diff --git a/Criterion.hs b/Criterion.hs
--- a/Criterion.hs
+++ b/Criterion.hs
@@ -59,4 +59,5 @@
   initializeTime
   withConfig cfg $ do
     _ <- note "benchmarking...\n"
-    runAndAnalyseOne 0 "function" bm
+    Analysed rpt <- runAndAnalyseOne 0 "function" bm
+    return rpt
diff --git a/Criterion/IO.hs b/Criterion/IO.hs
--- a/Criterion/IO.hs
+++ b/Criterion/IO.hs
@@ -13,13 +13,12 @@
 module Criterion.IO
     (
       header
-    , hGetReports
-    , hPutReports
-    , readReports
-    , writeReports
+    , hGetRecords
+    , hPutRecords
+    , readRecords
+    , writeRecords
     ) where
 
-import Criterion.Types (Report(..))
 import Data.Binary (Binary(..), encode)
 #if MIN_VERSION_binary(0, 6, 3)
 import Data.Binary.Get (runGetOrFail)
@@ -41,27 +40,27 @@
   putByteString "criterio"
   mapM_ (putWord16be . fromIntegral) (versionBranch version)
 
--- | Read all reports from the given 'Handle'.
-hGetReports :: Handle -> IO (Either String [Report])
-hGetReports handle = do
+-- | Read all records from the given 'Handle'.
+hGetRecords :: Binary a => Handle -> IO (Either String [a])
+hGetRecords handle = do
   bs <- L.hGet handle (fromIntegral (L.length header))
   if bs == header
     then Right `fmap` readAll handle
     else return $ Left "unexpected header"
 
--- | Write reports to the given 'Handle'.
-hPutReports :: Handle -> [Report] -> IO ()
-hPutReports handle rs = do
+-- | Write records to the given 'Handle'.
+hPutRecords :: Binary a => Handle -> [a] -> IO ()
+hPutRecords handle rs = do
   L.hPut handle header
   mapM_ (L.hPut handle . encode) rs
 
--- | Read all reports from the given file.
-readReports :: FilePath -> IO (Either String [Report])
-readReports path = withFile path ReadMode hGetReports
+-- | Read all records from the given file.
+readRecords :: Binary a => FilePath -> IO (Either String [a])
+readRecords path = withFile path ReadMode hGetRecords
 
--- | Write reports to the given file.
-writeReports :: FilePath -> [Report] -> IO ()
-writeReports path rs = withFile path WriteMode (flip hPutReports rs)
+-- | Write records to the given file.
+writeRecords :: Binary a => FilePath -> [a] -> IO ()
+writeRecords path rs = withFile path WriteMode (flip hPutRecords rs)
 
 #if MIN_VERSION_binary(0, 6, 3)
 readAll :: Binary a => Handle -> IO [a]
diff --git a/Criterion/IO/Printf.hs b/Criterion/IO/Printf.hs
--- a/Criterion/IO/Printf.hs
+++ b/Criterion/IO/Printf.hs
@@ -25,7 +25,7 @@
 import Criterion.Monad (Criterion)
 import Criterion.Types (Config(csvFile, verbosity), Verbosity(..))
 import Data.Foldable (forM_)
-import System.IO (Handle, stderr, stdout)
+import System.IO (Handle, hFlush, stderr, stdout)
 import Text.Printf (PrintfArg)
 import qualified Data.ByteString.Lazy as B
 import qualified Data.Csv as Csv
@@ -34,7 +34,7 @@
 -- First item is the action to print now, given all the arguments
 -- gathered together so far.  The second item is the function that
 -- will take a further argument and give back a new PrintfCont.
-data PrintfCont = PrintfCont (IO ()) (PrintfArg a => a -> PrintfCont)
+data PrintfCont = PrintfCont (IO ()) (forall a. PrintfArg a => a -> PrintfCont)
 
 -- | An internal class that acts like Printf/HPrintf.
 --
@@ -47,12 +47,12 @@
 instance CritHPrintfType (Criterion a) where
   chPrintfImpl check (PrintfCont final _)
     = do x <- ask
-         when (check x) (liftIO final)
+         when (check x) (liftIO (final >> hFlush stderr >> hFlush stdout))
          return undefined
 
 instance CritHPrintfType (IO a) where
   chPrintfImpl _ (PrintfCont final _)
-    = final >> return undefined
+    = final >> hFlush stderr >> hFlush stdout >> return undefined
 
 instance (CritHPrintfType r, PrintfArg a) => CritHPrintfType (a -> r) where
   chPrintfImpl check (PrintfCont _ anotherArg) x
diff --git a/Criterion/Internal.hs b/Criterion/Internal.hs
--- a/Criterion/Internal.hs
+++ b/Criterion/Internal.hs
@@ -14,39 +14,48 @@
     (
       runAndAnalyse
     , runAndAnalyseOne
-    , runNotAnalyse
+    , runOne
+    , runFixedIters
     ) where
 
+import Control.Applicative ((<$>))
 import Control.DeepSeq (rnf)
 import Control.Exception (evaluate)
 import Control.Monad (foldM, forM_, void, when)
 import Control.Monad.Reader (ask, asks)
-import Control.Monad.Trans (liftIO)
+import Control.Monad.Trans (MonadIO, liftIO)
 import Control.Monad.Trans.Except
 import Data.Binary (encode)
 import Data.Int (Int64)
 import qualified Data.ByteString.Lazy as L
 import Criterion.Analysis (analyseSample, noteOutliers)
-import Criterion.IO (header, hGetReports)
+import Criterion.IO (header, hGetRecords)
 import Criterion.IO.Printf (note, printError, prolix, writeCsv)
 import Criterion.Measurement (runBenchmark, secs)
 import Criterion.Monad (Criterion)
 import Criterion.Report (report)
 import Criterion.Types hiding (measure)
 import qualified Data.Map as Map
+import Data.Vector (Vector)
 import Statistics.Resampling.Bootstrap (Estimate(..))
 import System.Directory (getTemporaryDirectory, removeFile)
 import System.IO (IOMode(..), SeekMode(..), hClose, hSeek, openBinaryFile,
                   openBinaryTempFile)
 import Text.Printf (printf)
 
--- | Run a single benchmark and analyse its performance.
-runAndAnalyseOne :: Int -> String -> Benchmarkable -> Criterion Report
-runAndAnalyseOne i desc bm = do
+-- | Run a single benchmark.
+runOne :: Int -> String -> Benchmarkable -> Criterion DataRecord
+runOne i desc bm = do
   Config{..} <- ask
   (meas,timeTaken) <- liftIO $ runBenchmark bm timeLimit
   when (timeTaken > timeLimit * 1.25) .
     void $ prolix "measurement took %s\n" (secs timeTaken)
+  return (Measurement i desc meas)
+
+-- | Analyse a single benchmark.
+analyseOne :: Int -> String -> Vector Measured -> Criterion DataRecord
+analyseOne i desc meas = do
+  Config{..} <- ask
   _ <- prolix "analysing with %d resamples\n" resamples
   erp <- runExceptT $ analyseSample i desc meas
   case erp of
@@ -81,7 +90,7 @@
              (round (ovFraction * 100) :: Int) wibble
         return ()
       _ <- note "\n"
-      return rpt
+      return (Analysed rpt)
       where bs :: (Double -> String) -> String -> Estimate -> Criterion ()
             bs f metric Estimate{..} =
               note "%-20s %-10s (%s .. %s%s)\n" metric
@@ -89,10 +98,11 @@
                    (if estConfidenceLevel == 0.95 then ""
                     else printf ", ci %.3f" estConfidenceLevel)
 
--- | Determine whether an Environment benchmark should be run.
-shouldRunEnv :: (String -> Bool) -> String -> (s -> Benchmark) -> Bool
-shouldRunEnv p pfx mkbench =
-  any (p . addPrefix pfx) . benchNames . mkbench $ undefined
+-- | Run a single benchmark and analyse its performance.
+runAndAnalyseOne :: Int -> String -> Benchmarkable -> Criterion DataRecord
+runAndAnalyseOne i desc bm = do
+  Measurement _ _ meas <- runOne i desc bm
+  analyseOne i desc meas
 
 -- | Run, and analyse, one or more benchmarks.
 runAndAnalyse :: (String -> Bool) -- ^ A predicate that chooses
@@ -100,7 +110,7 @@
                                   -- name.
               -> Benchmark
               -> Criterion ()
-runAndAnalyse p bs' = do
+runAndAnalyse select bs = do
   mbRawFile <- asks rawDataFile
   (rawFile, handle) <- liftIO $
     case mbRawFile of
@@ -112,28 +122,14 @@
         return (file, handle)
   liftIO $ L.hPut handle header
 
-  let go !k (pfx, Environment mkenv mkbench)
-          | shouldRunEnv p pfx mkbench = do
-              e <- liftIO $ do
-                     ee <- mkenv
-                     evaluate (rnf ee)
-                     return ee
-              go k (pfx, mkbench e)
-          | otherwise = return (k :: Int)
-      go !k (pfx, Benchmark desc b)
-          | p desc'   = do _ <- note "benchmarking %s\n" desc'
-                           rpt <- runAndAnalyseOne k desc' b
-                           liftIO $ L.hPut handle (encode rpt)
-                           return $! k + 1
-          | otherwise = return (k :: Int)
-          where desc' = addPrefix pfx desc
-      go !k (pfx, BenchGroup desc bs) =
-          foldM go k [(addPrefix pfx desc, b) | b <- bs]
-  _ <- go 0 ("", bs')
+  for select bs $ \idx desc bm -> do
+    _ <- note "benchmarking %s\n" desc
+    rpt <- runAndAnalyseOne idx desc bm
+    liftIO $ L.hPut handle (encode rpt)
 
   rpts <- (either fail return =<<) . liftIO $ do
     hSeek handle AbsoluteSeek 0
-    rs <- hGetReports handle
+    rs <- fmap (map (\(Analysed r) -> r)) <$> hGetRecords handle
     hClose handle
     case mbRawFile of
       Just _ -> return rs
@@ -143,28 +139,40 @@
   junit rpts
 
 -- | Run a benchmark without analysing its performance.
-runNotAnalyse :: Int64            -- ^ Number of loop iterations to run.
+runFixedIters :: Int64            -- ^ Number of loop iterations to run.
               -> (String -> Bool) -- ^ A predicate that chooses
                                   -- whether to run a benchmark by its
                                   -- name.
               -> Benchmark
               -> Criterion ()
-runNotAnalyse iters p bs' = goQuickly "" bs'
-  where goQuickly :: String -> Benchmark -> Criterion ()
-        goQuickly pfx (Environment mkenv mkbench)
-            | shouldRunEnv p pfx mkbench = do
-                e <- liftIO mkenv
-                goQuickly pfx (mkbench e)
-            | otherwise = return ()
-        goQuickly pfx (Benchmark desc b)
-            | p desc'   = do _ <- note "benchmarking %s\n" desc'
-                             runOne b
-            | otherwise = return ()
-            where desc' = addPrefix pfx desc
-        goQuickly pfx (BenchGroup desc bs) =
-            mapM_ (goQuickly (addPrefix pfx desc)) bs
+runFixedIters iters select bs =
+  for select bs $ \_idx desc bm -> do
+    _ <- note "benchmarking %s\n" desc
+    liftIO $ runRepeatedly bm iters
 
-        runOne (Benchmarkable run) = liftIO (run iters)
+-- | Iterate over benchmarks.
+for :: MonadIO m => (String -> Bool) -> Benchmark
+    -> (Int -> String -> Benchmarkable -> m ()) -> m ()
+for select bs0 handle = go (0::Int) ("", bs0) >> return ()
+  where
+    go !idx (pfx, Environment mkenv mkbench)
+      | shouldRun pfx mkbench = do
+        e <- liftIO $ do
+          ee <- mkenv
+          evaluate (rnf ee)
+          return ee
+        go idx (pfx, mkbench e)
+      | otherwise = return idx
+    go idx (pfx, Benchmark desc b)
+      | select desc' = do handle idx desc' b; return $! idx + 1
+      | otherwise    = return idx
+      where desc' = addPrefix pfx desc
+    go idx (pfx, BenchGroup desc bs) =
+      foldM go idx [(addPrefix pfx desc, b) | b <- bs]
+
+    shouldRun pfx mkbench =
+      any (select . addPrefix pfx) . benchNames . mkbench $
+      error "Criterion.env could not determine the list of your benchmarks since they force the environment (see the documentation for details)"
 
 -- | Write summary JUnit file (if applicable)
 junit :: [Report] -> Criterion ()
diff --git a/Criterion/Main.hs b/Criterion/Main.hs
--- a/Criterion/Main.hs
+++ b/Criterion/Main.hs
@@ -42,12 +42,13 @@
     , defaultConfig
     -- * Other useful code
     , makeMatcher
+    , runMode
     ) where
 
 import Control.Monad (unless)
 import Control.Monad.Trans (liftIO)
 import Criterion.IO.Printf (printError, writeCsv)
-import Criterion.Internal (runAndAnalyse, runNotAnalyse)
+import Criterion.Internal (runAndAnalyse, runFixedIters)
 import Criterion.Main.Options (MatchType(..), Mode(..), defaultConfig, describe,
                                versionInfo)
 import Criterion.Measurement (initializeTime)
@@ -130,14 +131,21 @@
                 -> IO ()
 defaultMainWith defCfg bs = do
   wat <- execParser (describe defCfg)
-  let bsgroup = BenchGroup "" bs
+  runMode wat bs
+
+-- | Run a set of 'Benchmark's with the given 'Mode'.
+--
+-- This can be useful if you have a 'Mode' from some other source (e.g. from a
+-- one in your benchmark driver's command-line parser).
+runMode :: Mode -> [Benchmark] -> IO ()
+runMode wat bs =
   case wat of
     List -> mapM_ putStrLn . sort . concatMap benchNames $ bs
     Version -> putStrLn versionInfo
-    OnlyRun iters matchType benches -> do
+    RunIters iters matchType benches -> do
       shouldRun <- selectBenches matchType benches bsgroup
       withConfig defaultConfig $
-        runNotAnalyse iters shouldRun bsgroup
+        runFixedIters iters shouldRun bsgroup
     Run cfg matchType benches -> do
       shouldRun <- selectBenches matchType benches bsgroup
       withConfig cfg $ do
@@ -145,6 +153,7 @@
                   "StddevUB")
         liftIO initializeTime
         runAndAnalyse shouldRun bsgroup
+  where bsgroup = BenchGroup "" bs
 
 -- | Display an error message from a command line parsing failure, and
 -- exit.
diff --git a/Criterion/Main/Options.hs b/Criterion/Main/Options.hs
--- a/Criterion/Main/Options.hs
+++ b/Criterion/Main/Options.hs
@@ -54,7 +54,7 @@
             -- ^ List all benchmarks.
           | Version
             -- ^ Print the version.
-          | OnlyRun Int64 MatchType [String]
+          | RunIters Int64 MatchType [String]
             -- ^ Run the given benchmarks, without collecting or
             -- analysing performance numbers.
           | Run Config MatchType [String]
@@ -84,51 +84,51 @@
           -> Parser Mode
 parseWith cfg =
     (matchNames (Run <$> config cfg)) <|>
-    onlyRun <|>
-    (List <$ switch (long "list" <> short 'l' <> help "list benchmarks")) <|>
-    (Version <$ switch (long "version" <> help "show version info"))
+    runIters <|>
+    (List <$ switch (long "list" <> short 'l' <> help "List benchmarks")) <|>
+    (Version <$ switch (long "version" <> help "Show version info"))
   where
-    onlyRun = matchNames $
-      OnlyRun <$> option auto
-                  (long "only-run" <> short 'n' <> metavar "ITERS" <>
-                   help "run benchmarks, don't analyse")
+    runIters = matchNames $
+      RunIters <$> option auto
+                  (long "iters" <> short 'n' <> metavar "ITERS" <>
+                   help "Run benchmarks, don't analyse")
     matchNames wat = wat
       <*> option match
           (long "match" <> short 'm' <> metavar "MATCH" <> value Prefix <>
-           help "how to match benchmark names")
+           help "How to match benchmark names (\"prefix\" or \"glob\")")
       <*> many (argument str (metavar "NAME..."))
 
 config :: Config -> Parser Config
 config Config{..} = Config
   <$> option (range 0.001 0.999)
       (long "ci" <> short 'I' <> metavar "CI" <> value confInterval <>
-       help "confidence interval")
+       help "Confidence interval")
   <*> (not <$> switch (long "no-gc" <> short 'G' <>
-                       help "do not collect garbage between iterations"))
+                       help "Do not collect garbage between iterations"))
   <*> option (range 0.1 86400)
       (long "time-limit" <> short 'L' <> metavar "SECS" <> value timeLimit <>
-       help "time limit to run a benchmark")
+       help "Time limit to run a benchmark")
   <*> option (range 1 1000000)
       (long "resamples" <> metavar "COUNT" <> value resamples <>
-       help "number of bootstrap resamples to perform")
+       help "Number of bootstrap resamples to perform")
   <*> many (option regressParams
             (long "regress" <> metavar "RESP:PRED.." <>
-             help "regressions to perform"))
+             help "Regressions to perform"))
   <*> outputOption rawDataFile (long "raw" <>
-                                help "file to write raw data to")
+                                help "File to write raw data to")
   <*> outputOption reportFile (long "output" <> short 'o' <>
-                               help "file to write report to")
+                               help "File to write report to")
   <*> outputOption csvFile (long "csv" <>
-                            help "file to write CSV summary to")
+                            help "File to write CSV summary to")
   <*> outputOption junitFile (long "junit" <>
-                              help "file to write JUnit summary to")
+                              help "File to write JUnit summary to")
   <*> (toEnum <$> option (range 0 2)
                   (long "verbosity" <> short 'v' <> metavar "LEVEL" <>
                    value (fromEnum verbosity) <>
-                   help "verbosity level"))
+                   help "Verbosity level"))
   <*> strOption (long "template" <> short 't' <> metavar "FILE" <>
                  value template <>
-                 help "template to use for report")
+                 help "Template to use for report")
 
 outputOption :: Maybe String -> Mod OptionFields String -> Parser (Maybe String)
 outputOption file m =
@@ -151,8 +151,9 @@
     mm | mm `isPrefixOf` "pfx"    -> return Prefix
        | mm `isPrefixOf` "prefix" -> return Prefix
        | mm `isPrefixOf` "glob"   -> return Glob
-       | otherwise                -> readerError $
-                                     show m ++ " is not a known match type"
+       | otherwise                ->
+         readerError $ show m ++ " is not a known match type. "
+                              ++ "Try \"prefix\" or \"glob\"."
 
 regressParams :: ReadM ([String], String)
 regressParams = do
diff --git a/Criterion/Types.hs b/Criterion/Types.hs
--- a/Criterion/Types.hs
+++ b/Criterion/Types.hs
@@ -60,6 +60,7 @@
     , KDE(..)
     , Report(..)
     , SampleAnalysis(..)
+    , DataRecord(..)
     ) where
 
 import Control.Applicative ((<$>), (<*>))
@@ -119,7 +120,7 @@
 -- | A pure function or impure action that can be benchmarked. The
 -- 'Int64' parameter indicates the number of times to run the given
 -- function or action.
-newtype Benchmarkable = Benchmarkable (Int64 -> IO ())
+newtype Benchmarkable = Benchmarkable { runRepeatedly :: Int64 -> IO () }
 
