コード例 #1
0
ファイル: formula.py プロジェクト: asialiugf/juejin_quant
def calc_ma(df):
    ar = [
        5, 8, 10, 13, 20, 21, 30, 34, 40, 55, 60, 89, 120, 144, 233, 250, 377,
        500, 610
    ]
    for i in ar:
        s = str(i)
        s = "ma" + s
        df[s] = MA(df['close'], i)  # 计算MA(5) MA(13) ... MA(610)

    fibs = _fibs(14)

    sum = abs(df['ma5'] - df['ma8'])  # 需要优化!!
    for i in range(3, 13):
        for j in range(i + 1, 14):
            ma_b = "ma" + str(fibs[i])
            ma_e = "ma" + str(fibs[j])
            sum = sum + abs(df[ma_b] - df[ma_e])
    df['diff'] = sum - abs(df['ma5'] - df['ma8'])  # 需要优化!!

    df['x8610'] = df['close'] - df['ma20']

    print('yyyyyyyyyyyy', df['diff'])

    return df
コード例 #2
0
ファイル: kdj_ok.py プロジェクト: ssh352/see
def makePicture(code, name):
    #df = ts.get_hist_data(code, start=begin_time, end=end_time)
    #df = ts.get_hist_data('600848')
    ret = md.init("13601380996","it@iZ23psatkqsZ")
    df = tt.get_bars("SHFE.ru1709", 3600*4,  "2017-02-01 09:00:00", "2017-06-02 23:05:00")
    print("kkkkkkkkkkkkkkkkkkkkkkkkkkkk!!!")
    print("df:",df)
    #df = df.sort_index(0)
#    df.plot()

    C = df['close']  # 切片收盘价
    C30 = C.tail(30)  # 取最后30个收盘价数据
    MA30 = C30.mean()  # 均值
    print("MA30:",MA30)
    xx = MA(C,5)
    print("MA30 ==== ",xx)
    kdj = KDJ(df,9,3,3)
    print("KDJ ==== ", kdj)
    drawPic(df, code, name)
コード例 #3
0
def calc_kdj_ma_ema(df):
    """
    # KDJ1
    df['k1'] = np.nan
    df['d1'] = np.nan
    df['j1'] = np.nan
    df['e1'] = np.nan
    df['x1'] = np.nan

    # KDJ2
    df['k2'] = np.nan
    df['d2'] = np.nan
    df['j2'] = np.nan
    df['e2'] = np.nan
    df['x2'] = np.nan

    # KDJ3
    df['k3'] = np.nan
    df['d3'] = np.nan
    df['j3'] = np.nan
    df['e3'] = np.nan
    df['x3'] = np.nan

    # KDJ4
    df['k4'] = np.nan
    df['d4'] = np.nan
    df['j4'] = np.nan
    df['e4'] = np.nan
    df['x4'] = np.nan

    # MA

    df['ma5'] = np.nan
    df['ma10'] = np.nan
    df['ma20'] = np.nan
    df['ma30'] = np.nan
    df['ma40'] = np.nan
    df['ma60'] = np.nan
    df['ma89'] = np.nan
    df['ma144'] = np.nan
    df['ma233'] = np.nan
    df['ma377'] = np.nan
    df['ma610'] = np.nan
    """
    # ------------------------------------------------------------
    df['ma5'] = MA(df['close'], 5)
    df['ma10'] = MA(df['close'], 10)
    df['ma20'] = MA(df['close'], 20)
    df['ma30'] = MA(df['close'], 30)
    df['ma40'] = MA(df['close'], 40)
    df['ma60'] = MA(df['close'], 60)
    df['ma89'] = MA(df['close'], 89)
    df['ma144'] = MA(df['close'], 144)
    df['ma233'] = MA(df['close'], 233)
    df['ma377'] = MA(df['close'], 377)
    df['ma610'] = MA(df['close'], 610)

    kdj1 = KDJ(df, 45, 15, 15)
    kdj2 = KDJ(df, 45 * 5, 15 * 5, 15 * 5)
    kdj3 = KDJ(df, 45 * 5 * 5, 15 * 5 * 5, 15 * 5 * 5)
    kdj4 = KDJ(df, 45 * 5 * 5 * 5, 15 * 5 * 5 * 5, 15 * 5 * 5 * 5)
    """
    #ema1 = EMA( kdj1['KDJ_J'], 5 )
    #ema2 = EMA( kdj2['KDJ_J'], 5*5 )
    #ema3 = EMA( kdj3['KDJ_J'], 5*5*5 )
    #ema4 = EMA( kdj4['KDJ_J'], 5*5*5*5 )
    """

    df['k1'] = kdj1['KDJ_K']
    df['d1'] = kdj1['KDJ_D']
    df['j1'] = kdj1['KDJ_J']
    df['e1'] = EMA(kdj1['KDJ_J'], 5)

    df['k2'] = kdj2['KDJ_K']
    df['d2'] = kdj2['KDJ_D']
    df['j2'] = kdj2['KDJ_J']
    df['e2'] = EMA(kdj2['KDJ_J'], 5 * 5)

    df['k3'] = kdj3['KDJ_K']
    df['d3'] = kdj3['KDJ_D']
    df['j3'] = kdj3['KDJ_J']
    df['e3'] = EMA(kdj3['KDJ_J'], 5 * 5 * 5)

    df['k4'] = kdj4['KDJ_K']
    df['d4'] = kdj4['KDJ_D']
    df['j4'] = kdj4['KDJ_J']
    df['e4'] = EMA(kdj4['KDJ_J'], 5 * 5 * 5 * 5)

