rmarcinkandClaude Opus 4.8
90ca05de06
The cpr `open` input parameter was named `open` (bare) instead of the `open_` convention used across the codebase. The DataFrame accessor's generic column mapper only maps the `open_` param to the `open` column, so `df.ta.cpr()` never fetched open prices: cpr() received open=None, returned None, and the accessor fell back to the unchanged input frame (the 11 CPR columns collapsed to the original OHLC 4). Direct positional calls were unaffected, which is why the existing tests passed. Rename the parameter to `open_`, regenerate core.pyi (the accessor stub no longer carries a stray `open` param), and add an accessor regression test asserting CPR_PIVOT is present in the result. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
188 lines
7.0 KiB
Python
188 lines
7.0 KiB
Python
from tests.config import get_sample_data
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from unittest import TestCase
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from pandas import DataFrame
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class TestTrendExtension(TestCase):
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@classmethod
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def setUpClass(cls):
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cls.data = get_sample_data()
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@classmethod
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def tearDownClass(cls):
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del cls.data
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def setUp(self):
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pass
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def tearDown(self):
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pass
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def test_adx_ext(self):
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self.data.ta.adx(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-3:]), ["ADX_14", "DMP_14", "DMN_14"])
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def test_amat_ext(self):
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self.data.ta.amat(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-2:]), ["AMATe_LR_8_21_2", "AMATe_SR_8_21_2"])
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def test_aroon_ext(self):
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self.data.ta.aroon(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-3:]), ["AROOND_14", "AROONU_14", "AROONOSC_14"])
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def test_chop_ext(self):
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self.data.ta.chop(append=True, ln=False)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "CHOP_14_1_100")
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self.data.ta.chop(append=True, ln=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "CHOPln_14_1_100")
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def test_cksp_ext(self):
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self.data.ta.cksp(tvmode=False, append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-2:]), ["CKSPl_10_3_20", "CKSPs_10_3_20"])
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def test_cksp_tv_ext(self):
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self.data.ta.cksp(tvmode=True, append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-2:]), ["CKSPl_10_1_9", "CKSPs_10_1_9"])
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def test_cpr_ext(self):
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# Regression: the generic accessor maps the open_ param to the 'open'
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# column. A bare 'open' param made df.ta.cpr() silently return the
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# unchanged input frame instead of computing CPR.
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result = self.data.ta.cpr()
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self.assertIsInstance(result, DataFrame)
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self.assertIn("CPR_PIVOT", result.columns)
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def test_decay_ext(self):
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self.data.ta.decay(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "LDECAY_5")
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self.data.ta.decay(mode="exp", append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "EXPDECAY_5")
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def test_decreasing_ext(self):
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self.data.ta.decreasing(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "DEC_1")
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self.data.ta.decreasing(length=3, strict=True, append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "SDEC_3")
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def test_dpo_ext(self):
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self.data.ta.dpo(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "DPO_20")
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def test_increasing_ext(self):
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self.data.ta.increasing(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "INC_1")
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self.data.ta.increasing(length=3, strict=True, append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "SINC_3")
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def test_long_run_ext(self):
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self.assertIsInstance(self.data.ta.long_run(append=True), DataFrame)
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fast = self.data.ta.ema(8)
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slow = self.data.ta.ema(21)
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self.data.ta.long_run(fast, slow, append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "LR_2")
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def test_psar_ext(self):
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self.data.ta.psar(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(
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list(self.data.columns[-4:]),
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["PSARl_0.02_0.2", "PSARs_0.02_0.2", "PSARaf_0.02_0.2", "PSARr_0.02_0.2"],
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)
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def test_qstick_ext(self):
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self.data.ta.qstick(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "QS_10")
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def test_short_run_ext(self):
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self.assertIsInstance(self.data.ta.short_run(append=True), DataFrame)
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fast = self.data.ta.ema(8)
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slow = self.data.ta.ema(21)
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self.data.ta.short_run(fast, slow, append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "SR_2")
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def test_ttm_trend_ext(self):
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self.data.ta.ttm_trend(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-1:]), ["TTM_TRND_6"])
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def test_vortext_ext(self):
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self.data.ta.vortex(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-2:]), ["VTXP_14", "VTXM_14"])
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def test_pmax_ext(self):
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self.data.ta.pmax(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "PMAX_E_10_3.0")
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def test_tsignals_ext(self):
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trend = (self.data.ta.sma(length=10) - self.data.ta.sma(length=20) > 0).astype(int)
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result = self.data.ta.tsignals(trend)
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self.assertIsInstance(result, DataFrame)
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self.assertEqual(list(result.columns), ["TS_Trends", "TS_Trades", "TS_Entries", "TS_Exits"])
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def test_xsignals_ext(self):
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signal = self.data.ta.rsi()
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result = self.data.ta.xsignals(signal, xa=70, xb=30)
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self.assertIsInstance(result, DataFrame)
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self.assertEqual(list(result.columns), ["TS_Trends", "TS_Trades", "TS_Entries", "TS_Exits"])
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def test_adxr_ext(self):
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self.data.ta.adxr(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(list(self.data.columns[-3:]), ["DMP_14", "DMN_14", "ADXR_14"])
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def test_dx_ext(self):
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self.data.ta.dx(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "DX_14")
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def test_edecay_ext(self):
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self.data.ta.edecay(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "EDECAY_5")
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def test_minus_dm_ext(self):
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self.data.ta.minus_dm(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "MINUS_DM_14")
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def test_plus_dm_ext(self):
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self.data.ta.plus_dm(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "PLUS_DM_14")
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def test_sarext_ext(self):
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self.data.ta.sarext(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "SAREXT")
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def test_vhf_ext(self):
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self.data.ta.vhf(append=True)
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self.assertIsInstance(self.data, DataFrame)
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self.assertEqual(self.data.columns[-1], "VHF_28")
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