 -- | A collection of measurements made while benchmarking.
 --
@@ -384,13 +385,13 @@
 -- benchmarks to be run.
 --
 -- > setupEnv = do
--- >   let small = replicate 1000 1
--- >   big <- readFile "/usr/dict/words"
+-- >   let small = replicate 1000 (1 :: Int)
+-- >   big <- map length . words <$> readFile "/usr/dict/words"
 -- >   return (small, big)
 -- >
 -- > main = defaultMain [
 -- >    -- notice the lazy pattern match here!
--- >    env setupEnv $ \ ~(small,big) ->
+-- >    env setupEnv $ \ ~(small,big) -> bgroup "main" [
 -- >    bgroup "small" [
 -- >      bench "length" $ whnf length small
 -- >    , bench "length . filter" $ whnf (length . filter (==1)) small
@@ -399,7 +400,7 @@
 -- >      bench "length" $ whnf length big
 -- >    , bench "length . filter" $ whnf (length . filter (==1)) big
 -- >    ]
--- >  ]
+-- >  ] ]
 --
 -- __Discussion.__ The environment created in the example above is
 -- intentionally /not/ ideal.  As Haskell's scoping rules suggest, the
@@ -636,3 +637,25 @@
       rnf reportNumber `seq` rnf reportName `seq` rnf reportKeys `seq`
       rnf reportMeasured `seq` rnf reportAnalysis `seq` rnf reportOutliers `seq`
       rnf reportKDEs
+
+data DataRecord = Measurement Int String (V.Vector Measured)
+                | Analysed Report
+                deriving (Eq, Read, Show, Typeable, Data, Generic)
+
+instance Binary DataRecord where
+  put (Measurement i n v) = putWord8 0 >> put i >> put n >> put v
+  put (Analysed r)        = putWord8 1 >> put r
+
+  get = do
+    w <- getWord8
+    case w of
+      0 -> Measurement <$> get <*> get <*> get
+      1 -> Analysed    <$> get
+      _ -> error ("bad tag " ++ show w)
+
+instance NFData DataRecord where
+  rnf (Measurement i n v) = rnf i `seq` rnf n `seq` rnf v
+  rnf (Analysed r)        = rnf r
+
+instance FromJSON DataRecord
+instance ToJSON DataRecord
diff --git a/app/App.hs b/app/App.hs
--- a/app/App.hs
+++ b/app/App.hs
@@ -1,5 +1,10 @@
 module Main (main) where
 
+import Options
+
 main :: IO ()
 main = do
-  return ()
+  cmd <- parseCommandLine
+  case cmd of
+    Version -> putStrLn versionInfo
+    _ -> print cmd
diff --git a/app/Options.hs b/app/Options.hs
new file mode 100644
--- /dev/null
+++ b/app/Options.hs
@@ -0,0 +1,39 @@
+{-# LANGUAGE DeriveDataTypeable, DeriveGeneric, RecordWildCards #-}
+
+module Options
+    (
+      CommandLine(..)
+    , commandLine
+    , parseCommandLine
+    , versionInfo
+    ) where
+
+import Data.Version (showVersion)
+import Data.Data (Data, Typeable)
+import GHC.Generics (Generic)
+import Paths_criterion (version)
+import Options.Applicative
+
+data CommandLine = Analyse [FilePath]
+                 | Version
+                 deriving (Eq, Read, Show, Typeable, Data, Generic)
+
+analyseOptions :: Parser CommandLine
+analyseOptions = Analyse <$> some (argument str (metavar "FILE [...]"))
+
+parseCommand :: Parser CommandLine
+parseCommand =
+  (Version <$ switch (long "version" <> help "Show version info")) <|>
+  (subparser $
+    command "analyse" (info analyseOptions (progDesc "Analyse measurements")))
+
+commandLine :: ParserInfo CommandLine
+commandLine = info (helper <*> parseCommand) $
+  header versionInfo <>
+  fullDesc
+
+parseCommandLine :: IO CommandLine
+parseCommandLine = execParser commandLine
+
+versionInfo :: String
+versionInfo = "criterion " ++ showVersion version
diff --git a/cbits/cycles.c b/cbits/cycles.c
--- a/cbits/cycles.c
+++ b/cbits/cycles.c
@@ -1,8 +1,57 @@
 #include "Rts.h"
 
+#if x86_64_HOST_ARCH
+
 StgWord64 criterion_rdtsc(void)
 {
   StgWord32 hi, lo;
   __asm__ __volatile__ ("rdtsc" : "=a"(lo), "=d"(hi));
   return ((StgWord64) lo) | (((StgWord64) hi)<<32);
 }
+
+#elif linux_HOST_OS
+
+/*
+ * This should work on all Linux.
+ *
+ * Technique by Austin Seipp found here:
+ *
+ * http://neocontra.blogspot.com/2013/05/user-mode-performance-counters-for.html
+ */
+
+#include <unistd.h>
+#include <asm-generic/unistd.h>
+#include <linux/perf_event.h>
+
+static int fddev = -1;
+__attribute__((constructor))
+static void
+init(void)
+{
+  static struct perf_event_attr attr;
+  attr.type = PERF_TYPE_HARDWARE;
+  attr.config = PERF_COUNT_HW_CPU_CYCLES;
+  fddev = syscall (__NR_perf_event_open, &attr, 0, -1, -1, 0);
+}
+
+__attribute__((destructor))
+static void
+fini(void)
+{
+  close(fddev);
+}
+
+StgWord64
+criterion_rdtsc (void)
+{
+  StgWord64 result = 0;
+  if (read (fddev, &result, sizeof(result)) < sizeof(result))
+    return 0;
+  return result;
+}
+
+#else
+
+#error Unsupported OS/architecture/compiler!
+
+#endif
diff --git a/changelog.md b/changelog.md
--- a/changelog.md
+++ b/changelog.md
@@ -1,6 +1,35 @@
+1.1.1.0
+
+* If a benchmark uses `Criterion.env` in a non-lazy way, and you try
+  to use `--list` to list benchmark names, you'll now get an
+  understandable error message instead of something cryptic.
+
+* We now flush stdout and stderr after printing messages, so that
+  output is printed promptly even when piped (e.g. into a pager).
+
+* A new function `runMode` allows custom benchmarking applications to
+  run benchmarks with control over the `Mode` used.
+
+* Added support for Linux on non-Intel CPUs.
+
+* This version supports GHC 8.
+
+* The `--only-run` option for benchmarks is renamed to `--iters`.
+
 1.1.0.0
 
-*
+* The dependency on the either package has been dropped in favour of a
+  dependency on transformers-compat.  This greatly reduces the number
+  of packages criterion depends on.  This shouldn't affect the
+  user-visible API.
+
+* The documentation claimed that environments were created only when
+  needed, but this wasn't implemented. (gh-76)
+
+* The package now compiles with GHC 7.10.
+
+* On Windows with a non-Unicode code page, printing results used to
+  cause a crash.  (gh-55)
 
 1.0.2.0
 
diff --git a/criterion.cabal b/criterion.cabal
--- a/criterion.cabal
+++ b/criterion.cabal
@@ -1,5 +1,5 @@
 name:           criterion
-version:        1.1.0.0
+version:        1.1.1.0
 synopsis:       Robust, reliable performance measurement and analysis
 license:        BSD3
 license-file:   LICENSE
@@ -104,16 +104,18 @@
     ghc-options: -fwarn-tabs
 
 executable criterion
-  buildable:      False
   hs-source-dirs: app
   main-is:        App.hs
+  other-modules:
+    Options
 
   ghc-options:
     -Wall -threaded -rtsopts
 
   build-depends:
     base,
-    criterion
+    criterion,
+    optparse-applicative
 
