[Mod] flake8 code quanlity improve
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vn.py
parent
65fc733a02
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3ed0131b44
@ -32,7 +32,7 @@ class DataAnalysis:
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self.orignal = pd.DataFrame()
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self.index_1to1 = []
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self.index_2to2 = []
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self.index_2to2 = []
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self.index_3to1 = []
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self.index_2to1 = []
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self.index_4to1 = []
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@ -42,10 +42,10 @@ class DataAnalysis:
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def load_history(
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self,
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symbol: str,
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exchange: Exchange,
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interval: Interval,
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start: datetime,
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symbol: str,
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exchange: Exchange,
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interval: Interval,
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start: datetime,
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end: datetime,
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rate: float = 0.0,
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index_1to1: list = None,
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@ -57,9 +57,9 @@ class DataAnalysis:
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window_volatility: int = 20,
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):
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""""""
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""""""
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output("开始加载历史数据")
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self.window_volatility = window_volatility
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self.window_index = window_index
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self.rate = rate
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@ -69,23 +69,23 @@ class DataAnalysis:
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self.index_2to1 = index_2to1
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self.index_4to1 = index_4to1
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# Load history data from database
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bars = database_manager.load_bar_data(
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symbol=symbol,
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exchange=exchange,
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interval=interval,
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start=start,
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# Load history data from database
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bars = database_manager.load_bar_data(
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symbol=symbol,
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exchange=exchange,
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interval=interval,
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start=start,
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end=end,
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)
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output(f"历史数据加载完成，数据量：{len(bars)}")
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# Generate history data in DataFrame
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t = []
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o = []
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h = []
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l = []
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l = [] # noqa
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c = []
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v = []
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@ -96,12 +96,12 @@ class DataAnalysis:
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low_price = bar.low_price
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close_price = bar.close_price
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volume = bar.volume
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t.append(time)
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o.append(open_price)
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h.append(high_price)
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l.append(low_price)
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c.append(close_price)
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c.append(close_price)
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v.append(volume)
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self.orignal["open"] = o
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@ -110,22 +110,22 @@ class DataAnalysis:
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self.orignal["close"] = c
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self.orignal["volume"] = v
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self.orignal.index = t
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def base_analysis(self, df: DataFrame = None):
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""""""
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if df is None:
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df = self.orignal
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if df is None:
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output("数据为空，请输入数据")
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close_price = df["close"]
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output("第一步:画出行情图，检查数据断点")
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close_price.plot(figsize=(20, 8), title="close_price")
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plt.show()
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random_test(close_price)
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stability_test(close_price)
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autocorrelation_test(close_price)
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@ -158,7 +158,7 @@ class DataAnalysis:
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df["relative_vol"].hist(bins=200, figsize=(20, 6), grid=False)
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plt.show()
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statitstic_info(df["relative_vol"])
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statitstic_info(df["relative_vol"])
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def growth_analysis(self, df: DataFrame = None):
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"""
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@ -173,8 +173,8 @@ class DataAnalysis:
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df["g%"].hist(bins=200, figsize=(20, 6), grid=False)
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plt.show()
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statitstic_info(df["g%"])
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statitstic_info(df["g%"])
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def calculate_index(self, df: DataFrame = None):
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""""""
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@ -184,20 +184,20 @@ class DataAnalysis:
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for i in self.index_1to1:
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func = getattr(talib, i)
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df[i] = func(
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np.array(df["close"]),
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np.array(df["close"]),
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self.window_index
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)
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if self.index_3to1:
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for i in self.index_3to1:
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func = getattr(talib, i)
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df[i] = func(
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df[i] = func(
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np.array(df["high"]),
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np.array(df["low"]),
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np.array(df["close"]),
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self.window_index
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)
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if self.index_2to2:
