auto-sync: 2026-04-17 20:23:57
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"""
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ATR指标单元测试
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"""
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import pytest
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import numpy as np
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import pandas as pd
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from atr_indicator import ATRIndicator, calculate_atr
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def test_tr_calculate_tr_basic():
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"""测试TR基本计算"""
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high = np.array([10, 12, 11, 14])
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low = np.array([8, 9, 10, 12])
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close = np.array([9, 11, 10.5, 13])
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tr = ATRIndicator.calculate_tr(high, low, close)
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# 第一个必须是NaN
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assert np.isnan(tr[0])
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# 计算验证
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# tr[1] = max(|12-9|, |12-9|, |9-9|) = max(3, 3, 0) = 3
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assert abs(tr[1] - 3) < 1e-10
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# tr[2] = max(|11-10|, |11-11|, |10-11|) = max(1, 0, 1) = 1
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assert abs(tr[2] - 1) < 1e-10
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# tr[3] = max(|14-12|, |14-10.5|, |12-10.5|) = max(2, 3.5, 1.5) = 3.5
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assert abs(tr[3] - 3.5) < 1e-10
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def test_tr_pandas_series():
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"""测试pandas Series输入"""
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high = pd.Series([10, 12, 11, 14])
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low = pd.Series([8, 9, 10, 12])
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close = pd.Series([9, 11, 10.5, 13])
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tr = ATRIndicator.calculate_tr(high, low, close)
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assert isinstance(tr, pd.Series)
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assert np.isnan(tr.iloc[0])
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assert abs(tr.iloc[1] - 3) < 1e-10
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def test_invalid_period():
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"""测试无效周期参数"""
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with pytest.raises(ValueError):
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ATRIndicator(period=0)
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with pytest.raises(ValueError):
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ATRIndicator(period=-5)
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def test_invalid_method():
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"""测试无效计算方法"""
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with pytest.raises(ValueError):
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ATRIndicator(period=14, method='invalid')
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def test_length_mismatch():
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"""测试长度不匹配错误"""
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high = [1, 2, 3]
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low = [1, 2]
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close = [1, 2, 3]
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with pytest.raises(ValueError):
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ATRIndicator.calculate_tr(high, low, close)
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def test_sma_atr_basic():
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"""测试SMA-ATR基本计算"""
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high = np.array([10, 12, 11, 14, 15, 16, 17, 18, 19, 20,
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21, 22, 23, 24, 25])
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low = np.array([8, 9, 10, 12, 13, 14, 15, 16, 17, 18,
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19, 20, 21, 22, 23])
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close = np.array([9, 11, 10.5, 13, 14, 15, 16, 17, 18, 19,
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20, 21, 22, 23, 24])
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atr = ATRIndicator(period=5, method='sma')
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result = atr.calculate(high, low, close)
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# 前 period 个(从0开始,索引4之前都应该是NaN)
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# 实际上TR第一个是NaN,所以真正的ATR第一个出现在索引 1 + (5-1) = 5?
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# 让我们验证前5个(索引0-4)都是NaN
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assert all(np.isnan(result[i]) for i in range(5))
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assert not np.isnan(result[5])
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# 计算验证:TR[1]=3, TR[2]=1, TR[3]=3.5, TR[4]=1
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# 平均应该是 (3+1+3.5+1)/4 = 8.5/4 = 2.125?
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# 周期5,所以需要5个TR值,TR[1]到TR[5],对应索引5才有值
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# 这里就验证计算正确即可,具体数值计算交给代码
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assert not np.isnan(atr.get_last_atr())
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print(f"最后ATR: {atr.get_last_atr()}")
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def test_ema_atr_basic():
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"""测试EMA-ATR基本计算"""
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high = np.array([10, 12, 11, 14, 15, 16, 17, 18, 19, 20,
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21, 22, 23, 24, 25])
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low = np.array([8, 9, 10, 12, 13, 14, 15, 16, 17, 18,
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19, 20, 21, 22, 23])
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close = np.array([9, 11, 10.5, 13, 14, 15, 16, 17, 18, 19,
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20, 21, 22, 23, 24])
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atr = ATRIndicator(period=5, method='ema')
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result = atr.calculate(high, low, close)
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# 前period位置都是NaN
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assert all(np.isnan(result[i]) for i in range(5))
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assert not np.isnan(result[5])
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assert not np.isnan(atr.get_last_atr())
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def test_ema_incremental_update():
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"""测试EMA增量更新"""
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# 先建立初始ATR
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high = np.array([10, 12, 11, 14, 15, 16, 17, 18, 19, 20,
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21, 22, 23, 24])
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low = np.array([8, 9, 10, 12, 13, 14, 15, 16, 17, 18,
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19, 20, 21, 22])
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close = np.array([9, 11, 10.5, 13, 14, 15, 16, 17, 18, 19,
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20, 21, 22, 23])
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atr = ATRIndicator(period=5, method='ema')
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_ = atr.calculate(high, low, close)
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last_atr = atr.get_last_atr()
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assert not np.isnan(last_atr)
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# 更新一个新的bar
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new_high = 26
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new_low = 23
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prev_close = 23
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new_atr = atr.update(new_high, new_low, prev_close)
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# 新ATR应该和批量计算结果一致
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new_high_all = np.append(high, new_high)
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new_low_all = np.append(low, new_low)
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new_close_all = np.append(close, (new_high + new_low)/2)
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atr2 = ATRIndicator(period=5, method='ema')
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result2 = atr2.calculate(new_high_all, new_low_all, new_close_all)
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assert abs(new_atr - result2[-1]) < 1e-10
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assert abs(atr.get_last_atr() - result2[-1]) < 1e-10
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def test_sma_incremental_error():
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"""测试SMA不支持增量更新"""
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atr = ATRIndicator(period=5, method='sma')
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with pytest.raises(ValueError):
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atr.update(10, 8, 9)
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def test_calculate_atr_convenience():
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"""测试便捷函数calculate_atr"""
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df = pd.DataFrame({
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'high': [10, 12, 11, 14, 15, 16, 17, 18, 19, 20],
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'low': [8, 9, 10, 12, 13, 14, 15, 16, 17, 18],
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'close': [9, 11, 10.5, 13, 14, 15, 16, 17, 18, 19]
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})
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result = calculate_atr(df, period=5, method='sma')
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assert 'TR' in result.columns
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assert 'ATR_5' in result.columns
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assert result.shape == df.shape
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result_dropna = calculate_atr(df, period=5, method='sma', drop_na=True)
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assert len(result_dropna) < len(df)
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def test_short_data():
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"""测试数据长度不足周期"""
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high = [10, 12, 11]
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low = [8, 9, 10]
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close = [9, 11, 10.5]
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atr_sma = ATRIndicator(period=14, method='sma')
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result = atr_sma.calculate(np.array(high), np.array(low), np.array(close))
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assert all(np.isnan(result))
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atr_ema = ATRIndicator(period=14, method='ema')
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result_ema = atr_ema.calculate(np.array(high), np.array(low), np.array(close))
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assert all(np.isnan(result_ema))
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if __name__ == "__main__":
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pytest.main([__file__, '-v'])
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