added lambdas to complexity report

include/benchmark/benchmark_api.h

@@ -152,6 +152,7 @@ BENCHMARK(BM_test)->Unit(benchmark::kMillisecond);
 #include <assert.h>
 #include <stddef.h>
 #include <stdint.h>
+#include <functional>
 
 #include "macros.h"
 
@@ -247,15 +248,20 @@ enum BigO {
   oNCubed,
   oLogN,
   oNLogN,
-  oAuto
+  oAuto,
+  oLambda
 };
 
+// BigOFunc is passed to a benchmark in order to specify the asymptotic 
+// computational complexity for the benchmark.
+typedef double(BigOFunc)(size_t);
+
 // State is passed to a running Benchmark and contains state for the
 // benchmark to use.
 class State {
 public:
   State(size_t max_iters, bool has_x, int x, bool has_y, int y,
-        int thread_i, int n_threads);
+    int thread_i, int n_threads);
 
   // Returns true iff the benchmark should continue through another iteration.
   // NOTE: A benchmark may not return from the test until KeepRunning() has
@@ -268,13 +274,13 @@ public:
     }
     bool const res = total_iterations_++ < max_iterations;
     if (BENCHMARK_BUILTIN_EXPECT(!res, false)) {
-        assert(started_ && (!finished_ || error_occurred_));
-        if (!error_occurred_) {
-            PauseTiming();
-        }
-        // Total iterations now is one greater than max iterations. Fix this.
-        total_iterations_ = max_iterations;
-        finished_ = true;
+      assert(started_ && (!finished_ || error_occurred_));
+      if (!error_occurred_) {
+        PauseTiming();
+      }
+      // Total iterations now is one greater than max iterations. Fix this.
+      total_iterations_ = max_iterations;
+      finished_ = true;
     }
     return res;
   }
@@ -359,7 +365,7 @@ public:
   // represent the length of N.
   BENCHMARK_ALWAYS_INLINE
   void SetComplexityN(size_t complexity_n) {
-    complexity_n_ = complexity_n;
+	  complexity_n_ = complexity_n;
   }
 
   BENCHMARK_ALWAYS_INLINE
@@ -533,10 +539,14 @@ public:
   // to control how many iterations are run, and in the printing of items/second
   // or MB/second values.
   Benchmark* UseManualTime();
-
+  
   // Set the asymptotic computational complexity for the benchmark. If called
   // the asymptotic computational complexity will be shown on the output. 
   Benchmark* Complexity(BigO complexity = benchmark::oAuto);
+  
+  // Set the asymptotic computational complexity for the benchmark. If called
+  // the asymptotic computational complexity will be shown on the output.
+  Benchmark* Complexity(BigOFunc* complexity);
 
   // Support for running multiple copies of the same benchmark concurrently
   // in multiple threads.  This may be useful when measuring the scaling

include/benchmark/reporter.h

@@ -83,11 +83,12 @@ class BenchmarkReporter {
 
     // This is set to 0.0 if memory tracing is not enabled.
     double max_heapbytes_used;
-
+    
     // Keep track of arguments to compute asymptotic complexity
-    BigO   complexity;
-    int complexity_n;
-
+    BigO complexity;
+    BigOFunc* complexity_lambda;
+    size_t complexity_n;
+    
     // Inform print function whether the current run is a complexity report
     bool report_big_o;
     bool report_rms;
@@ -113,7 +114,7 @@ class BenchmarkReporter {
   // 'reports' contains additional entries representing the asymptotic
   // complexity and RMS of that benchmark family.
   virtual void ReportRuns(const std::vector<Run>& report) = 0;
-
+  
   // Called once and only once after ever group of benchmarks is run and
   // reported.
   virtual void Finalize() {}
@@ -159,7 +160,7 @@ class ConsoleReporter : public BenchmarkReporter {
   virtual bool ReportContext(const Context& context);
   virtual void ReportRuns(const std::vector<Run>& reports);
 
-protected:
+ protected:
   virtual void PrintRunData(const Run& report);
 
   size_t name_field_width_;
@@ -189,25 +190,25 @@ private:
 
 inline const char* GetTimeUnitString(TimeUnit unit) {
   switch (unit) {
-    case kMillisecond:
-      return "ms";
-    case kMicrosecond:
-      return "us";
-    case kNanosecond:
-    default:
-      return "ns";
+  case kMillisecond:
+    return "ms";
+  case kMicrosecond:
+    return "us";
+  case kNanosecond:
+  default:
+    return "ns";
   }
 }
 