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for i in self.index_2to2:
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func = getattr(talib, i)
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@ -210,7 +210,7 @@ class DataAnalysis:
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down = i + "_DOWN"
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df[up] = result_up
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df[down] = result_down
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if self.index_2to1:
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for i in self.index_2to1:
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func = getattr(talib, i)
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@ -223,13 +223,13 @@ class DataAnalysis:
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if self.index_4to1:
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for i in self.index_4to1:
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func = getattr(talib, i)
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df[i] = func(
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np.array(df["open"]),
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df[i] = func(
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np.array(df["open"]),
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np.array(df["high"]),
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np.array(df["low"]),
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np.array(df["close"]),
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)
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return df
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def multi_time_frame_analysis(self, intervals: list = None, df: DataFrame = None):
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@ -245,10 +245,10 @@ class DataAnalysis:
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output("请先加载数据")
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return
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for interval in intervals:
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output("------------------------------------------------")
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for interval in intervals:
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output("------------------------------------------------")
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output(f"合成{interval}周期K先并开始数据分析")
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data = pd.DataFrame()
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data["open"] = df["open"].resample(interval, how="first")
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data["high"] = df["high"].resample(interval, how="max")
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@ -260,25 +260,27 @@ class DataAnalysis:
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self.results[interval] = result
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def show_chart(self, data, boll_wide):
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""""""
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""""""
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data["boll_up"] = data["SMA"] + data["STDDEV"] * boll_wide
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data["boll_down"] = data["SMA"] - data["STDDEV"] * boll_wide
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up_signal = []
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down_signal = []
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len_data = len(data["close"])
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len_data = len(data["close"])
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for i in range(1, len_data):
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if data.iloc[i]["close"] > data.iloc[i]["boll_up"]and data.iloc[i-1]["close"] < data.iloc[i - 1]["boll_up"]:
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if data.iloc[i]["close"] > data.iloc[i]["boll_up"]and data.iloc[i - 1]["close"] < data.iloc[i - 1]["boll_up"]:
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up_signal.append(i)
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elif data.iloc[i]["close"] < data.iloc[i]["boll_down"] and data.iloc[i-1]["close"] > data.iloc[i - 1]["boll_down"]:
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elif data.iloc[i]["close"] < data.iloc[i]["boll_down"] and data.iloc[i - 1]["close"] > data.iloc[i - 1]["boll_down"]:
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down_signal.append(i)
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fig = plt.figure(figsize=(20, 8))
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plt.figure(figsize=(20, 8))
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close = data["close"]
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plt.plot(close, lw=1)
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plt.plot(close, '^', markersize=5, color='r', label='UP signal', markevery=up_signal)
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plt.plot(close, 'v', markersize=5, color='g', label='DOWN signal', markevery=down_signal)
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plt.plot(close, '^', markersize=5, color='r',
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label='UP signal', markevery=up_signal)
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plt.plot(close, 'v', markersize=5, color='g',
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label='DOWN signal', markevery=down_signal)
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plt.plot(data["boll_up"], lw=0.5, color="r")
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plt.plot(data["boll_down"], lw=0.5, color="g")
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plt.legend()
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@ -327,7 +329,7 @@ def autocorrelation_test(close_price):
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def statitstic_info(df):
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""""""
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mean = round(df.mean(), 4)
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median = round(df.median(), 4)
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median = round(df.median(), 4)
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output(f"样本平均数：{mean}, 中位数: {median}")
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skew = round(df.skew(), 4)
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@ -339,14 +341,14 @@ def statitstic_info(df):
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skew_attribute = "分布偏左"
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else:
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skew_attribute = "分布偏右"
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if kurt == 0:
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kurt_attribute = "正态分布"
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elif kurt > 0:
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kurt_attribute = "分布陡峭"
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else:
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kurt_attribute = "分布平缓"
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output(f"偏度为：{skew}，属于{skew_attribute}；峰度为：{kurt}，属于{kurt_attribute}\n")
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@ -396,12 +396,12 @@ class BitfinexWebsocketApi(WebsocketClient):
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self.subscribed = {}
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def connect(
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self,
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key: str,
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secret: str,
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proxy_host: str,
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self,
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key: str,
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secret: str,
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proxy_host: str,
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proxy_port: int,
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margin: bool
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margin: bool
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):
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""""""
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self.key = key
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@ -251,7 +251,7 @@ class BybitRestApi(RestClient):
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}
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order = req.create_order_data(order_id, self.gateway_name)
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# Only add price for limit order.
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data["order_type"] = ORDER_TYPE_VT2BYBIT[req.type]
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data["price"] = req.price
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