 test-suite sanity
   type:           exitcode-stdio-1.0
diff --git a/examples/fibber.html b/examples/fibber.html
deleted file mode 100644
--- a/examples/fibber.html
+++ /dev/null
@@ -1,726 +0,0 @@
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series=[],options={colors:["#edc240","#afd8f8","#cb4b4b","#4da74d","#9440ed"],legend:{show:true,noColumns:1,labelFormatter:null,labelBoxBorderColor:"#ccc",container:null,position:"ne",margin:5,backgroundColor:null,backgroundOpacity:.85,sorted:null},xaxis:{show:null,position:"bottom",mode:null,font:null,color:null,tickColor:null,transform:null,inverseTransform:null,min:null,max:null,autoscaleMargin:null,ticks:null,tickFormatter:null,labelWidth:null,labelHeight:null,reserveSpace:null,tickLength:null,alignTicksWithAxis:null,tickDecimals:null,tickSize:null,minTickSize:null},yaxis:{autoscaleMargin:.02,position:"left"},xaxes:[],yaxes:[],series:{points:{show:false,radius:3,lineWidth:2,fill:true,fillColor:"#ffffff",symbol:"circle"},lines:{lineWidth:2,fill:false,fillColor:null,steps:false},bars:{show:false,lineWidth:2,barWidth:1,fill:true,fillColor:null,align:"left",horizontal:false,zero:true},shadowSize:3,highlightColor:null},grid:{show:true,aboveData:false,color:"#545454",backgroundColor:null,borderColor:null,tickColor:null,margin:0,labelMargin:5,axisMargin:8,borderWidth:2,minBorderMargin:null,markings:null,markingsColor:"#f4f4f4",markingsLineWidth:2,clickable:false,hoverable:false,autoHighlight:true,mouseActiveRadius:10},interaction:{redrawOverlayInterval:1e3/60},hooks:{}},surface=null,overlay=null,eventHolder=null,ctx=null,octx=null,xaxes=[],yaxes=[],plotOffset={left:0,right:0,top:0,bottom:0},plotWidth=0,plotHeight=0,hooks={processOptions:[],processRawData:[],processDatapoints:[],processOffset:[],drawBackground:[],drawSeries:[],draw:[],bindEvents:[],drawOverlay:[],shutdown:[]},plot=this;plot.setData=setData;plot.setupGrid=setupGrid;plot.draw=draw;plot.getPlaceholder=function(){return placeholder};plot.getCanvas=function(){return surface.element};plot.getPlotOffset=function(){return plotOffset};plot.width=function(){return plotWidth};plot.height=function(){return plotHeight};plot.offset=function(){var o=eventHolder.offset();o.left+=plotOffset.left;o.top+=plotOffset.top;return o};plot.getData=function(){return series};plot.getAxes=function(){var res={},i;$.each(xaxes.concat(yaxes),function(_,axis){if(axis)res[axis.direction+(axis.n!=1?axis.n:"")+"axis"]=axis});return res};plot.getXAxes=function(){return xaxes};plot.getYAxes=function(){return yaxes};plot.c2p=canvasToAxisCoords;plot.p2c=axisToCanvasCoords;plot.getOptions=function(){return options};plot.highlight=highlight;plot.unhighlight=unhighlight;plot.triggerRedrawOverlay=triggerRedrawOverlay;plot.pointOffset=function(point){return{left:parseInt(xaxes[axisNumber(point,"x")-1].p2c(+point.x)+plotOffset.left,10),top:parseInt(yaxes[axisNumber(point,"y")-1].p2c(+point.y)+plotOffset.top,10)}};plot.shutdown=shutdown;plot.destroy=function(){shutdown();placeholder.removeData("plot").empty();series=[];options=null;surface=null;overlay=null;eventHolder=null;ctx=null;octx=null;xaxes=[];yaxes=[];hooks=null;highlights=[];plot=null};plot.resize=function(){var width=placeholder.width(),height=placeholder.height();surface.resize(width,height);overlay.resize(width,height)};plot.hooks=hooks;initPlugins(plot);parseOptions(options_);setupCanvases();setData(data_);setupGrid();draw();bindEvents();function executeHooks(hook,args){args=[plot].concat(args);for(var i=0;i<hook.length;++i)hook[i].apply(this,args)}function initPlugins(){var classes={Canvas:Canvas};for(var i=0;i<plugins.length;++i){var p=plugins[i];p.init(plot,classes);if(p.options)$.extend(true,options,p.options)}}function parseOptions(opts){$.extend(true,options,opts);if(opts&&opts.colors){options.colors=opts.colors}if(options.xaxis.color==null)options.xaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.yaxis.color==null)options.yaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.xaxis.tickColor==null)options.xaxis.tickColor=options.grid.tickColor||options.xaxis.color;if(options.yaxis.tickColor==null)options.yaxis.tickColor=options.grid.tickColor||options.yaxis.color;if(options.grid.borderColor==null)options.grid.borderColor=options.grid.color;if(options.grid.tickColor==null)options.grid.tickColor=$.color.parse(options.grid.color).scale("a",.22).toString();var i,axisOptions,axisCount,fontSize=placeholder.css("font-size"),fontSizeDefault=fontSize?+fontSize.replace("px",""):13,fontDefaults={style:placeholder.css("font-style"),size:Math.round(.8*fontSizeDefault),variant:placeholder.css("font-variant"),weight:placeholder.css("font-weight"),family:placeholder.css("font-family")};axisCount=options.xaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.xaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.xaxis,axisOptions);options.xaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}axisCount=options.yaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.yaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.yaxis,axisOptions);options.yaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}if(options.xaxis.noTicks&&options.xaxis.ticks==null)options.xaxis.ticks=options.xaxis.noTicks;if(options.yaxis.noTicks&&options.yaxis.ticks==null)options.yaxis.ticks=options.yaxis.noTicks;if(options.x2axis){options.xaxes[1]=$.extend(true,{},options.xaxis,options.x2axis);options.xaxes[1].position="top";if(options.x2axis.min==null){options.xaxes[1].min=null}if(options.x2axis.max==null){options.xaxes[1].max=null}}if(options.y2axis){options.yaxes[1]=$.extend(true,{},options.yaxis,options.y2axis);options.yaxes[1].position="right";if(options.y2axis.min==null){options.yaxes[1].min=null}if(options.y2axis.max==null){options.yaxes[1].max=null}}if(options.grid.coloredAreas)options.grid.markings=options.grid.coloredAreas;if(options.grid.coloredAreasColor)options.grid.markingsColor=options.grid.coloredAreasColor;if(options.lines)$.extend(true,options.series.lines,options.lines);if(options.points)$.extend(true,options.series.points,options.points);if(options.bars)$.extend(true,options.series.bars,options.bars);if(options.shadowSize!=null)options.series.shadowSize=options.shadowSize;if(options.highlightColor!=null)options.series.highlightColor=options.highlightColor;for(i=0;i<options.xaxes.length;++i)getOrCreateAxis(xaxes,i+1).options=options.xaxes[i];for(i=0;i<options.yaxes.length;++i)getOrCreateAxis(yaxes,i+1).options=options.yaxes[i];for(var n in hooks)if(options.hooks[n]&&options.hooks[n].length)hooks[n]=hooks[n].concat(options.hooks[n]);executeHooks(hooks.processOptions,[options])}function setData(d){series=parseData(d);fillInSeriesOptions();processData()}function parseData(d){var res=[];for(var i=0;i<d.length;++i){var s=$.extend(true,{},options.series);if(d[i].data!=null){s.data=d[i].data;delete d[i].data;$.extend(true,s,d[i]);d[i].data=s.data}else s.data=d[i];res.push(s)}return res}function axisNumber(obj,coord){var a=obj[coord+"axis"];if(typeof a=="object")a=a.n;if(typeof a!="number")a=1;return a}function allAxes(){return $.grep(xaxes.concat(yaxes),function(a){return a})}function canvasToAxisCoords(pos){var res={},i,axis;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used)res["x"+axis.n]=axis.c2p(pos.left)}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used)res["y"+axis.n]=axis.c2p(pos.top)}if(res.x1!==undefined)res.x=res.x1;if(res.y1!==undefined)res.y=res.y1;return res}function axisToCanvasCoords(pos){var res={},i,axis,key;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used){key="x"+axis.n;if(pos[key]==null&&axis.n==1)key="x";if(pos[key]!=null){res.left=axis.p2c(pos[key]);break}}}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used){key="y"+axis.n;if(pos[key]==null&&axis.n==1)key="y";if(pos[key]!=null){res.top=axis.p2c(pos[key]);break}}}return res}function getOrCreateAxis(axes,number){if(!axes[number-1])axes[number-1]={n:number,direction:axes==xaxes?"x":"y",options:$.extend(true,{},axes==xaxes?options.xaxis:options.yaxis)};return axes[number-1]}function fillInSeriesOptions(){var neededColors=series.length,maxIndex=-1,i;for(i=0;i<series.length;++i){var sc=series[i].color;if(sc!=null){neededColors--;if(typeof sc=="number"&&sc>maxIndex){maxIndex=sc}}}if(neededColors<=maxIndex){neededColors=maxIndex+1}var c,colors=[],colorPool=options.colors,colorPoolSize=colorPool.length,variation=0;for(i=0;i<neededColors;i++){c=$.color.parse(colorPool[i%colorPoolSize]||"#666");if(i%colorPoolSize==0&&i){if(variation>=0){if(variation<.5){variation=-variation-.2}else variation=0}else variation=-variation}colors[i]=c.scale("rgb",1+variation)}var colori=0,s;for(i=0;i<series.length;++i){s=series[i];if(s.color==null){s.color=colors[colori].toString();++colori}else if(typeof s.color=="number")s.color=colors[s.color].toString();if(s.lines.show==null){var v,show=true;for(v in s)if(s[v]&&s[v].show){show=false;break}if(show)s.lines.show=true}if(s.lines.zero==null){s.lines.zero=!!s.lines.fill}s.xaxis=getOrCreateAxis(xaxes,axisNumber(s,"x"));s.yaxis=getOrCreateAxis(yaxes,axisNumber(s,"y"))}}function processData(){var topSentry=Number.POSITIVE_INFINITY,bottomSentry=Number.NEGATIVE_INFINITY,fakeInfinity=Number.MAX_VALUE,i,j,k,m,length,s,points,ps,x,y,axis,val,f,p,data,format;function updateAxis(axis,min,max){if(min<axis.datamin&&min!=-fakeInfinity)axis.datamin=min;if(max>axis.datamax&&max!=fakeInfinity)axis.datamax=max}$.each(allAxes(),function(_,axis){axis.datamin=topSentry;axis.datamax=bottomSentry;axis.used=false});for(i=0;i<series.length;++i){s=series[i];s.datapoints={points:[]};executeHooks(hooks.processRawData,[s,s.data,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];data=s.data;format=s.datapoints.format;if(!format){format=[];format.push({x:true,number:true,required:true});format.push({y:true,number:true,required:true});if(s.bars.show||s.lines.show&&s.lines.fill){var autoscale=!!(s.bars.show&&s.bars.zero||s.lines.show&&s.lines.zero);format.push({y:true,number:true,required:false,defaultValue:0,autoscale:autoscale});if(s.bars.horizontal){delete format[format.length-1].y;format[format.length-1].x=true}}s.datapoints.format=format}if(s.datapoints.pointsize!=null)continue;s.datapoints.pointsize=format.length;ps=s.datapoints.pointsize;points=s.datapoints.points;var insertSteps=s.lines.show&&s.lines.steps;s.xaxis.used=s.yaxis.used=true;for(j=k=0;j<data.length;++j,k+=ps){p=data[j];var nullify=p==null;if(!nullify){for(m=0;m<ps;++m){val=p[m];f=format[m];if(f){if(f.number&&val!=null){val=+val;if(isNaN(val))val=null;else if(val==Infinity)val=fakeInfinity;else if(val==-Infinity)val=-fakeInfinity}if(val==null){if(f.required)nullify=true;if(f.defaultValue!=null)val=f.defaultValue}}points[k+m]=val}}if(nullify){for(m=0;m<ps;++m){val=points[k+m];if(val!=null){f=format[m];if(f.autoscale!==false){if(f.x){updateAxis(s.xaxis,val,val)}if(f.y){updateAxis(s.yaxis,val,val)}}}points[k+m]=null}}else{if(insertSteps&&k>0&&points[k-ps]!=null&&points[k-ps]!=points[k]&&points[k-ps+1]!=points[k+1]){for(m=0;m<ps;++m)points[k+ps+m]=points[k+m];points[k+1]=points[k-ps+1];k+=ps}}}}for(i=0;i<series.length;++i){s=series[i];executeHooks(hooks.processDatapoints,[s,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];points=s.datapoints.points;ps=s.datapoints.pointsize;format=s.datapoints.format;var xmin=topSentry,ymin=topSentry,xmax=bottomSentry,ymax=bottomSentry;for(j=0;j<points.length;j+=ps){if(points[j]==null)continue;for(m=0;m<ps;++m){val=points[j+m];f=format[m];if(!f||f.autoscale===false||val==fakeInfinity||val==-fakeInfinity)continue;if(f.x){if(val<xmin)xmin=val;if(val>xmax)xmax=val}if(f.y){if(val<ymin)ymin=val;if(val>ymax)ymax=val}}}if(s.bars.show){var delta;switch(s.bars.align){case"left":delta=0;break;case"right":delta=-s.bars.barWidth;break;default:delta=-s.bars.barWidth/2}if(s.bars.horizontal){ymin+=delta;ymax+=delta+s.bars.barWidth}else{xmin+=delta;xmax+=delta+s.bars.barWidth}}updateAxis(s.xaxis,xmin,xmax);updateAxis(s.yaxis,ymin,ymax)}$.each(allAxes(),function(_,axis){if(axis.datamin==topSentry)axis.datamin=null;if(axis.datamax==bottomSentry)axis.datamax=null})}function setupCanvases(){placeholder.css("padding",0).children().filter(function(){return!$(this).hasClass("flot-overlay")&&!$(this).hasClass("flot-base")}).remove();if(placeholder.css("position")=="static")placeholder.css("position","relative");surface=new Canvas("flot-base",placeholder);overlay=new Canvas("flot-overlay",placeholder);ctx=surface.context;octx=overlay.context;eventHolder=$(overlay.element).unbind();var existing=placeholder.data("plot");if(existing){existing.shutdown();overlay.clear()}placeholder.data("plot",plot)}function bindEvents(){if(options.grid.hoverable){eventHolder.mousemove(onMouseMove);eventHolder.bind("mouseleave",onMouseLeave)}if(options.grid.clickable)eventHolder.click(onClick);executeHooks(hooks.bindEvents,[eventHolder])}function shutdown(){if(redrawTimeout)clearTimeout(redrawTimeout);eventHolder.unbind("mousemove",onMouseMove);eventHolder.unbind("mouseleave",onMouseLeave);eventHolder.unbind("click",onClick);executeHooks(hooks.shutdown,[eventHolder])}function setTransformationHelpers(axis){function identity(x){return x}var s,m,t=axis.options.transform||identity,it=axis.options.inverseTransform;if(axis.direction=="x"){s=axis.scale=plotWidth/Math.abs(t(axis.max)-t(axis.min));m=Math.min(t(axis.max),t(axis.min))}else{s=axis.scale=plotHeight/Math.abs(t(axis.max)-t(axis.min));s=-s;m=Math.max(t(axis.max),t(axis.min))}if(t==identity)axis.p2c=function(p){return(p-m)*s};else axis.p2c=function(p){return(t(p)-m)*s};if(!it)axis.c2p=function(c){return m+c/s};else axis.c2p=function(c){return it(m+c/s)}}function measureTickLabels(axis){var opts=axis.options,ticks=axis.ticks||[],labelWidth=opts.labelWidth||0,labelHeight=opts.labelHeight||0,maxWidth=labelWidth||(axis.direction=="x"?Math.floor(surface.width/(ticks.length||1)):null),legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=opts.font||"flot-tick-label tickLabel";for(var i=0;i<ticks.length;++i){var t=ticks[i];if(!t.label)continue;var info=surface.getTextInfo(layer,t.label,font,null,maxWidth);labelWidth=Math.max(labelWidth,info.width);labelHeight=Math.max(labelHeight,info.height)}axis.labelWidth=opts.labelWidth||labelWidth;axis.labelHeight=opts.labelHeight||labelHeight}function allocateAxisBoxFirstPhase(axis){var lw=axis.labelWidth,lh=axis.labelHeight,pos=axis.options.position,isXAxis=axis.direction==="x",tickLength=axis.options.tickLength,axisMargin=options.grid.axisMargin,padding=options.grid.labelMargin,innermost=true,outermost=true,first=true,found=false;$.each(isXAxis?xaxes:yaxes,function(i,a){if(a&&(a.show||a.reserveSpace)){if(a===axis){found=true}else if(a.options.position===pos){if(found){outermost=false}else{innermost=false}}if(!found){first=false}}});if(outermost){axisMargin=0}if(tickLength==null){tickLength=first?"full":5}if(!isNaN(+tickLength))padding+=+tickLength;if(isXAxis){lh+=padding;if(pos=="bottom"){plotOffset.bottom+=lh+axisMargin;axis.box={top:surface.height-plotOffset.bottom,height:lh}}else{axis.box={top:plotOffset.top+axisMargin,height:lh};plotOffset.top+=lh+axisMargin}}else{lw+=padding;if(pos=="left"){axis.box={left:plotOffset.left+axisMargin,width:lw};plotOffset.left+=lw+axisMargin}else{plotOffset.right+=lw+axisMargin;axis.box={left:surface.width-plotOffset.right,width:lw}}}axis.position=pos;axis.tickLength=tickLength;axis.box.padding=padding;axis.innermost=innermost}function allocateAxisBoxSecondPhase(axis){if(axis.direction=="x"){axis.box.left=plotOffset.left-axis.labelWidth/2;axis.box.width=surface.width-plotOffset.left-plotOffset.right+axis.labelWidth}else{axis.box.top=plotOffset.top-axis.labelHeight/2;axis.box.height=surface.height-plotOffset.bottom-plotOffset.top+axis.labelHeight}}function adjustLayoutForThingsStickingOut(){var minMargin=options.grid.minBorderMargin,axis,i;if(minMargin==null){minMargin=0;for(i=0;i<series.length;++i)minMargin=Math.max(minMargin,2*(series[i].points.radius+series[i].points.lineWidth/2))}var margins={left:minMargin,right:minMargin,top:minMargin,bottom:minMargin};$.each(allAxes(),function(_,axis){if(axis.reserveSpace&&axis.ticks&&axis.ticks.length){if(axis.direction==="x"){margins.left=Math.max(margins.left,axis.labelWidth/2);margins.right=Math.max(margins.right,axis.labelWidth/2)}else{margins.bottom=Math.max(margins.bottom,axis.labelHeight/2);margins.top=Math.max(margins.top,axis.labelHeight/2)}}});plotOffset.left=Math.ceil(Math.max(margins.left,plotOffset.left));plotOffset.right=Math.ceil(Math.max(margins.right,plotOffset.right));plotOffset.top=Math.ceil(Math.max(margins.top,plotOffset.top));plotOffset.bottom=Math.ceil(Math.max(margins.bottom,plotOffset.bottom))}function setupGrid(){var i,axes=allAxes(),showGrid=options.grid.show;for(var a in plotOffset){var margin=options.grid.margin||0;plotOffset[a]=typeof margin=="number"?margin:margin[a]||0}executeHooks(hooks.processOffset,[plotOffset]);for(var a in plotOffset){if(typeof options.grid.borderWidth=="object"){plotOffset[a]+=showGrid?options.grid.borderWidth[a]:0}else{plotOffset[a]+=showGrid?options.grid.borderWidth:0}}$.each(axes,function(_,axis){var axisOpts=axis.options;axis.show=axisOpts.show==null?axis.used:axisOpts.show;axis.reserveSpace=axisOpts.reserveSpace==null?axis.show:axisOpts.reserveSpace;setRange(axis)});if(showGrid){var allocatedAxes=$.grep(axes,function(axis){return axis.show||axis.reserveSpace});$.each(allocatedAxes,function(_,axis){setupTickGeneration(axis);setTicks(axis);snapRangeToTicks(axis,axis.ticks);measureTickLabels(axis)});for(i=allocatedAxes.length-1;i>=0;--i)allocateAxisBoxFirstPhase(allocatedAxes[i]);adjustLayoutForThingsStickingOut();$.each(allocatedAxes,function(_,axis){allocateAxisBoxSecondPhase(axis)})}plotWidth=surface.width-plotOffset.left-plotOffset.right;plotHeight=surface.height-plotOffset.bottom-plotOffset.top;$.each(axes,function(_,axis){setTransformationHelpers(axis)});if(showGrid){drawAxisLabels()}insertLegend()}function setRange(axis){var opts=axis.options,min=+(opts.min!=null?opts.min:axis.datamin),max=+(opts.max!=null?opts.max:axis.datamax),delta=max-min;if(delta==0){var widen=max==0?1:.01;if(opts.min==null)min-=widen;if(opts.max==null||opts.min!=null)max+=widen}else{var margin=opts.autoscaleMargin;if(margin!=null){if(opts.min==null){min-=delta*margin;if(min<0&&axis.datamin!=null&&axis.datamin>=0)min=0}if(opts.max==null){max+=delta*margin;if(max>0&&axis.datamax!=null&&axis.datamax<=0)max=0}}}axis.min=min;axis.max=max}function setupTickGeneration(axis){var opts=axis.options;var noTicks;if(typeof opts.ticks=="number"&&opts.ticks>0)noTicks=opts.ticks;else noTicks=.3*Math.sqrt(axis.direction=="x"?surface.width:surface.height);var delta=(axis.max-axis.min)/noTicks,dec=-Math.floor(Math.log(delta)/Math.LN10),maxDec=opts.tickDecimals;if(maxDec!=null&&dec>maxDec){dec=maxDec}var magn=Math.pow(10,-dec),norm=delta/magn,size;if(norm<1.5){size=1}else if(norm<3){size=2;if(norm>2.25&&(maxDec==null||dec+1<=maxDec)){size=2.5;++dec}}else if(norm<7.5){size=5}else{size=10}size*=magn;if(opts.minTickSize!=null&&size<opts.minTickSize){size=opts.minTickSize}axis.delta=delta;axis.tickDecimals=Math.max(0,maxDec!=null?maxDec:dec);axis.tickSize=opts.tickSize||size;if(opts.mode=="time"&&!axis.tickGenerator){throw new Error("Time mode requires the flot.time plugin.")}if(!axis.tickGenerator){axis.tickGenerator=function(axis){var ticks=[],start=floorInBase(axis.min,axis.tickSize),i=0,v=Number.NaN,prev;do{prev=v;v=start+i*axis.tickSize;ticks.push(v);++i}while(v<axis.max&&v!