seq_vs_tab.nim

import times
import tables
import random
import ggplotnim
import weave
import locks

const runs = 1_000
const sizes = 1_000
var lock: Lock
lock.initLock()

proc oneSizeRun(size: int): DataFrame =
  var myTable = initTable[int, int]()
  var myList: seq[int]
  for i in 0 .. size:
      myTable[i] = i
      myList.add(i)

  myList.shuffle()
  var dummyCounter = 0
  var listTimes = newSeq[float](runs + 1)
  var tableTimes = newSeq[float](runs + 1)

  for n in 0 .. runs:

    const trytimes = 10

    var start = epochTime()
    for j in 0 .. trytimes:
      for i in 0 ..< n:
          if myList.contains(i):
            inc dummyCounter
    let listTime = epochTime() - start

    start = epochTime()
    for j in 0 .. trytimes:
      for i in 0 ..< n:
          if myTable.hasKey(i):
            inc dummyCounter
    let tableTime = epochTime() - start

    listTimes[n] = listTime/trytimes
    tableTimes[n] = tableTime/trytimes

  echo dummyCounter

  result = seqsToDf({ "list" : listTimes,
                      "table" : tableTimes,
                      "runs" : arange(0, runs + 1) })
    .gather(["table", "list"], key = "type", value = "time")
  result["size"] = constantColumn(size, result.len)

init(Weave)
var dfs = newSeq[DataFrame](sizes + 1)
var dfBuf = cast[ptr UncheckedArray[DataFrame]](dfs[0].addr)
#parallelFor i in 0 .. sizes:
#  captures: {dfBuf}
#  dfBuf[i] = spawn oneSizeRun(i)
parallelFor i in 0 .. sizes:
  captures: {dfBuf}
  dfBuf[i] = oneSizeRun(i)

#let res = df.addr # For mutation we need to capture the address.
#parallelForStaged i in 0 .. sizes:
#  captures: {res}
#  prologue:
#    var localDf = newDataFrame()
#  loop:
#    localDf = oneSizeRun(i * 5)
#  epilogue:
#    echo "Thread ", getThreadID(Weave), ": localDf ", localDf
#    lock.acquire()
#    res[].add localDf
#    lock.release()
syncRoot(Weave)
var df = newDataFrame()
for i in 0 .. sizes:
  echo df
  let toadd = dfBuf[i]
  echo toadd.len
  echo getKeys(toadd)
  echo toAdd
  echo "////////////////////////////////"
  df.add toadd

exit(Weave)

#echo df.pretty(-1)
echo df
#ggplot(df, aes("runs", "time", color = "type")) +
#  geom_line() +
#  ggsave("mini_bench.pdf")
ggplot(df, aes("runs", "size", fill = "time")) +
  geom_raster(aes = aes(height = 5, width = 1)) +
  scale_x_continuous() +
  facet_wrap("type") +
  ggsave("bench_heatmap.pdf")