 inline double GetTimeUnitMultiplier(TimeUnit unit) {
-    switch (unit) {
-    case kMillisecond:
-      return 1e3;
-    case kMicrosecond:
-      return 1e6;
-    case kNanosecond:
-    default:
-      return 1e9;
+  switch (unit) {
+  case kMillisecond:
+    return 1e3;
+  case kMicrosecond:
+    return 1e6;
+  case kNanosecond:
+  default:
+    return 1e9;
   }
 }
 

src/complexity.cc

@@ -25,43 +25,43 @@
 #include <functional>
 
 namespace benchmark {
-  
+
 // Internal function to calculate the different scalability forms
-std::function<double(int)> FittingCurve(BigO complexity) {
+BigOFunc* FittingCurve(BigO complexity) {
   switch (complexity) {
-    case oN:
-      return [](int n) {return n; };
-    case oNSquared:
-      return [](int n) {return n*n; };
-    case oNCubed:
-      return [](int n) {return n*n*n; };
-    case oLogN:
-      return [](int n) {return log2(n); };
-    case oNLogN:
-      return [](int n) {return n * log2(n); };
-    case o1:
-    default:
-      return [](int) {return 1; };
+  case oN:
+    return [](size_t n) -> double {return n; };
+  case oNSquared:
+    return [](size_t n) -> double {return n * n; };
+  case oNCubed:
+    return [](size_t n) -> double {return n * n * n; };
+  case oLogN:
+    return [](size_t n) {return log2(n); };
+  case oNLogN:
+    return [](size_t n) {return n * log2(n); };
+  case o1:
+  default:
+    return [](size_t) {return 1.0; };
   }
 }
 
 // Function to return an string for the calculated complexity
 std::string GetBigOString(BigO complexity) {
   switch (complexity) {
-    case oN:
-      return "* N";
-    case oNSquared:
-      return "* N**2";
-    case oNCubed:
-      return "* N**3";
-    case oLogN:
-      return "* lgN";
-    case oNLogN:
-      return "* NlgN";
-    case o1:
-      return "* 1";
-    default:
-      return "";
+  case oN:
+    return "N";
+  case oNSquared:
+    return "N^2";
+  case oNCubed:
+    return "N^3";
+  case oLogN:
+    return "lgN";
+  case oNLogN:
+    return "NlgN";
+  case o1:
+    return "(1)";
+  default:
+    return "f(N)";
   }
 }
 
@@ -75,21 +75,9 @@ std::string GetBigOString(BigO complexity) {
 // For a deeper explanation on the algorithm logic, look the README file at
 // http://github.com/ismaelJimenez/Minimal-Cpp-Least-Squared-Fit
 
-// This interface is currently not used from the oustide, but it has been 
-// provided for future upgrades. If in the future it is not needed to support 
-// Cxx03, then all the calculations could be upgraded to use lambdas because 
-// they are more powerful and provide a cleaner inferface than enumerators, 
-// but complete implementation with lambdas will not work for Cxx03 
-// (e.g. lack of std::function).
-// In case lambdas are implemented, the interface would be like :
-//   -> Complexity([](int n) {return n;};)
-// and any arbitrary and valid  equation would be allowed, but the option to 
-// calculate the best fit to the most common scalability curves will still 
-// be kept.
-
-LeastSq CalculateLeastSq(const std::vector<int>& n, 
-                         const std::vector<double>& time, 
-                         std::function<double(int)> fitting_curve) {
+LeastSq MinimalLeastSq(const std::vector<int>& n,
+                       const std::vector<double>& time,
+                       BigOFunc* fitting_curve) {
   double sigma_gn = 0.0;
   double sigma_gn_squared = 0.0;
   double sigma_time = 0.0;
@@ -105,6 +93,7 @@ LeastSq CalculateLeastSq(const std::vector<int>& n,
   }
 
   LeastSq result;
+  result.complexity = oLambda;
 
   // Calculate complexity.
   result.coef = sigma_time_gn / sigma_gn_squared;
@@ -144,19 +133,19 @@ LeastSq MinimalLeastSq(const std::vector<int>& n,
       oLogN, oN, oNLogN, oNSquared, oNCubed };
 
     // Take o1 as default best fitting curve
-    best_fit = CalculateLeastSq(n, time, FittingCurve(o1));
+    best_fit = MinimalLeastSq(n, time, FittingCurve(o1));
     best_fit.complexity = o1;
 
     // Compute all possible fitting curves and stick to the best one
     for (const auto& fit : fit_curves) {
-      LeastSq current_fit = CalculateLeastSq(n, time, FittingCurve(fit));
+      LeastSq current_fit = MinimalLeastSq(n, time, FittingCurve(fit));
       if (current_fit.rms < best_fit.rms) {
         best_fit = current_fit;
         best_fit.complexity = fit;
       }
     }
   } else {
-    best_fit = CalculateLeastSq(n, time, FittingCurve(complexity));
+    best_fit = MinimalLeastSq(n, time, FittingCurve(complexity));
     best_fit.complexity = complexity;
   }
 