=prev);return ticks};axis.tickFormatter=function(value,axis){var factor=axis.tickDecimals?Math.pow(10,axis.tickDecimals):1;var formatted=""+Math.round(value*factor)/factor;if(axis.tickDecimals!=null){var decimal=formatted.indexOf(".");var precision=decimal==-1?0:formatted.length-decimal-1;if(precision<axis.tickDecimals){return(precision?formatted:formatted+".")+(""+factor).substr(1,axis.tickDecimals-precision)}}return formatted}}if($.isFunction(opts.tickFormatter))axis.tickFormatter=function(v,axis){return""+opts.tickFormatter(v,axis)};if(opts.alignTicksWithAxis!=null){var otherAxis=(axis.direction=="x"?xaxes:yaxes)[opts.alignTicksWithAxis-1];if(otherAxis&&otherAxis.used&&otherAxis!=axis){var niceTicks=axis.tickGenerator(axis);if(niceTicks.length>0){if(opts.min==null)axis.min=Math.min(axis.min,niceTicks[0]);if(opts.max==null&&niceTicks.length>1)axis.max=Math.max(axis.max,niceTicks[niceTicks.length-1])}axis.tickGenerator=function(axis){var ticks=[],v,i;for(i=0;i<otherAxis.ticks.length;++i){v=(otherAxis.ticks[i].v-otherAxis.min)/(otherAxis.max-otherAxis.min);v=axis.min+v*(axis.max-axis.min);ticks.push(v)}return ticks};if(!axis.mode&&opts.tickDecimals==null){var extraDec=Math.max(0,-Math.floor(Math.log(axis.delta)/Math.LN10)+1),ts=axis.tickGenerator(axis);if(!(ts.length>1&&/\..*0$/.test((ts[1]-ts[0]).toFixed(extraDec))))axis.tickDecimals=extraDec}}}}function setTicks(axis){var oticks=axis.options.ticks,ticks=[];if(oticks==null||typeof oticks=="number"&&oticks>0)ticks=axis.tickGenerator(axis);else if(oticks){if($.isFunction(oticks))ticks=oticks(axis);else ticks=oticks}var i,v;axis.ticks=[];for(i=0;i<ticks.length;++i){var label=null;var t=ticks[i];if(typeof t=="object"){v=+t[0];if(t.length>1)label=t[1]}else v=+t;if(label==null)label=axis.tickFormatter(v,axis);if(!isNaN(v))axis.ticks.push({v:v,label:label})}}function snapRangeToTicks(axis,ticks){if(axis.options.autoscaleMargin&&ticks.length>0){if(axis.options.min==null)axis.min=Math.min(axis.min,ticks[0].v);if(axis.options.max==null&&ticks.length>1)axis.max=Math.max(axis.max,ticks[ticks.length-1].v)}}function draw(){surface.clear();executeHooks(hooks.drawBackground,[ctx]);var grid=options.grid;if(grid.show&&grid.backgroundColor)drawBackground();if(grid.show&&!grid.aboveData){drawGrid()}for(var i=0;i<series.length;++i){executeHooks(hooks.drawSeries,[ctx,series[i]]);drawSeries(series[i])}executeHooks(hooks.draw,[ctx]);if(grid.show&&grid.aboveData){drawGrid()}surface.render();triggerRedrawOverlay()}function extractRange(ranges,coord){var axis,from,to,key,axes=allAxes();for(var i=0;i<axes.length;++i){axis=axes[i];if(axis.direction==coord){key=coord+axis.n+"axis";if(!ranges[key]&&axis.n==1)key=coord+"axis";if(ranges[key]){from=ranges[key].from;to=ranges[key].to;break}}}if(!ranges[key]){axis=coord=="x"?xaxes[0]:yaxes[0];from=ranges[coord+"1"];to=ranges[coord+"2"]}if(from!=null&&to!=null&&from>to){var tmp=from;from=to;to=tmp}return{from:from,to:to,axis:axis}}function drawBackground(){ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.fillStyle=getColorOrGradient(options.grid.backgroundColor,plotHeight,0,"rgba(255, 255, 255, 0)");ctx.fillRect(0,0,plotWidth,plotHeight);ctx.restore()}function drawGrid(){var i,axes,bw,bc;ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var markings=options.grid.markings;if(markings){if($.isFunction(markings)){axes=plot.getAxes();axes.xmin=axes.xaxis.min;axes.xmax=axes.xaxis.max;axes.ymin=axes.yaxis.min;axes.ymax=axes.yaxis.max;markings=markings(axes)}for(i=0;i<markings.length;++i){var m=markings[i],xrange=extractRange(m,"x"),yrange=extractRange(m,"y");if(xrange.from==null)xrange.from=xrange.axis.min;if(xrange.to==null)xrange.to=xrange.axis.max;
-if(yrange.from==null)yrange.from=yrange.axis.min;if(yrange.to==null)yrange.to=yrange.axis.max;if(xrange.to<xrange.axis.min||xrange.from>xrange.axis.max||yrange.to<yrange.axis.min||yrange.from>yrange.axis.max)continue;xrange.from=Math.max(xrange.from,xrange.axis.min);xrange.to=Math.min(xrange.to,xrange.axis.max);yrange.from=Math.max(yrange.from,yrange.axis.min);yrange.to=Math.min(yrange.to,yrange.axis.max);var xequal=xrange.from===xrange.to,yequal=yrange.from===yrange.to;if(xequal&&yequal){continue}xrange.from=Math.floor(xrange.axis.p2c(xrange.from));xrange.to=Math.floor(xrange.axis.p2c(xrange.to));yrange.from=Math.floor(yrange.axis.p2c(yrange.from));yrange.to=Math.floor(yrange.axis.p2c(yrange.to));if(xequal||yequal){var lineWidth=m.lineWidth||options.grid.markingsLineWidth,subPixel=lineWidth%2?.5:0;ctx.beginPath();ctx.strokeStyle=m.color||options.grid.markingsColor;ctx.lineWidth=lineWidth;if(xequal){ctx.moveTo(xrange.to+subPixel,yrange.from);ctx.lineTo(xrange.to+subPixel,yrange.to)}else{ctx.moveTo(xrange.from,yrange.to+subPixel);ctx.lineTo(xrange.to,yrange.to+subPixel)}ctx.stroke()}else{ctx.fillStyle=m.color||options.grid.markingsColor;ctx.fillRect(xrange.from,yrange.to,xrange.to-xrange.from,yrange.from-yrange.to)}}}axes=allAxes();bw=options.grid.borderWidth;for(var j=0;j<axes.length;++j){var axis=axes[j],box=axis.box,t=axis.tickLength,x,y,xoff,yoff;if(!axis.show||axis.ticks.length==0)continue;ctx.lineWidth=1;if(axis.direction=="x"){x=0;if(t=="full")y=axis.position=="top"?0:plotHeight;else y=box.top-plotOffset.top+(axis.position=="top"?box.height:0)}else{y=0;if(t=="full")x=axis.position=="left"?0:plotWidth;else x=box.left-plotOffset.left+(axis.position=="left"?box.width:0)}if(!axis.innermost){ctx.strokeStyle=axis.options.color;ctx.beginPath();xoff=yoff=0;if(axis.direction=="x")xoff=plotWidth+1;else yoff=plotHeight+1;if(ctx.lineWidth==1){if(axis.direction=="x"){y=Math.floor(y)+.5}else{x=Math.floor(x)+.5}}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff);ctx.stroke()}ctx.strokeStyle=axis.options.tickColor;ctx.beginPath();for(i=0;i<axis.ticks.length;++i){var v=axis.ticks[i].v;xoff=yoff=0;if(isNaN(v)||v<axis.min||v>axis.max||t=="full"&&(typeof bw=="object"&&bw[axis.position]>0||bw>0)&&(v==axis.min||v==axis.max))continue;if(axis.direction=="x"){x=axis.p2c(v);yoff=t=="full"?-plotHeight:t;if(axis.position=="top")yoff=-yoff}else{y=axis.p2c(v);xoff=t=="full"?-plotWidth:t;if(axis.position=="left")xoff=-xoff}if(ctx.lineWidth==1){if(axis.direction=="x")x=Math.floor(x)+.5;else y=Math.floor(y)+.5}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff)}ctx.stroke()}if(bw){bc=options.grid.borderColor;if(typeof bw=="object"||typeof bc=="object"){if(typeof bw!=="object"){bw={top:bw,right:bw,bottom:bw,left:bw}}if(typeof bc!=="object"){bc={top:bc,right:bc,bottom:bc,left:bc}}if(bw.top>0){ctx.strokeStyle=bc.top;ctx.lineWidth=bw.top;ctx.beginPath();ctx.moveTo(0-bw.left,0-bw.top/2);ctx.lineTo(plotWidth,0-bw.top/2);ctx.stroke()}if(bw.right>0){ctx.strokeStyle=bc.right;ctx.lineWidth=bw.right;ctx.beginPath();ctx.moveTo(plotWidth+bw.right/2,0-bw.top);ctx.lineTo(plotWidth+bw.right/2,plotHeight);ctx.stroke()}if(bw.bottom>0){ctx.strokeStyle=bc.bottom;ctx.lineWidth=bw.bottom;ctx.beginPath();ctx.moveTo(plotWidth+bw.right,plotHeight+bw.bottom/2);ctx.lineTo(0,plotHeight+bw.bottom/2);ctx.stroke()}if(bw.left>0){ctx.strokeStyle=bc.left;ctx.lineWidth=bw.left;ctx.beginPath();ctx.moveTo(0-bw.left/2,plotHeight+bw.bottom);ctx.lineTo(0-bw.left/2,0);ctx.stroke()}}else{ctx.lineWidth=bw;ctx.strokeStyle=options.grid.borderColor;ctx.strokeRect(-bw/2,-bw/2,plotWidth+bw,plotHeight+bw)}}ctx.restore()}function drawAxisLabels(){$.each(allAxes(),function(_,axis){var box=axis.box,legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=axis.options.font||"flot-tick-label tickLabel",tick,x,y,halign,valign;surface.removeText(layer);if(!axis.show||axis.ticks.length==0)return;for(var i=0;i<axis.ticks.length;++i){tick=axis.ticks[i];if(!tick.label||tick.v<axis.min||tick.v>axis.max)continue;if(axis.direction=="x"){halign="center";x=plotOffset.left+axis.p2c(tick.v);if(axis.position=="bottom"){y=box.top+box.padding}else{y=box.top+box.height-box.padding;valign="bottom"}}else{valign="middle";y=plotOffset.top+axis.p2c(tick.v);if(axis.position=="left"){x=box.left+box.width-box.padding;halign="right"}else{x=box.left+box.padding}}surface.addText(layer,x,y,tick.label,font,null,null,halign,valign)}})}function drawSeries(series){if(series.lines.show)drawSeriesLines(series);if(series.bars.show)drawSeriesBars(series);if(series.points.show)drawSeriesPoints(series)}function drawSeriesLines(series){function plotLine(datapoints,xoffset,yoffset,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,prevx=null,prevy=null;ctx.beginPath();for(var i=ps;i<points.length;i+=ps){var x1=points[i-ps],y1=points[i-ps+1],x2=points[i],y2=points[i+1];if(x1==null||x2==null)continue;if(y1<=y2&&y1<axisy.min){if(y2<axisy.min)continue;x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min){if(y1<axisy.min)continue;x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max){if(y2>axisy.max)continue;x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max){if(y1>axisy.max)continue;x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(x1!=prevx||y1!=prevy)ctx.moveTo(axisx.p2c(x1)+xoffset,axisy.p2c(y1)+yoffset);prevx=x2;prevy=y2;ctx.lineTo(axisx.p2c(x2)+xoffset,axisy.p2c(y2)+yoffset)}ctx.stroke()}function plotLineArea(datapoints,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,bottom=Math.min(Math.max(0,axisy.min),axisy.max),i=0,top,areaOpen=false,ypos=1,segmentStart=0,segmentEnd=0;while(true){if(ps>0&&i>points.length+ps)break;i+=ps;var x1=points[i-ps],y1=points[i-ps+ypos],x2=points[i],y2=points[i+ypos];if(areaOpen){if(ps>0&&x1!=null&&x2==null){segmentEnd=i;ps=-ps;ypos=2;continue}if(ps<0&&i==segmentStart+ps){ctx.fill();areaOpen=false;ps=-ps;ypos=1;i=segmentStart=segmentEnd+ps;continue}}if(x1==null||x2==null)continue;if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(!areaOpen){ctx.beginPath();ctx.moveTo(axisx.p2c(x1),axisy.p2c(bottom));areaOpen=true}if(y1>=axisy.max&&y2>=axisy.max){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.max));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.max));continue}else if(y1<=axisy.min&&y2<=axisy.min){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.min));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.min));continue}var x1old=x1,x2old=x2;if(y1<=y2&&y1<axisy.min&&y2>=axisy.min){x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min&&y1>=axisy.min){x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max&&y2<=axisy.max){x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max&&y1<=axisy.max){x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1!=x1old){ctx.lineTo(axisx.p2c(x1old),axisy.p2c(y1))}ctx.lineTo(axisx.p2c(x1),axisy.p2c(y1));ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));if(x2!=x2old){ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));ctx.lineTo(axisx.p2c(x2old),axisy.p2c(y2))}}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineJoin="round";var lw=series.lines.lineWidth,sw=series.shadowSize;if(lw>0&&sw>0){ctx.lineWidth=sw;ctx.strokeStyle="rgba(0,0,0,0.1)";var angle=Math.PI/18;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/2),Math.cos(angle)*(lw/2+sw/2),series.xaxis,series.yaxis);ctx.lineWidth=sw/2;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/4),Math.cos(angle)*(lw/2+sw/4),series.xaxis,series.yaxis)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;var fillStyle=getFillStyle(series.lines,series.color,0,plotHeight);if(fillStyle){ctx.fillStyle=fillStyle;plotLineArea(series.datapoints,series.xaxis,series.yaxis)}if(lw>0)plotLine(series.datapoints,0,0,series.xaxis,series.yaxis);ctx.restore()}function drawSeriesPoints(series){function plotPoints(datapoints,radius,fillStyle,offset,shadow,axisx,axisy,symbol){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){var x=points[i],y=points[i+1];if(x==null||x<axisx.min||x>axisx.max||y<axisy.min||y>axisy.max)continue;ctx.beginPath();x=axisx.p2c(x);y=axisy.p2c(y)+offset;if(symbol=="circle")ctx.arc(x,y,radius,0,shadow?Math.PI:Math.PI*2,false);else symbol(ctx,x,y,radius,shadow);ctx.closePath();if(fillStyle){ctx.fillStyle=fillStyle;ctx.fill()}ctx.stroke()}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var lw=series.points.lineWidth,sw=series.shadowSize,radius=series.points.radius,symbol=series.points.symbol;if(lw==0)lw=1e-4;if(lw>0&&sw>0){var w=sw/2;ctx.lineWidth=w;ctx.strokeStyle="rgba(0,0,0,0.1)";plotPoints(series.datapoints,radius,null,w+w/2,true,series.xaxis,series.yaxis,symbol);ctx.strokeStyle="rgba(0,0,0,0.2)";plotPoints(series.datapoints,radius,null,w/2,true,series.xaxis,series.yaxis,symbol)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;plotPoints(series.datapoints,radius,getFillStyle(series.points,series.color),0,false,series.xaxis,series.yaxis,symbol);ctx.restore()}function drawBar(x,y,b,barLeft,barRight,fillStyleCallback,axisx,axisy,c,horizontal,lineWidth){var left,right,bottom,top,drawLeft,drawRight,drawTop,drawBottom,tmp;if(horizontal){drawBottom=drawRight=drawTop=true;drawLeft=false;left=b;right=x;top=y+barLeft;bottom=y+barRight;if(right<left){tmp=right;right=left;left=tmp;drawLeft=true;drawRight=false}}else{drawLeft=drawRight=drawTop=true;drawBottom=false;left=x+barLeft;right=x+barRight;bottom=b;top=y;if(top<bottom){tmp=top;top=bottom;bottom=tmp;drawBottom=true;drawTop=false}}if(right<axisx.min||left>axisx.max||top<axisy.min||bottom>axisy.max)return;if(left<axisx.min){left=axisx.min;drawLeft=false}if(right>axisx.max){right=axisx.max;drawRight=false}if(bottom<axisy.min){bottom=axisy.min;drawBottom=false}if(top>axisy.max){top=axisy.max;drawTop=false}left=axisx.p2c(left);bottom=axisy.p2c(bottom);right=axisx.p2c(right);top=axisy.p2c(top);if(fillStyleCallback){c.fillStyle=fillStyleCallback(bottom,top);c.fillRect(left,top,right-left,bottom-top)}if(lineWidth>0&&(drawLeft||drawRight||drawTop||drawBottom)){c.beginPath();c.moveTo(left,bottom);if(drawLeft)c.lineTo(left,top);else c.moveTo(left,top);if(drawTop)c.lineTo(right,top);else c.moveTo(right,top);if(drawRight)c.lineTo(right,bottom);else c.moveTo(right,bottom);if(drawBottom)c.lineTo(left,bottom);else c.moveTo(left,bottom);c.stroke()}}function drawSeriesBars(series){function plotBars(datapoints,barLeft,barRight,fillStyleCallback,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){if(points[i]==null)continue;drawBar(points[i],points[i+1],points[i+2],barLeft,barRight,fillStyleCallback,axisx,axisy,ctx,series.bars.horizontal,series.bars.lineWidth)}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineWidth=series.bars.lineWidth;ctx.strokeStyle=series.color;var barLeft;switch(series.bars.align){case"left":barLeft=0;break;case"right":barLeft=-series.bars.barWidth;break;default:barLeft=-series.bars.barWidth/2}var fillStyleCallback=series.bars.fill?function(bottom,top){return 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- </head>
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-     <div id="wrap">
-      <div id="main" class="body">
-    <h1>criterion performance measurements</h1>
-
-<h2>overview</h2>
-
-<p><a href="#grokularation">want to understand this report?</a></p>
-
-<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
-
-<h2><a name="b0">fib/1</a></h2>
- <table width="100%">
-  <tbody>
-   <tr>
-    <td><div id="kde0" class="kdechart"
-             style="width:450px;height:278px;"></div></td>
-    <td><div id="time0" class="timechart"
-             style="width:450px;height:278px;"></div></td>
-<!--
-    <td><div id="cycle0" class="cyclechart"
-             style="width:300px;height:278px;"></div></td>
--->
-   </tr>
-  </tbody>
- </table>
-
- <table>
-  <thead class="analysis">
-   <th></th>
-   <th class="cibound"
-       title="0.95 confidence level">lower bound</th>
-   <th>estimate</th>
-   <th class="cibound"
-       title="0.95 confidence level">upper bound</th>
-  </thead>
-  <tbody>
-   <tr>
-    <td>OLS regression</td>
-    <td><span class="confinterval olstimelb0">xxx</span></td>
-    <td><span class="olstimept0">xxx</span></td>
-    <td><span class="confinterval olstimeub0">xxx</span></td>
-   </tr>
-   <tr>
-    <td>R&#xb2; goodness-of-fit</td>
-    <td><span class="confinterval olsr2lb0">xxx</span></td>
-    <td><span class="olsr2pt0">xxx</span></td>
-    <td><span class="confinterval olsr2ub0">xxx</span></td>
-   </tr>
-   <tr>
-    <td>Mean execution time</td>
-    <td><span class="confinterval citime">1.534933170419988e-8</span></td>
-    <td><span class="time">1.559289558335549e-8</span></td>
-    <td><span class="confinterval citime">1.5955027539726543e-8</span></td>
-   </tr>
-   <tr>
-    <td>Standard deviation</td>
-    <td><span class="confinterval citime">6.920776075641315e-10</span></td>
-    <td><span class="time">9.603540851522639e-10</span></td>
-    <td><span class="confinterval citime">1.5315630337882154e-9</span></td>
-   </tr>
-  </tbody>
- </table>
-
- <span class="outliers">
-   <p>Outlying measurements have severe
-     (<span class="percent">0.8088974150289796</span>%)
-     effect on estimated standard deviation.</p>
- </span>
-<h2><a name="b1">fib/5</a></h2>
- <table width="100%">
-  <tbody>
-   <tr>
-    <td><div id="kde1" class="kdechart"
-             style="width:450px;height:278px;"></div></td>
-    <td><div id="time1" class="timechart"
-             style="width:450px;height:278px;"></div></td>
-<!--
-    <td><div id="cycle1" class="cyclechart"
-             style="width:300px;height:278px;"></div></td>
--->
-   </tr>
-  </tbody>
- </table>
-
- <table>
-  <thead class="analysis">
-   <th></th>
-   <th class="cibound"
-       title="0.95 confidence level">lower bound</th>
-   <th>estimate</th>
-   <th class="cibound"
-       title="0.95 confidence level">upper bound</th>
-  </thead>
-  <tbody>
-   <tr>
-    <td>OLS regression</td>
-    <td><span class="confinterval olstimelb1">xxx</span></td>
-    <td><span class="olstimept1">xxx</span></td>
-    <td><span class="confinterval olstimeub1">xxx</span></td>
-   </tr>
-   <tr>
-    <td>R&#xb2; goodness-of-fit</td>
-    <td><span class="confinterval olsr2lb1">xxx</span></td>
-    <td><span class="olsr2pt1">xxx</span></td>
-    <td><span class="confinterval olsr2ub1">xxx</span></td>
-   </tr>
-   <tr>
-    <td>Mean execution time</td>
-    <td><span class="confinterval citime">2.0708698124838526e-7</span></td>
-    <td><span class="time">2.1107084459065708e-7</span></td>
-    <td><span class="confinterval citime">2.1648984992614215e-7</span></td>
-   </tr>
-   <tr>
-    <td>Standard deviation</td>
-    <td><span class="confinterval citime">1.0816855360797646e-8</span></td>
-    <td><span class="time">1.509440180252194e-8</span></td>
-    <td><span class="confinterval citime">2.2611667067984586e-8</span></td>
-   </tr>
-  </tbody>
- </table>
-
- <span class="outliers">
-   <p>Outlying measurements have severe
-     (<span class="percent">0.8225875438214796</span>%)
-     effect on estimated standard deviation.</p>
- </span>
-<h2><a name="b2">fib/9</a></h2>
- <table width="100%">
-  <tbody>
-   <tr>
-    <td><div id="kde2" class="kdechart"
-             style="width:450px;height:278px;"></div></td>
-    <td><div id="time2" class="timechart"
-             style="width:450px;height:278px;"></div></td>
-<!--
-    <td><div id="cycle2" class="cyclechart"
-             style="width:300px;height:278px;"></div></td>
--->
-   </tr>
-  </tbody>
- </table>
-
- <table>
-  <thead class="analysis">
-   <th></th>
-   <th class="cibound"
-       title="0.95 confidence level">lower bound</th>
-   <th>estimate</th>
-   <th class="cibound"
-       title="0.95 confidence level">upper bound</th>
-  </thead>
-  <tbody>
-   <tr>
-    <td>OLS regression</td>
