[Add]change variable names
This commit is contained in:
vn.py
parent
4385dd871a
commit
6e3b7faae3
@ -10,12 +10,11 @@
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"import multiprocessing\n",
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"import multiprocessing\n",
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"import numpy as np\n",
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"import numpy as np\n",
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"from deap import creator, base, tools, algorithms\n",
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"from deap import creator, base, tools, algorithms\n",
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"from backtesting import BacktestingEngine,OptimizationSetting\n",
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"from vnpy.app.cta_strategy.backtesting import BacktestingEngine,OptimizationSetting\n",
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"from boll_channel_strategy import BollChannelStrategy\n",
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"from vnpy.app.cta_strategy.strategies.boll_channel_strategy import BollChannelStrategy\n",
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"from atr_rsi_strategy import AtrRsiStrategy\n",
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"from vnpy.app.cta_strategy.strategies.atr_rsi_strategy import AtrRsiStrategy\n",
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"from datetime import datetime\n",
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"from datetime import datetime\n",
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"import multiprocessing #多进程\n",
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"import multiprocessing #多进程\n",
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"from scoop import futures #多进程\n",
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"from functools import lru_cache"
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"from functools import lru_cache"
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]
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]
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},
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},
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@ -89,7 +88,7 @@
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{
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{
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"data": {
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"data": {
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"text/plain": [
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"text/plain": [
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"[22, 28, 22]"
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"[48, 6, 26]"
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]
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]
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},
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},
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"execution_count": 5,
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"execution_count": 5,
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@ -109,7 +108,7 @@
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{
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{
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"data": {
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"data": {
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"text/plain": [
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"text/plain": [
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"{'boll_window': 24, 'cci_window': 14, 'atr_window': 28}"
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"{'boll_window': 16, 'cci_window': 48, 'atr_window': 6}"
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]
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]
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},
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},
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"execution_count": 6,
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"execution_count": 6,
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@ -171,10 +170,24 @@
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"execution_count": 8,
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"execution_count": 8,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2019-05-03 15:02:07.528909\t开始加载历史数据\n",
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"2019-05-03 15:02:34.854177\t历史数据加载完成，数据量：175440\n",
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"2019-05-03 15:02:34.877616\t策略初始化完成\n",
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"2019-05-03 15:02:34.877616\t开始回放历史数据\n",
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"2019-05-03 15:02:37.000744\t历史数据回放结束\n",
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"2019-05-03 15:02:37.000744\t开始计算逐日盯市盈亏\n",
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"2019-05-03 15:02:37.012463\t逐日盯市盈亏计算完成\n",
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"2019-05-03 15:02:37.012463\t开始计算策略统计指标\n"
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]
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},
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{
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{
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"data": {
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"data": {
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"text/plain": [
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"text/plain": [
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"(-0.51, -0.28)"
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"(0.96, 0.38)"
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]
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]
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},
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},
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"execution_count": 8,
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"execution_count": 8,
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@ -224,8 +237,8 @@
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" toolbox.register(\"mutate\", tools.mutUniformInt,low = 4,up = 40,indpb=1) \n",
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" toolbox.register(\"mutate\", tools.mutUniformInt,low = 4,up = 40,indpb=1) \n",
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" toolbox.register(\"evaluate\", object_func) \n",
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" toolbox.register(\"evaluate\", object_func) \n",
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" toolbox.register(\"select\", tools.selNSGA2) \n",
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" toolbox.register(\"select\", tools.selNSGA2) \n",
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" #pool = multiprocessing.Pool()\n",
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" pool = multiprocessing.Pool(multiprocessing.cpu_count())\n",
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" #toolbox.register(\"map\", pool.map)\n",
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" toolbox.register(\"map\", pool.map)\n",
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" #toolbox.register(\"map\", futures.map)\n",
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" #toolbox.register(\"map\", futures.map)\n",
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" \n",
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" \n",
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" \n",
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" \n",
