values[startIndex + i]; + var sampleMean = sum / length; + // FIXME: Maybe we should be using the biased sample variance. + var unbiasedSampleVariance = (squareSum - sum * sum / length) / (length - 1); + return { + mean: sampleMean, + variance: unbiasedSampleVariance, + size: length, + degreesOfFreedom: length - 1, + } + } + + this.movingAverage = function (values, backwardWindowSize, forwardWindowSize) { + var averages = new Array(values.length); + // We use naive O(n^2) algorithm for simplicy as well as to avoid accumulating round-off errors. + for (var i = 0; i < values.length; i++) { + var sum = 0; + var count = 0; + for (var j = i - backwardWindowSize; j <= i + forwardWindowSize; j++) { + if (j >= 0 && j < values.length) { + sum += values[j]; + count++; + } + } + averages[i] = sum / count; + } + return averages; + } + + this.cumulativeMovingAverage = function (values) { + var averages = new Array(values.length); + var sum = 0; + for (var i = 0; i < values.length; i++) { + sum += values[i]; + averages[i] = sum / (i + 1); + } + return averages; + } + + this.exponentialMovingAverage = function (values, smoothingFactor) { + var averages = new Array(values.length); + var movingAverage = values[0]; + averages[0] = movingAverage; + for (var i = 1; i < values.length; i++) { + movingAverage = smoothingFactor * values[i] + (1 - smoothingFactor) * movingAverage; + averages[i] = movingAverage; + } + return averages; + } + + // The return value is the starting indices of each segment. + this.segmentTimeSeriesGreedyWithStudentsTTest = function (values, minLength) { + if (values.length < 2) + return [0]; + var segments = new Array; + recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, 0, values.length, minLength, segments); + segments.push(values.length); + return segments; + } + + this.debuggingSegmentation = false; + this.segmentTimeSeriesByMaximizingSchwarzCriterion = function (values, segmentCountWeight, gridSize) { + // Split the time series into grids since splitIntoSegmentsUntilGoodEnough is O(n^2). + var gridLength = gridSize || 500; + var totalSegmentation = [0]; + for (var gridCount = 0; gridCount < Math.ceil(values.length / gridLength); gridCount++) { + var gridValues = values.slice(gridCount * gridLength, (gridCount + 1) * gridLength); + var segmentation = splitIntoSegmentsUntilGoodEnough(gridValues, segmentCountWeight); + + if (Statistics.debuggingSegmentation) + console.log('grid=' + gridCount, segmentation); + + for (var i = 1; i < segmentation.length - 1; i++) + totalSegmentation.push(gridCount * gridLength + segmentation[i]); + } + + if (Statistics.debuggingSegmentation) + console.log('Final Segmentation', totalSegmentation); + + totalSegmentation.push(values.length); + + return totalSegmentation; + } + + function recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, startIndex, length, minLength, segments) { + var tMax = 0; + var argTMax = null; + for (var i = 1; i < length - 1; i++) { + var firstLength = i; + var secondLength = length - i; + if (firstLength < minLength || secondLength < minLength) + continue; + var result = Statistics.computeWelchsT(values, startIndex, firstLength, values, startIndex + i, secondLength, 0.9); + if (result.significantlyDifferent && result.t > tMax) { + tMax = result.t; + argTMax = i; + } + } + if (!tMax) { + segments.push(startIndex); + return; + } + recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, startIndex, argTMax, minLength, segments); + recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, startIndex + argTMax, length - argTMax, minLength, segments); + } + + var tDistributionByOneSidedProbability = { + 0.9: [ + 3.077684, 1.885618, 1.637744, 1.533206, 1.475884, 1.439756, 1.414924, 1.396815, 1.383029, 1.372184, + 1.363430, 1.356217, 1.350171, 1.345030, 1.340606, 1.336757, 1.333379, 1.330391, 1.327728, 1.325341, + 1.323188, 1.321237, 1.319460, 1.317836, 1.316345, 1.314972, 1.313703, 1.312527, 1.311434, 1.310415, + 1.309464, 1.308573, 1.307737, 1.306952, 1.306212, 1.305514, 1.304854, 1.304230, 1.303639, 1.303077, + 1.302543, 1.302035, 1.301552, 1.301090, 1.300649, 1.300228, 1.299825, 1.299439, 1.299069, 1.298714, + + 1.298373, 1.298045, 1.297730, 1.297426, 1.297134, 1.296853, 1.296581, 1.296319, 1.296066, 1.295821, + 1.295585, 1.295356, 1.295134, 1.294920, 1.294712, 1.294511, 1.294315, 1.294126, 1.293942, 1.293763, + 1.293589, 1.293421, 1.293256, 1.293097, 1.292941, 1.292790, 1.292643, 1.292500, 1.292360, 1.292224, + 1.292091, 1.291961, 1.291835, 1.291711, 1.291591, 1.291473, 1.291358, 1.291246, 1.291136, 1.291029, + 1.290924, 1.290821, 1.290721, 1.290623, 1.290527, 1.290432, 1.290340, 1.290250, 1.290161, 1.290075], + 0.95: [ + 6.313752, 2.919986, 2.353363, 2.131847, 2.015048, 1.943180, 1.894579, 1.859548, 1.833113, 1.812461, + 1.795885, 1.782288, 1.770933, 1.761310, 1.753050, 1.745884, 1.739607, 1.734064, 1.729133, 1.724718, + 1.720743, 1.717144, 1.713872, 1.710882, 1.708141, 1.705618, 1.703288, 1.701131, 1.699127, 1.697261, + 1.695519, 1.693889, 1.692360, 1.690924, 1.689572, 1.688298, 1.687094, 1.685954, 1.684875, 1.683851, + 1.682878, 1.681952, 1.681071, 1.680230, 1.679427, 1.678660, 1.677927, 1.677224, 1.676551, 1.675905, + + 1.675285, 1.674689, 1.674116, 1.673565, 1.673034, 1.672522, 1.672029, 1.671553, 1.671093, 1.670649, + 1.670219, 1.669804, 1.669402, 1.669013, 1.668636, 1.668271, 1.667916, 1.667572, 1.667239, 1.666914, + 1.666600, 1.666294, 1.665996, 1.665707, 1.665425, 1.665151, 1.664885, 1.664625, 1.664371, 1.664125, + 1.663884, 1.663649, 1.663420, 1.663197, 1.662978, 1.662765, 1.662557, 1.662354, 1.662155, 1.661961, + 1.661771, 1.661585, 1.661404, 1.661226, 1.661052, 1.660881, 1.660715, 1.660551, 1.660391, 1.660234], + 0.975: [ + 12.706205, 4.302653, 3.182446, 2.776445, 2.570582, 2.446912, 2.364624, 2.306004, 2.262157, 2.228139, + 2.200985, 2.178813, 2.160369, 2.144787, 2.131450, 2.119905, 2.109816, 2.100922, 2.093024, 2.085963, + 2.079614, 2.073873, 2.068658, 2.063899, 2.059539, 2.055529, 2.051831, 2.048407, 2.045230, 2.042272, + 2.039513, 2.036933, 2.034515, 2.032245, 2.030108, 2.028094, 2.026192, 2.024394, 2.022691, 2.021075, + 2.019541, 2.018082, 2.016692, 2.015368, 2.014103, 2.012896, 2.011741, 2.010635, 2.009575, 2.008559, + + 2.007584, 2.006647, 2.005746, 2.004879, 2.004045, 2.003241, 2.002465, 2.001717, 2.000995, 2.000298, + 1.999624, 1.998972, 1.998341, 1.997730, 1.997138, 1.996564, 1.996008, 1.995469, 1.994945, 1.994437, + 1.993943, 1.993464, 1.992997, 1.992543, 1.992102, 1.991673, 1.991254, 1.990847, 1.990450, 1.990063, + 1.989686, 1.989319, 1.988960, 1.988610, 1.988268, 1.987934, 1.987608, 1.987290, 1.986979, 1.986675, + 1.986377, 1.986086, 1.985802, 1.985523, 1.985251, 1.984984, 1.984723, 1.984467, 1.984217, 1.983972], + 0.99: [ + 31.820516, 6.964557, 