import numpy as np
import pandas as pd
from intelligence.technical_analysis import calculate_indicators
def test_calculate_indicators():
# Generate simple data
# 100 periods
close = np.linspace(100, 200, 100)
volume = np.random.randint(100, 1000, 100)
df = pd.DataFrame({
"close": close,
"high": close + 1,
"low": close - 1,
"volume": volume
})
df_out = calculate_indicators(df)
assert "rsi" in df_out.columns
assert "bb_high" in df_out.columns
assert "macd" in df_out.columns
assert "ema_20" in df_out.columns
assert "vwap" in df_out.columns
# Check values exist (after warmup)
assert not pd.isna(df_out["rsi"].iloc[-1])
assert not pd.isna(df_out["ema_20"].iloc[-1])