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@ -266,7 +279,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": null,
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"metadata": {
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"metadata": {
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"scrolled": false
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"scrolled": false
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},
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},
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@ -275,43 +288,7 @@
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"name": "stdout",
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"name": "stdout",
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"output_type": "stream",
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"output_type": "stream",
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"text": [
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"text": [
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"开始运行遗传算法，每代族群总数：34, 优良品种筛选个数：27，迭代次数：30，交叉概率：0.95，突变概率：0.05\n",
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"开始运行遗传算法，每代族群总数：34, 优良品种筛选个数：27，迭代次数：30，交叉概率：0.95，突变概率：0.05\n"
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"gen\tnevals\tmean \tstd \tmin \tmax \n",
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"0 \t34 \t[0.08852941 0.00352941]\t[0.5373362 0.29107188]\t[-0.7 -0.63]\t[1.51 0.5 ]\n",
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"1 \t34 \t[0.60148148 0.27518519]\t[0.31013383 0.08573734]\t[0.32 0.18] \t[1.51 0.5 ]\n",
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"2 \t34 \t[0.79333333 0.33851852]\t[0.27758215 0.06742369]\t[0.47 0.25] \t[1.54 0.5 ]\n",
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"3 \t34 \t[1.00888889 0.39777778]\t[0.3147525 0.06214281]\t[0.7 0.33] \t[1.54 0.5 ]\n",
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"4 \t34 \t[1.41074074 0.47444444]\t[0.22881217 0.04661373]\t[0.96 0.36] \t[1.92 0.57]\n",
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"5 \t34 \t[1.59666667 0.51222222]\t[0.14714568 0.0255797 ]\t[1.51 0.49] \t[1.92 0.57]\n",
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"6 \t34 \t[1.66259259 0.52185185]\t[0.16585564 0.02981884]\t[1.52 0.49] \t[1.92 0.57]\n",
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"7 \t34 \t[1.8737037 0.55666667]\t[0.07713135 0.01763834]\t[1.75 0.53] \t[1.95 0.57]\n",
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"8 \t34 \t[1.93666667 0.57 ]\t[0.01490712 0. ]\t[1.92 0.57] \t[1.95 0.57]\n",
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"9 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"10 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"11 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"12 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"13 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"14 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"15 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"16 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"17 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"18 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"19 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"20 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"21 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"22 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"23 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"24 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"25 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"26 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"27 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"28 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"29 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"30 \t34 \t[1.95 0.57] \t[0. 0.] \t[1.95 0.57] \t[1.95 0.57]\n",
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"遗传算法优化完成，耗时309秒\n",
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"输出帕累托前沿解集：\n",
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"{'boll_window': 48, 'cci_window': 40, 'atr_window': 22, 'return_drawdown_ratio': 1.95, 'sharpe_ratio': 0.57}\n",
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"{'boll_window': 48, 'cci_window': 50, 'atr_window': 22, 'return_drawdown_ratio': 1.95, 'sharpe_ratio': 0.57}\n"
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]
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]
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}
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}
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],
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],
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@ -61,517 +61,33 @@
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"name": "stdout",
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"name": "stdout",
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"output_type": "stream",
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"output_type": "stream",
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"text": [
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"text": [
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"2019-05-02 22:29:22.289010\t开始运行遗传算法，每代族群总数：100, 优良品种筛选个数：80，迭代次数：300，交叉概率：0.95，突变概率：0.05\n",
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"2019-05-03 14:58:44.510371\t开始运行遗传算法，每代族群总数：20, 优良品种筛选个数：16，迭代次数：300，交叉概率：0.95，突变概率：0.05\n"
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"2019-05-02 22:29:22.289010\t开始加载历史数据\n",
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"2019-05-02 22:29:24.103532\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:24.173848\t策略初始化完成\n",
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"2019-05-02 22:29:24.173848\t开始回放历史数据\n",
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"2019-05-02 22:29:24.788129\t历史数据回放结束\n",
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"2019-05-02 22:29:24.789106\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:24.789106\t成交记录为空，无法计算\n",
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"2019-05-02 22:29:24.789106\t开始计算策略统计指标\n",
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"2019-05-02 22:29:24.789106\t开始加载历史数据\n",
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"2019-05-02 22:29:24.789106\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:24.867234\t策略初始化完成\n",
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"2019-05-02 22:29:24.868210\t开始回放历史数据\n",
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"2019-05-02 22:29:25.834068\t历史数据回放结束\n",
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"2019-05-02 22:29:25.835044\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:25.839927\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:25.840904\t开始计算策略统计指标\n",
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"2019-05-02 22:29:25.856529\t开始加载历史数据\n",
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"2019-05-02 22:29:25.857506\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:25.939540\t策略初始化完成\n",
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"2019-05-02 22:29:25.939540\t开始回放历史数据\n",
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"2019-05-02 22:29:27.055794\t历史数据回放结束\n",
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"2019-05-02 22:29:27.056771\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:27.062630\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:27.062630\t开始计算策略统计指标\n",
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"2019-05-02 22:29:27.074350\t开始加载历史数据\n",
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"2019-05-02 22:29:27.074350\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:27.156384\t策略初始化完成\n",
