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[Mod] flake8 code quanlity improve

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vn.py 2019-11-07 15:33:48 +08:00
parent 65fc733a02
commit 3ed0131b44
3 changed files with 52 additions and 50 deletions
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90
examples/data_analysis/data_analysis.py
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@ -32,7 +32,7 @@ class DataAnalysis:
self.orignal = pd.DataFrame() self.orignal = pd.DataFrame()
self.index_1to1 = [] self.index_1to1 = []
self.index_2to2 = [] self.index_2to2 = []
self.index_3to1 = [] self.index_3to1 = []
self.index_2to1 = [] self.index_2to1 = []
self.index_4to1 = [] self.index_4to1 = []
@ -42,10 +42,10 @@ class DataAnalysis:
def load_history( def load_history(
self, self,
symbol: str, symbol: str,
exchange: Exchange, exchange: Exchange,
interval: Interval, interval: Interval,
start: datetime, start: datetime,
end: datetime, end: datetime,
rate: float = 0.0, rate: float = 0.0,
index_1to1: list = None, index_1to1: list = None,
@ -57,9 +57,9 @@ class DataAnalysis:
window_volatility: int = 20, window_volatility: int = 20,
): ):
"""""" """"""
output("开始加载历史数据") output("开始加载历史数据")
self.window_volatility = window_volatility self.window_volatility = window_volatility
self.window_index = window_index self.window_index = window_index
self.rate = rate self.rate = rate
@ -69,23 +69,23 @@ class DataAnalysis:
self.index_2to1 = index_2to1 self.index_2to1 = index_2to1
self.index_4to1 = index_4to1 self.index_4to1 = index_4to1
# Load history data from database # Load history data from database
bars = database_manager.load_bar_data( bars = database_manager.load_bar_data(
symbol=symbol, symbol=symbol,
exchange=exchange, exchange=exchange,
interval=interval, interval=interval,
start=start, start=start,
end=end, end=end,
) )
output(f"历史数据加载完成，数据量：{len(bars)}") output(f"历史数据加载完成，数据量：{len(bars)}")
# Generate history data in DataFrame # Generate history data in DataFrame
t = [] t = []
o = [] o = []
h = [] h = []
l = [] l = [] # noqa
c = [] c = []
v = [] v = []
@ -96,12 +96,12 @@ class DataAnalysis:
low_price = bar.low_price low_price = bar.low_price
close_price = bar.close_price close_price = bar.close_price
volume = bar.volume volume = bar.volume
t.append(time) t.append(time)
o.append(open_price) o.append(open_price)
h.append(high_price) h.append(high_price)
l.append(low_price) l.append(low_price)
c.append(close_price) c.append(close_price)
v.append(volume) v.append(volume)
self.orignal["open"] = o self.orignal["open"] = o
@ -110,22 +110,22 @@ class DataAnalysis:
self.orignal["close"] = c self.orignal["close"] = c
self.orignal["volume"] = v self.orignal["volume"] = v
self.orignal.index = t self.orignal.index = t
def base_analysis(self, df: DataFrame = None): def base_analysis(self, df: DataFrame = None):
"""""" """"""
if df is None: if df is None:
df = self.orignal df = self.orignal
if df is None: if df is None:
output("数据为空，请输入数据") output("数据为空，请输入数据")
close_price = df["close"] close_price = df["close"]
output("第一步:画出行情图，检查数据断点") output("第一步:画出行情图，检查数据断点")
close_price.plot(figsize=(20, 8), title="close_price") close_price.plot(figsize=(20, 8), title="close_price")
plt.show() plt.show()
random_test(close_price) random_test(close_price)
