def turtle_test(loadtype='pgs', dataString='pyalg'):
"""
:param dataString:
:return:
"""
# 从postgres 中加载
if loadtype == 'pgs':
from api.stock.histmd import to_postgres_md as tpd
dat = tpd.get_h_data('600848')
else:
from api.stock.histmd.to_mongodb_md import k_data_dao as tmd
w = tmd.KdataDbCache()
dat = w.get_k_data(index=False,start='2015-02-05', end='2015-02-19',code='300426')
feed = dataFramefeed.Feed()
feed.addBarsFromDataFrame("orcl", dat)
myStrategy = pdr.turtle(feed, "orcl", 20, 10)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
if dataString == 'pyalg_util':
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
if dataString == 'pyalg_util':
rs = ds.getDefault() # 获取默认的交易信息，dic格式
plot(rs["cumulativeReturns"][:, 0], rs["cumulativeReturns"][:, 1]) # 简单作图示例
plt.plot()
def turtle_test(dataString='pyalg'):
"""
:param dataString:
:return:
"""
feed = yahoofeed.Feed()
feed.addBarsFromCSV(
"orcl", "../../api/stock/csv/orcl-2000.csv") #注意查看该csv的格式，Open为大写
myStrategy = pdr.turtle(feed, "orcl", 20, 10)
# Attach a returns analyzers to the trategy.
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
if dataString == 'pyalg_util':
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
if dataString == 'pyalg_util':
rs = ds.getDefault() # 获取默认的交易信息，dic格式
plot(rs["cumulativeReturns"][:, 0],
rs["cumulativeReturns"][:, 1]) # 简单作图示例
plt.plot()
def turtle_test(loadtype='tushare', dataString='pyalg'):
"""
:param dataString:
:return:
"""
# 从dataFrame中加载，
if loadtype == 'tushare':
import tushare as ts
dat = ts.get_h_data('600848')
dat.index.name = 'date'
else:
dat = pd.read_csv("../../api/stock/csv/600848.csv",
index_col=0,
encoding='gbk')
print(dat.head())
feed = dataFramefeed.Feed()
feed.addBarsFromDataFrame("orcl", dat)
myStrategy = pdr.turtle(feed, "orcl", 20, 10)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
if dataString == 'pyalg_util':
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
if dataString == 'pyalg_util':
rs = ds.getDefault() # 获取默认的交易信息，dic格式
plot(rs["cumulativeReturns"][:, 0],
rs["cumulativeReturns"][:, 1]) # 简单作图示例
plt.plot()