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"2019-05-02 22:29:27.156384\t开始回放历史数据\n",
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"2019-05-02 22:29:28.159352\t历史数据回放结束\n",
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"2019-05-02 22:29:28.160329\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:28.165212\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:28.165212\t开始计算策略统计指标\n",
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"2019-05-02 22:29:28.176931\t开始加载历史数据\n",
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"2019-05-02 22:29:28.176931\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:28.260919\t策略初始化完成\n",
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"2019-05-02 22:29:28.260919\t开始回放历史数据\n",
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"2019-05-02 22:29:29.418190\t历史数据回放结束\n",
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"2019-05-02 22:29:29.418190\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:29.424049\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:29.424049\t开始计算策略统计指标\n",
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"2019-05-02 22:29:29.436745\t开始加载历史数据\n",
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"2019-05-02 22:29:29.436745\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:29.521709\t策略初始化完成\n",
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"2019-05-02 22:29:29.522686\t开始回放历史数据\n",
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"2019-05-02 22:29:30.513935\t历史数据回放结束\n",
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"2019-05-02 22:29:30.514911\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:30.519794\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:30.519794\t开始计算策略统计指标\n",
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"2019-05-02 22:29:30.531514\t开始加载历史数据\n",
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"2019-05-02 22:29:30.531514\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:30.611595\t策略初始化完成\n",
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"2019-05-02 22:29:30.611595\t开始回放历史数据\n",
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"2019-05-02 22:29:31.729802\t历史数据回放结束\n",
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"2019-05-02 22:29:31.730778\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:31.735661\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:31.735661\t开始计算策略统计指标\n",
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"2019-05-02 22:29:31.747381\t开始加载历史数据\n",
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"2019-05-02 22:29:31.747381\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:31.825509\t策略初始化完成\n",
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"2019-05-02 22:29:31.826485\t开始回放历史数据\n",
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"2019-05-02 22:29:32.840196\t历史数据回放结束\n",
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"2019-05-02 22:29:32.840196\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:32.846056\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:32.847032\t开始计算策略统计指标\n",
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"2019-05-02 22:29:32.858751\t开始加载历史数据\n",
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"2019-05-02 22:29:32.858751\t历史数据加载完成，数据量：18240\n",
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"2019-05-02 22:29:32.936879\t策略初始化完成\n",
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"2019-05-02 22:29:32.936879\t开始回放历史数据\n",
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"2019-05-02 22:29:34.065829\t历史数据回放结束\n",
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"2019-05-02 22:29:34.066806\t开始计算逐日盯市盈亏\n",
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"2019-05-02 22:29:34.071689\t逐日盯市盈亏计算完成\n",
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"2019-05-02 22:29:34.072665\t开始计算策略统计指标\n",
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|
||||||
"2019-05-02 22:29:34.085361\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:34.085361\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:34.161536\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:34.162512\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:35.174270\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:35.175247\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:35.180130\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:35.180130\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:35.192825\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:35.192825\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:35.274860\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:35.274860\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:35.918439\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:35.918439\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:35.918439\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:29:35.918439\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:35.918439\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:35.918439\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:35.999497\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:35.999497\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:36.671398\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:36.671398\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:36.672374\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:29:36.672374\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:36.673351\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:36.673351\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:36.761245\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:36.762222\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:37.830622\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:37.831599\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:37.837458\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:37.837458\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:37.849177\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:37.849177\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:37.926329\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:37.927305\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:38.877537\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:38.878514\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:38.884373\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:38.884373\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:38.895116\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:38.896093\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:38.974221\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:38.974221\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:40.131492\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:40.131492\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:40.137351\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:40.137351\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:40.149070\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:40.149070\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:40.234035\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:40.235011\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:41.257511\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:41.258488\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:41.263371\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:41.263371\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:41.275090\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:41.275090\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:41.353218\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:41.353218\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:42.819095\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:42.819095\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:42.823978\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:42.823978\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:42.835697\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:42.836674\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:42.917731\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:42.917731\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:43.901168\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:43.901168\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:43.907027\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:43.908004\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:43.920700\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:43.921676\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:44.004687\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:44.005664\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:45.120941\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:45.121918\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:45.126801\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:45.126801\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:45.137543\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:45.138520\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:45.216648\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:45.217624\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:46.272352\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:46.272352\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:46.277235\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:46.278212\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:46.289931\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:46.289931\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:46.372942\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:46.372942\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:47.500915\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:47.501892\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:47.507751\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:47.507751\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:47.519471\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:47.519471\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:47.590762\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:47.590762\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:48.230435\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:48.231412\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:48.231412\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:29:48.231412\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:48.231412\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:48.231412\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:48.315400\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:48.315400\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:49.317391\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:49.317391\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:49.323251\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:49.323251\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:49.335947\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:49.335947\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:49.416028\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:49.416028\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:50.513726\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:50.513726\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:50.519586\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:50.519586\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:50.531305\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:50.531305\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:50.610410\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:50.611386\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:51.688576\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:51.689553\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:51.694436\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:51.695412\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:51.707131\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:51.708108\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:51.804791\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:51.807721\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:53.077301\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:53.078278\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:53.083161\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:53.083161\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:53.094880\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:53.094880\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:53.182774\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:53.183751\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:54.420126\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:54.421103\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:54.425986\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:54.425986\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:54.437705\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:54.437705\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:54.517786\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:54.517786\t开始回放历史数据\n"
|
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"name": "stdout",
|
"ename": "AttributeError",
|
||||||
"output_type": "stream",
|
"evalue": "Can't pickle local object 'create_ga_optimize.<locals>.ga_optimize'",
|
||||||
"text": [
|
|
||||||
"2019-05-02 22:29:55.671151\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:55.672127\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:55.677010\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:55.677987\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:55.689706\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:55.689706\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:55.767834\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:55.767834\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:56.790334\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:56.790334\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:56.796194\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:56.796194\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:56.806937\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:56.807913\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:56.889948\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:56.890924\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:57.607749\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:57.608725\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:57.608725\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:29:57.608725\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:57.608725\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:57.609702\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:57.698572\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:57.699549\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:29:58.882212\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:29:58.882212\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:29:58.888071\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:29:58.888071\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:29:58.898814\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:29:58.898814\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:29:58.986708\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:29:58.987684\