Pratik Bhadane
208 lines
7.9 KiB
Python
208 lines
7.9 KiB
Python
"""Unit tests for ferro_ta.indicators.pattern (CDL* functions)"""
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import numpy as np
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import pytest
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from ferro_ta.indicators.pattern import (
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CDL2CROWS, CDL3BLACKCROWS, CDL3INSIDE, CDL3LINESTRIKE, CDL3OUTSIDE,
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CDL3STARSINSOUTH, CDL3WHITESOLDIERS, CDLABANDONEDBABY, CDLADVANCEBLOCK,
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CDLBELTHOLD, CDLBREAKAWAY, CDLCLOSINGMARUBOZU, CDLCONCEALBABYSWALL,
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CDLCOUNTERATTACK, CDLDARKCLOUDCOVER, CDLDOJI, CDLDOJISTAR, CDLDRAGONFLYDOJI,
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CDLENGULFING, CDLEVENINGDOJISTAR, CDLEVENINGSTAR, CDLGAPSIDESIDEWHITE,
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CDLGRAVESTONEDOJI, CDLHAMMER, CDLHANGINGMAN, CDLHARAMI, CDLHARAMICROSS,
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CDLHIGHWAVE, CDLHIKKAKE, CDLHIKKAKEMOD, CDLHOMINGPIGEON, CDLIDENTICAL3CROWS,
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CDLINNECK, CDLINVERTEDHAMMER, CDLKICKING, CDLKICKINGBYLENGTH, CDLLADDERBOTTOM,
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CDLLONGLEGGEDDOJI, CDLLONGLINE, CDLMARUBOZU, CDLMATCHINGLOW, CDLMATHOLD,
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CDLMORNINGDOJISTAR, CDLMORNINGSTAR, CDLONNECK, CDLPIERCING, CDLRICKSHAWMAN,
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CDLRISEFALL3METHODS, CDLSEPARATINGLINES, CDLSHOOTINGSTAR, CDLSHORTLINE,
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CDLSPINNINGTOP, CDLSTALLEDPATTERN, CDLSTICKSANDWICH, CDLTAKURI, CDLTASUKIGAP,
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CDLTHRUSTING, CDLTRISTAR, CDLUNIQUE3RIVER, CDLUPSIDEGAP2CROWS, CDLXSIDEGAP3METHODS,
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)
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# ---------------------------------------------------------------------------
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# Shared random OHLCV data (realistic OHLCV, proper H >= O,C >= L)
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# ---------------------------------------------------------------------------
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RNG = np.random.default_rng(42)
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N = 200
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_C = 100 + np.cumsum(RNG.normal(0, 0.5, N))
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_O = _C + RNG.normal(0, 0.2, N)
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_H = np.maximum(np.maximum(_O, _C) + np.abs(RNG.normal(0, 0.3, N)), np.maximum(_O, _C))
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_L = np.minimum(np.minimum(_O, _C) - np.abs(RNG.normal(0, 0.3, N)), np.minimum(_O, _C))
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# All CDL* functions to test systematically
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ALL_CDL = [
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("CDL2CROWS", CDL2CROWS),
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("CDL3BLACKCROWS", CDL3BLACKCROWS),
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("CDL3INSIDE", CDL3INSIDE),
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("CDL3LINESTRIKE", CDL3LINESTRIKE),
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("CDL3OUTSIDE", CDL3OUTSIDE),
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("CDL3STARSINSOUTH", CDL3STARSINSOUTH),
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("CDL3WHITESOLDIERS", CDL3WHITESOLDIERS),
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("CDLABANDONEDBABY", CDLABANDONEDBABY),
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("CDLADVANCEBLOCK", CDLADVANCEBLOCK),
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("CDLBELTHOLD", CDLBELTHOLD),
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("CDLBREAKAWAY", CDLBREAKAWAY),
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("CDLCLOSINGMARUBOZU", CDLCLOSINGMARUBOZU),
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("CDLCONCEALBABYSWALL", CDLCONCEALBABYSWALL),
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("CDLCOUNTERATTACK", CDLCOUNTERATTACK),
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("CDLDARKCLOUDCOVER", CDLDARKCLOUDCOVER),
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("CDLDOJI", CDLDOJI),
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("CDLDOJISTAR", CDLDOJISTAR),
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("CDLDRAGONFLYDOJI", CDLDRAGONFLYDOJI),
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("CDLENGULFING", CDLENGULFING),
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("CDLEVENINGDOJISTAR", CDLEVENINGDOJISTAR),
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("CDLEVENINGSTAR", CDLEVENINGSTAR),
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("CDLGAPSIDESIDEWHITE", CDLGAPSIDESIDEWHITE),
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("CDLGRAVESTONEDOJI", CDLGRAVESTONEDOJI),
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("CDLHAMMER", CDLHAMMER),
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("CDLHANGINGMAN", CDLHANGINGMAN),
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("CDLHARAMI", CDLHARAMI),