-    <td><span class="confinterval olstimelb2">xxx</span></td>
-    <td><span class="olstimept2">xxx</span></td>
-    <td><span class="confinterval olstimeub2">xxx</span></td>
-   </tr>
-   <tr>
-    <td>R&#xb2; goodness-of-fit</td>
-    <td><span class="confinterval olsr2lb2">xxx</span></td>
-    <td><span class="olsr2pt2">xxx</span></td>
-    <td><span class="confinterval olsr2ub2">xxx</span></td>
-   </tr>
-   <tr>
-    <td>Mean execution time</td>
-    <td><span class="confinterval citime">1.5092983334102336e-6</span></td>
-    <td><span class="time">1.531476067375206e-6</span></td>
-    <td><span class="confinterval citime">1.5561257644394457e-6</span></td>
-   </tr>
-   <tr>
-    <td>Standard deviation</td>
-    <td><span class="confinterval citime">6.251710322835121e-8</span></td>
-    <td><span class="time">8.358628655460513e-8</span></td>
-    <td><span class="confinterval citime">1.1570124318539241e-7</span></td>
-   </tr>
-  </tbody>
- </table>
-
- <span class="outliers">
-   <p>Outlying measurements have severe
-     (<span class="percent">0.6916115394455409</span>%)
-     effect on estimated standard deviation.</p>
- </span>
-<h2><a name="b3">fib/11</a></h2>
- <table width="100%">
-  <tbody>
-   <tr>
-    <td><div id="kde3" class="kdechart"
-             style="width:450px;height:278px;"></div></td>
-    <td><div id="time3" class="timechart"
-             style="width:450px;height:278px;"></div></td>
-<!--
-    <td><div id="cycle3" class="cyclechart"
-             style="width:300px;height:278px;"></div></td>
--->
-   </tr>
-  </tbody>
- </table>
-
- <table>
-  <thead class="analysis">
-   <th></th>
-   <th class="cibound"
-       title="0.95 confidence level">lower bound</th>
-   <th>estimate</th>
-   <th class="cibound"
-       title="0.95 confidence level">upper bound</th>
-  </thead>
-  <tbody>
-   <tr>
-    <td>OLS regression</td>
-    <td><span class="confinterval olstimelb3">xxx</span></td>
-    <td><span class="olstimept3">xxx</span></td>
-    <td><span class="confinterval olstimeub3">xxx</span></td>
-   </tr>
-   <tr>
-    <td>R&#xb2; goodness-of-fit</td>
-    <td><span class="confinterval olsr2lb3">xxx</span></td>
-    <td><span class="olsr2pt3">xxx</span></td>
-    <td><span class="confinterval olsr2ub3">xxx</span></td>
-   </tr>
-   <tr>
-    <td>Mean execution time</td>
-    <td><span class="confinterval citime">4.0381903380782345e-6</span></td>
-    <td><span class="time">4.1056747646400756e-6</span></td>
-    <td><span class="confinterval citime">4.177267574309266e-6</span></td>
-   </tr>
-   <tr>
-    <td>Standard deviation</td>
-    <td><span class="confinterval citime">1.967404221672586e-7</span></td>
-    <td><span class="time">2.3166650962027132e-7</span></td>
-    <td><span class="confinterval citime">2.8018472343096967e-7</span></td>
-   </tr>
-  </tbody>
- </table>
-
- <span class="outliers">
-   <p>Outlying measurements have severe
-     (<span class="percent">0.6846724652533784</span>%)
-     effect on estimated standard deviation.</p>
- </span>
-
- <h2><a name="grokularation">understanding this report</a></h2>
-
- <p>In this report, each function benchmarked by criterion is assigned
-   a section of its own.  The charts in each section are active; if
-   you hover your mouse over data points and annotations, you will see
-   more details.</p>
-
- <ul>
-   <li>The chart on the left is a
-     <a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
-       density estimate</a> (also known as a KDE) of time
-     measurements.  This graphs the probability of any given time
-     measurement occurring.  A spike indicates that a measurement of a
-     particular time occurred; its height indicates how often that
-     measurement was repeated.</li>
-
-   <li>The chart on the right is the raw data from which the kernel
-     density estimate is built.  The <i>x</i> axis indicates the
-     number of loop iterations, while the <i>y</i> axis shows measured
-     execution time for the given number of loop iterations.  The
-     line behind the values is the linear regression prediction of
-     execution time for a given number of iterations. Ideally, all
-     measurements will be on (or very near) this line.</li>
- </ul>
-
- <p>Under the charts is a small table.
-   The first two rows are the results of a linear regression run
-     on the measurements displayed in the right-hand chart.</p>
-
- <ul>
-   <li><i>OLS regression</i> indicates the
-     time estimated for a single loop iteration using an ordinary
-     least-squares regression model.  This number is more accurate
-     than the <i>mean</i> estimate below it, as it more effectively
-     eliminates measurement overhead and other constant factors.</li>
-   <li><i>R&#xb2; goodness-of-fit</i> is a measure of how
-     accurately the linear regression model fits the observed
-     measurements.  If the measurements are not too noisy, R&#xb2;
-     should lie between 0.99 and 1, indicating an excellent fit. If
-     the number is below 0.99, something is confounding the accuracy
-     of the linear model.</li>
-   <li><i>Mean execution time</i> and <i>standard deviation</i> are
-     statistics calculated from execution time
-     divided by number of iterations.</li>
- </ul>
-
- <p>We use a statistical technique called
-   the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
-   to provide confidence intervals on our estimates.  The
-   bootstrap-derived upper and lower bounds on estimates let you see
-   how accurate we believe those estimates to be.  (Hover the mouse
-   over the table headers to see the confidence levels.)</p>
-
- <p>A noisy benchmarking environment can cause some or many
-   measurements to fall far from the mean.  These outlying
-   measurements can have a significant inflationary effect on the
-   estimate of the standard deviation.  We calculate and display an
-   estimate of the extent to which the standard deviation has been
-   inflated by outliers.</p>
-
-<script type="text/javascript">
-$(function () {
-  function mangulate(rpt) {
-    var measured = function(key) {
-      var idx = rpt.reportKeys.indexOf(key);
-      return rpt.reportMeasured.map(function(r) { return r[idx]; });
-    };
-    var number = rpt.reportNumber;
-    var name = rpt.reportName;
-    var mean = rpt.reportAnalysis.anMean.estPoint;
-    var iters = measured("iters");
-    var times = measured("time");
-    var kdetimes = rpt.reportKDEs[0].kdeValues;
-    var kdepdf = rpt.reportKDEs[0].kdePDF;
-
-    var meanSecs = mean;
-    var units = $.timeUnits(mean);
-    var rgrs = rpt.reportAnalysis.anRegress[0];
-    var scale = units[0];
-    var olsTime = rgrs.regCoeffs.iters;
-    $(".olstimept" + number).text(function() {
-        return $.renderTime(olsTime.estPoint);
-      });
-    $(".olstimelb" + number).text(function() {
-        return $.renderTime(olsTime.estLowerBound);
-      });
-    $(".olstimeub" + number).text(function() {
-        return $.renderTime(olsTime.estUpperBound);
-      });
-    $(".olsr2pt" + number).text(function() {
-        return rgrs.regRSquare.estPoint.toFixed(3);
-      });
-    $(".olsr2lb" + number).text(function() {
-        return rgrs.regRSquare.estLowerBound.toFixed(3);
-      });
-    $(".olsr2ub" + number).text(function() {
-        return rgrs.regRSquare.estUpperBound.toFixed(3);
-      });
-    mean *= scale;
-    kdetimes = $.scaleBy(scale, kdetimes);
-    var kq = $("#kde" + number);
-    var k = $.plot(kq,
-           [{ label: name + " time densities",
-              data: $.zip(kdetimes, kdepdf),
-              }],
-           { xaxis: { tickFormatter: $.unitFormatter(scale) },
-             yaxis: { ticks: false },
-             grid: { borderColor: "#777",
-                     hoverable: true, markings: [ { color: '#6fd3fb',
-                     lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] },
-           });
-    var o = k.pointOffset({ x: mean, y: 0});
-    kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) +
-              '" style="position:absolute;left:' + (o.left + 4) +
-              'px;bottom:139px;">mean</div>');
-    $.addTooltip("#kde" + number,
-                 function(secs) { return $.renderTime(secs / scale); });
-    var timepairs = new Array(times.length);
-    var lastiter = iters[iters.length-1];
-    var olspairs = [[0,0], [lastiter, lastiter * scale * olsTime.estPoint]];
-    for (var i = 0; i < times.length; i++)
-      timepairs[i] = [iters[i],times[i]*scale];
-    iterFormatter = function() {
-      var denom = 0;
-      return function(iters) {
-	if (iters == 0)
-          return '';
-	if (denom > 0)
-	  return (iters / denom).toFixed();
-        var power;
-	if (iters >= 1e9) {
-	    denom = '1e9'; power = '&#x2079;';
-        }
-	if (iters >= 1e6) {
-	    denom = '1e6'; power = '&#x2076;';
-        }
-        else if (iters >= 1e3) {
-            denom = '1e3'; power = '&#xb3;';
-        }
-        else denom = 1;
-        if (denom > 1) {
-          iters = (iters / denom).toFixed();
-	  iters += '&times;10' + power + ' iters';
-        } else {
-          iters += ' iters';
-        }
-        return iters;
-      };
-    };
-    $.plot($("#time" + number),
-           [{ label: "regression", data: olspairs,
-              lines: { show: true } },
-            { label: name + " times", data: timepairs,
-              points: { show: true } }],
-            { grid: { borderColor: "#777", hoverable: true },
-              xaxis: { tickFormatter: iterFormatter() },
-              yaxis: { tickFormatter: $.unitFormatter(scale) } });
-    $.addTooltip("#time" + number,
-		 function(iters,secs) {
-		   return ($.renderTime(secs / scale) + ' / ' +
-			   iters.toLocaleString() + ' iters');
-		 });
-    if (0) {
-      var cyclepairs = new Array(cycles.length);
-      for (var i = 0; i < cycles.length; i++)
-	cyclepairs[i] = [cycles[i],i];
-      $.plot($("#cycle" + number),
-	     [{ label: name + " cycles",
-		data: cyclepairs }],
-	     { points: { show: true },
-	       grid: { borderColor: "#777", hoverable: true },
-	       xaxis: { tickFormatter:
-			function(cycles,axis) { return cycles + ' cycles'; }},
-	       yaxis: { ticks: false },
-	     });
-      $.addTooltip("#cycles" + number, function(x,y) { return x + ' cycles'; });
-    }
-  };
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-  reports.map(mangulate);
-
-  var benches = ["fib/1","fib/5","fib/9","fib/11",];
-  var ylabels = [[-0,'<a href="#b0">fib/1</a>'],[-1,'<a href="#b1">fib/5</a>'],[-2,'<a href="#b2">fib/9</a>'],[-3,'<a href="#b3">fib/11</a>'],];
-  var means = $.scaleTimes([1.559289558335549e-8,2.1107084459065708e-7,1.531476067375206e-6,4.1056747646400756e-6,]);
-  var xs = [];
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-  for (var i = 0; i < means[0].length; i++) {
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-    name.pop();
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-      prev = name;
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-      xs[xs.length-1].data.push([means[0][i],-i]);
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-  var oq = $("#overview");
-  o = $.plot(oq, xs, { bars: { show: true, horizontal: true,
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-                       xaxis: { max: Math.max.apply(undefined,means[0]) * 1.02 },
-                       yaxis: { ticks: ylabels, tickColor: '#ffffff' } });
-  if (benches.length > 3)
-    o.getPlaceholder().height(28*benches.length);
-  o.resize();
-  o.setupGrid();
-  o.draw();
-  $.addTooltip("#overview", function(x,y) { return $.renderTime(x / means[1]); });
-});
-$(document).ready(function () {
-    $(".time").text(function(_, text) {
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-      <p>This report was created using the
-	<a href="http://hackage.haskell.org/package/criterion">criterion</a>
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-      <p>Criterion is developed and maintained
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series=[],options={colors:["#edc240","#afd8f8","#cb4b4b","#4da74d","#9440ed"],legend:{show:true,noColumns:1,labelFormatter:null,labelBoxBorderColor:"#ccc",container:null,position:"ne",margin:5,backgroundColor:null,backgroundOpacity:.85,sorted:null},xaxis:{show:null,position:"bottom",mode:null,font:null,color:null,tickColor:null,transform:null,inverseTransform:null,min:null,max:null,autoscaleMargin:null,ticks:null,tickFormatter:null,labelWidth:null,labelHeight:null,reserveSpace:null,tickLength:null,alignTicksWithAxis:null,tickDecimals:null,tickSize:null,minTickSize:null},yaxis:{autoscaleMargin:.02,position:"left"},xaxes:[],yaxes:[],series:{points:{show:false,radius:3,lineWidth:2,fill:true,fillColor:"#ffffff",symbol:"circle"},lines:{lineWidth:2,fill:false,fillColor:null,steps:false},bars:{show:false,lineWidth:2,barWidth:1,fill:true,fillColor:null,align:"left",horizontal:false,zero:true},shadowSize:3,highlightColor:null},grid:{show:true,aboveData:false,color:"#545454",backgroundColor:null,borderColor:null,tickColor:null,margin:0,labelMargin:5,axisMargin:8,borderWidth:2,minBorderMargin:null,markings:null,markingsColor:"#f4f4f4",markingsLineWidth:2,clickable:false,hoverable:false,autoHighlight:true,mouseActiveRadius:10},interaction:{redrawOverlayInterval:1e3/60},hooks:{}},surface=null,overlay=null,eventHolder=null,ctx=null,octx=null,xaxes=[],yaxes=[],plotOffset={left:0,right:0,top:0,bottom:0},plotWidth=0,plotHeight=0,hooks={processOptions:[],processRawData:[],processDatapoints:[],processOffset:[],drawBackground:[],drawSeries:[],draw:[],bindEvents:[],drawOverlay:[],shutdown:[]},plot=this;plot.setData=setData;plot.setupGrid=setupGrid;plot.draw=draw;plot.getPlaceholder=function(){return placeholder};plot.getCanvas=function(){return surface.element};plot.getPlotOffset=function(){return plotOffset};plot.width=function(){return plotWidth};plot.height=function(){return plotHeight};plot.offset=function(){var o=eventHolder.offset();o.left+=plotOffset.left;o.top+=plotOffset.top;return o};plot.getData=function(){return series};plot.getAxes=function(){var res={},i;$.each(xaxes.concat(yaxes),function(_,axis){if(axis)res[axis.direction+(axis.n!=1?axis.n:"")+"axis"]=axis});return res};plot.getXAxes=function(){return xaxes};plot.getYAxes=function(){return yaxes};plot.c2p=canvasToAxisCoords;plot.p2c=axisToCanvasCoords;plot.getOptions=function(){return options};plot.highlight=highlight;plot.unhighlight=unhighlight;plot.triggerRedrawOverlay=triggerRedrawOverlay;plot.pointOffset=function(point){return{left:parseInt(xaxes[axisNumber(point,"x")-1].p2c(+point.x)+plotOffset.left,10),top:parseInt(yaxes[axisNumber(point,"y")-1].p2c(+point.y)+plotOffset.top,10)}};plot.shutdown=shutdown;plot.destroy=function(){shutdown();placeholder.removeData("plot").empty();series=[];options=null;surface=null;overlay=null;eventHolder=null;ctx=null;octx=null;xaxes=[];yaxes=[];hooks=null;highlights=[];plot=null};plot.resize=function(){var width=placeholder.width(),height=placeholder.height();surface.resize(width,height);overlay.resize(width,height)};plot.hooks=hooks;initPlugins(plot);parseOptions(options_);setupCanvases();setData(data_);setupGrid();draw();bindEvents();function executeHooks(hook,args){args=[plot].concat(args);for(var i=0;i<hook.length;++i)hook[i].apply(this,args)}function initPlugins(){var classes={Canvas:Canvas};for(var i=0;i<plugins.length;++i){var p=plugins[i];p.init(plot,classes);if(p.options)$.extend(true,options,p.options)}}function parseOptions(opts){$.extend(true,options,opts);if(opts&&opts.colors){options.colors=opts.colors}if(options.xaxis.color==null)options.xaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.yaxis.color==null)options.yaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.xaxis.tickColor==null)options.xaxis.tickColor=options.grid.tickColor||options.xaxis.color;if(options.yaxis.tickColor==null)options.yaxis.tickColor=options.grid.tickColor||options.yaxis.color;if(options.grid.borderColor==null)options.grid.borderColor=options.grid.color;if(options.grid.tickColor==null)options.grid.tickColor=$.color.parse(options.grid.color).scale("a",.22).toString();var i,axisOptions,axisCount,fontSize=placeholder.css("font-size"),fontSizeDefault=fontSize?+fontSize.replace("px",""):13,fontDefaults={style:placeholder.css("font-style"),size:Math.round(.8*fontSizeDefault),variant:placeholder.css("font-variant"),weight:placeholder.css("font-weight"),family:placeholder.css("font-family")};axisCount=options.xaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.xaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.xaxis,axisOptions);options.xaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}axisCount=options.yaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.yaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.yaxis,axisOptions);options.yaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}if(options.xaxis.noTicks&&options.xaxis.ticks==null)options.xaxis.ticks=options.xaxis.noTicks;if(options.yaxis.noTicks&&options.yaxis.ticks==null)options.yaxis.ticks=options.yaxis.noTicks;if(options.x2axis){options.xaxes[1]=$.extend(true,{},options.xaxis,options.x2axis);options.xaxes[1].position="top";if(options.x2axis.min==null){options.xaxes[1].min=null}if(options.x2axis.max==null){options.xaxes[1].max=null}}if(options.y2axis){options.yaxes[1]=$.extend(true,{},options.yaxis,options.y2axis);options.yaxes[1].position="right";if(options.y2axis.min==null){options.yaxes[1].min=null}if(options.y2axis.max==null){options.yaxes[1].max=null}}if(options.grid.coloredAreas)options.grid.markings=options.grid.coloredAreas;if(options.grid.coloredAreasColor)options.grid.markingsColor=options.grid.coloredAreasColor;if(options.lines)$.extend(true,options.series.lines,options.lines);if(options.points)$.extend(true,options.series.points,options.points);if(options.bars)$.extend(true,options.series.bars,options.bars);if(options.shadowSize!=null)options.series.shadowSize=options.shadowSize;if(options.highlightColor!=null)options.series.highlightColor=options.highlightColor;for(i=0;i<options.xaxes.length;++i)getOrCreateAxis(xaxes,i+1).options=options.xaxes[i];for(i=0;i<options.yaxes.length;++i)getOrCreateAxis(yaxes,i+1).options=options.yaxes[i];for(var n in hooks)if(options.hooks[n]&&options.hooks[n].length)hooks[n]=hooks[n].concat(options.hooks[n]);executeHooks(hooks.processOptions,[options])}function setData(d){series=parseData(d);fillInSeriesOptions();processData()}function parseData(d){var res=[];for(var i=0;i<d.length;++i){var s=$.extend(true,{},options.series);if(d[i].data!=null){s.data=d[i].data;delete d[i].data;$.extend(true,s,d[i]);d[i].data=s.data}else s.data=d[i];res.push(s)}return res}function axisNumber(obj,coord){var a=obj[coord+"axis"];if(typeof a=="object")a=a.n;if(typeof a!="number")a=1;return a}function allAxes(){return $.grep(xaxes.concat(yaxes),function(a){return a})}function canvasToAxisCoords(pos){var res={},i,axis;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used)res["x"+axis.n]=axis.c2p(pos.left)}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used)res["y"+axis.n]=axis.c2p(pos.top)}if(res.x1!==undefined)res.x=res.x1;if(res.y1!==undefined)res.y=res.y1;return res}function axisToCanvasCoords(pos){var res={},i,axis,key;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used){key="x"+axis.n;if(pos[key]==null&&axis.n==1)key="x";if(pos[key]!