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:00.071710\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:00.072687\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:00.077570\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:00.081476\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:00.092219\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:00.095149\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:00.173277\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:00.174253\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:00.906703\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:00.907680\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:00.907680\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:30:00.908657\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:00.908657\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:00.908657\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:01.018036\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:01.019012\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:02.128430\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:02.135266\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:02.141126\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:02.141126\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:02.151868\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:02.152845\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:02.229020\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:02.229020\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:03.410706\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:03.411682\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:03.416565\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:03.416565\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:03.428285\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:03.429261\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:03.533757\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:03.533757\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:04.638292\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:04.638292\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:04.643175\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:04.644152\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:04.654894\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:04.654894\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:04.738882\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:04.738882\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:05.721341\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:05.722318\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:05.728178\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:05.728178\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:05.739897\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:05.739897\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:05.824861\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:05.825838\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:06.928419\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:06.928419\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:06.933302\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:06.934279\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:06.945998\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:06.945998\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:07.024126\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:07.025102\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:08.041743\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:08.042720\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:08.048579\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:08.048579\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:08.062252\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:08.062252\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:08.145263\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:08.145263\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:09.292768\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:09.293744\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:09.298627\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:09.298627\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:09.311323\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:09.311323\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:09.393357\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:09.393357\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:10.363121\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:10.363121\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:10.368981\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:10.369957\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:10.380700\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:10.381677\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:10.459805\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:10.459805\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:11.536994\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:11.536994\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:11.542854\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:11.542854\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:11.554573\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:11.554573\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:11.638561\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:11.639537\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:12.632740\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:12.633716\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:12.638599\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:12.639576\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:12.650318\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:12.651295\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:12.733329\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:12.734306\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:13.352494\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:13.353470\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:13.353470\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:30:13.353470\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:13.354447\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:13.354447\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:13.436481\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:13.436481\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:14.540039\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:14.541016\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:14.546876\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:14.546876\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:14.558595\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:14.558595\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:14.650395\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:14.650395\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:15.294951\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:15.294951\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:15.294951\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:30:15.294951\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:15.294951\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:15.294951\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:15.377962\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:15.377962\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:16.346749\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:16.346749\