stability_test(close_price) stability_test(close_price)
autocorrelation_test(close_price) autocorrelation_test(close_price)
@ -158,7 +158,7 @@ class DataAnalysis:
df["relative_vol"].hist(bins=200, figsize=(20, 6), grid=False) df["relative_vol"].hist(bins=200, figsize=(20, 6), grid=False)
plt.show() plt.show()
statitstic_info(df["relative_vol"]) statitstic_info(df["relative_vol"])
def growth_analysis(self, df: DataFrame = None): def growth_analysis(self, df: DataFrame = None):
""" """
@ -173,8 +173,8 @@ class DataAnalysis:
df["g%"].hist(bins=200, figsize=(20, 6), grid=False) df["g%"].hist(bins=200, figsize=(20, 6), grid=False)
plt.show() plt.show()
statitstic_info(df["g%"]) statitstic_info(df["g%"])
def calculate_index(self, df: DataFrame = None): def calculate_index(self, df: DataFrame = None):
"""""" """"""
@ -184,20 +184,20 @@ class DataAnalysis:
for i in self.index_1to1: for i in self.index_1to1:
func = getattr(talib, i) func = getattr(talib, i)
df[i] = func( df[i] = func(
np.array(df["close"]), np.array(df["close"]),
self.window_index self.window_index
) )
if self.index_3to1: if self.index_3to1:
for i in self.index_3to1: for i in self.index_3to1:
func = getattr(talib, i) func = getattr(talib, i)
df[i] = func( df[i] = func(
np.array(df["high"]), np.array(df["high"]),
np.array(df["low"]), np.array(df["low"]),
np.array(df["close"]), np.array(df["close"]),
self.window_index self.window_index
) )
if self.index_2to2: if self.index_2to2:
for i in self.index_2to2: for i in self.index_2to2:
func = getattr(talib, i) func = getattr(talib, i)
@ -210,7 +210,7 @@ class DataAnalysis:
down = i + "_DOWN" down = i + "_DOWN"
df[up] = result_up df[up] = result_up
df[down] = result_down df[down] = result_down
if self.index_2to1: if self.index_2to1:
for i in self.index_2to1: for i in self.index_2to1:
func = getattr(talib, i) func = getattr(talib, i)
@ -223,13 +223,13 @@ class DataAnalysis:
if self.index_4to1: if self.index_4to1:
for i in self.index_4to1: for i in self.index_4to1:
func = getattr(talib, i) func = getattr(talib, i)
df[i] = func( df[i] = func(
np.array(df["open"]), np.array(df["open"]),
np.array(df["high"]), np.array(df["high"]),
np.array(df["low"]), np.array(df["low"]),
np.array(df["close"]), np.array(df["close"]),
) )
return df return df
def multi_time_frame_analysis(self, intervals: list = None, df: DataFrame = None): def multi_time_frame_analysis(self, intervals: list = None, df: DataFrame = None):
@ -245,10 +245,10 @@ class DataAnalysis:
output("请先加载数据") output("请先加载数据")
return return
for interval in intervals: for interval in intervals:
output("------------------------------------------------") output("------------------------------------------------")
output(f"合成{interval}周期K先并开始数据分析") output(f"合成{interval}周期K先并开始数据分析")
data = pd.DataFrame() data = pd.DataFrame()
data["open"] = df["open"].resample(interval, how="first") data["open"] = df["open"].resample(interval, how="first")
data["high"] = df["high"].resample(interval, how="max") data["high"] = df["high"].resample(interval, how="max")
@ -260,25 +260,27 @@ class DataAnalysis:
self.results[interval] = result self.results[interval] = result
def show_chart(self, data, boll_wide): def show_chart(self, data, boll_wide):
"""""" """"""
data["boll_up"] = data["SMA"] + data["STDDEV"] * boll_wide data["boll_up"] = data["SMA"] + data["STDDEV"] * boll_wide