=null){res.left=axis.p2c(pos[key]);break}}}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used){key="y"+axis.n;if(pos[key]==null&&axis.n==1)key="y";if(pos[key]!=null){res.top=axis.p2c(pos[key]);break}}}return res}function getOrCreateAxis(axes,number){if(!axes[number-1])axes[number-1]={n:number,direction:axes==xaxes?"x":"y",options:$.extend(true,{},axes==xaxes?options.xaxis:options.yaxis)};return axes[number-1]}function fillInSeriesOptions(){var neededColors=series.length,maxIndex=-1,i;for(i=0;i<series.length;++i){var sc=series[i].color;if(sc!=null){neededColors--;if(typeof sc=="number"&&sc>maxIndex){maxIndex=sc}}}if(neededColors<=maxIndex){neededColors=maxIndex+1}var c,colors=[],colorPool=options.colors,colorPoolSize=colorPool.length,variation=0;for(i=0;i<neededColors;i++){c=$.color.parse(colorPool[i%colorPoolSize]||"#666");if(i%colorPoolSize==0&&i){if(variation>=0){if(variation<.5){variation=-variation-.2}else variation=0}else variation=-variation}colors[i]=c.scale("rgb",1+variation)}var colori=0,s;for(i=0;i<series.length;++i){s=series[i];if(s.color==null){s.color=colors[colori].toString();++colori}else if(typeof s.color=="number")s.color=colors[s.color].toString();if(s.lines.show==null){var v,show=true;for(v in s)if(s[v]&&s[v].show){show=false;break}if(show)s.lines.show=true}if(s.lines.zero==null){s.lines.zero=!!s.lines.fill}s.xaxis=getOrCreateAxis(xaxes,axisNumber(s,"x"));s.yaxis=getOrCreateAxis(yaxes,axisNumber(s,"y"))}}function processData(){var topSentry=Number.POSITIVE_INFINITY,bottomSentry=Number.NEGATIVE_INFINITY,fakeInfinity=Number.MAX_VALUE,i,j,k,m,length,s,points,ps,x,y,axis,val,f,p,data,format;function updateAxis(axis,min,max){if(min<axis.datamin&&min!=-fakeInfinity)axis.datamin=min;if(max>axis.datamax&&max!=fakeInfinity)axis.datamax=max}$.each(allAxes(),function(_,axis){axis.datamin=topSentry;axis.datamax=bottomSentry;axis.used=false});for(i=0;i<series.length;++i){s=series[i];s.datapoints={points:[]};executeHooks(hooks.processRawData,[s,s.data,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];data=s.data;format=s.datapoints.format;if(!format){format=[];format.push({x:true,number:true,required:true});format.push({y:true,number:true,required:true});if(s.bars.show||s.lines.show&&s.lines.fill){var autoscale=!!(s.bars.show&&s.bars.zero||s.lines.show&&s.lines.zero);format.push({y:true,number:true,required:false,defaultValue:0,autoscale:autoscale});if(s.bars.horizontal){delete format[format.length-1].y;format[format.length-1].x=true}}s.datapoints.format=format}if(s.datapoints.pointsize!=null)continue;s.datapoints.pointsize=format.length;ps=s.datapoints.pointsize;points=s.datapoints.points;var insertSteps=s.lines.show&&s.lines.steps;s.xaxis.used=s.yaxis.used=true;for(j=k=0;j<data.length;++j,k+=ps){p=data[j];var nullify=p==null;if(!nullify){for(m=0;m<ps;++m){val=p[m];f=format[m];if(f){if(f.number&&val!=null){val=+val;if(isNaN(val))val=null;else if(val==Infinity)val=fakeInfinity;else if(val==-Infinity)val=-fakeInfinity}if(val==null){if(f.required)nullify=true;if(f.defaultValue!=null)val=f.defaultValue}}points[k+m]=val}}if(nullify){for(m=0;m<ps;++m){val=points[k+m];if(val!=null){f=format[m];if(f.autoscale!==false){if(f.x){updateAxis(s.xaxis,val,val)}if(f.y){updateAxis(s.yaxis,val,val)}}}points[k+m]=null}}else{if(insertSteps&&k>0&&points[k-ps]!=null&&points[k-ps]!=points[k]&&points[k-ps+1]!=points[k+1]){for(m=0;m<ps;++m)points[k+ps+m]=points[k+m];points[k+1]=points[k-ps+1];k+=ps}}}}for(i=0;i<series.length;++i){s=series[i];executeHooks(hooks.processDatapoints,[s,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];points=s.datapoints.points;ps=s.datapoints.pointsize;format=s.datapoints.format;var xmin=topSentry,ymin=topSentry,xmax=bottomSentry,ymax=bottomSentry;for(j=0;j<points.length;j+=ps){if(points[j]==null)continue;for(m=0;m<ps;++m){val=points[j+m];f=format[m];if(!f||f.autoscale===false||val==fakeInfinity||val==-fakeInfinity)continue;if(f.x){if(val<xmin)xmin=val;if(val>xmax)xmax=val}if(f.y){if(val<ymin)ymin=val;if(val>ymax)ymax=val}}}if(s.bars.show){var delta;switch(s.bars.align){case"left":delta=0;break;case"right":delta=-s.bars.barWidth;break;default:delta=-s.bars.barWidth/2}if(s.bars.horizontal){ymin+=delta;ymax+=delta+s.bars.barWidth}else{xmin+=delta;xmax+=delta+s.bars.barWidth}}updateAxis(s.xaxis,xmin,xmax);updateAxis(s.yaxis,ymin,ymax)}$.each(allAxes(),function(_,axis){if(axis.datamin==topSentry)axis.datamin=null;if(axis.datamax==bottomSentry)axis.datamax=null})}function setupCanvases(){placeholder.css("padding",0).children().filter(function(){return!$(this).hasClass("flot-overlay")&&!$(this).hasClass("flot-base")}).remove();if(placeholder.css("position")=="static")placeholder.css("position","relative");surface=new Canvas("flot-base",placeholder);overlay=new Canvas("flot-overlay",placeholder);ctx=surface.context;octx=overlay.context;eventHolder=$(overlay.element).unbind();var existing=placeholder.data("plot");if(existing){existing.shutdown();overlay.clear()}placeholder.data("plot",plot)}function bindEvents(){if(options.grid.hoverable){eventHolder.mousemove(onMouseMove);eventHolder.bind("mouseleave",onMouseLeave)}if(options.grid.clickable)eventHolder.click(onClick);executeHooks(hooks.bindEvents,[eventHolder])}function shutdown(){if(redrawTimeout)clearTimeout(redrawTimeout);eventHolder.unbind("mousemove",onMouseMove);eventHolder.unbind("mouseleave",onMouseLeave);eventHolder.unbind("click",onClick);executeHooks(hooks.shutdown,[eventHolder])}function setTransformationHelpers(axis){function identity(x){return x}var s,m,t=axis.options.transform||identity,it=axis.options.inverseTransform;if(axis.direction=="x"){s=axis.scale=plotWidth/Math.abs(t(axis.max)-t(axis.min));m=Math.min(t(axis.max),t(axis.min))}else{s=axis.scale=plotHeight/Math.abs(t(axis.max)-t(axis.min));s=-s;m=Math.max(t(axis.max),t(axis.min))}if(t==identity)axis.p2c=function(p){return(p-m)*s};else axis.p2c=function(p){return(t(p)-m)*s};if(!it)axis.c2p=function(c){return m+c/s};else axis.c2p=function(c){return it(m+c/s)}}function measureTickLabels(axis){var opts=axis.options,ticks=axis.ticks||[],labelWidth=opts.labelWidth||0,labelHeight=opts.labelHeight||0,maxWidth=labelWidth||(axis.direction=="x"?Math.floor(surface.width/(ticks.length||1)):null),legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=opts.font||"flot-tick-label tickLabel";for(var i=0;i<ticks.length;++i){var t=ticks[i];if(!t.label)continue;var info=surface.getTextInfo(layer,t.label,font,null,maxWidth);labelWidth=Math.max(labelWidth,info.width);labelHeight=Math.max(labelHeight,info.height)}axis.labelWidth=opts.labelWidth||labelWidth;axis.labelHeight=opts.labelHeight||labelHeight}function allocateAxisBoxFirstPhase(axis){var lw=axis.labelWidth,lh=axis.labelHeight,pos=axis.options.position,isXAxis=axis.direction==="x",tickLength=axis.options.tickLength,axisMargin=options.grid.axisMargin,padding=options.grid.labelMargin,innermost=true,outermost=true,first=true,found=false;$.each(isXAxis?xaxes:yaxes,function(i,a){if(a&&(a.show||a.reserveSpace)){if(a===axis){found=true}else if(a.options.position===pos){if(found){outermost=false}else{innermost=false}}if(!found){first=false}}});if(outermost){axisMargin=0}if(tickLength==null){tickLength=first?"full":5}if(!isNaN(+tickLength))padding+=+tickLength;if(isXAxis){lh+=padding;if(pos=="bottom"){plotOffset.bottom+=lh+axisMargin;axis.box={top:surface.height-plotOffset.bottom,height:lh}}else{axis.box={top:plotOffset.top+axisMargin,height:lh};plotOffset.top+=lh+axisMargin}}else{lw+=padding;if(pos=="left"){axis.box={left:plotOffset.left+axisMargin,width:lw};plotOffset.left+=lw+axisMargin}else{plotOffset.right+=lw+axisMargin;axis.box={left:surface.width-plotOffset.right,width:lw}}}axis.position=pos;axis.tickLength=tickLength;axis.box.padding=padding;axis.innermost=innermost}function allocateAxisBoxSecondPhase(axis){if(axis.direction=="x"){axis.box.left=plotOffset.left-axis.labelWidth/2;axis.box.width=surface.width-plotOffset.left-plotOffset.right+axis.labelWidth}else{axis.box.top=plotOffset.top-axis.labelHeight/2;axis.box.height=surface.height-plotOffset.bottom-plotOffset.top+axis.labelHeight}}function adjustLayoutForThingsStickingOut(){var minMargin=options.grid.minBorderMargin,axis,i;if(minMargin==null){minMargin=0;for(i=0;i<series.length;++i)minMargin=Math.max(minMargin,2*(series[i].points.radius+series[i].points.lineWidth/2))}var margins={left:minMargin,right:minMargin,top:minMargin,bottom:minMargin};$.each(allAxes(),function(_,axis){if(axis.reserveSpace&&axis.ticks&&axis.ticks.length){if(axis.direction==="x"){margins.left=Math.max(margins.left,axis.labelWidth/2);margins.right=Math.max(margins.right,axis.labelWidth/2)}else{margins.bottom=Math.max(margins.bottom,axis.labelHeight/2);margins.top=Math.max(margins.top,axis.labelHeight/2)}}});plotOffset.left=Math.ceil(Math.max(margins.left,plotOffset.left));plotOffset.right=Math.ceil(Math.max(margins.right,plotOffset.right));plotOffset.top=Math.ceil(Math.max(margins.top,plotOffset.top));plotOffset.bottom=Math.ceil(Math.max(margins.bottom,plotOffset.bottom))}function setupGrid(){var i,axes=allAxes(),showGrid=options.grid.show;for(var a in plotOffset){var margin=options.grid.margin||0;plotOffset[a]=typeof margin=="number"?margin:margin[a]||0}executeHooks(hooks.processOffset,[plotOffset]);for(var a in plotOffset){if(typeof options.grid.borderWidth=="object"){plotOffset[a]+=showGrid?options.grid.borderWidth[a]:0}else{plotOffset[a]+=showGrid?options.grid.borderWidth:0}}$.each(axes,function(_,axis){var axisOpts=axis.options;axis.show=axisOpts.show==null?axis.used:axisOpts.show;axis.reserveSpace=axisOpts.reserveSpace==null?axis.show:axisOpts.reserveSpace;setRange(axis)});if(showGrid){var allocatedAxes=$.grep(axes,function(axis){return axis.show||axis.reserveSpace});$.each(allocatedAxes,function(_,axis){setupTickGeneration(axis);setTicks(axis);snapRangeToTicks(axis,axis.ticks);measureTickLabels(axis)});for(i=allocatedAxes.length-1;i>=0;--i)allocateAxisBoxFirstPhase(allocatedAxes[i]);adjustLayoutForThingsStickingOut();$.each(allocatedAxes,function(_,axis){allocateAxisBoxSecondPhase(axis)})}plotWidth=surface.width-plotOffset.left-plotOffset.right;plotHeight=surface.height-plotOffset.bottom-plotOffset.top;$.each(axes,function(_,axis){setTransformationHelpers(axis)});if(showGrid){drawAxisLabels()}insertLegend()}function setRange(axis){var opts=axis.options,min=+(opts.min!=null?opts.min:axis.datamin),max=+(opts.max!=null?opts.max:axis.datamax),delta=max-min;if(delta==0){var widen=max==0?1:.01;if(opts.min==null)min-=widen;if(opts.max==null||opts.min!=null)max+=widen}else{var margin=opts.autoscaleMargin;if(margin!=null){if(opts.min==null){min-=delta*margin;if(min<0&&axis.datamin!=null&&axis.datamin>=0)min=0}if(opts.max==null){max+=delta*margin;if(max>0&&axis.datamax!=null&&axis.datamax<=0)max=0}}}axis.min=min;axis.max=max}function setupTickGeneration(axis){var opts=axis.options;var noTicks;if(typeof opts.ticks=="number"&&opts.ticks>0)noTicks=opts.ticks;else noTicks=.3*Math.sqrt(axis.direction=="x"?surface.width:surface.height);var delta=(axis.max-axis.min)/noTicks,dec=-Math.floor(Math.log(delta)/Math.LN10),maxDec=opts.tickDecimals;if(maxDec!=null&&dec>maxDec){dec=maxDec}var magn=Math.pow(10,-dec),norm=delta/magn,size;if(norm<1.5){size=1}else if(norm<3){size=2;if(norm>2.25&&(maxDec==null||dec+1<=maxDec)){size=2.5;++dec}}else if(norm<7.5){size=5}else{size=10}size*=magn;if(opts.minTickSize!=null&&size<opts.minTickSize){size=opts.minTickSize}axis.delta=delta;axis.tickDecimals=Math.max(0,maxDec!=null?maxDec:dec);axis.tickSize=opts.tickSize||size;if(opts.mode=="time"&&!axis.tickGenerator){throw new Error("Time mode requires the flot.time plugin.")}if(!axis.tickGenerator){axis.tickGenerator=function(axis){var ticks=[],start=floorInBase(axis.min,axis.tickSize),i=0,v=Number.NaN,prev;do{prev=v;v=start+i*axis.tickSize;ticks.push(v);++i}while(v<axis.max&&v!=prev);return ticks};axis.tickFormatter=function(value,axis){var factor=axis.tickDecimals?Math.pow(10,axis.tickDecimals):1;var formatted=""+Math.round(value*factor)/factor;if(axis.tickDecimals!=null){var decimal=formatted.indexOf(".");var precision=decimal==-1?0:formatted.length-decimal-1;if(precision<axis.tickDecimals){return(precision?formatted:formatted+".")+(""+factor).substr(1,axis.tickDecimals-precision)}}return formatted}}if($.isFunction(opts.tickFormatter))axis.tickFormatter=function(v,axis){return""+opts.tickFormatter(v,axis)};if(opts.alignTicksWithAxis!=null){var otherAxis=(axis.direction=="x"?xaxes:yaxes)[opts.alignTicksWithAxis-1];if(otherAxis&&otherAxis.used&&otherAxis!=axis){var niceTicks=axis.tickGenerator(axis);if(niceTicks.length>0){if(opts.min==null)axis.min=Math.min(axis.min,niceTicks[0]);if(opts.max==null&&niceTicks.length>1)axis.max=Math.max(axis.max,niceTicks[niceTicks.length-1])}axis.tickGenerator=function(axis){var ticks=[],v,i;for(i=0;i<otherAxis.ticks.length;++i){v=(otherAxis.ticks[i].v-otherAxis.min)/(otherAxis.max-otherAxis.min);v=axis.min+v*(axis.max-axis.min);ticks.push(v)}return ticks};if(!axis.mode&&opts.tickDecimals==null){var extraDec=Math.max(0,-Math.floor(Math.log(axis.delta)/Math.LN10)+1),ts=axis.tickGenerator(axis);if(!(ts.length>1&&/\..*0$/.test((ts[1]-ts[0]).toFixed(extraDec))))axis.tickDecimals=extraDec}}}}function setTicks(axis){var oticks=axis.options.ticks,ticks=[];if(oticks==null||typeof oticks=="number"&&oticks>0)ticks=axis.tickGenerator(axis);else if(oticks){if($.isFunction(oticks))ticks=oticks(axis);else ticks=oticks}var i,v;axis.ticks=[];for(i=0;i<ticks.length;++i){var label=null;var t=ticks[i];if(typeof t=="object"){v=+t[0];if(t.length>1)label=t[1]}else v=+t;if(label==null)label=axis.tickFormatter(v,axis);if(!isNaN(v))axis.ticks.push({v:v,label:label})}}function snapRangeToTicks(axis,ticks){if(axis.options.autoscaleMargin&&ticks.length>0){if(axis.options.min==null)axis.min=Math.min(axis.min,ticks[0].v);if(axis.options.max==null&&ticks.length>1)axis.max=Math.max(axis.max,ticks[ticks.length-1].v)}}function draw(){surface.clear();executeHooks(hooks.drawBackground,[ctx]);var grid=options.grid;if(grid.show&&grid.backgroundColor)drawBackground();if(grid.show&&!grid.aboveData){drawGrid()}for(var i=0;i<series.length;++i){executeHooks(hooks.drawSeries,[ctx,series[i]]);drawSeries(series[i])}executeHooks(hooks.draw,[ctx]);if(grid.show&&grid.aboveData){drawGrid()}surface.render();triggerRedrawOverlay()}function extractRange(ranges,coord){var axis,from,to,key,axes=allAxes();for(var i=0;i<axes.length;++i){axis=axes[i];if(axis.direction==coord){key=coord+axis.n+"axis";if(!ranges[key]&&axis.n==1)key=coord+"axis";if(ranges[key]){from=ranges[key].from;to=ranges[key].to;break}}}if(!ranges[key]){axis=coord=="x"?xaxes[0]:yaxes[0];from=ranges[coord+"1"];to=ranges[coord+"2"]}if(from!=null&&to!=null&&from>to){var tmp=from;from=to;to=tmp}return{from:from,to:to,axis:axis}}function drawBackground(){ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.fillStyle=getColorOrGradient(options.grid.backgroundColor,plotHeight,0,"rgba(255, 255, 255, 0)");ctx.fillRect(0,0,plotWidth,plotHeight);ctx.restore()}function drawGrid(){var i,axes,bw,bc;ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var markings=options.grid.markings;if(markings){if($.isFunction(markings)){axes=plot.getAxes();axes.xmin=axes.xaxis.min;axes.xmax=axes.xaxis.max;axes.ymin=axes.yaxis.min;axes.ymax=axes.yaxis.max;markings=markings(axes)}for(i=0;i<markings.length;++i){var m=markings[i],xrange=extractRange(m,"x"),yrange=extractRange(m,"y");if(xrange.from==null)xrange.from=xrange.axis.min;if(xrange.to==null)xrange.to=xrange.axis.max;
-if(yrange.from==null)yrange.from=yrange.axis.min;if(yrange.to==null)yrange.to=yrange.axis.max;if(xrange.to<xrange.axis.min||xrange.from>xrange.axis.max||yrange.to<yrange.axis.min||yrange.from>yrange.axis.max)continue;xrange.from=Math.max(xrange.from,xrange.axis.min);xrange.to=Math.min(xrange.to,xrange.axis.max);yrange.from=Math.max(yrange.from,yrange.axis.min);yrange.to=Math.min(yrange.to,yrange.axis.max);var xequal=xrange.from===xrange.to,yequal=yrange.from===yrange.to;if(xequal&&yequal){continue}xrange.from=Math.floor(xrange.axis.p2c(xrange.from));xrange.to=Math.floor(xrange.axis.p2c(xrange.to));yrange.from=Math.floor(yrange.axis.p2c(yrange.from));yrange.to=Math.floor(yrange.axis.p2c(yrange.to));if(xequal||yequal){var lineWidth=m.lineWidth||options.grid.markingsLineWidth,subPixel=lineWidth%2?.5:0;ctx.beginPath();ctx.strokeStyle=m.color||options.grid.markingsColor;ctx.lineWidth=lineWidth;if(xequal){ctx.moveTo(xrange.to+subPixel,yrange.from);ctx.lineTo(xrange.to+subPixel,yrange.to)}else{ctx.moveTo(xrange.from,yrange.to+subPixel);ctx.lineTo(xrange.to,yrange.to+subPixel)}ctx.stroke()}else{ctx.fillStyle=m.color||options.grid.markingsColor;ctx.fillRect(xrange.from,yrange.to,xrange.to-xrange.from,yrange.from-yrange.to)}}}axes=allAxes();bw=options.grid.borderWidth;for(var j=0;j<axes.length;++j){var axis=axes[j],box=axis.box,t=axis.tickLength,x,y,xoff,yoff;if(!axis.show||axis.ticks.length==0)continue;ctx.lineWidth=1;if(axis.direction=="x"){x=0;if(t=="full")y=axis.position=="top"?0:plotHeight;else y=box.top-plotOffset.top+(axis.position=="top"?box.height:0)}else{y=0;if(t=="full")x=axis.position=="left"?0:plotWidth;else x=box.left-plotOffset.left+(axis.position=="left"?box.width:0)}if(!axis.innermost){ctx.strokeStyle=axis.options.color;ctx.beginPath();xoff=yoff=0;if(axis.direction=="x")xoff=plotWidth+1;else yoff=plotHeight+1;if(ctx.lineWidth==1){if(axis.direction=="x"){y=Math.floor(y)+.5}else{x=Math.floor(x)+.5}}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff);ctx.stroke()}ctx.strokeStyle=axis.options.tickColor;ctx.beginPath();for(i=0;i<axis.ticks.length;++i){var v=axis.ticks[i].v;xoff=yoff=0;if(isNaN(v)||v<axis.min||v>axis.max||t=="full"&&(typeof bw=="object"&&bw[axis.position]>0||bw>0)&&(v==axis.min||v==axis.max))continue;if(axis.direction=="x"){x=axis.p2c(v);yoff=t=="full"?-plotHeight:t;if(axis.position=="top")yoff=-yoff}else{y=axis.p2c(v);xoff=t=="full"?-plotWidth:t;if(axis.position=="left")xoff=-xoff}if(ctx.lineWidth==1){if(axis.direction=="x")x=Math.floor(x)+.5;else y=Math.floor(y)+.5}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff)}ctx.stroke()}if(bw){bc=options.grid.borderColor;if(typeof bw=="object"||typeof bc=="object"){if(typeof bw!=="object"){bw={top:bw,right:bw,bottom:bw,left:bw}}if(typeof bc!