test: 更新测试以验证框架重构正确性
- 测试文件改用strategies.shared的具体实现 - 新增framework_comparison_test.py对比新旧实现结果 - 因子计算相关系数达到1.0000，差异为0.000000 - 79个单元测试全部通过
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"""
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框架核心测试
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集成测试
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验证框架整体功能
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测试框架与定制组件的集成
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"""
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import pandas as pd
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import numpy as np
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import pytest
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from framework.factors import FactorBase, FactorRegistry, FactorCombiner
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from framework.factors.momentum import MomentumFactor, TrendFactor, ReversalFactor, VolatilityFactor
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from framework.signals import TopNSelector, TrendFollower, ReversalTrader
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from framework.risk import StopLossControl, CallbackHook, Position, premium_filter_callback
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from framework.factors import FactorRegistry, FactorCombiner
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from framework.signals import SignalGenerator
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from framework.risk import CallbackHook, Position
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from framework.strategy import StrategyBase
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from framework.execution import Portfolio, BacktestExecutor
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from strategies.shared.factors.momentum import MomentumFactor, VolatilityFactor
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from strategies.shared.signals.selectors import TopNSelector
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from strategies.shared.risk.controls import StopLossControl, premium_filter_callback
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from strategies.rotation.strategy import RotationStrategy
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class TestFrameworkIntegration:
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"""测试框架集成"""
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class TestFactorIntegration:
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"""测试因子集成"""
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def test_rotation_strategy_workflow(self):
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"""测试轮动策略完整流程"""
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# 清空注册表
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def setup_method(self):
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"""每个测试前清空注册表"""
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FactorRegistry.clear()
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def test_register_and_use_custom_factor(self):
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"""测试注册并使用定制因子"""
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FactorRegistry.register(MomentumFactor)
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# 1. 注册因子
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factor = FactorRegistry.get('momentum', n_days=25, crash_filter=True)
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dates = pd.date_range('2020-01-01', periods=100)
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data = pd.DataFrame({
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'close': np.random.randn(100).cumsum() + 100
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}, index=dates)
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values = factor.compute(data)
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assert len(values) == len(data)
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def test_combiner_with_custom_factors(self):
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"""测试组合器使用定制因子"""
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FactorRegistry.register(MomentumFactor)
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FactorRegistry.register(VolatilityFactor)
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# 2. 创建因子组合
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factors = FactorCombiner([
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FactorRegistry.get('momentum', n_days=25, crash_filter=True),
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], weights=[1.0])
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# 3. 生成测试数据（需要'close'列）
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dates = pd.date_range('2020-01-01', periods=100)
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data = pd.DataFrame({
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'close': np.random.randn(100).cumsum() + 100,
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'code1': np.random.randn(100).cumsum() + 100,
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'code2': np.random.randn(100).cumsum() + 100,
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'code3': np.random.randn(100).cumsum() + 100,
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}, index=dates)
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# 4. 计算因子
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factor_result = factors.compute(data)
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# 5. 生成信号
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selector = TopNSelector(select_num=2)
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signals = selector.generate(factor_result)
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# 6. 验证结果
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assert 'signal' in signals.columns
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assert len(signals) == len(data)
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def test_trend_strategy_workflow(self):
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"""测试趋势策略完整流程"""
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FactorRegistry.clear()
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FactorRegistry.register(TrendFactor)
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factors = FactorCombiner([
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FactorRegistry.get('trend', method='ma_cross', fast=5, slow=20),
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])
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momentum = FactorRegistry.get('momentum', n_days=25)
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volatility = FactorRegistry.get('volatility', method='std', period=20)
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dates = pd.date_range('2020-01-01', periods=100)
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data = pd.DataFrame({
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'close': np.random.randn(100).cumsum() + 100,
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'high': np.random.randn(100).cumsum() + 105,
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'low': np.random.randn(100).cumsum() + 95
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}, index=dates)
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factor_result = factors.compute(data)
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follower = TrendFollower(entry_threshold=0.02)
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signals = follower.generate(factor_result)
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combiner = FactorCombiner([momentum, volatility], weights=[0.7, 0.3])