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("CDLHARAMICROSS", CDLHARAMICROSS),
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("CDLHIGHWAVE", CDLHIGHWAVE),
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("CDLHIKKAKE", CDLHIKKAKE),
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("CDLHIKKAKEMOD", CDLHIKKAKEMOD),
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("CDLHOMINGPIGEON", CDLHOMINGPIGEON),
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("CDLIDENTICAL3CROWS", CDLIDENTICAL3CROWS),
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("CDLINNECK", CDLINNECK),
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("CDLINVERTEDHAMMER", CDLINVERTEDHAMMER),
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("CDLKICKING", CDLKICKING),
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("CDLKICKINGBYLENGTH", CDLKICKINGBYLENGTH),
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("CDLLADDERBOTTOM", CDLLADDERBOTTOM),
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("CDLLONGLEGGEDDOJI", CDLLONGLEGGEDDOJI),
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("CDLLONGLINE", CDLLONGLINE),
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("CDLMARUBOZU", CDLMARUBOZU),
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("CDLMATCHINGLOW", CDLMATCHINGLOW),
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("CDLMATHOLD", CDLMATHOLD),
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("CDLMORNINGDOJISTAR", CDLMORNINGDOJISTAR),
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("CDLMORNINGSTAR", CDLMORNINGSTAR),
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("CDLONNECK", CDLONNECK),
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("CDLPIERCING", CDLPIERCING),
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("CDLRICKSHAWMAN", CDLRICKSHAWMAN),
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("CDLRISEFALL3METHODS", CDLRISEFALL3METHODS),
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("CDLSEPARATINGLINES", CDLSEPARATINGLINES),
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("CDLSHOOTINGSTAR", CDLSHOOTINGSTAR),
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("CDLSHORTLINE", CDLSHORTLINE),
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("CDLSPINNINGTOP", CDLSPINNINGTOP),
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("CDLSTALLEDPATTERN", CDLSTALLEDPATTERN),
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("CDLSTICKSANDWICH", CDLSTICKSANDWICH),
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("CDLTAKURI", CDLTAKURI),
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("CDLTASUKIGAP", CDLTASUKIGAP),
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("CDLTHRUSTING", CDLTHRUSTING),
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("CDLTRISTAR", CDLTRISTAR),
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("CDLUNIQUE3RIVER", CDLUNIQUE3RIVER),
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("CDLUPSIDEGAP2CROWS", CDLUPSIDEGAP2CROWS),
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("CDLXSIDEGAP3METHODS", CDLXSIDEGAP3METHODS),
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]
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# ---------------------------------------------------------------------------
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# Parametrised tests: all CDL patterns
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize("name,fn", ALL_CDL)
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def test_cdl_output_length(name, fn):
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result = fn(_O, _H, _L, _C)
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assert len(result) == N, f"{name}: expected length {N}, got {len(result)}"
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@pytest.mark.parametrize("name,fn", ALL_CDL)
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def test_cdl_values_in_valid_set(name, fn):
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result = fn(_O, _H, _L, _C)
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assert np.all(np.isin(result, [-100, 0, 100])), \
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f"{name}: unexpected values {np.unique(result)}"
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@pytest.mark.parametrize("name,fn", ALL_CDL)
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def test_cdl_no_nan(name, fn):
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result = fn(_O, _H, _L, _C)
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assert np.all(np.isfinite(result.astype(float))), f"{name}: contains NaN/Inf"
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# ---------------------------------------------------------------------------
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# Specific tests for previously untested patterns
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# ---------------------------------------------------------------------------
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class TestCDLSPINNINGTOP:
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def test_detects_pattern(self):
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# Spinning top: small body, long upper and lower shadows
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# open ≈ close (small body), high much higher, low much lower
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o = np.array([10.0, 10.1, 10.0])
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h = np.array([15.0, 15.1, 15.0])
