mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
Kevin Johnson
348 lines
14 KiB
Python
348 lines
14 KiB
Python
from .config import sample_data
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from .context import pandas_ta
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from unittest import skip, TestCase
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from unittest.mock import patch
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import numpy as np
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import numpy.testing as npt
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from pandas import DataFrame, Series
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from pandas.api.types import is_datetime64_ns_dtype, is_datetime64tz_dtype
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data = {
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"zero": [0, 0],
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"a": [0, 1],
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"b": [1, 0],
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"c": [1, 1],
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"crossed": [0, 1],
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}
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class TestUtilities(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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@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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self.crosseddf = DataFrame(data)
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self.utils = pandas_ta.utils
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def tearDown(self):
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del self.crosseddf
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del self.utils
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def test__add_prefix_suffix(self):
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result = self.data.ta.hl2(append=False, prefix="pre")
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self.assertEqual(result.name, "pre_HL2")
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result = self.data.ta.hl2(append=False, suffix="suf")
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self.assertEqual(result.name, "HL2_suf")
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result = self.data.ta.hl2(append=False, prefix="pre", suffix="suf")
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self.assertEqual(result.name, "pre_HL2_suf")
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result = self.data.ta.hl2(append=False, prefix=1, suffix=2)
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self.assertEqual(result.name, "1_HL2_2")
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result = self.data.ta.macd(append=False, prefix="pre", suffix="suf")
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for col in result.columns:
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self.assertTrue(col.startswith("pre_") and col.endswith("_suf"))
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@skip
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def test__above_below(self):
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result = self.utils._above_below(self.crosseddf["a"], self.crosseddf["zero"], above=True)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "a_A_zero")
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npt.assert_array_equal(result, self.crosseddf["c"])
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result = self.utils._above_below(self.crosseddf["a"], self.crosseddf["zero"], above=False)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "a_B_zero")
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npt.assert_array_equal(result, self.crosseddf["b"])
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result = self.utils._above_below(self.crosseddf["c"], self.crosseddf["zero"], above=True)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "c_A_zero")
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npt.assert_array_equal(result, self.crosseddf["c"])
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result = self.utils._above_below(self.crosseddf["c"], self.crosseddf["zero"], above=False)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "c_B_zero")
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npt.assert_array_equal(result, self.crosseddf["zero"])
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def test_above(self):
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result = self.utils.above(self.crosseddf["a"], self.crosseddf["zero"])
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "a_A_zero")
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npt.assert_array_equal(result, self.crosseddf["c"])
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result = self.utils.above(self.crosseddf["zero"], self.crosseddf["a"])
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "zero_A_a")
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npt.assert_array_equal(result, self.crosseddf["b"])
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def test_above_value(self):
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result = self.utils.above_value(self.crosseddf["a"], 0)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "a_A_0")
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npt.assert_array_equal(result, self.crosseddf["c"])
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result = self.utils.above_value(self.crosseddf["a"], self.crosseddf["zero"])
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self.assertIsNone(result)
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def test_below(self):
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result = self.utils.below(self.crosseddf["zero"], self.crosseddf["a"])
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "zero_B_a")
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npt.assert_array_equal(result, self.crosseddf["c"])
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result = self.utils.below(self.crosseddf["zero"], self.crosseddf["a"])
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "zero_B_a")
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npt.assert_array_equal(result, self.crosseddf["c"])
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def test_below_value(self):
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result = self.utils.below_value(self.crosseddf["a"], 0)
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self.assertIsInstance(result, Series)
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self.assertEqual(result.name, "a_B_0")
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npt.assert_array_equal(result, self.crosseddf["b"])
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result = self.utils.below_value(self.crosseddf["a"], self.crosseddf["zero"])
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self.assertIsNone(result)
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def test_combination(self):
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self.assertIsNotNone(self.utils.combination())
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self.assertEqual(self.utils.combination(), 1)
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self.assertEqual(self.utils.combination(r=-1), 1)
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self.assertEqual(self.utils.combination(n=10, r=4, repetition=False), 210)
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self.assertEqual(self.utils.combination(n=10, r=4, repetition=True), 715)
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def test_cross_above(self):
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result = self.utils.cross(self.crosseddf["a"], self.crosseddf["b"])
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self.assertIsInstance(result, Series)
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npt.assert_array_equal(result, self.crosseddf["crossed"])
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result = self.utils.cross(self.crosseddf["a"], self.crosseddf["b"], above=True)
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self.assertIsInstance(result, Series)
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npt.assert_array_equal(result, self.crosseddf["crossed"])
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def test_cross_below(self):
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result = self.utils.cross(self.crosseddf["b"], self.crosseddf["a"], above=False)
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self.assertIsInstance(result, Series)
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npt.assert_array_equal(result, self.crosseddf["crossed"])
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def test_df_dates(self):
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result = self.utils.df_dates(self.data)
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self.assertEqual(None, result)