=="object"){bc={top:bc,right:bc,bottom:bc,left:bc}}if(bw.top>0){ctx.strokeStyle=bc.top;ctx.lineWidth=bw.top;ctx.beginPath();ctx.moveTo(0-bw.left,0-bw.top/2);ctx.lineTo(plotWidth,0-bw.top/2);ctx.stroke()}if(bw.right>0){ctx.strokeStyle=bc.right;ctx.lineWidth=bw.right;ctx.beginPath();ctx.moveTo(plotWidth+bw.right/2,0-bw.top);ctx.lineTo(plotWidth+bw.right/2,plotHeight);ctx.stroke()}if(bw.bottom>0){ctx.strokeStyle=bc.bottom;ctx.lineWidth=bw.bottom;ctx.beginPath();ctx.moveTo(plotWidth+bw.right,plotHeight+bw.bottom/2);ctx.lineTo(0,plotHeight+bw.bottom/2);ctx.stroke()}if(bw.left>0){ctx.strokeStyle=bc.left;ctx.lineWidth=bw.left;ctx.beginPath();ctx.moveTo(0-bw.left/2,plotHeight+bw.bottom);ctx.lineTo(0-bw.left/2,0);ctx.stroke()}}else{ctx.lineWidth=bw;ctx.strokeStyle=options.grid.borderColor;ctx.strokeRect(-bw/2,-bw/2,plotWidth+bw,plotHeight+bw)}}ctx.restore()}function drawAxisLabels(){$.each(allAxes(),function(_,axis){var box=axis.box,legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=axis.options.font||"flot-tick-label tickLabel",tick,x,y,halign,valign;surface.removeText(layer);if(!axis.show||axis.ticks.length==0)return;for(var i=0;i<axis.ticks.length;++i){tick=axis.ticks[i];if(!tick.label||tick.v<axis.min||tick.v>axis.max)continue;if(axis.direction=="x"){halign="center";x=plotOffset.left+axis.p2c(tick.v);if(axis.position=="bottom"){y=box.top+box.padding}else{y=box.top+box.height-box.padding;valign="bottom"}}else{valign="middle";y=plotOffset.top+axis.p2c(tick.v);if(axis.position=="left"){x=box.left+box.width-box.padding;halign="right"}else{x=box.left+box.padding}}surface.addText(layer,x,y,tick.label,font,null,null,halign,valign)}})}function drawSeries(series){if(series.lines.show)drawSeriesLines(series);if(series.bars.show)drawSeriesBars(series);if(series.points.show)drawSeriesPoints(series)}function drawSeriesLines(series){function plotLine(datapoints,xoffset,yoffset,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,prevx=null,prevy=null;ctx.beginPath();for(var i=ps;i<points.length;i+=ps){var x1=points[i-ps],y1=points[i-ps+1],x2=points[i],y2=points[i+1];if(x1==null||x2==null)continue;if(y1<=y2&&y1<axisy.min){if(y2<axisy.min)continue;x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min){if(y1<axisy.min)continue;x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max){if(y2>axisy.max)continue;x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max){if(y1>axisy.max)continue;x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(x1!=prevx||y1!=prevy)ctx.moveTo(axisx.p2c(x1)+xoffset,axisy.p2c(y1)+yoffset);prevx=x2;prevy=y2;ctx.lineTo(axisx.p2c(x2)+xoffset,axisy.p2c(y2)+yoffset)}ctx.stroke()}function plotLineArea(datapoints,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,bottom=Math.min(Math.max(0,axisy.min),axisy.max),i=0,top,areaOpen=false,ypos=1,segmentStart=0,segmentEnd=0;while(true){if(ps>0&&i>points.length+ps)break;i+=ps;var x1=points[i-ps],y1=points[i-ps+ypos],x2=points[i],y2=points[i+ypos];if(areaOpen){if(ps>0&&x1!=null&&x2==null){segmentEnd=i;ps=-ps;ypos=2;continue}if(ps<0&&i==segmentStart+ps){ctx.fill();areaOpen=false;ps=-ps;ypos=1;i=segmentStart=segmentEnd+ps;continue}}if(x1==null||x2==null)continue;if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(!areaOpen){ctx.beginPath();ctx.moveTo(axisx.p2c(x1),axisy.p2c(bottom));areaOpen=true}if(y1>=axisy.max&&y2>=axisy.max){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.max));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.max));continue}else if(y1<=axisy.min&&y2<=axisy.min){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.min));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.min));continue}var x1old=x1,x2old=x2;if(y1<=y2&&y1<axisy.min&&y2>=axisy.min){x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min&&y1>=axisy.min){x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max&&y2<=axisy.max){x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max&&y1<=axisy.max){x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1!=x1old){ctx.lineTo(axisx.p2c(x1old),axisy.p2c(y1))}ctx.lineTo(axisx.p2c(x1),axisy.p2c(y1));ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));if(x2!=x2old){ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));ctx.lineTo(axisx.p2c(x2old),axisy.p2c(y2))}}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineJoin="round";var lw=series.lines.lineWidth,sw=series.shadowSize;if(lw>0&&sw>0){ctx.lineWidth=sw;ctx.strokeStyle="rgba(0,0,0,0.1)";var angle=Math.PI/18;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/2),Math.cos(angle)*(lw/2+sw/2),series.xaxis,series.yaxis);ctx.lineWidth=sw/2;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/4),Math.cos(angle)*(lw/2+sw/4),series.xaxis,series.yaxis)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;var fillStyle=getFillStyle(series.lines,series.color,0,plotHeight);if(fillStyle){ctx.fillStyle=fillStyle;plotLineArea(series.datapoints,series.xaxis,series.yaxis)}if(lw>0)plotLine(series.datapoints,0,0,series.xaxis,series.yaxis);ctx.restore()}function drawSeriesPoints(series){function plotPoints(datapoints,radius,fillStyle,offset,shadow,axisx,axisy,symbol){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){var x=points[i],y=points[i+1];if(x==null||x<axisx.min||x>axisx.max||y<axisy.min||y>axisy.max)continue;ctx.beginPath();x=axisx.p2c(x);y=axisy.p2c(y)+offset;if(symbol=="circle")ctx.arc(x,y,radius,0,shadow?Math.PI:Math.PI*2,false);else symbol(ctx,x,y,radius,shadow);ctx.closePath();if(fillStyle){ctx.fillStyle=fillStyle;ctx.fill()}ctx.stroke()}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var lw=series.points.lineWidth,sw=series.shadowSize,radius=series.points.radius,symbol=series.points.symbol;if(lw==0)lw=1e-4;if(lw>0&&sw>0){var w=sw/2;ctx.lineWidth=w;ctx.strokeStyle="rgba(0,0,0,0.1)";plotPoints(series.datapoints,radius,null,w+w/2,true,series.xaxis,series.yaxis,symbol);ctx.strokeStyle="rgba(0,0,0,0.2)";plotPoints(series.datapoints,radius,null,w/2,true,series.xaxis,series.yaxis,symbol)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;plotPoints(series.datapoints,radius,getFillStyle(series.points,series.color),0,false,series.xaxis,series.yaxis,symbol);ctx.restore()}function drawBar(x,y,b,barLeft,barRight,fillStyleCallback,axisx,axisy,c,horizontal,lineWidth){var left,right,bottom,top,drawLeft,drawRight,drawTop,drawBottom,tmp;if(horizontal){drawBottom=drawRight=drawTop=true;drawLeft=false;left=b;right=x;top=y+barLeft;bottom=y+barRight;if(right<left){tmp=right;right=left;left=tmp;drawLeft=true;drawRight=false}}else{drawLeft=drawRight=drawTop=true;drawBottom=false;left=x+barLeft;right=x+barRight;bottom=b;top=y;if(top<bottom){tmp=top;top=bottom;bottom=tmp;drawBottom=true;drawTop=false}}if(right<axisx.min||left>axisx.max||top<axisy.min||bottom>axisy.max)return;if(left<axisx.min){left=axisx.min;drawLeft=false}if(right>axisx.max){right=axisx.max;drawRight=false}if(bottom<axisy.min){bottom=axisy.min;drawBottom=false}if(top>axisy.max){top=axisy.max;drawTop=false}left=axisx.p2c(left);bottom=axisy.p2c(bottom);right=axisx.p2c(right);top=axisy.p2c(top);if(fillStyleCallback){c.fillStyle=fillStyleCallback(bottom,top);c.fillRect(left,top,right-left,bottom-top)}if(lineWidth>0&&(drawLeft||drawRight||drawTop||drawBottom)){c.beginPath();c.moveTo(left,bottom);if(drawLeft)c.lineTo(left,top);else c.moveTo(left,top);if(drawTop)c.lineTo(right,top);else c.moveTo(right,top);if(drawRight)c.lineTo(right,bottom);else c.moveTo(right,bottom);if(drawBottom)c.lineTo(left,bottom);else c.moveTo(left,bottom);c.stroke()}}function drawSeriesBars(series){function plotBars(datapoints,barLeft,barRight,fillStyleCallback,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){if(points[i]==null)continue;drawBar(points[i],points[i+1],points[i+2],barLeft,barRight,fillStyleCallback,axisx,axisy,ctx,series.bars.horizontal,series.bars.lineWidth)}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineWidth=series.bars.lineWidth;ctx.strokeStyle=series.color;var barLeft;switch(series.bars.align){case"left":barLeft=0;break;case"right":barLeft=-series.bars.barWidth;break;default:barLeft=-series.bars.barWidth/2}var fillStyleCallback=series.bars.fill?function(bottom,top){return 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- </head>
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-     <div id="wrap">
-      <div id="main" class="body">
-    <h1>criterion performance measurements</h1>
-
-<h2>overview</h2>
-
-<p><a href="#grokularation">want to understand this report?</a></p>
-
-<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
-
-<h2><a name="b0">ByteString/HashMap/random</a></h2>
- <table width="100%">
-  <tbody>
-   <tr>
-    <td><div id="kde0" class="kdechart"
-             style="width:450px;height:278px;"></div></td>
-    <td><div id="time0" class="timechart"
-             style="width:450px;height:278px;"></div></td>
-<!--
-    <td><div id="cycle0" class="cyclechart"
-             style="width:300px;height:278px;"></div></td>
--->
-   </tr>
-  </tbody>
- </table>
-
- <table>
-  <thead class="analysis">
-   <th></th>
-   <th class="cibound"
-       title="0.95 confidence level">lower bound</th>
-   <th>estimate</th>
-   <th class="cibound"
-       title="0.95 confidence level">upper bound</th>
-  </thead>
-  <tbody>
-   <tr>
-    <td>OLS regression</td>
-    <td><span class="confinterval olstimelb0">xxx</span></td>
-    <td><span class="olstimept0">xxx</span></td>
-    <td><span class="confinterval olstimeub0">xxx</span></td>
-   </tr>
-   <tr>
-    <td>R&#xb2; goodness-of-fit</td>
-    <td><span class="confinterval olsr2lb0">xxx</span></td>
-    <td><span class="olsr2pt0">xxx</span></td>
-    <td><span class="confinterval olsr2ub0">xxx</span></td>
-   </tr>
-   <tr>
-    <td>Mean execution time</td>
-    <td><span class="confinterval citime">5.54613319607341e-3</span></td>
-    <td><span class="time">5.621667703915931e-3</span></td>
-    <td><span class="confinterval citime">5.713526073454561e-3</span></td>
-   </tr>
-   <tr>
-    <td>Standard deviation</td>
-    <td><span class="confinterval citime">1.972562820146363e-4</span></td>
-    <td><span class="time">2.494938876886024e-4</span></td>
-    <td><span class="confinterval citime">3.1487131555210624e-4</span></td>
-   </tr>
-  </tbody>
- </table>
-
- <span class="outliers">
-   <p>Outlying measurements have moderate
-     (<span class="percent">0.21993690418913867</span>%)
-     effect on estimated standard deviation.</p>
- </span>
-
- <h2><a name="grokularation">understanding this report</a></h2>
-
- <p>In this report, each function benchmarked by criterion is assigned
-   a section of its own.  The charts in each section are active; if
-   you hover your mouse over data points and annotations, you will see
-   more details.</p>
-
- <ul>
-   <li>The chart on the left is a
-     <a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
-       density estimate</a> (also known as a KDE) of time
-     measurements.  This graphs the probability of any given time
-     measurement occurring.  A spike indicates that a measurement of a
-     particular time occurred; its height indicates how often that
-     measurement was repeated.</li>
-
-   <li>The chart on the right is the raw data from which the kernel
-     density estimate is built.  The <i>x</i> axis indicates the
-     number of loop iterations, while the <i>y</i> axis shows measured
-     execution time for the given number of loop iterations.  The
-     line behind the values is the linear regression prediction of
-     execution time for a given number of iterations. Ideally, all
-     measurements will be on (or very near) this line.</li>
- </ul>
-
- <p>Under the charts is a small table.
-   The first two rows are the results of a linear regression run
-     on the measurements displayed in the right-hand chart.</p>
-
- <ul>
-   <li><i>OLS regression</i> indicates the
-     time estimated for a single loop iteration using an ordinary
-     least-squares regression model.  This number is more accurate
-     than the <i>mean</i> estimate below it, as it more effectively
-     eliminates measurement overhead and other constant factors.</li>
-   <li><i>R&#xb2; goodness-of-fit</i> is a measure of how
-     accurately the linear regression model fits the observed
-     measurements.  If the measurements are not too noisy, R&#xb2;
-     should lie between 0.99 and 1, indicating an excellent fit. If
-     the number is below 0.99, something is confounding the accuracy
-     of the linear model.</li>
-   <li><i>Mean execution time</i> and <i>standard deviation</i> are
-     statistics calculated from execution time
-     divided by number of iterations.</li>
- </ul>
-
- <p>We use a statistical technique called
-   the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
-   to provide confidence intervals on our estimates.  The
-   bootstrap-derived upper and lower bounds on estimates let you see
-   how accurate we believe those estimates to be.  (Hover the mouse
-   over the table headers to see the confidence levels.)</p>
-
- <p>A noisy benchmarking environment can cause some or many
-   measurements to fall far from the mean.  These outlying
-   measurements can have a significant inflationary effect on the
-   estimate of the standard deviation.  We calculate and display an
-   estimate of the extent to which the standard deviation has been
-   inflated by outliers.</p>
-
-<script type="text/javascript">
-$(function () {
-  function mangulate(rpt) {
-    var measured = function(key) {
-      var idx = rpt.reportKeys.indexOf(key);
-      return rpt.reportMeasured.map(function(r) { return r[idx]; });
-    };
-    var number = rpt.reportNumber;
-    var name = rpt.reportName;
-    var mean = rpt.reportAnalysis.anMean.estPoint;
-    var iters = measured("iters");
-    var times = measured("time");
-    var kdetimes = rpt.reportKDEs[0].kdeValues;
-    var kdepdf = rpt.reportKDEs[0].kdePDF;
-
-    var meanSecs = mean;
-    var units = $.timeUnits(mean);
-    var rgrs = rpt.reportAnalysis.anRegress[0];
-    var scale = units[0];
-    var olsTime = rgrs.regCoeffs.iters;
-    $(".olstimept" + number).text(function() {
-        return $.renderTime(olsTime.estPoint);
-      });
-    $(".olstimelb" + number).text(function() {
-        return $.renderTime(olsTime.estLowerBound);
-      });
-    $(".olstimeub" + number).text(function() {
-        return $.renderTime(olsTime.estUpperBound);
-      });
-    $(".olsr2pt" + number).text(function() {
-        return rgrs.regRSquare.estPoint.toFixed(3);
-      });
-    $(".olsr2lb" + number).text(function() {
-        return rgrs.regRSquare.estLowerBound.toFixed(3);
-      });
-    $(".olsr2ub" + number).text(function() {
-        return rgrs.regRSquare.estUpperBound.toFixed(3);
-      });
-    mean *= scale;
-    kdetimes = $.scaleBy(scale, kdetimes);
-    var kq = $("#kde" + number);
-    var k = $.plot(kq,
-           [{ label: name + " time densities",
-              data: $.zip(kdetimes, kdepdf),
-              }],
-           { xaxis: { tickFormatter: $.unitFormatter(scale) },
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-           });
-    var o = k.pointOffset({ x: mean, y: 0});
-    kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) +
-              '" style="position:absolute;left:' + (o.left + 4) +
-              'px;bottom:139px;">mean</div>');
-    $.addTooltip("#kde" + number,
-                 function(secs) { return $.renderTime(secs / scale); });
-    var timepairs = new Array(times.length);
-    var lastiter = iters[iters.length-1];
-    var olspairs = [[0,0], [lastiter, lastiter * scale * olsTime.estPoint]];
-    for (var i = 0; i < times.length; i++)
-      timepairs[i] = [iters[i],times[i]*scale];
-    iterFormatter = function() {
-      var denom = 0;
-      return function(iters) {
-	if (iters == 0)
-          return '';
-	if (denom > 0)
-	  return (iters / denom).toFixed();
-        var power;
-	if (iters >= 1e9) {
-	    denom = '1e9'; power = '&#x2079;';
-        }
-	if (iters >= 1e6) {
-	    denom = '1e6'; power = '&#x2076;';
-        }
-        else if (iters >= 1e3) {
-            denom = '1e3'; power = '&#xb3;';
-        }
-        else denom = 1;
-        if (denom > 1) {
-          iters = (iters / denom).toFixed();
-	  iters += '&times;10' + power + ' iters';
-        } else {
-          iters += ' iters';
-        }
-        return iters;
-      };
-    };
-    $.plot($("#time" + number),
-           [{ label: "regression", data: olspairs,
-              lines: { show: true } },
-            { label: name + " times", data: timepairs,
-              points: { show: true } }],
-            { grid: { borderColor: "#777", hoverable: true },
-              xaxis: { tickFormatter: iterFormatter() },
-              yaxis: { tickFormatter: $.unitFormatter(scale) } });
-    $.addTooltip("#time" + number,
-		 function(iters,secs) {
-		   return ($.renderTime(secs / scale) + ' / ' +
-			   iters.toLocaleString() + ' iters');
-		 });
-    if (0) {
-      var cyclepairs = new Array(cycles.length);
-      for (var i = 0; i < cycles.length; i++)
-	cyclepairs[i] = [cycles[i],i];
-      $.plot($("#cycle" + number),
-	     [{ label: name + " cycles",
-		data: cyclepairs }],
-	     { points: { show: true },
-	       grid: { borderColor: "#777", hoverable: true },
-	       xaxis: { tickFormatter:
-			function(cycles,axis) { return cycles + ' cycles'; }},
-	       yaxis: { ticks: false },
-	     });
-      $.addTooltip("#cycles" + number, function(x,y) { return x + ' cycles'; });
-    }
-  };
-  var reports = [{"reportAnalysis":{"anMean":{"estUpperBound":5.713526073454561e-3,"estLowerBound":5.54613319607341e-3,"estPoint":5.621667703915931e-3,"estConfidenceLevel":0.95},"anRegress":[{"regRSquare":{"estUpperBound":0.9981729010272332,"estLowerBound":0.9933906306034458,"estPoint":0.9962485177728473,"estConfidenceLevel":0.95},"regResponder":"time","regCoeffs":{"y":{"estUpperBound":1.73831239286272e-3,"estLowerBound":-2.6907153863794868e-3,"estPoint":-5.701833877751966e-4,"estConfidenceLevel":0.95},"iters":{"estUpperBound":5.78662208554795e-3,"estLowerBound":5.560561655965624e-3,"estPoint":5.671235930328669e-3,"estConfidenceLevel":0.95}}}],"anStdDev":{"estUpperBound":3.1487131555210624e-4,"estLowerBound":1.972562820146363e-4,"estPoint":2.494938876886024e-4,"estConfidenceLevel":0.95},"anOutlierVar":{"ovFraction":0.21993690418913867,"ovDesc":"moderate","ovEffect":"Moderate"},"anOverhead":2.7511337567346434e-6},"reportKDEs":[{"kdeValues":[5.119598999459214e-3,5.128773133785027e-3,5.137947268110841e-3,5.1471214024366545e-3,5.156295536762469e-3,5.165469671088282e-3,5.174643805414095e-3,5.1838179397399094e-3,5.192992074065723e-3,5.202166208391536e-3,5.21134034271735e-3,5.2205144770431635e-3,5.229688611368978e-3,5.238862745694791e-3,5.248036880020604e-3,5.2572110143464185e-3,5.266385148672232e-3,5.275559282998045e-3,5.284733417323859e-3,5.293907551649673e-3,5.303081685975487e-3,5.3122558203013e-3,5.321429954627113e-3,5.3306040889529276e-3,5.339778223278741e-3,5.348952357604554e-3,5.358126491930368e-3,5.367300626256182e-3,5.376474760581996e-3,5.385648894907809e-3,5.3948230292336224e-3,5.403997163559437e-3,5.41317129788525e-3,5.422345432211064e-3,5.431519566536877e-3,5.440693700862691e-3,5.449867835188505e-3,5.459041969514318e-3,5.4682161038401315e-3,5.477390238165946e-3,5.486564372491759e-3,5.495738506817573e-3,5.5049126411433865e-3,5.5140867754692e-3,5.523260909795014e-3,5.532435044120827e-3,5.541609178446641e-3,5.550783312772455e-3,5.559957447098268e-3,5.569131581424082e-3,5.5783057157498955e-3,5.587479850075709e-3,5.596653984401523e-3,5.605828118727336e-3,5.6150022530531505e-3,5.624176387378964e-3,5.633350521704777e-3,5.642524656030591e-3,5.651698790356405e-3,5.660872924682218e-3,5.670047059008032e-3,5.679221193333845e-3,5.688395327659659e-3,5.697569461985473e-3,5.706743596311286e-3,5.7159177306371e-3,5.725091864962914e-3,5.734265999288727e-3,5.743440133614541e-3,5.7526142679403544e-3,5.761788402266169e-3,5.770962536591982e-3,5.780136670917795e-3,5.789310805243609e-3,5.798484939569423e-3,5.807659073895236e-3,5.81683320822105e-3,5.8260073425468635e-3,5.835181476872677e-3,5.844355611198491e-3,5.853529745524304e-3,5.8627038798501185e-3,5.871878014175932e-3,5.881052148501745e-3,5.890226282827559e-3,5.8994004171533726e-3,5.908574551479187e-3,5.917748685805e-3,5.926922820130813e-3,5.9360969544566275e-3,5.945271088782441e-3,5.954445223108255e-3,5.963619357434068e-3,5.972793491759882e-3,5.981967626085696e-3,5.991141760411509e-3,6.000315894737322e-3,6.009490029063137e-3,6.01866416338895e-3,6.027838297714763e-3,6.037012432040577e-3,6.046186566366391e-3,6.055360700692205e-3,6.064534835018018e-3,6.0737089693438315e-3,6.082883103669646e-3,6.092057237995