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:16.352609\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:16.352609\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:16.365305\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:16.365305\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:16.445386\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:16.446363\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:17.544061\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:17.545038\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:17.550897\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:17.550897\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:17.563593\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:17.563593\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:17.640744\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:17.640744\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:18.641759\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:18.642736\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:18.647619\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:18.647619\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:18.659338\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:18.660315\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:18.736490\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:18.736490\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:19.827352\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:19.828328\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:19.833211\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:19.833211\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:19.844931\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:19.845907\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:19.927942\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:19.928918\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:20.916261\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:20.916261\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:20.922120\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:20.922120\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:20.934816\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:20.935793\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:21.010991\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:21.011968\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:22.131151\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:22.131151\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:22.137011\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:22.137011\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:22.149707\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:22.149707\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:22.227835\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:22.228811\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:23.201505\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:23.202481\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:23.207364\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:23.207364\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:23.219084\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:23.219084\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:23.295258\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:23.295258\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:24.418348\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:24.418348\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:24.423231\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:24.424208\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:24.437880\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:24.437880\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:24.517962\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:24.517962\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:25.200605\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:25.201582\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:25.201582\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:30:25.202558\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:25.202558\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:25.203535\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:25.275803\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:25.276780\t开始回放历史数据\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"2019-05-02 22:30:25.947704\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:25.948681\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:25.948681\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:30:25.949657\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:25.949657\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:25.949657\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:26.027785\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:26.027785\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:27.024894\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:27.025870\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:27.030753\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:27.030753\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:27.042473\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:27.042473\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:27.127437\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:27.128413\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:28.317912\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:28.317912\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:28.323772\t逐日盯市盈亏计算完成\n",
|
|
||||||
"2019-05-02 22:30:28.324748\t开始计算策略统计指标\n",
|
|
||||||
"2019-05-02 22:30:28.335491\t开始加载历史数据\n",
|
|
||||||
"2019-05-02 22:30:28.336468\t历史数据加载完成，数据量：18240\n",
|
|
||||||
"2019-05-02 22:30:28.412642\t策略初始化完成\n",
|
|
||||||
"2019-05-02 22:30:28.413619\t开始回放历史数据\n",
|
|
||||||
"2019-05-02 22:30:29.072824\t历史数据回放结束\n",
|
|
||||||
"2019-05-02 22:30:29.072824\t开始计算逐日盯市盈亏\n",
|
|
||||||
"2019-05-02 22:30:29.072824\t成交记录为空，无法计算\n",
|
|
||||||
"2019-05-02 22:30:29.072824\t开始计算策略统计指标\n",
|
|
||||||
"gen\tnevals\tmean \tstd \tmin \tmax \n",
|
|
||||||
"0 \t100 \t[1.24452619]\t[2.90495733]\t[-3.24204978]\t[8.88922512]\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"ename": "ValueError",
|
|
||||||
"evalue": "empty range for randrange() (1,1, 0)",
|
|
||||||
"output_type": "error",
|
"output_type": "error",
|
||||||
"traceback": [
|
"traceback": [
|
||||||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
||||||
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
|
"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
|
||||||
"\u001b[1;32m<ipython-input-3-4726e35b67fb>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0msetting\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_parameter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"atr_length\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m105\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_ga_optimization\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msetting\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
|
"\u001b[1;32m<ipython-input-3-d83ea019c683>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0msetting\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_parameter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"atr_ma_length\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m80\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_ga_optimization\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msetting\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||||
