Example #1
0
    check_l_in_l0(l, l0)
    >>> True
    '''
    l_ = set(l)
    l0_ = set(l0)
    return len(l_ - l0_) == 0


if __name__ == '__main__':
    from utils_hoo import load_csv
    from utils_hoo.utils_fin.utils_fin import CCI
    from utils_hoo.utils_plot.plot_Common import plot_Series

    # 50ETF日线行情------------------------------------------------------------
    fpath = './test/510050_daily_pre_fq.csv'
    data = load_csv(fpath)
    data.set_index('date', drop=False, inplace=True)

    data['cci'] = CCI(data)
    data['cci_100'] = data['cci'].apply(lambda x: 1 if x > 100 else \
                                                    (-1 if x < -100 else 0))

    plot_Series(
        data.iloc[-200:, :], {'close': ('.-k', False)},
        cols_styl_low_left={'cci': ('.-c', False)},
        cols_to_label_info={
            'cci': [['cci_100', (-1, 1), ('r^', 'bv'), False]]
        },
        xparls_info={'cci': [(100, 'r', '-', 1.3), (-100, 'r', '-', 1.3)]},
        figsize=(8, 7),
        grids=True)
Example #2
0
def T_transform(df, T=5):
    '''
    数据周期转化
    df应包含列['open', 'high', 'low', 'close']
    '''
    raise NotImplementedError
    dfT = df.reindex(columns=['open', 'high', 'low', 'close'])


if __name__ == '__main__':
    strt_tm = time.time()

    # 50ETF日线行情
    fpath = '../test/510050_daily_pre_fq.csv'
    df = load_csv(fpath)
    df.set_index('date', drop=False, inplace=True)
    # df = df.reindex(columns=['high', 'low', 'close'])

    # CCI --------------------------------------------------------------------
    N = 14
    r = 0.015
    df['cci'] = CCI(df, N=N, r=r)

    plot_Series(
        df.iloc[-200:, :], {'close': ('.-k', False)},
        cols_styl_low_left={'cci': ('.-b', False)},
        xparls_info={'cci': [(100, 'r', '-', 1.3), (-100, 'r', '-', 1.3)]},
        figsize=(8.5, 7),
        grids=True)
Example #3
0
    plt.xlabel('时间', {'fontsize': fontsize})

    plt.tight_layout()

    if fig_save_path:
        plt.savefig(fig_save_path)

    plt.show()


if __name__ == '__main__':
    from utils_hoo import load_csv

    daily_50etf_pre_fq_path = '../test/510050_daily_pre_fq.csv'
    data = load_csv(daily_50etf_pre_fq_path)
    data.rename(columns={'date': 'time'}, inplace=True)

    N = 100
    #    args_ma = None
    args_ma = [5, 10, 20, 30, 50]
    args_boll = None
    #    args_boll = [15, 2]
    #    plot_below = None
    plot_below = 'volume'
    #    args_ma_below = None
    args_ma_below = [3, 5, 10]
    figsize = (11, 10)
    #    fig_save_path = None
    fig_save_path = './plot_test/Candle_test.png'
    title = '50ETF'
Example #4
0
        func_confirm = confirm_high if ktype == -1 else confirm_low
        k, OK_mid, OK_right = func_confirm(k)
        if OK_mid and OK_right:
            df.loc[df.index[k], 'zigzag'] = -ktype
            ktype = -ktype
        elif OK_mid:
            df.loc[df.index[k], 'zigzag'] = -ktype * 0.5
            break

    return df['zigzag']


if __name__ == '__main__':
    # zigzig测试--------------------------------------------------------------
    fpath = '../test/510050_daily_pre_fq.csv'
    his_data = load_csv(fpath)
    his_data.rename(columns={'date': 'time'}, inplace=True)
    his_data.set_index('time', drop=False, inplace=True)

    # N = his_data.shape[0]
    N = 100
    col = 'close'
    data = his_data.iloc[-N:-1, :].copy()

    high_col, low_col, up_pct, down_pct = 'high', 'low', 3 / 100, 3 / 100
    data['zigzag'] = ZigZag(data, high_col, low_col, up_pct, down_pct)
    plot_Candle_zz(data,
                   N=data.shape[0],
                   zz_high=high_col,
                   zz_low=low_col,
                   args_ma=None,