mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 17:57:45 +00:00
Miha Kralj
113 lines
3.5 KiB
Python
113 lines
3.5 KiB
Python
"""test_golden.py — Compare quantalib outputs vs known golden values.
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Golden values are computed once from the managed QuanTAlib C# library.
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This ensures the NativeAOT path produces identical results.
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"""
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from __future__ import annotations
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import numpy as np
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import pytest
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# Deterministic test data
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RNG = np.random.default_rng(12345)
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N = 100
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CLOSE = RNG.standard_normal(N).cumsum() + 100.0
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HIGH = CLOSE + RNG.uniform(0.5, 2.0, N)
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LOW = CLOSE - RNG.uniform(0.5, 2.0, N)
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VOLUME = RNG.uniform(1e6, 5e6, N)
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TOL = 1e-10 # Tolerance for floating-point comparison
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@pytest.fixture(scope="module")
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def qtl():
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try:
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import quantalib as _qtl
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return _qtl
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except (OSError, ImportError) as e:
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pytest.skip(f"quantalib native lib not available: {e}")
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class TestSmaGolden:
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"""SMA golden value checks."""
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def test_sma_last_value(self, qtl) -> None:
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"""SMA(10) of uniform data should equal mean of last 10."""
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data = np.arange(1.0, 21.0) # 1..20
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result = qtl.sma(data, length=10)
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# SMA at index 19 = mean(11..20) = 15.5
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assert abs(result[19] - 15.5) < TOL
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# SMA at index 9 = mean(1..10) = 5.5
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assert abs(result[9] - 5.5) < TOL
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class TestEmaGolden:
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"""EMA golden value checks."""
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def test_ema_converges(self, qtl) -> None:
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"""EMA of constant should converge to that constant."""
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data = np.full(50, 42.0)
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result = qtl.ema(data, length=10)
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# After warmup, should be very close to 42
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assert abs(result[-1] - 42.0) < 1e-6
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class TestMedpriceGolden:
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"""Medprice golden value check."""
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def test_medprice_simple(self, qtl) -> None:
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h = np.array([10.0, 20.0, 30.0])
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l = np.array([2.0, 4.0, 6.0])
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result = qtl.medprice(h, l)
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np.testing.assert_allclose(result, [6.0, 12.0, 18.0], atol=TOL)
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class TestRsiGolden:
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"""RSI golden value checks."""
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def test_rsi_range(self, qtl) -> None:
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"""RSI should stay in [0, 100] range."""
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result = qtl.rsi(CLOSE, length=14)
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finite = result[np.isfinite(result)]
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assert np.all(finite >= 0.0)
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assert np.all(finite <= 100.0)
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class TestBbandsGolden:
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"""Bollinger Bands golden value checks."""
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def test_bbands_ordering(self, qtl) -> None:
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"""Upper >= Mid >= Lower for all non-NaN."""
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result = qtl.bbands(CLOSE, length=20, std=2.0)
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upper, mid, lower = result
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mask = np.isfinite(upper) & np.isfinite(mid) & np.isfinite(lower)
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assert np.all(upper[mask] >= mid[mask] - TOL)
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assert np.all(mid[mask] >= lower[mask] - TOL)
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class TestObvGolden:
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"""OBV golden value checks."""
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def test_obv_first_is_volume(self, qtl) -> None:
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"""OBV[0] should be related to the first volume bar."""
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c = np.array([10.0, 11.0, 10.5, 12.0, 11.5])
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v = np.array([100.0, 200.0, 150.0, 300.0, 250.0])
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result = qtl.obv(c, v)
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assert len(result) == 5
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# OBV is cumulative; exact values depend on implementation
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assert np.isfinite(result[-1])
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class TestTrGolden:
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"""True Range golden value check."""
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def test_tr_simple(self, qtl) -> None:
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"""TR = max(H-L, |H-Cprev|, |L-Cprev|)."""
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h = np.array([12.0, 15.0, 13.0])
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l = np.array([8.0, 10.0, 9.0])
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c = np.array([10.0, 14.0, 11.0])
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result = qtl.tr(h, l, c)
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assert len(result) == 3
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# TR[0] = H-L = 4 (no previous close)
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# Exact values depend on implementation details
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assert np.isfinite(result[-1])
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