Esempio n. 1
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def test_kline_analyze():
    file_kline = os.path.join(cur_path, "data/000001.SH_D.csv")
    kline = pd.read_csv(file_kline, encoding="utf-8")
    kline.loc[:, "dt"] = pd.to_datetime(kline.dt)
    ka = KlineAnalyze(kline,
                      name="日线",
                      max_count=1000,
                      use_xd=True,
                      verbose=False)

    # 测试绘图
    file_img = "kline.png"
    ka.to_image(file_img, max_k_count=5000)
    assert os.path.exists(file_img)

    # 测试分型识别结果
    assert ka.fx_list[-1]['fx_mark'] == 'g'
    assert ka.fx_list[-5]['fx_mark'] == 'g'

    # 测试笔识别结果
    assert ka.bi_list[-1]['fx_mark'] == 'g'
    assert ka.bi_list[-4]['fx_mark'] == 'd'

    # 测试线段识别结果
    assert ka.xd_list[-2]['fx_mark'] == 'g'
    assert ka.xd_list[-3]['fx_mark'] == 'd'

    # 测试增量更新
    for x in [2890, 2910, 2783, 3120]:
        k = dict(ka.kline_raw[-1])
        k['close'] = x
        ka.update(k)
        assert ka.kline_raw[-1]['close'] == x
Esempio n. 2
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def test_ka_update():
    file_kline = os.path.join(cur_path, "data/000001.SH_D.csv")
    kline = pd.read_csv(file_kline, encoding="utf-8")
    kline.loc[:, "dt"] = pd.to_datetime(kline.dt)
    kline1 = kline.iloc[:2000]
    kline2 = kline.iloc[2000:]

    ka1 = KlineAnalyze(kline,
                       name="日线",
                       max_count=1000,
                       use_xd=True,
                       verbose=False)
    ka2 = KlineAnalyze(kline1,
                       name="日线",
                       max_count=1000,
                       use_xd=True,
                       verbose=False)

    for _, row in kline2.iterrows():
        ka2.update(row.to_dict())

    assert ka1.kline_new[-1]['dt'] == ka2.kline_new[-1]['dt']
    assert ka1.fx_list[-1]['dt'] == ka2.fx_list[-1]['dt']
    assert ka1.bi_list[-1]['dt'] == ka2.bi_list[-1]['dt']
    assert ka1.xd_list[-1]['dt'] == ka2.xd_list[-1]['dt']

    ka3 = KlineAnalyze(kline,
                       name="日线",
                       max_count=1000,
                       use_xd=False,
                       verbose=False)
    assert ka3.kline_new[-1]['dt'] == ka2.kline_new[-1]['dt']
    assert ka3.fx_list[-1]['dt'] == ka2.fx_list[-1]['dt']
    assert ka3.bi_list[-1]['dt'] == ka2.bi_list[-1]['dt']
    assert not ka3.xd_list
Esempio n. 3
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def test_kline_analyze():
    ka = KlineAnalyze(kline, name="日线", max_raw_len=2000)

    # 测试绘图
    file_img = "kline.png"
    ka.to_image(file_img, max_k_count=5000)
    assert os.path.exists(file_img)
    os.remove(file_img)

    file_html = "kline.html"
    ka.to_html(file_html)
    assert os.path.exists(file_html)
    os.remove(file_html)

    # 测试分型识别结果
    assert ka.fx_list[-1]['fx_mark'] == 'g' and ka.fx_list[-1]['fx'] == 3456.97
    assert ka.fx_list[-5]['fx_mark'] == 'g' and ka.fx_list[-5]['fx'] == 2983.44

    # 测试笔识别结果
    assert ka.bi_list[-1]['fx_mark'] == 'g' and ka.bi_list[-1]['bi'] == 3456.97
    assert ka.bi_list[-4]['fx_mark'] == 'd' and ka.bi_list[-4]['bi'] == 2646.8

    # 测试线段识别结果
    assert ka.xd_list[-2]['fx_mark'] == 'g' and ka.xd_list[-2]['xd'] == 3288.45
    assert ka.xd_list[-3]['fx_mark'] == 'd' and ka.xd_list[-3]['xd'] == 2440.91

    # 测试增量更新
    ka_raw_len = len(ka.kline_raw)
    for x in [2890, 2910, 2783, 3120]:
        k = dict(ka.kline_raw[-1])
        k['close'] = x
        ka.update(k)
        assert len(ka.kline_raw) == ka_raw_len
        assert ka.kline_raw[-1]['close'] == x
Esempio n. 4
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def test_update_ta():
    ka = KlineAnalyze(kline, name="日线", max_raw_len=2000, verbose=False)
    ma_x1 = dict(ka.ma[-1])
    macd_x1 = dict(ka.macd[-1])
    ka.update(kline.iloc[-1].to_dict())
    ma_x2 = dict(ka.ma[-1])
    macd_x2 = dict(ka.macd[-1])
    assert ma_x1['dt'] == ma_x2['dt']
    assert [round(x, 2) for x in ma_x1.values() if isinstance(x, float)] == \
           [round(x, 2) for x in ma_x2.values() if isinstance(x, float)]

    assert macd_x1['dt'] == macd_x2['dt']
    assert [round(x, 2) for x in macd_x1.values() if isinstance(x, float)] == \
           [round(x, 2) for x in macd_x2.values() if isinstance(x, float)]
Esempio n. 5
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def test_ka_update():
    file_kline = os.path.join(cur_path, "data/000001.SH_D.csv")
    kline = pd.read_csv(file_kline, encoding="utf-8")
    kline.loc[:, "dt"] = pd.to_datetime(kline.dt)
    kline1 = kline.iloc[:2000]
    kline2 = kline.iloc[2000:]

    ka1 = KlineAnalyze(kline, name="日线", max_raw_len=5000, verbose=False)
    ka2 = KlineAnalyze(kline1, name="日线", max_raw_len=5000, verbose=False)

    for _, row in kline2.iterrows():
        ka2.update(row.to_dict())

    assert len(ka1.kline_new) == len(ka2.kline_new)
    assert len(ka1.fx_list) == len(ka2.fx_list)
    assert len(ka1.bi_list) == len(ka2.bi_list)
Esempio n. 6
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def test_update_ta():
    file_kline = os.path.join(cur_path, "data/000001.SH_D.csv")
    kline = pd.read_csv(file_kline, encoding="utf-8")
    kline.loc[:, "dt"] = pd.to_datetime(kline.dt)
    ka = KlineAnalyze(kline, name="日线", max_xd_len=10, verbose=False)

    ma_x1 = dict(ka.ma[-1])
    macd_x1 = dict(ka.macd[-1])
    ka.update(kline.iloc[-1].to_dict())
    ma_x2 = dict(ka.ma[-1])
    macd_x2 = dict(ka.macd[-1])
    assert ma_x1['dt'] == ma_x2['dt']
    assert [round(x, 2) for x in ma_x1.values() if isinstance(x, float)] == \
           [round(x, 2) for x in ma_x2.values() if isinstance(x, float)]

    assert macd_x1['dt'] == macd_x2['dt']
    assert [round(x, 2) for x in macd_x1.values() if isinstance(x, float)] == \
           [round(x, 2) for x in macd_x2.values() if isinstance(x, float)]