@@ -164,14 +153,14 @@ LeastSq MinimalLeastSq(const std::vector<int>& n,
 }
 
 std::vector<BenchmarkReporter::Run> ComputeStats(
-    const std::vector<BenchmarkReporter::Run>& reports)
+  const std::vector<BenchmarkReporter::Run>& reports)
 {
   typedef BenchmarkReporter::Run Run;
   std::vector<Run> results;
 
   auto error_count = std::count_if(
-      reports.begin(), reports.end(),
-      [](Run const& run) {return run.error_occurred;});
+    reports.begin(), reports.end(),
+    [](Run const& run) {return run.error_occurred;});
 
   if (reports.size() - error_count < 2) {
     // We don't report aggregated data if there was a single run.
@@ -193,9 +182,9 @@ std::vector<BenchmarkReporter::Run> ComputeStats(
     if (run.error_occurred)
       continue;
     real_accumulated_time_stat +=
-        Stat1_d(run.real_accumulated_time/run.iterations, run.iterations);
+      Stat1_d(run.real_accumulated_time/run.iterations, run.iterations);
     cpu_accumulated_time_stat +=
-        Stat1_d(run.cpu_accumulated_time/run.iterations, run.iterations);
+      Stat1_d(run.cpu_accumulated_time/run.iterations, run.iterations);
     items_per_second_stat += Stat1_d(run.items_per_second, run.iterations);
     bytes_per_second_stat += Stat1_d(run.bytes_per_second, run.iterations);
   }
@@ -205,9 +194,9 @@ std::vector<BenchmarkReporter::Run> ComputeStats(
   mean_data.benchmark_name = reports[0].benchmark_name + "_mean";
   mean_data.iterations = run_iterations;
   mean_data.real_accumulated_time = real_accumulated_time_stat.Mean() *
-                                     run_iterations;
+    run_iterations;
   mean_data.cpu_accumulated_time = cpu_accumulated_time_stat.Mean() *
-                                    run_iterations;
+    run_iterations;
   mean_data.bytes_per_second = bytes_per_second_stat.Mean();
   mean_data.items_per_second = items_per_second_stat.Mean();
 
@@ -225,9 +214,9 @@ std::vector<BenchmarkReporter::Run> ComputeStats(
   stddev_data.report_label = mean_data.report_label;
   stddev_data.iterations = 0;
   stddev_data.real_accumulated_time =
-      real_accumulated_time_stat.StdDev();
+    real_accumulated_time_stat.StdDev();
   stddev_data.cpu_accumulated_time =
-      cpu_accumulated_time_stat.StdDev();
+    cpu_accumulated_time_stat.StdDev();
   stddev_data.bytes_per_second = bytes_per_second_stat.StdDev();
   stddev_data.items_per_second = items_per_second_stat.StdDev();
 
@@ -237,7 +226,7 @@ std::vector<BenchmarkReporter::Run> ComputeStats(
 }
 
 std::vector<BenchmarkReporter::Run> ComputeBigO(
-    const std::vector<BenchmarkReporter::Run>& reports)
+  const std::vector<BenchmarkReporter::Run>& reports)
 {
   typedef BenchmarkReporter::Run Run;
   std::vector<Run> results;
@@ -256,14 +245,16 @@ std::vector<BenchmarkReporter::Run> ComputeBigO(
     cpu_time.push_back(run.cpu_accumulated_time/run.iterations);
   }
 
-  LeastSq result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity);
-
-  // result_cpu.complexity is passed as parameter to result_real because in case
-  // reports[0].complexity is oAuto, the noise on the measured data could make
-  // the best fit function of Cpu and Real differ. In order to solve this, we
-  // take the best fitting function for the Cpu, and apply it to Real data.
-  LeastSq result_real = MinimalLeastSq(n, real_time, result_cpu.complexity);
+  LeastSq result_cpu;
+  LeastSq result_real;
 
+  if (reports[0].complexity != oLambda) {
+    result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity);
+    result_real = MinimalLeastSq(n, real_time, result_cpu.complexity);
+  } else {
+    result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity_lambda);
+    result_real = MinimalLeastSq(n, real_time, reports[0].complexity_lambda);
+  }
   std::string benchmark_name = reports[0].benchmark_name.substr(0, reports[0].benchmark_name.find('/'));
 
   // Get the data from the accumulator to BenchmarkReporter::Run's.

