python k线合成_手把手教你写一个Python版的K线合成函数
手把手教你寫一個Python版的K線合成函數
在編寫、使用策略時，經常會使用一些不常用的K線周期數據。然而交易所、數據源又沒有提供這些周期的數據。只能通過使用已有周期的數據進行合成。合成算法已經有一個JavaScript版本了(鏈接)，其實移植一段JavaScript代碼為Python版本很簡單。接下來我們一起寫一個Python版本的K線合成算法。
JavaScript版本
function GetNewCycleRecords (sourceRecords, targetCycle) { // K線合成函數
var ret = []
// 首先獲取源K線數據的周期
if (!sourceRecords || sourceRecords.length < 2) {
return null
}
var sourceLen = sourceRecords.length
var sourceCycle = sourceRecords[sourceLen - 1].Time - sourceRecords[sourceLen - 2].Time
if (targetCycle % sourceCycle != 0) {
Log("targetCycle:", targetCycle)
Log("sourceCycle:", sourceCycle)
throw "targetCycle is not an integral multiple of sourceCycle."
}
if ((1000 * 60 * 60) % targetCycle != 0 && (1000 * 60 * 60 * 24) % targetCycle != 0) {
Log("targetCycle:", targetCycle)
Log("sourceCycle:", sourceCycle)
Log((1000 * 60 * 60) % targetCycle, (1000 * 60 * 60 * 24) % targetCycle)
throw "targetCycle cannot complete the cycle."
}
var multiple = targetCycle / sourceCycle
var isBegin = false
var count = 0
var high = 0
var low = 0
var open = 0
var close = 0
var time = 0
var vol = 0
for (var i = 0 ; i < sourceLen ; i++) {
// 獲取 時區偏移數值
var d = new Date()
var n = d.getTimezoneOffset()
if (((1000 * 60 * 60 * 24) - sourceRecords[i].Time % (1000 * 60 * 60 * 24) + (n * 1000 * 60)) % targetCycle == 0) {
isBegin = true
}
if (isBegin) {
if (count == 0) {
high = sourceRecords[i].High
low = sourceRecords[i].Low
open = sourceRecords[i].Open
close = sourceRecords[i].Close
time = sourceRecords[i].Time
vol = sourceRecords[i].Volume
count++
} else if (count < multiple) {
high = Math.max(high, sourceRecords[i].High)
low = Math.min(low, sourceRecords[i].Low)
close = sourceRecords[i].Close
vol += sourceRecords[i].Volume
count++
}
if (count == multiple || i == sourceLen - 1) {
ret.push({
High : high,
Low : low,
Open : open,
Close : close,
Time : time,
Volume : vol,
})
count = 0
}
}
}
return ret
}
有JavaScript算法，對于Python其實逐行翻譯移植就可以了，遇到JavaScript的內置函數，或者固有方法，對應的去Python中查找對應的方法即可，所以移植還是比較容易的。
算法邏輯完全一模一樣，只是JavaScript的函數調用var n = d.getTimezoneOffset()，移植到Python時，使用Python的time庫中的n = time.altzone代替。其它差異僅僅是語言語法方面的了(例如for循環的使用，布爾值的差別，邏輯與、邏輯非、邏輯或的使用差別等…)。
移植后的Python代碼：
import time
def GetNewCycleRecords(sourceRecords, targetCycle):
ret = []
# 首先獲取源K線數據的周期
if not sourceRecords or len(sourceRecords) < 2 :
return None
sourceLen = len(sourceRecords)
sourceCycle = sourceRecords[-1]["Time"] - sourceRecords[-2]["Time"]
if targetCycle % sourceCycle != 0 :
Log("targetCycle:", targetCycle)
Log("sourceCycle:", sourceCycle)
raise "targetCycle is not an integral multiple of sourceCycle."
if (1000 * 60 * 60) % targetCycle != 0 and (1000 * 60 * 60 * 24) % targetCycle != 0 :
Log("targetCycle:", targetCycle)
Log("sourceCycle:", sourceCycle)
Log((1000 * 60 * 60) % targetCycle, (1000 * 60 * 60 * 24) % targetCycle)
raise "targetCycle cannot complete the cycle."
multiple = targetCycle / sourceCycle
isBegin = False
count = 0
barHigh = 0
barLow = 0
barOpen = 0
barClose = 0
barTime = 0
barVol = 0
for i in range(sourceLen) :
# 獲取時區偏移數值
n = time.altzone
if ((1000 * 60 * 60 * 24) - (sourceRecords[i]["Time"] * 1000) % (1000 * 60 * 60 * 24) + (n * 1000)) % targetCycle == 0 :
isBegin = True
if isBegin :
if count == 0 :
barHigh = sourceRecords[i]["High"]
barLow = sourceRecords[i]["Low"]
barOpen = sourceRecords[i]["Open"]
barClose = sourceRecords[i]["Close"]
barTime = sourceRecords[i]["Time"]
barVol = sourceRecords[i]["Volume"]
count += 1
elif count < multiple :
barHigh = max(barHigh, sourceRecords[i]["High"])
barLow = min(barLow, sourceRecords[i]["Low"])
barClose = sourceRecords[i]["Close"]
barVol += sourceRecords[i]["Volume"]
count += 1
if count == multiple or i == sourceLen - 1 :
ret.append({
"High" : barHigh,
"Low" : barLow,
"Open" : barOpen,
"Close" : barClose,
"Time" : barTime,
"Volume" : barVol,
})
count = 0
return ret
# 測試
def main():
while True:
r = exchange.GetRecords()
r2 = GetNewCycleRecords(r, 1000 * 60 * 60 * 4)
ext.PlotRecords(r2, "r2")
Sleep(1000)
測試
火幣行情圖表
回測合成4小時圖表
以上代碼僅作為學習參考使用，如果用于具體策略中，請根據需求修改、測試。
如有BUG或者改進建議，歡迎留言，十分感謝 o^_^o
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