feat(agents): market summary builder for hypothesis prompt
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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import numpy as np
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import pandas as pd
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from multi_swarm.agents.market_summary import build_market_summary
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def test_build_summary_basic() -> None:
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idx = pd.date_range("2024-01-01", periods=200, freq="1h", tz="UTC")
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np.random.seed(0)
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close = 100 + np.cumsum(np.random.normal(0, 1, 200))
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df = pd.DataFrame(
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{"open": close, "high": close + 0.5, "low": close - 0.5, "close": close, "volume": 1.0},
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index=idx,
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)
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s = build_market_summary(df, symbol="BTC/USDT", timeframe="1h")
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assert s.symbol == "BTC/USDT"
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assert s.timeframe == "1h"
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assert s.n_bars == 200
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assert isinstance(s.return_mean, float)
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assert isinstance(s.return_std, float)
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assert s.volatility_regime in {"low", "medium", "high"}
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def test_volatility_regime_high_for_volatile() -> None:
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idx = pd.date_range("2024-01-01", periods=200, freq="1h", tz="UTC")
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np.random.seed(0)
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close = 100 + np.cumsum(np.random.normal(0, 5.0, 200)) # alta vol
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df = pd.DataFrame(
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{"open": close, "high": close + 0.5, "low": close - 0.5, "close": close, "volume": 1.0},
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index=idx,
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)
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s = build_market_summary(df, symbol="BTC/USDT", timeframe="1h")
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assert s.volatility_regime in {"medium", "high"}
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