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l = np.array([5.0, 5.1, 5.0])
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c = np.array([10.0, 10.0, 10.05])
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result = CDLSPINNINGTOP(o, h, l, c)
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assert np.all(np.isin(result, [-100, 0, 100]))
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def test_output_values_random(self):
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result = CDLSPINNINGTOP(_O, _H, _L, _C)
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assert np.all(np.isin(result, [-100, 0, 100]))
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class TestCDLEVENINGSTAR:
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def test_basic_run(self):
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result = CDLEVENINGSTAR(_O, _H, _L, _C)
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assert len(result) == N
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assert np.all(np.isin(result, [-100, 0, 100]))
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def test_large_dataset_has_valid_output(self):
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# On 200 bars of random data, result should be all in {-100,0,100}
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result = CDLEVENINGSTAR(_O, _H, _L, _C)
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assert np.all(np.isin(result, [-100, 0, 100]))
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class TestCDLMORNINGSTAR:
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def test_basic_run(self):
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result = CDLMORNINGSTAR(_O, _H, _L, _C)
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assert len(result) == N
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assert np.all(np.isin(result, [-100, 0, 100]))
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def test_bullish_signal_is_100(self):
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# Any detected signal must be 100 (bullish)
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result = CDLMORNINGSTAR(_O, _H, _L, _C)
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assert np.all(result[result != 0] == 100)
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class TestCDL2CROWS:
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def test_basic_run(self):
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result = CDL2CROWS(_O, _H, _L, _C)
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assert len(result) == N
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assert np.all(np.isin(result, [-100, 0, 100]))
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def test_bearish_signal_is_minus_100(self):
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# Any detected signal must be -100 (bearish)
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result = CDL2CROWS(_O, _H, _L, _C)
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assert np.all(result[result != 0] == -100)
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class TestCDLDOJI:
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def test_detects_doji(self):
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# Exact doji: open == close
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o = np.array([10.0, 10.0, 10.0])
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h = np.array([12.0, 12.0, 12.0])
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l = np.array([8.0, 8.0, 8.0])
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c = np.array([10.0, 10.0, 10.0])
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result = CDLDOJI(o, h, l, c)
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assert np.all(result == 100)
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def test_non_doji_returns_zero(self):
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o = np.array([10.0, 11.0, 12.0])
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h = np.array([15.0, 16.0, 17.0])
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l = np.array([9.0, 10.0, 11.0])
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c = np.array([14.0, 15.0, 16.0]) # large body, not doji
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result = CDLDOJI(o, h, l, c)
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assert np.all(result == 0)
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class TestCDLMARUBOZU:
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def test_detects_bullish_marubozu(self):
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# Bullish marubozu: open == low, close == high, close > open
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o = np.array([10.0, 10.0])
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h = np.array([15.0, 15.0])
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l = np.array([10.0, 10.0])
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c = np.array([15.0, 15.0])
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result = CDLMARUBOZU(o, h, l, c)
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assert np.all(np.isin(result, [-100, 0, 100]))
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def test_length(self):
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result = CDLMARUBOZU(_O, _H, _L, _C)
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assert len(result) == N
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