"\u001b[1;32mC:\\Github\\vnpy\\vnpy\\app\\cta_strategy\\backtesting.py\u001b[0m in \u001b[0;36mrun_ga_optimization\u001b[1;34m(self, optimization_setting, output)\u001b[0m\n\u001b[0;32m 602\u001b[0m \u001b[0mNGEN\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 603\u001b[0m \u001b[0mstats\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 604\u001b[1;33m \u001b[0mhalloffame\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mhof\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 605\u001b[0m ) \n\u001b[0;32m 606\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
"\u001b[1;32mC:\\Github\\vnpy\\vnpy\\app\\cta_strategy\\backtesting.py\u001b[0m in \u001b[0;36mrun_ga_optimization\u001b[1;34m(self, optimization_setting, output)\u001b[0m\n\u001b[0;32m 601\u001b[0m \u001b[0mngen\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 602\u001b[0m \u001b[0mstats\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 603\u001b[1;33m \u001b[0mhalloffame\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mhof\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 604\u001b[0m ) \n\u001b[0;32m 605\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
"\u001b[1;32mc:\\miniconda3\\lib\\site-packages\\deap\\algorithms.py\u001b[0m in \u001b[0;36meaMuPlusLambda\u001b[1;34m(population, toolbox, mu, lambda_, cxpb, mutpb, ngen, stats, halloffame, verbose)\u001b[0m\n\u001b[0;32m 316\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mgen\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mngen\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 317\u001b[0m \u001b[1;31m# Vary the population\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 318\u001b[1;33m \u001b[0moffspring\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvarOr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpopulation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtoolbox\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlambda_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcxpb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmutpb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 319\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 320\u001b[0m \u001b[1;31m# Evaluate the individuals with an invalid fitness\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
"\u001b[1;32mc:\\miniconda3\\lib\\site-packages\\deap\\algorithms.py\u001b[0m in \u001b[0;36meaMuPlusLambda\u001b[1;34m(population, toolbox, mu, lambda_, cxpb, mutpb, ngen, stats, halloffame, verbose)\u001b[0m\n\u001b[0;32m 301\u001b[0m \u001b[1;31m# Evaluate the individuals with an invalid fitness\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 302\u001b[0m \u001b[0minvalid_ind\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mind\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mind\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mpopulation\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mind\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfitness\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalid\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 303\u001b[1;33m \u001b[0mfitnesses\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtoolbox\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtoolbox\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mevaluate\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minvalid_ind\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 304\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mind\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfit\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minvalid_ind\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfitnesses\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 305\u001b[0m \u001b[0mind\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfitness\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfit\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
"\u001b[1;32mc:\\miniconda3\\lib\\site-packages\\deap\\algorithms.py\u001b[0m in \u001b[0;36mvarOr\u001b[1;34m(population, toolbox, lambda_, cxpb, mutpb)\u001b[0m\n\u001b[0;32m 234\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mop_choice\u001b[0m \u001b[1;33m<\u001b[0m \u001b[0mcxpb\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# Apply crossover\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 235\u001b[0m \u001b[0mind1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mind2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtoolbox\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrandom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpopulation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 236\u001b[1;33m \u001b[0mind1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mind2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtoolbox\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mind1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mind2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 237\u001b[0m \u001b[1;32mdel\u001b[0m \u001b[0mind1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfitness\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 238\u001b[0m \u001b[0moffspring\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mind1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
"\u001b[1;32mc:\\miniconda3\\lib\\multiprocessing\\pool.py\u001b[0m in \u001b[0;36mmap\u001b[1;34m(self, func, iterable, chunksize)\u001b[0m\n\u001b[0;32m 288\u001b[0m \u001b[1;32min\u001b[0m \u001b[0ma\u001b[0m \u001b[0mlist\u001b[0m \u001b[0mthat\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mreturned\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 289\u001b[0m '''\n\u001b[1;32m--> 290\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_map_async\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miterable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmapstar\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mchunksize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 291\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 292\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mstarmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miterable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
"\u001b[1;32mc:\\miniconda3\\lib\\site-packages\\deap\\tools\\crossover.py\u001b[0m in \u001b[0;36mcxTwoPoint\u001b[1;34m(ind1, ind2)\u001b[0m\n\u001b[0;32m 42\u001b[0m \u001b[0msize\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mind1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mind2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 43\u001b[0m \u001b[0mcxpoint1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrandom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrandint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 44\u001b[1;33m \u001b[0mcxpoint2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrandom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrandint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m \u001b[1;33m-\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 45\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mcxpoint2\u001b[0m \u001b[1;33m>=\u001b[0m \u001b[0mcxpoint1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 46\u001b[0m \u001b[0mcxpoint2\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
"\u001b[1;32mc:\\miniconda3\\lib\\multiprocessing\\pool.py\u001b[0m in \u001b[0;36mget\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m 681\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_value\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 682\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 683\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_value\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 684\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 685\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_set\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