4.540703, 3.746947, 3.364930, 3.142668, 2.997952, 2.896459, 2.821438, 2.763769, + 2.718079, 2.680998, 2.650309, 2.624494, 2.602480, 2.583487, 2.566934, 2.552380, 2.539483, 2.527977, + 2.517648, 2.508325, 2.499867, 2.492159, 2.485107, 2.478630, 2.472660, 2.467140, 2.462021, 2.457262, + 2.452824, 2.448678, 2.444794, 2.441150, 2.437723, 2.434494, 2.431447, 2.428568, 2.425841, 2.423257, + 2.420803, 2.418470, 2.416250, 2.414134, 2.412116, 2.410188, 2.408345, 2.406581, 2.404892, 2.403272, + + 2.401718, 2.400225, 2.398790, 2.397410, 2.396081, 2.394801, 2.393568, 2.392377, 2.391229, 2.390119, + 2.389047, 2.388011, 2.387008, 2.386037, 2.385097, 2.384186, 2.383302, 2.382446, 2.381615, 2.380807, + 2.380024, 2.379262, 2.378522, 2.377802, 2.377102, 2.376420, 2.375757, 2.375111, 2.374482, 2.373868, + 2.373270, 2.372687, 2.372119, 2.371564, 2.371022, 2.370493, 2.369977, 2.369472, 2.368979, 2.368497, + 2.368026, 2.367566, 2.367115, 2.366674, 2.366243, 2.365821, 2.365407, 2.365002, 2.364606, 2.364217] + }; + function oneSidedToTwoSidedProbability(probability) { return 2 * probability - 1; } + function twoSidedToOneSidedProbability(probability) { return (1 - (1 - probability) / 2); } + + function splitIntoSegmentsUntilGoodEnough(values, BirgeAndMassartC) { + if (values.length < 2) + return [0, values.length]; + + var matrix = new SampleVarianceUpperTriangularMatrix(values); + + var SchwarzCriterionBeta = Math.log1p(values.length - 1) / values.length; + + BirgeAndMassartC = BirgeAndMassartC || 2.5; // Suggested by the authors. + var BirgeAndMassartPenalization = function (segmentCount) { + return segmentCount * (1 + BirgeAndMassartC * Math.log1p(values.length / segmentCount - 1)); + } + + var segmentation; + var minTotalCost = Infinity; + var maxK = Math.min(50, values.length); + + for (var k = 1; k < maxK; k++) { + var start = Date.now(); + var result = findOptimalSegmentation(values, matrix, k); + var cost = result.cost / values.length; + var penalty = SchwarzCriterionBeta * BirgeAndMassartPenalization(k); + if (cost + penalty < minTotalCost) { + minTotalCost = cost + penalty; + segmentation = result.segmentation; + } else + maxK = Math.min(maxK, k + 3); + if (Statistics.debuggingSegmentation) + console.log('splitIntoSegmentsUntilGoodEnough', k, Date.now() - start, cost + penalty); + } + + return segmentation; + } + + function allocateCostUpperTriangularForSegmentation(values, segmentCount) + { + // Dynamic programming. cost[i][k] = The cost to segmenting values up to i into k segments. + var cost = new Array(values.length); + for (var segmentEnd = 0; segmentEnd < values.length; segmentEnd++) + cost[segmentEnd] = new Float32Array(segmentCount + 1); + return cost; + } + + function allocatePreviousNodeForSegmentation(values, segmentCount) + { + // previousNode[i][k] = The start of the last segment in an optimal segmentation that ends at i with k segments. + var previousNode = new Array(values.length); + for (var i = 0; i < values.length; i++) + previousNode[i] = new Array(segmentCount + 1); + return previousNode; + } + + function findOptimalSegmentationInternal(cost, previousNode, values, costMatrix, segmentCount) + { + cost[0] = [0]; // The cost of segmenting single value is always 0. + previousNode[0] = [-1]; + for (var segmentStart = 0; segmentStart < values.length; segmentStart++) { + var costOfOptimalSegmentationThatEndAtCurrentStart = cost[segmentStart]; + for (var k = 0; k < segmentCount; k++) { + var noSegmentationOfLenghtKEndsAtCurrentStart = previousNode[segmentStart][k] === undefined; + if (noSegmentationOfLenghtKEndsAtCurrentStart) + continue; + for (var segmentEnd = segmentStart + 1; segmentEnd < values.length; segmentEnd++) { + var costOfOptimalSegmentationOfLengthK = costOfOptimalSegmentationThatEndAtCurrentStart[k]; + var costOfCurrentSegment = costMatrix.costBetween(segmentStart, segmentEnd); + var totalCost = costOfOptimalSegmentationOfLengthK + costOfCurrentSegment; + if (previousNode[segmentEnd][k + 1] === undefined || totalCost < cost[segmentEnd][k + 1]) { + cost[segmentEnd][k + 1] = totalCost; + previousNode[segmentEnd][k + 1] = segmentStart; + } + } + } + } + } + + function findOptimalSegmentation(values, costMatrix, segmentCount) { + var cost = allocateCostUpperTriangularForSegmentation(values, segmentCount); + var previousNode = allocatePreviousNodeForSegmentation(values, segmentCount); + + findOptimalSegmentationInternal(cost, previousNode, values, costMatrix, segmentCount); + + if (Statistics.debuggingSegmentation) { + console.log('findOptimalSegmentation with', segmentCount, 'segments'); + for (var end = 0; end < values.length; end++) { + for (var k = 0; k <= segmentCount; k++) { + var start = previousNode[end][k]; + if (start === undefined) + continue; + console.log(`C(segment=[${start}, ${end + 1}], segmentCount=${k})=${cost[end][k]}`); + } + } + } + + var segmentEnd = values.length - 1; + var segmentation = new Array(segmentCount + 1); + segmentation[segmentCount] = values.length; + for (var k = segmentCount; k > 0; k--) { + segmentEnd = previousNode[segmentEnd][k]; + segmentation[k - 1] = segmentEnd; + } + var costOfOptimalSegmentation = cost[values.length - 1][segmentCount]; + + if (Statistics.debuggingSegmentation) + console.log('Optimal segmentation:', segmentation, 'with cost =', costOfOptimalSegmentation); + + return {segmentation: segmentation, cost: costOfOptimalSegmentation}; + } + + function SampleVarianceUpperTriangularMatrix(values) { + // The cost of segment (i, j]. + var costMatrix = new Array(values.length - 1); + for (var i = 0; i < values.length - 1; i++) { + var remainingValueCount = values.length - i - 1; + costMatrix[i] = new Float32Array(remainingValueCount); + var sum = values[i]; + var squareSum = sum * sum; + costMatrix[i][0] = 0; + for (var j = i + 1; j < values.length; j++) { + var currentValue = values[j]; + sum += currentValue; + squareSum += currentValue * currentValue; + var sampleSize = j - i + 1; + var stdev = Statistics.sampleStandardDeviation(sampleSize, sum, squareSum); + costMatrix[i][j - i - 1] = stdev > 0 ? sampleSize * Math.log(stdev * stdev) : 0; + } + } + this.costMatrix = costMatrix; + } + + SampleVarianceUpperTriangularMatrix.prototype.costBetween = function(from, to) { + if (from >= this.costMatrix.length || from == to) + return 0; // The cost of the segment that starts at the last data point is 0. + return this.costMatrix[from][to - from - 1]; + } + +})(); + +class Benchmark { + constructor() { + this.d1 = 