mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-07-11 00:40:06 +08:00
Kevin Johnson
95 lines
3.0 KiB
Python
95 lines
3.0 KiB
Python
from .config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
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from .context import pandas_ta
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from unittest import TestCase, skip
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import pandas.testing as pdt
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from pandas import DataFrame, Series
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import talib as tal
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class TestStatistics(TestCase):
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@classmethod
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def setUpClass(cls):
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cls.data = sample_data
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cls.data.columns = cls.data.columns.str.lower()
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cls.open = cls.data['open']
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cls.high = cls.data['high']
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cls.low = cls.data['low']
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cls.close = cls.data['close']
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if 'volume' in cls.data.columns: cls.volume = cls.data['volume']
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@classmethod
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def tearDownClass(cls):
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del cls.open
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del cls.high
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del cls.low
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del cls.close
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if hasattr(cls, 'volume'): del cls.volume
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del cls.data
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def setUp(self): pass
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def tearDown(self): pass
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def test_kurtosis(self):
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result = pandas_ta.kurtosis(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'KURT_30')
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def test_mad(self):
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result = pandas_ta.mad(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'MAD_30')
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def test_median(self):
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result = pandas_ta.median(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'MEDIAN_30')
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def test_quantile(self):
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result = pandas_ta.quantile(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'QTL_30_0.5')
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def test_skew(self):
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result = pandas_ta.skew(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'SKEW_30')
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def test_stdev(self):
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result = pandas_ta.stdev(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'STDEV_30')
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try:
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expected = tal.STDDEV(self.close, 30)
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pdt.assert_series_equal(result, expected, check_names=False)
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except AssertionError as ae:
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try:
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corr = pandas_ta.utils.df_error_analysis(result, expected, col=CORRELATION)
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self.assertGreater(corr, CORRELATION_THRESHOLD)
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except Exception as ex:
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error_analysis(result, CORRELATION, ex)
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def test_variance(self):
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result = pandas_ta.variance(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'VAR_30')
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try:
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expected = tal.VAR(self.close, 30)
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pdt.assert_series_equal(result, expected, check_names=False)
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except AssertionError as ae:
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try:
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corr = pandas_ta.utils.df_error_analysis(result, expected, col=CORRELATION)
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self.assertGreater(corr, CORRELATION_THRESHOLD)
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except Exception as ex:
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error_analysis(result, CORRELATION, ex)
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def test_zscore(self):
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result = pandas_ta.zscore(self.close)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, 'Z_30') |