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result = combiner.compute(data)
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assert 'signal' in signals.columns
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assert 'momentum' in result.columns
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assert 'volatility' in result.columns
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assert 'combined' in result.columns
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class TestSignalIntegration:
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"""测试信号生成器集成"""
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def test_callbacks_workflow(self):
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"""测试回调钩子完整流程"""
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def test_custom_signal_generator_with_factors(self):
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"""测试定制信号生成器与因子集成"""
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dates = pd.date_range('2020-01-01', periods=50)
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factor_data = pd.DataFrame({
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'momentum_A': np.random.randn(50),
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'momentum_B': np.random.randn(50),
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'momentum_C': np.random.randn(50),
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}, index=dates)
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selector = TopNSelector(select_num=2, min_score=0.0)
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result = selector.generate(factor_data)
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assert 'signal' in result.columns
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class TestRiskIntegration:
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"""测试风控组件集成"""
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def test_custom_risk_control(self):
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"""测试定制风控组件"""
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control = StopLossControl(threshold=-0.05, trailing=True)
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position = Position(
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code='AAPL',
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entry_price=100.0,
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current_price=105.0,
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entry_time=pd.Timestamp.now()
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)
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# 首次检查，设置最高价
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assert control.check(position) == True
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# 价格下跌，触发跟踪止损
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position.current_price = 100.0
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assert control.check(position) == False
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def test_callback_hook_with_custom_callback(self):
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"""测试回调钩子与定制回调集成"""
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hook = CallbackHook()
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# 注册回调
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hook.register('before_entry', premium_filter_callback(0.10))
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hook.register('dynamic_stoploss', lambda pos: -0.05)
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# 注册定制回调
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callback = premium_filter_callback(threshold=0.10)
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hook.register('before_entry', callback)
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# 测试入场前回调
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result = hook.trigger('before_entry', 'code1', 100.0, premium=0.05)
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# 正常溢价通过
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result = hook.trigger('before_entry', 'AAPL', 100.0, premium=0.05)
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assert result == True
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# 测试动态止损
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position = Position(
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code='code1',
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entry_price=100.0,
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entry_date=pd.Timestamp('2020-01-01'),
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current_price=95.0,
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current_date=pd.Timestamp('2020-01-10'),
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quantity=100,
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weight=0.33
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)
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stoploss = hook.trigger('dynamic_stoploss', position)
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assert stoploss == -0.05
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# 高溢价拒绝
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result = hook.trigger('before_entry', 'AAPL', 100.0, premium=0.15)
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assert result == False
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class TestStrategyIntegration:
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"""测试策略集成"""
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def setup_method(self):
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"""每个测试前清空注册表"""
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FactorRegistry.clear()
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def test_rotation_strategy_full_flow(self):
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"""测试轮动策略完整流程"""
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strategy = RotationStrategy()
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# 生成测试数据
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dates = pd.date_range('2020-01-01', periods=100)
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data = pd.DataFrame({
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'close': np.random.randn(100).cumsum() + 100
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}, index=dates)
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# 运行策略
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result = strategy.run(data)
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assert 'signal' in result.columns
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def test_strategy_with_backtest_executor(self):
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"""测试策略与回测执行器集成"""
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FactorRegistry.clear()
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strategy = RotationStrategy()
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dates = pd.date_range('2020-01-01', periods=100)
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data = pd.DataFrame({
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'close': np.random.randn(100).cumsum() + 100
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}, index=dates)
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signals = strategy.run(data)
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executor = BacktestExecutor(initial_capital=100000, trade_cost=0.001)
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portfolio = executor.execute(signals, data)
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assert isinstance(portfolio, Portfolio)
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if __name__ == '__main__':
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