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,370987008,392921088,378163200,370626560,382029824,365228032,384765952,382304256,374382592,375435264,372224000,372408320,375484416,371417088,373063680,371789824,382992384,374312960,374153216,379752448,373673984,388976640,370274304,381718528,372396032,372920320,373051392,372477952,369123328,372879360,372219904,392192000,372551680,368996352,370192384,379498496,370888704,374292480,370147328,370642944,380588032,370896896,371666944,370024448,370839552,370667520,378220544,371490816,373350400,371224576,372219904,372510720,375754752,388562944,373059584,378142720,372654080,370835456,386736128,372809728,373325824,373276672,372150272,387133440,372412416,382504960,378040320,372613120,368168960,375123968,375136256,384065536,371671040,380882944,382021632,371478528,377614336,372588544,387661824,370311168,370790400,387084288,381628416,384303104,382279680,380313600,379609088,371838976,371834880,367751168,370061312,386146304,368447488,371228672,372101120,373080064,368340992,383873024,395632640,374468608,379928576,381923328,370511872,369000448,373669888,382623744,371200000,389341184,382124032,378892288,373874688,369467392,373313536,378941440,376381440,377860096,370102272,370937856,395755520,385273856,378195968,381595648,382029824,372129792,370794496,378376192,373465088,369266688,368513024,369901568,371245056,373334016,362967040,373473280,376500224,371118080,367845376,368312320,368164864,377597952,379117568,371425280,366784512,370692096,368910336,370978816,372547584,370343936,372080640,371109888,366940160,379387904,368119808,371728384,372416512,369967104,369332224,377061376,385376256,369225728,369848320,389013504,372367360,378388480,377720832,387248128,370417664,381558784,370139136,382668800,367198208,371838976,367915008,367620096,371101696,369205248,373731328,369627136,369651712,381599744,390742016,371814400,371048448,362299392,368099328,379396096,369119232,367681536,366387200,366268416,366825472,368615424,380604416,376455168,367116288,364990464,368521216,366899200,366141440,369451008,379838464,373055488,369520640,393150464,384552960,366624768,368615424,368406528,366325760,365395968,380497920,377622528,379215872,379101184,370495488,373059584,371806208,371269632,387858432,385708032,371236864,370954240,379895808,381620224,372211712,394719232,369860608,372924416,371527680,370757632,368431104,390426624,369766400,379793408,369954816,387121152,387162112,381812736,379297792,382279680,371814400,372318208,371326976,371146752,373252096,369623040,385957888,380936192,385626112,384794624,366374912,389472256,380719104,380309504,368304128,371027968,388665344,370974720,384122880,379248640,372711424,389300224,393555968,387596288,371970048,391942144,372527104,369471488,385052672,385064960,394190848,385081344,372797440,369909760,372535296,369557504,383819776,372375552,375762944,369844224,384839680,388796416,371859456,375693312,372879360,370106368,379752448,373714944,370425856,372535296,378732544,372543488,371085312,371208192,370233344,385236992,378343424,385323008,374513664,391991296,371798016,375418880,382160896,393342976,397946880,395812864,374747136,376135680,373137408,393773056]; + } + + _invokeSegmentationAlgorithm(segmentationName, parameters, timeSeriesValues) + { + var args = [timeSeriesValues].concat(parameters || []); + var method = Statistics[segmentationName]; + return method.apply(Statistics, args); + } + + runIteration() { + const params = [2.5, 500]; + let data = [this.d1, this.d2]; + let results = []; + for (let d of data) + results.push(this._invokeSegmentationAlgorithm("segmentTimeSeriesByMaximizingSchwarzCriterion", params, d)); + + const expectedResults = [ + [0, 97, 174, 211, 301, 1270, 1278, 2696, 3613, 3700], + [0, 175, 1194, 1237, 2310] + ]; + + for (let i = 0; i < results.length; ++i) { + let result = results[i]; + if (result.toString() !