"\u001b[1;32mc:\\miniconda3\\lib\\random.py\u001b[0m in \u001b[0;36mrandint\u001b[1;34m(self, a, b)\u001b[0m\n\u001b[0;32m 220\u001b[0m \"\"\"\n\u001b[0;32m 221\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 222\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrandrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 223\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 224\u001b[0m def _randbelow(self, n, int=int, maxsize=1<<BPF, type=type,\n",
|
"\u001b[1;32mc:\\miniconda3\\lib\\multiprocessing\\pool.py\u001b[0m in \u001b[0;36m_handle_tasks\u001b[1;34m(taskqueue, put, outqueue, pool, cache)\u001b[0m\n\u001b[0;32m 455\u001b[0m \u001b[1;32mbreak\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 456\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 457\u001b[1;33m \u001b[0mput\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtask\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 458\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 459\u001b[0m \u001b[0mjob\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0midx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtask\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
"\u001b[1;32mc:\\miniconda3\\lib\\random.py\u001b[0m in \u001b[0;36mrandrange\u001b[1;34m(self, start, stop, step, _int)\u001b[0m\n\u001b[0;32m 198\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mistart\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_randbelow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 199\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mstep\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 200\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"empty range for randrange() (%d,%d, %d)\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mistart\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mistop\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 201\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 202\u001b[0m \u001b[1;31m# Non-unit step argument supplied.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
"\u001b[1;32mc:\\miniconda3\\lib\\multiprocessing\\connection.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 204\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_closed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 205\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_writable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 206\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_send_bytes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_ForkingPickler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 207\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 208\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mrecv_bytes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmaxlength\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
"\u001b[1;31mValueError\u001b[0m: empty range for randrange() (1,1, 0)"
|
"\u001b[1;32mc:\\miniconda3\\lib\\multiprocessing\\reduction.py\u001b[0m in \u001b[0;36mdumps\u001b[1;34m(cls, obj, protocol)\u001b[0m\n\u001b[0;32m 49\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprotocol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 50\u001b[0m \u001b[0mbuf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mBytesIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 51\u001b[1;33m \u001b[0mcls\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbuf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprotocol\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 52\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mbuf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetbuffer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 53\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
|
||||||
|
"\u001b[1;31mAttributeError\u001b[0m: Can't pickle local object 'create_ga_optimize.<locals>.ga_optimize'"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"setting = OptimizationSetting()\n",
|
"setting = OptimizationSetting()\n",
|
||||||
"setting.set_target(\"total_return\")\n",
|
"setting.set_target(\"sharpe_ratio\")\n",
|
||||||
"setting.add_parameter(\"atr_length\", 3, 105, 1)\n",
|
"setting.add_parameter(\"atr_length\", 3, 105, 1)\n",
|
||||||
|
"setting.add_parameter(\"atr_ma_length\", 10, 80, 1)\n",
|
||||||
"\n",
|
"\n",
|
||||||
"engine.run_ga_optimization(setting)"
|
"engine.run_ga_optimization(setting)"
|
||||||
]
|
]
|
||||||
|
|||||||
@ -565,41 +565,40 @@ class BacktestingEngine:
|
|||||||
toolbox.register("evaluate", object_func)
|
toolbox.register("evaluate", object_func)
|
||||||
toolbox.register("select", tools.selNSGA2)
|
toolbox.register("select", tools.selNSGA2)
|
||||||
|
|
||||||
# pool = multiprocessing.Pool(multiprocessing.cpu_count())
|
pool = multiprocessing.Pool(multiprocessing.cpu_count())
|
||||||
# toolbox.register("map", pool.map)
|
toolbox.register("map", pool.map)
|
||||||
|
|
||||||
MU = 80 # 设置每一代选择的个体数
|
mu = 16 # number of individuals to select for the next generation
|
||||||
LAMBDA = 100 # 设置每一代产生的子女数
|
lambda_ = 20 # number of children to produce at each generation
|
||||||
POP = 100
|
cxpb = 0.95 # probability that an offspring is produced by crossover
|
||||||
CXPB = 0.95 # 交叉概率
|
mutpb = 0.05 # probability that an offspring is produced by mutation
|
||||||
MUTPB = 0.05 # 变异概率
|
ngen = 300 # number of generation
|
||||||
NGEN = 300 # 种群代数
|
|
||||||
|
|
||||||
pop = toolbox.population(POP) # 设置族群里面的个体数量
|
pop_size = 20 # number of individuals in each generation
|
||||||
hof = tools.ParetoFront() # 解的集合：帕累托前沿(非占优最优集)
|
pop = toolbox.population(pop_size)
|
||||||
|
hof = tools.ParetoFront() # end result of pareto front
|
||||||
|
|
||||||
stats = tools.Statistics(lambda ind: ind.fitness.values)
|
stats = tools.Statistics(lambda ind: ind.fitness.values)
|
||||||
np.set_printoptions(suppress=True) # 对numpy默认输出的科学计数法转换
|
np.set_printoptions(suppress=True)
|
||||||
stats.register("mean", np.mean, axis=0) # 统计目标优化函数结果的平均值
|
stats.register("mean", np.mean, axis=0)
|
||||||
stats.register("std", np.std, axis=0) # 统计目标优化函数结果的标准差
|
stats.register("std", np.std, axis=0)
|
||||||
stats.register("min", np.min, axis=0) # 统计目标优化函数结果的最小值
|
stats.register("min", np.min, axis=0)
|
||||||
stats.register("max", np.max, axis=0) # 统计目标优化函数结果的最大值
|
stats.register("max", np.max, axis=0)
|
||||||
|
|
||||||
msg = "开始运行遗传算法，每代族群总数：%s, 优良品种筛选个数：%s，迭代次数：%s，交叉概率：%s，突变概率：%s" %(POP,MU,NGEN,CXPB,MUTPB)
|
msg = "开始运行遗传算法，每代族群总数：%s, 优良品种筛选个数：%s，迭代次数：%s，交叉概率：%s，突变概率：%s" %(pop_size, mu, ngen, cxpb, mutpb)
|
||||||
self.output(msg)
|
self.output(msg)
|
||||||
|
|
||||||
# Run ga optimization
|
# Run ga optimization
|
||||||
# esMuPlusLambda是一种基于(μ+λ)选择策略的多目标优化分段遗传算法
|
|
||||||
start = time()
|
start = time()
|
||||||
|
|
||||||
algorithms.eaMuPlusLambda(
|
algorithms.eaMuPlusLambda(
|
||||||
pop,
|
pop,
|
||||||
toolbox,
|
toolbox,
|
||||||
MU,
|
mu,
|
||||||
LAMBDA,
|
lambda_,
|
||||||
CXPB,
|
cxpb,
|
||||||
MUTPB,
|
mutpb,
|
||||||
NGEN,
|
ngen,
|
||||||
stats,
|
stats,
|
||||||
halloffame=hof
|
halloffame=hof
|
||||||
)
|
)
|
||||||
@ -1139,3 +1138,19 @@ def load_tick_data(
|
|||||||
return database_manager.load_tick_data(
|
return database_manager.load_tick_data(
|
||||||
symbol, exchange, start, end
|
symbol, exchange, start, end
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
|
# GA related global value
|
||||||
|
ga_target_name = None
|
||||||
|
ga_strategy_class = None
|
||||||
|
ga_setting = None
|
||||||
|
ga_vt_symbol = None
|
||||||
|
ga_interval = None
|
||||||
|
ga_start = None
|
||||||
|
ga_rate = None
|
||||||
|
ga_slippage = None
|
||||||
|
ga_size = None
|
||||||
|
ga_pricetick = None
|
||||||
|
ga_capital = None
|
||||||
|
ga_end = None
|
||||||
|
ga_mode = None
|
||||||
Loading…
Reference in New Issue
Block a user