459e-3,6.101231372321273e-3,6.1104055066470864e-3,6.1195796409729e-3,6.128753775298714e-3,6.137927909624527e-3,6.147102043950341e-3,6.156276178276155e-3,6.165450312601968e-3,6.174624446927781e-3,6.1837985812535955e-3,6.192972715579409e-3,6.202146849905223e-3,6.211320984231036e-3,6.22049511855685e-3,6.229669252882664e-3,6.238843387208477e-3,6.248017521534291e-3,6.2571916558601046e-3,6.266365790185918e-3,6.275539924511732e-3,6.284714058837545e-3],"kdeType":"time","kdePDF":[545.3406018643898,547.7604964408598,552.5835234544184,559.7762994995815,569.2891013325717,581.0562871577982,594.9968565868016,611.0151474314513,629.0016666408812,648.8340516123199,670.3781567871325,693.4892588878535,718.0133723788433,743.7886647772734,770.646959352757,798.4153105965786,826.9176356903382,855.9763831421388,885.414217874883,915.0557004354534,944.7289367329893,974.2671738896564,1003.5103174688135,1032.3063455895392,1060.5125962828472,1087.9969059134382,1114.638578580714,1140.3291691007228,1164.9730654118175,1188.4878599745812,1210.804503865528,1231.8672416915,1251.6333300617102,1270.0725470211678,1287.166504442057,1302.9077797566918,1317.2988874695457,1330.3511144872584,1342.0832463483428,1352.5202138285747,1361.6916910736854,1369.630677319676,1376.372094378115,1381.9514313884627,1386.4034668948157,1389.7610961362368,1392.0542886142364,1393.3091976024104,1393.5474393905565,1392.7855558190963,1391.0346691763316,1388.3003339216605,1384.5825850817816,1379.8761786596651,1374.1710151048017,1367.4527329151629,1359.703455859914,1350.9026741969292,1341.028237663689,1330.057435982098,1317.9681411582083,1304.739984983345,1290.35554484537,1274.801511217554,1258.0698109758134,1240.1586619629556,1221.0735359229834,1200.8280090176215,1179.4444815546556,1156.9547512468462,1133.4004272230616,1108.8331750741968,1083.314786380294,1056.9170693808599,1029.7215606678844,1001.8190609552112,973.309001064742,944.2986472297946,914.9021576099989,885.2395045052625,855.4352791137583,825.6173977689432,795.9157303818314,766.4606732786749,737.3816897331639,708.8058422221862,680.8563407630685,653.6511316010611,627.3015499956838,601.9110598974106,577.5741019124631,554.3750691326807,532.3874281777079,511.6730001869569,492.2814135481128,474.24973690783065,457.6022975395997,442.35068651491076,428.4939484168154,416.0189496374037,404.9009157051916,395.1041246902782,386.58274062916485,379.28176818856923,373.1381075322609,368.08168664034343,364.03664721565093,360.9225598393534,358.6556442299356,357.1499713174148,356.31862534611537,356.0748063195876,356.3328557329458,357.00919161294235,358.0231422981528,359.29767202005786,360.7599950594725,362.34207891564233,363.98104040137895,365.61944173689216,367.2054964387313,368.6931969866561,370.04237781945346,371.21872810527947,372.19376892518954,372.9448090019323,373.45489193123836,373.7127460898599]}],"reportKeys":["time","cpuTime","cycles","iters","allocated","numGcs","bytesCopied","mutatorWallSeconds","mutatorCpuSeconds","gcWallSeconds","gcCpuSeconds"],"reportNumber":0,"reportName":"ByteString/HashMap/random","reportOutliers":{"highSevere":0,"highMild":0,"lowMild":0,"samplesSeen":34,"lowSevere":0},"reportMeasured":[[4.97827198705636e-3,4.97199999999999e-3,10935260,1,null,null,null,null,null,null,null],[1.0848715988686308e-2,1.0847999999999997e-2,23877636,2,null,null,null,null,null,null,null],[1.7607376008527353e-2,1.7608e-2,38752116,3,null,null,null,null,null,null,null],[2.2017084003891796e-2,2.201800000000001e-2,48451954,4,null,null,null,null,null,null,null],[2.8329552995273843e-2,2.8330000000000022e-2,62340584,5,null,null,null,null,null,null,null],[3.288370498921722e-2,3.2885e-2,72359180,6,null,null,null,null,null,null,null],[3.651821901439689e-2,3.6518999999999996e-2,80349114,7,null,null,null,null,null,null,null],[4.358184800366871e-2,4.358200000000001e-2,95888910,8,null,null,null,null,null,null,null],[4.937931601307355e-2,4.937999999999998e-2,108645950,9,null,null,null,null,null,null,null],[5.358721798984334e-2,5.3586999999999996e-2,117903888,10,null,null,null,null,null,null,null],[5.955264199292287e-2,5.9538000000000035e-2,131027266,11,null,null,null,null,null,null,null],[6.518080999376252e-2,6.518099999999993e-2,143410836,12,null,null,null,null,null,null,null],[7.247712599928491e-2,7.247799999999993e-2,159464728,13,null,null,null,null,null,null,null],[8.270343899494037e-2,8.269899999999997e-2,181965766,14,null,null,null,null,null,null,null],[9.246958102448843e-2,9.240900000000007e-2,203443998,15,null,null,null,null,null,null,null],[9.887698100646958e-2,9.882600000000019e-2,217539578,16,null,null,null,null,null,null,null],[9.008563501993194e-2,9.0086e-2,198198564,17,null,null,null,null,null,null,null],[9.605592401931062e-2,9.605600000000003e-2,211332948,18,null,null,null,null,null,null,null],[0.1098186599847395,0.10976399999999997,241619440,19,null,null,null,null,null,null,null],[0.11373145499965176,0.11368299999999998,250220460,20,null,null,null,null,null,null,null],[0.11196174900396727,0.11196300000000003,246324226,21,null,null,null,null,null,null,null],[0.11884062600438483,0.11883500000000025,261465680,22,null,null,null,null,null,null,null],[0.1309775369882118,0.13096599999999992,288160116,23,null,null,null,null,null,null,null],[0.15469190399744548,0.15454900000000027,340335528,25,null,null,null,null,null,null,null],[0.149413135019131,0.14938300000000004,328727582,26,null,null,null,null,null,null,null],[0.15268685299088247,0.1526869999999998,335924804,27,null,null,null,null,null,null,null],[0.16147131499019451,0.16141300000000003,355254128,28,null,null,null,null,null,null,null],[0.16141338399029337,0.16139899999999985,355124102,30,null,null,null,null,null,null,null],[0.1728718529921025,0.17285800000000018,380334180,31,null,null,null,null,null,null,null],[0.1909069080138579,0.1908850000000002,420007910,33,null,null,null,null,null,null,null],[0.2043934800021816,0.20432799999999984,449680454,35,null,null,null,null,null,null,null],[0.20723143400391564,0.2070940000000001,455922034,36,null,null,null,null,null,null,null],[0.21014673498575576,0.21012200000000014,462335922,38,null,null,null,null,null,null,null],[0.22118496999610215,0.22116299999999978,486620020,40,null,null,null,null,null,null,null],[0.23701548800454475,0.23698700000000006,521448894,42,null,null,null,null,null,null,null],[0.23784394899848849,0.2378,523268016,44,null,null,null,null,null,null,null],[0.26553260401124135,0.26552299999999995,584189408,47,null,null,null,null,null,null,null],[0.28692550500272773,0.28688300000000044,631256144,49,null,null,null,null,null,null,null],[0.29316152300452814,0.29309600000000025,644973614,52,null,null,null,null,null,null,null]]}];
-  reports.map(mangulate);
-
-  var benches = ["ByteString/HashMap/random",];
-  var ylabels = [[-0,'<a href="#b0">ByteString/HashMap/random</a>'],];
-  var means = $.scaleTimes([5.621667703915931e-3,]);
-  var xs = [];
-  var prev = null;
-  for (var i = 0; i < means[0].length; i++) {
-    var name = benches[i].split(/\//);
-    name.pop();
-    name = name.join('/');
-    if (name != prev) {
-      xs.push({ label: name, data: [[means[0][i], -i]]});
-      prev = name;
-    }
-    else
-      xs[xs.length-1].data.push([means[0][i],-i]);
-  }
-  var oq = $("#overview");
-  o = $.plot(oq, xs, { bars: { show: true, horizontal: true,
-                               barWidth: 0.75, align: "center" },
-                       grid: { borderColor: "#777", hoverable: true },
-                       legend: { show: xs.length > 1 },
-                       xaxis: { max: Math.max.apply(undefined,means[0]) * 1.02 },
-                       yaxis: { ticks: ylabels, tickColor: '#ffffff' } });
-  if (benches.length > 3)
-    o.getPlaceholder().height(28*benches.length);
-  o.resize();
-  o.setupGrid();
-  o.draw();
-  $.addTooltip("#overview", function(x,y) { return $.renderTime(x / means[1]); });
-});
-$(document).ready(function () {
-    $(".time").text(function(_, text) {
-        return $.renderTime(text);
-      });
-    $(".citime").text(function(_, text) {
-        return $.renderTime(text);
-      });
-    $(".percent").text(function(_, text) {
-        return (text*100).toFixed(1);
-      });
-  });
-</script>
-
-   </div>
-  </div>
-  <div id="footer">
-    <div class="body">
-     <div class="footfirst">
-      <h2>colophon</h2>
-      <p>This report was created using the
-	<a href="http://hackage.haskell.org/package/criterion">criterion</a>
-	benchmark execution and performance analysis tool.</p>
-      <p>Criterion is developed and maintained
-      by <a href="http://www.serpentine.com/blog/">Bryan O'Sullivan</a>.</p>
-     </div>
-    </div>
-  </div>
- </body>
-</html>
diff --git a/templates/default2.tpl b/templates/default2.tpl
deleted file mode 100644
--- a/templates/default2.tpl
+++ /dev/null
@@ -1,296 +0,0 @@
-<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
-<html>
- <head>
-    <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>criterion report</title>
-    <!--[if lte IE 8]>
-      <script language="javascript" type="text/javascript">
-        {{#include}}js/excanvas-r3.min.js{{/include}}
-      </script>
-    <![endif]-->
-    <script language="javascript" type="text/javascript">
-      {{#include}}js/jquery-1.6.4.min.js{{/include}}
-    </script>
-    <script language="javascript" type="text/javascript">
-      {{#include}}js/jquery.flot-0.7.min.js{{/include}}
-    </script>
-    <script language="javascript" type="text/javascript">
-      {{#include}}js/jquery.criterion.js{{/include}}
-    </script>
-    <style type="text/css">
-{{#include}}criterion.css{{/include}}
-    </style>
-    <!--[if !IE 7]>
-	    <style type="text/css">
-		    #wrap {display:table;height:100%}
-	    </style>
-    <![endif]-->
- </head>
-    <body>
-     <div id="wrap">
-      <div id="main" class="body">
-    <h1>criterion performance measurements</h1>
-
-<h2>overview</h2>
-
-<p><a href="#grokularation">want to understand this report?</a></p>
-
-<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
-
-{{#report}}
-<h2><a name="b{{number}}">{{name}}</a></h2>
- <table width="100%">
-  <tbody>
-   <tr>
-    <td><div id="kde{{number}}" class="kdechart"
-             style="width:450px;height:278px;"></div></td>
-    <td><div id="time{{number}}" class="timechart"
-             style="width:450px;height:278px;"></div></td>
-<!--
-    <td><div id="cycle{{number}}" class="cyclechart"
-             style="width:300px;height:278px;"></div></td>
--->
-   </tr>
-  </tbody>
- </table>
- <table>
-  <thead class="analysis">
-   <th></th>
-   <th class="cibound"
-       title="{{anMean.estConfidenceLevel}} confidence level">lower bound</th>
-   <th>estimate</th>
-   <th class="cibound"
-       title="{{anMean.estConfidenceLevel}} confidence level">upper bound</th>
-  </thead>
-  <tbody>
-   <tr>
-    <td>Mean execution time</td>
-    <td><span class="citime">{{anMean.estLowerBound}}</span></td>
-    <td><span class="time">{{anMean.estPoint}}</span></td>
-    <td><span class="citime">{{anMean.estUpperBound}}</span></td>
-   </tr>
-   <tr>
-    <td>Standard deviation</td>
-    <td><span class="citime">{{anStdDev.estLowerBound}}</span></td>
-    <td><span class="time">{{anStdDev.estPoint}}</span></td>
-    <td><span class="citime">{{anStdDev.estUpperBound}}</span></td>
-   </tr>
-  </tbody>
- </table>
-
- <span class="outliers">
-   <p>Outlying measurements have {{anOutlierVar.ovDesc}}
-     (<span class="percent">{{anOutlierVar.ovFraction}}</span>%)
-     effect on estimated standard deviation.</p>
- </span>
-{{/report}}
-
- <h2><a name="grokularation">understanding this report</a></h2>
-
- <p>In this report, each function benchmarked by criterion is assigned
-   a section of its own.  In each section, we display two charts, each
-   with an <i>x</i> axis that represents measured execution time.
-   These charts are active; if you hover your mouse over data points
-   and annotations, you will see more details.</p>
-
- <ul>
-   <li>The chart on the left is a
-     <a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
-       density estimate</a> (also known as a KDE) of time
-     measurements.  This graphs the probability of any given time
-     measurement occurring.  A spike indicates that a measurement of a
-     particular time occurred; its height indicates how often that
-     measurement was repeated.</li>
-
-   <li>The chart on the right is the raw data from which the kernel
-     density estimate is built.  Measurements are displayed on
-     the <i>x</i> axis in the order in which they occurred.  The
-     number of iterations of the measurement loop increases with each
-     successive measurement.</li>
- </ul>
-
- <p>Under the charts is a small table displaying the mean and standard
-   deviation of the measurements.  We use a statistical technique
-   called
-   the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
-   to provide confidence intervals on our estimates of these values.
-   The bootstrap-derived upper and lower bounds on the mean and
-   standard deviation let you see how accurate we believe those
-   estimates to be.  (Hover the mouse over the table headers to see
-   the confidence levels.)</p>
-
- <p>A noisy benchmarking environment can cause some or many
-   measurements to fall far from the mean.  These outlying
-   measurements can have a significant inflationary effect on the
-   estimate of the standard deviation.  We calculate and display an
-   estimate of the extent to which the standard deviation has been
-   inflated by outliers.</p>
-
-<script type="text/javascript">
-$(function () {
-/*
-  function mangulate(number, name, mean, iters, times, cycles,
-                     kdetimes, kdepdf) */
-  function mangulate(rpt) {
-    var number = rpt.reportNumber;
-    var name = rpt.reportName;
-    var mean = rpt.reportAnalysis.anMean.estPoint;
-    var measured = function(key) {
-      var idx = rpt.reportKeys.indexOf(key);
-      return rpt.reportMeasured.map(function(r) { return r[idx]; });
-    };
-    var iters = measured("iters");
-    var times = measured("times");
-    var meanSecs = mean;
-    var units = $.timeUnits(mean);
-    var scale = units[0];
-    mean *= scale;
-    kdetimes = $.scaleBy(scale, kdetimes);
-    var kq = $("#kde" + number);
-    var k = $.plot(kq,
-           [{ label: name + " time densities",
-              data: $.zip(kdetimes, kdepdf),
-              }],
-           { xaxis: { tickFormatter: $.unitFormatter(scale) },
-             yaxis: { ticks: false },
-             grid: { borderColor: "#777",
-                     hoverable: true, markings: [ { color: '#6fd3fb',
-                     lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] },
-           });
-    var o = k.pointOffset({ x: mean, y: 0});
-    kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) +
-              '" style="position:absolute;left:' + (o.left + 4) +
-              'px;bottom:139px;">mean</div>');
-    $.addTooltip("#kde" + number,
-                 function(secs) { return $.renderTime(secs / scale); });
-    var timepairs = new Array(times.length);
-    for (var i = 0; i < times.length; i++)
-      timepairs[i] = [iters[i],times[i]*scale];
-    iterFormatter = function() {
-      var denom = 0;
-      return function(iters) {
-	if (iters == 0)
-          return '';
-	if (denom > 0)
-	  return (iters / denom).toFixed();
-        var exp;
-	if (iters >= 1e9) {
-	    denom = '1e9'; exp = 9;
-        }
-	if (iters >= 1e6) {
-	    denom = '1e6'; exp = 6;
-        }
-        else if (iters >= 1e3) {
-            denom = '1e3'; exp = 3;
-        }
-        else denom = 1;
-        if (denom > 1) {
-          iters = (iters / denom).toFixed();
-	  iters += '&times;10<sup>' + exp + '</sup> iters';
-        } else {
-          iters += ' iters';
-        }
-        return iters;
-      };
-    };
-    $.plot($("#time" + number),
-           [{ label: name + " times",
-              data: timepairs }],
-           { points: { show: true },
-             grid: { borderColor: "#777", hoverable: true },
-             xaxis: { tickFormatter: iterFormatter() },
-             yaxis: { tickFormatter: $.unitFormatter(scale) },
-           });
-    $.addTooltip("#time" + number,
-		 function(iters,secs) {
-		   return ($.renderTime(secs / scale) + ' / ' +
-			   iters.toLocaleString() + ' iters');
-		 });
-    if (0) {
-      var cyclepairs = new Array(cycles.length);
-      for (var i = 0; i < cycles.length; i++)
-	cyclepairs[i] = [cycles[i],i];
-      $.plot($("#cycle" + number),
-	     [{ label: name + " cycles",
-		data: cyclepairs }],
-	     { points: { show: true },
-	       grid: { borderColor: "#777", hoverable: true },
-	       xaxis: { tickFormatter:
-			function(cycles,axis) { return cycles + ' cycles'; }},
-	       yaxis: { ticks: false },
-	     });
-      $.addTooltip("#cycles" + number, function(x,y) { return x + ' cycles'; });
-    }
-  };
-  var reports = {{json}};
-  reports.map(mangulate);
-  {{#report}}
-  mangulate(/* report number */ {{number}},
-            /* report name */ "{{name}}",
-            /* estimated mean */ {{anMean.estPoint}},
-            /* iterations */ [{{#iters}}{{x}},{{/iters}}],
-            /* measured times */ [{{#times}}{{x}},{{/times}}],
-            /* measured cycles */ [{{#cycles}}{{x}},{{/cycles}}],
-            /* kde times */ [{{#kdetimes}}{{x}},{{/kdetimes}}],
-            /* kde pdf */ [{{#kdepdf}}{{x}},{{/kdepdf}}]);
-  {{/report}}
-
-  var benches = [{{#report}}"{{name}}",{{/report}}];
-  var ylabels = [{{#report}}[-{{number}},'<a href="#b{{number}}">{{name}}</a>'],{{/report}}];
-  var means = $.scaleTimes([{{#report}}{{anMean.estPoint}},{{/report}}]);
-  var xs = [];
-  var prev = null;
-  for (var i = 0; i < means[0].length; i++) {
-    var name = benches[i].split(/\//);
-    name.pop();
-    name = name.join('/');
-    if (name != prev) {
-      xs.push({ label: name, data: [[means[0][i], -i]]});
-      prev = name;
-    }
-    else
-      xs[xs.length-1].data.push([means[0][i],-i]);
-  }
-  var oq = $("#overview");
-  o = $.plot(oq, xs, { bars: { show: true, horizontal: true,
-                               barWidth: 0.75, align: "center" },
-                       grid: { borderColor: "#777", hoverable: true },
-                       legend: { show: xs.length > 1 },
-                       xaxis: { max: Math.max.apply(undefined,means[0]) * 1.02 },
-                       yaxis: { ticks: ylabels, tickColor: '#ffffff' } });
-  if (benches.length > 3)
-    o.getPlaceholder().height(28*benches.length);
-  o.resize();
-  o.setupGrid();
-  o.draw();
-  $.addTooltip("#overview", function(x,y) { return $.renderTime(x / means[1]); });
-});
-$(document).ready(function () {
-    $(".time").text(function(_, text) {
-        return $.renderTime(text);
-      });
-    $(".citime").text(function(_, text) {
-        return $.renderTime(text);
-      });
-    $(".percent").text(function(_, text) {
-        return (text*100).toFixed(1);
-      });
-  });
-</script>
-
-   </div>
-  </div>
-  <div id="footer">
-    <div class="body">
-     <div class="footfirst">
-      <h2>colophon</h2>
-      <p>This report was created using the
-	<a href="http://hackage.haskell.org/package/criterion">criterion</a>
-	benchmark execution and performance analysis tool.</p>
-      <p>Criterion is developed and maintained
-      by <a href="http://www.serpentine.com/blog/">Bryan O'Sullivan</a>.</p>
-     </div>
-    </div>
-  </div>
- </body>
-</html>