== expectedResults[i].toString()) + throw new Error("Bad result"); + } + } + + reset() { + } +}; + + + +function main () { + const iterations = 75, warming_iterations = 20; + + console.log("Initializing..."); + + var b = new Benchmark(); + var timings = new Array(iterations); + + for (var i = 0; i < warming_iterations; i++) + b.runIteration(); + + b.reset(); + + console.log("Running", iterations, "times..."); + + var started = Date.now(); + + for (var i = 0; i < iterations; i++) { + var substarted = Date.now(); + b.runIteration(); + timings[i] = Date.now() - substarted; + } + + console.log("Elapsed", Date.now() - started); + var tsum = 0, tmin = 999999999, tmax = 0; + + for (var i = 0; i < iterations; i++) { + tsum += timings[i]; + tmin = Math.min(tmin, timings[i]); + tmax = Math.max(tmax, timings[i]); + } + + console.log("ms/iter avg =", tsum / iterations); + console.log("min =", tmin); + console.log("max =", tmax); +} + +main();
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/test-runner.js b/sdks/wasm/standalone-benchmarks/test-runner.js new file mode 100755 index 00000000000..5ff287c8f51 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/test-runner.js @@ -0,0 +1,70 @@ +if (process.argv.length != 4) {
+ console.log("usage: node test-runner.js assemblyName packagerOutputDirectory");
+ process.exit(1);
+}
+
+var root = process.argv[3];
+var assemblyName = process.argv[2];
+
+var vm = require("vm");
+var fs = require("fs");
+var path = require("path");
+
+var context = Object.create(null);
+
+// Necessary because dotnet.js decides we're v8/sm shell without it
+context.process = process;
+
+// dotnet.js assumes __dirname and similar globals will be available but they aren't
+// unless you're the top-level script being run from the command line
+context.require = require;
+context.console = console;
+context.setTimeout = setTimeout;
+context.setInterval = setInterval;
+context.clearInterval = clearInterval;
+
+context.App = {
+ init: function () {
+ console.log("Priming interpreter...");
+ var wu = context.Module.mono_bind_static_method ("[" + assemblyName + "] Program:WakeUp");
+ wu();
+ console.log("Sleeping to allow time for tiered JIT...");
+ setTimeout(function () {
+ var f = context.Module.cwrap ('mono_wasm_enable_on_demand_gc', 'void', []);
+ f ();
+ console.log("Running benchmark...");
+ context.Module.mono_call_assembly_entry_point (assemblyName, []);
+ console.log("Benchmark complete.");
+ }, 5000);
+ }
+};
+context.global = context;
+
+var contextOptions = {};
+vm.createContext(context, contextOptions);
+
+function loadAndRun (filename) {
+ var virtualFilename, virtualDirname, absoluteRoot;
+ if ((root[0] === "/") || (root[1] === ":"))
+ absoluteRoot = root;
+ else
+ absoluteRoot = path.normalize(path.join(process.cwd(), root));
+
+ virtualFilename = path.join(absoluteRoot, filename);
+ virtualDirname = path.dirname(virtualFilename);
+
+ var runOptions = {};
+ var text = fs.readFileSync(virtualFilename);
+ console.log("Compiling " + filename);
+ var script = new vm.Script(text, virtualFilename);
+ console.log("Running " + filename);
+
+ context.__filename = virtualFilename;
+ context.__dirname = virtualDirname;
+
+ script.runInContext(context, runOptions);