    df['x1'] = np.nan
    df['x2'] = np.nan
    df['x3'] = np.nan
    df['x4'] = np.nan

    n = 6
    x = np.arange(n)

    yy = df['e1'].values
    for i in range(n - 1, len(df)):
        y1 = df['e1'][i - n + 1:i + 1].values
        y2 = df['e2'][i - n + 1:i + 1].values
        y3 = df['e3'][i - n + 1:i + 1].values
        y4 = df['e4'][i - n + 1:i + 1].values
        # print(x)
        # print(y)
        z1 = np.polyfit(x, y1, 3)
        z2 = np.polyfit(x, y2, 3)
        z3 = np.polyfit(x, y3, 3)
        z4 = np.polyfit(x, y4, 3)
        # print('zzzzzz',z)
        r1 = z1[0] * x[n - 1] * x[n - 1] + z1[1] * x[n - 1] + z1[2]
        r2 = z2[0] * x[n - 1] * x[n - 1] + z2[1] * x[n - 1] + z2[2]
        r3 = z3[0] * x[n - 1] * x[n - 1] + z3[1] * x[n - 1] + z3[2]
        r4 = z4[0] * x[n - 1] * x[n - 1] + z4[1] * x[n - 1] + z4[2]
        df['x1'].iat[i] = r1
        df['x2'].iat[i] = r2
        df['x3'].iat[i] = r3
        df['x4'].iat[i] = r4
    return df
コード例 #4
0
def calc_ma(df):
    df['ma5'] = MA(df['close'], 5)
    df['ma8'] = MA(df['close'], 8)
    df['ma10'] = MA(df['close'], 10)
    df['ma13'] = MA(df['close'], 13)
    df['ma20'] = MA(df['close'], 20)
    df['ma21'] = MA(df['close'], 21)
    df['ma30'] = MA(df['close'], 30)
    df['ma34'] = MA(df['close'], 34)
    df['ma40'] = MA(df['close'], 40)
    df['ma55'] = MA(df['close'], 55)
    df['ma60'] = MA(df['close'], 60)
    df['ma89'] = MA(df['close'], 89)
    df['ma144'] = MA(df['close'], 144)
    df['ma233'] = MA(df['close'], 233)
    df['ma377'] = MA(df['close'], 377)
    df['ma610'] = MA(df['close'], 610)

    df['diff'] = abs( df['ma5']-df['ma8'] )+abs( df['ma5']-df['ma13'] ) \
                 +abs( df['ma5']-df['ma21'] )+abs( df['ma5']-df['ma34'] ) \
                 +abs( df['ma5']-df['ma55'] )+abs( df['ma5']-df['ma89'] ) \
                 +abs( df['ma5']-df['ma144'] )+abs( df['ma5']-df['ma233'] ) \
                 +abs( df['ma5']-df['ma377'] )+abs( df['ma5']-df['ma610'] ) \
                 +abs( df['ma8']-df['ma13'] ) \
                 +abs( df['ma8']-df['ma21'] )+abs( df['ma8']-df['ma34'] ) \
                 +abs( df['ma8']-df['ma55'] )+abs( df['ma8']-df['ma89'] ) \
                 +abs( df['ma8']-df['ma144'] )+abs( df['ma8']-df['ma233'] ) \
                 +abs( df['ma8']-df['ma377'] )+abs( df['ma8']-df['ma610'] ) \
                 +abs( df['ma13']-df['ma21'] )+abs( df['ma13']-df['ma34'] ) \
                 +abs( df['ma13']-df['ma55'] )+abs( df['ma13']-df['ma89'] ) \
                 +abs( df['ma13']-df['ma144'] )+abs( df['ma13']-df['ma233'] ) \
                 +abs( df['ma13']-df['ma377'] )+abs( df['ma13']-df['ma610'] ) \
                 +abs( df['ma21']-df['ma34'] ) \
                 +abs( df['ma21']-df['ma55'] )+abs( df['ma21']-df['ma89'] ) \
                 +abs( df['ma21']-df['ma144'] )+abs( df['ma21']-df['ma233'] ) \
                 +abs( df['ma21']-df['ma377'] )+abs( df['ma21']-df['ma610'] ) \
                 +abs( df['ma34']-df['ma55'] )+abs( df['ma34']-df['ma89'] ) \
                 +abs( df['ma34']-df['ma144'] )+abs( df['ma34']-df['ma233'] ) \
                 +abs( df['ma34']-df['ma377'] )+abs( df['ma34']-df['ma610'] ) \
                 +abs( df['ma55']-df['ma89'] ) \
                 +abs( df['ma55']-df['ma144'] )+abs( df['ma55']-df['ma233'] ) \
                 +abs( df['ma55']-df['ma377'] )+abs( df['ma55']-df['ma610'] ) \
                 +abs( df['ma89']-df['ma144'] )+abs( df['ma89']-df['ma233'] ) \
                 +abs( df['ma89']-df['ma377'] )+abs( df['ma89']-df['ma610'] ) \
                 +abs( df['ma144']-df['ma233'] ) \
                 +abs( df['ma144']-df['ma377'] )+abs( df['ma144']-df['ma610'] ) \
                 +abs( df['ma233']-df['ma377'] )+abs( df['ma233']-df['ma610'] ) \
                 +abs( df['ma377']-df['ma610'] )

    df['x8610'] = df['ma5'] - df['ma610']
    return df