data["boll_down"] = data["SMA"] - data["STDDEV"] * boll_wide data["boll_down"] = data["SMA"] - data["STDDEV"] * boll_wide
up_signal = [] up_signal = []
down_signal = [] down_signal = []
len_data = len(data["close"]) len_data = len(data["close"])
for i in range(1, len_data): for i in range(1, len_data):
if data.iloc[i]["close"] > data.iloc[i]["boll_up"]and data.iloc[i-1]["close"] < data.iloc[i - 1]["boll_up"]: if data.iloc[i]["close"] > data.iloc[i]["boll_up"]and data.iloc[i - 1]["close"] < data.iloc[i - 1]["boll_up"]:
up_signal.append(i) up_signal.append(i)
elif data.iloc[i]["close"] < data.iloc[i]["boll_down"] and data.iloc[i-1]["close"] > data.iloc[i - 1]["boll_down"]: elif data.iloc[i]["close"] < data.iloc[i]["boll_down"] and data.iloc[i - 1]["close"] > data.iloc[i - 1]["boll_down"]:
down_signal.append(i) down_signal.append(i)
fig = plt.figure(figsize=(20, 8)) plt.figure(figsize=(20, 8))
close = data["close"] close = data["close"]
plt.plot(close, lw=1) plt.plot(close, lw=1)
plt.plot(close, '^', markersize=5, color='r', label='UP signal', markevery=up_signal) plt.plot(close, '^', markersize=5, color='r',
plt.plot(close, 'v', markersize=5, color='g', label='DOWN signal', markevery=down_signal) label='UP signal', markevery=up_signal)
plt.plot(close, 'v', markersize=5, color='g',
label='DOWN signal', markevery=down_signal)
plt.plot(data["boll_up"], lw=0.5, color="r") plt.plot(data["boll_up"], lw=0.5, color="r")
plt.plot(data["boll_down"], lw=0.5, color="g") plt.plot(data["boll_down"], lw=0.5, color="g")
plt.legend() plt.legend()
@ -327,7 +329,7 @@ def autocorrelation_test(close_price):
def statitstic_info(df): def statitstic_info(df):
"""""" """"""
mean = round(df.mean(), 4) mean = round(df.mean(), 4)
median = round(df.median(), 4) median = round(df.median(), 4)
output(f"样本平均数：{mean}, 中位数: {median}") output(f"样本平均数：{mean}, 中位数: {median}")
skew = round(df.skew(), 4) skew = round(df.skew(), 4)
@ -339,14 +341,14 @@ def statitstic_info(df):
skew_attribute = "分布偏左" skew_attribute = "分布偏左"
else: else:
skew_attribute = "分布偏右" skew_attribute = "分布偏右"
if kurt == 0: if kurt == 0:
kurt_attribute = "正态分布" kurt_attribute = "正态分布"
elif kurt > 0: elif kurt > 0:
kurt_attribute = "分布陡峭" kurt_attribute = "分布陡峭"
else: else:
kurt_attribute = "分布平缓" kurt_attribute = "分布平缓"
output(f"偏度为：{skew}，属于{skew_attribute}；峰度为：{kurt}，属于{kurt_attribute}\n") output(f"偏度为：{skew}，属于{skew_attribute}；峰度为：{kurt}，属于{kurt_attribute}\n")

10
vnpy/gateway/bitfinex/bitfinex_gateway.py
View File

@ -396,12 +396,12 @@ class BitfinexWebsocketApi(WebsocketClient):
self.subscribed = {} self.subscribed = {}
def connect( def connect(
self, self,
key: str, key: str,
secret: str, secret: str,
proxy_host: str, proxy_host: str,
proxy_port: int, proxy_port: int,
margin: bool margin: bool
): ):
"""""" """"""
self.key = key self.key = key

2
vnpy/gateway/bybit/bybit_gateway.py
View File

@ -251,7 +251,7 @@ class BybitRestApi(RestClient):
} }
order = req.create_order_data(order_id, self.gateway_name) order = req.create_order_data(order_id, self.gateway_name)
# Only add price for limit order. # Only add price for limit order.
data["order_type"] = ORDER_TYPE_VT2BYBIT[req.type] data["order_type"] = ORDER_TYPE_VT2BYBIT[req.type]
data["price"] = req.price data["price"] = req.price