+};
+
+loadAndRun("mono-config.js");
+loadAndRun("runtime.js");
+loadAndRun("dotnet.js");
\ No newline at end of file diff --git a/sdks/wasm/standalone-benchmarks/wasm-aot/BLANK b/sdks/wasm/standalone-benchmarks/wasm-aot/BLANK new file mode 100755 index 00000000000..e69de29bb2d --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/wasm-aot/BLANK diff --git a/sdks/wasm/standalone-benchmarks/wasm/BLANK b/sdks/wasm/standalone-benchmarks/wasm/BLANK new file mode 100644 index 00000000000..e69de29bb2d --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/wasm/BLANK diff --git a/sdks/wasm/standalone-benchmarks/wasmbenches.sln b/sdks/wasm/standalone-benchmarks/wasmbenches.sln new file mode 100755 index 00000000000..51fd645b020 --- /dev/null +++ b/sdks/wasm/standalone-benchmarks/wasmbenches.sln @@ -0,0 +1,43 @@ + +Microsoft Visual Studio Solution File, Format Version 12.00 +# Visual Studio 15 +VisualStudioVersion = 15.0.28307.779 +MinimumVisualStudioVersion = 10.0.40219.1 +Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "segmentation", "segmentation\segmentation.csproj", "{1AC0FA2E-B317-4B55-ADF4-0F7C7B3BA637}" +EndProject +Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "poker", "poker\poker.csproj", "{09FF7D11-4B6C-41DF-9332-19337E7F2852}" +EndProject +Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "bilinear", "bilinear\bilinear.csproj", "{3777441D-92CE-4FE0-88A7-B699C165BD3D}" +EndProject +Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "exceptions", "exceptions\exceptions.csproj", "{D6780F16-D363-4860-A464-524F18ACB58C}" +EndProject +Global + GlobalSection(SolutionConfigurationPlatforms) = preSolution + Debug|Any CPU = Debug|Any CPU + Release|Any CPU = Release|Any CPU + EndGlobalSection + GlobalSection(ProjectConfigurationPlatforms) = postSolution + {1AC0FA2E-B317-4B55-ADF4-0F7C7B3BA637}.Debug|Any CPU.ActiveCfg = Debug|Any CPU + {1AC0FA2E-B317-4B55-ADF4-0F7C7B3BA637}.Debug|Any CPU.Build.0 = Debug|Any CPU + {1AC0FA2E-B317-4B55-ADF4-0F7C7B3BA637}.Release|Any CPU.ActiveCfg = Release|Any CPU + {1AC0FA2E-B317-4B55-ADF4-0F7C7B3BA637}.Release|Any CPU.Build.0 = Release|Any CPU + {09FF7D11-4B6C-41DF-9332-19337E7F2852}.Debug|Any CPU.ActiveCfg = Debug|Any CPU + {09FF7D11-4B6C-41DF-9332-19337E7F2852}.Debug|Any CPU.Build.0 = Debug|Any CPU + {09FF7D11-4B6C-41DF-9332-19337E7F2852}.Release|Any CPU.ActiveCfg = Release|Any CPU + {09FF7D11-4B6C-41DF-9332-19337E7F2852}.Release|Any CPU.Build.0 = Release|Any CPU + {3777441D-92CE-4FE0-88A7-B699C165BD3D}.Debug|Any CPU.ActiveCfg = Debug|Any CPU + {3777441D-92CE-4FE0-88A7-B699C165BD3D}.Debug|Any CPU.Build.0 = Debug|Any CPU + {3777441D-92CE-4FE0-88A7-B699C165BD3D}.Release|Any CPU.ActiveCfg = Release|Any CPU + {3777441D-92CE-4FE0-88A7-B699C165BD3D}.Release|Any CPU.Build.0 = Release|Any CPU + {D6780F16-D363-4860-A464-524F18ACB58C}.Debug|Any CPU.ActiveCfg = Debug|Any CPU + {D6780F16-D363-4860-A464-524F18ACB58C}.Debug|Any CPU.Build.0 = Debug|Any CPU + {D6780F16-D363-4860-A464-524F18ACB58C}.Release|Any CPU.ActiveCfg = Release|Any CPU + {D6780F16-D363-4860-A464-524F18ACB58C}.Release|Any CPU.Build.0 = Release|Any CPU + EndGlobalSection + GlobalSection(SolutionProperties) = preSolution + HideSolutionNode = FALSE + EndGlobalSection + GlobalSection(ExtensibilityGlobals) = postSolution + SolutionGuid = {082FC9E2-78FD-4AC5-B8B6-D199366B988A} + EndGlobalSection +EndGlobal |