src/complexity.h

@@ -26,15 +26,15 @@
 
 namespace benchmark {
 
-// Return a vector containing the mean and standard devation information for
-// the specified list of reports. If 'reports' contains less than two
-// non-errored runs an empty vector is returned
-std::vector<BenchmarkReporter::Run> ComputeStats(
+  // Return a vector containing the mean and standard devation information for
+  // the specified list of reports. If 'reports' contains less than two
+  // non-errored runs an empty vector is returned
+  std::vector<BenchmarkReporter::Run> ComputeStats(
     const std::vector<BenchmarkReporter::Run>& reports);
 
-// Return a vector containing the bigO and RMS information for the specified
-// list of reports. If 'reports.size() < 2' an empty vector is returned.
-std::vector<BenchmarkReporter::Run> ComputeBigO(
+  // Return a vector containing the bigO and RMS information for the specified
+  // list of reports. If 'reports.size() < 2' an empty vector is returned.
+  std::vector<BenchmarkReporter::Run> ComputeBigO(
     const std::vector<BenchmarkReporter::Run>& reports);
 
 // This data structure will contain the result returned by MinimalLeastSq
@@ -60,11 +60,5 @@ struct LeastSq {
 // Function to return an string for the calculated complexity
 std::string GetBigOString(BigO complexity);
 
-// Find the coefficient for the high-order term in the running time, by
-// minimizing the sum of squares of relative error.
-LeastSq MinimalLeastSq(const std::vector<int>& n,
-                       const std::vector<double>& time,
-                       const BigO complexity = oAuto);
-
 } // end namespace benchmark
 #endif // COMPLEXITY_H_

src/console_reporter.cc

@@ -90,8 +90,8 @@ void ConsoleReporter::PrintRunData(const Run& result) {
   const double cpu_time = result.GetAdjustedCPUTime();
 
   if(result.report_big_o) {
-    std::string big_o = result.report_big_o ? GetBigOString(result.complexity) : "";
-    ColorPrintf(Out, COLOR_YELLOW, "%10.4f %s %10.4f %s ",
+    std::string big_o = GetBigOString(result.complexity);
+    ColorPrintf(Out, COLOR_YELLOW, "%10.2f %s %10.2f %s ",
                 real_time, big_o.c_str(), cpu_time, big_o.c_str());
   } else if(result.report_rms) {
     ColorPrintf(Out, COLOR_YELLOW, "%10.0f %% %10.0f %% ",

src/csv_reporter.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "benchmark/reporter.h"
+#include "complexity.h"
 
 #include <cstdint>
 #include <algorithm>
@@ -87,8 +88,10 @@ void CSVReporter::PrintRunData(const Run & run) {
   Out << run.GetAdjustedRealTime() << ",";
   Out << run.GetAdjustedCPUTime() << ",";
 
-  // Do not print timeLabel on RMS report
-  if(!run.report_rms) {
+  // Do not print timeLabel on bigO and RMS report
+  if(run.report_big_o) {
+    Out << GetBigOString(run.complexity);
+  } else if(!run.report_rms){
     Out << GetTimeUnitString(run.time_unit);
   }
   Out << ",";

src/json_reporter.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "benchmark/reporter.h"
+#include "complexity.h"
 
 #include <cstdint>
 #include <algorithm>
@@ -132,15 +133,29 @@ void JSONReporter::PrintRunData(Run const& run) {
         out << indent
             << FormatKV("iterations", run.iterations)
             << ",\n";
-    }
-    out << indent
-        << FormatKV("real_time", RoundDouble(run.GetAdjustedRealTime()))
-        << ",\n";
-    out << indent
-        << FormatKV("cpu_time", RoundDouble(run.GetAdjustedCPUTime()));
-    if(!run.report_rms) {
+        out << indent
+            << FormatKV("real_time", RoundDouble(run.GetAdjustedRealTime()))
+            << ",\n";
+        out << indent
+            << FormatKV("cpu_time", RoundDouble(run.GetAdjustedCPUTime()));
         out << ",\n" << indent
             << FormatKV("time_unit", GetTimeUnitString(run.time_unit));
+    } else if(run.report_big_o) {
+        out << indent
+            << FormatKV("cpu_coefficient", RoundDouble(run.GetAdjustedCPUTime()))
+            << ",\n";
+        out << indent
+            << FormatKV("real_coefficient", RoundDouble(run.GetAdjustedRealTime()))
+            << ",\n";
+        out << indent
+            << FormatKV("big_o", GetBigOString(run.complexity))
+            << ",\n";
+        out << indent
+            << FormatKV("time_unit", GetTimeUnitString(run.time_unit));
+    } else if(run.report_rms) {
+        out << indent
+            << FormatKV("rms", RoundDouble(run.GetAdjustedCPUTime()*100))
+            << "%";
     }
     if (run.bytes_per_second > 0.0) {
         out << ",\n" << indent