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result = self.utils.df_dates(self.data, "1999-11-01")
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self.assertEqual(1, result.shape[0])
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result = self.utils.df_dates(self.data, ["1999-11-01", "2020-08-15", "2020-08-24", "2020-08-25", "2020-08-26", "2020-08-27"])
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self.assertEqual(5, result.shape[0])
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@skip
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def test_df_month_to_date(self):
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result = self.utils.df_month_to_date(self.data)
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@skip
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def test_df_quarter_to_date(self):
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result = self.utils.df_quarter_to_date(self.data)
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@skip
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def test_df_year_to_date(self):
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result = self.utils.df_year_to_date(self.data)
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def test_fibonacci(self):
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self.assertIs(type(self.utils.fibonacci(zero=True, weighted=False)), np.ndarray)
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npt.assert_array_equal(self.utils.fibonacci(zero=True), np.array([0, 1, 1]))
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npt.assert_array_equal(self.utils.fibonacci(zero=False), np.array([1, 1]))
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npt.assert_array_equal(self.utils.fibonacci(n=0, zero=True, weighted=False), np.array([0]))
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npt.assert_array_equal(self.utils.fibonacci(n=0, zero=False, weighted=False), np.array([1]))
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npt.assert_array_equal(self.utils.fibonacci(n=5, zero=True, weighted=False), np.array([0, 1, 1, 2, 3, 5]))
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npt.assert_array_equal(self.utils.fibonacci(n=5, zero=False, weighted=False), np.array([1, 1, 2, 3, 5]))
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def test_fibonacci_weighted(self):
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self.assertIs(type(self.utils.fibonacci(zero=True, weighted=True)), np.ndarray)
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npt.assert_array_equal(self.utils.fibonacci(n=0, zero=True, weighted=True), np.array([0]))
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npt.assert_array_equal(self.utils.fibonacci(n=0, zero=False, weighted=True), np.array([1]))
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npt.assert_allclose(self.utils.fibonacci(n=5, zero=True, weighted=True), np.array([0, 1 / 12, 1 / 12, 1 / 6, 1 / 4, 5 / 12]))
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npt.assert_allclose(self.utils.fibonacci(n=5, zero=False, weighted=True), np.array([1 / 12, 1 / 12, 1 / 6, 1 / 4, 5 / 12]))
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def test_geometric_mean(self):
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returns = pandas_ta.percent_return(self.data.close)
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result = self.utils.geometric_mean(returns)
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self.assertIsInstance(result, float)
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result = self.utils.geometric_mean(Series([12, 14, 11, 8]))
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self.assertIsInstance(result, float)
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result = self.utils.geometric_mean(Series([100, 50, 0, 25, 0, 60]))
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self.assertIsInstance(result, float)
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series = Series([0, 1, 2, 3])
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result = self.utils.geometric_mean(series)
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self.assertIsInstance(result, float)
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result = self.utils.geometric_mean(-series)
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self.assertIsInstance(result, int)
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self.assertAlmostEqual(result, 0)
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def test_get_time(self):
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result = self.utils.get_time(to_string=True)
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self.assertIsInstance(result, str)
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result = self.utils.get_time("NZSX", to_string=True)
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self.assertTrue("NZSX" in result)
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self.assertIsInstance(result, str)
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result = self.utils.get_time("SSE", to_string=True)
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self.assertIsInstance(result, str)
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self.assertTrue("SSE" in result)
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def test_linear_regression(self):
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x = Series([1, 2, 3, 4, 5])
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y = Series([1.8, 2.1, 2.7, 3.2, 4])
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result = self.utils.linear_regression(x, y)
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self.assertIsInstance(result, dict)
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self.assertIsInstance(result["a"], float)
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self.assertIsInstance(result["b"], float)
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self.assertIsInstance(result["r"], float)
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self.assertIsInstance(result["t"], float)
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self.assertIsInstance(result["line"], Series)
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def test_log_geometric_mean(self):
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returns = pandas_ta.percent_return(self.data.close)
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result = self.utils.log_geometric_mean(returns)
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self.assertIsInstance(result, float)
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result = self.utils.log_geometric_mean(Series([12, 14, 11, 8]))
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self.assertIsInstance(result, float)
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result = self.utils.log_geometric_mean(Series([100, 50, 0, 25, 0, 60]))
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self.assertIsInstance(result, float)
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series = Series([0, 1, 2, 3])
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result = self.utils.log_geometric_mean(series)
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self.assertIsInstance(result, float)
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result = self.utils.log_geometric_mean(-series)
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self.assertIsInstance(result, int)
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self.assertAlmostEqual(result, 0)
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def test_pascals_triangle(self):
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self.assertIsNone(self.utils.pascals_triangle(inverse=True), None)
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array_1 = np.array([1])
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npt.assert_array_equal(self.utils.pascals_triangle(), array_1)
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npt.assert_array_equal(self.utils.pascals_triangle(weighted=True), array_1)
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npt.assert_array_equal(self.utils.pascals_triangle(weighted=True, inverse=True), np.array([0]))
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array_5 = self.utils.pascals_triangle(n=5) # or np.array([1, 5, 10, 10, 5, 1])
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array_5w = array_5 / np.sum(array_5)
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array_5iw = 1 - array_5w
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npt.assert_array_equal(self.utils.pascals_triangle(n=-5), array_5)
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npt.assert_array_equal(self.utils.pascals_triangle(n=-5, weighted=True), array_5w)
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npt.assert_array_equal(self.utils.pascals_triangle(n=-5, weighted=True, inverse=True), array_5iw)
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npt.assert_array_equal(self.utils.pascals_triangle(n=5), array_5)
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npt.assert_array_equal(self.utils.pascals_triangle(n=5, weighted=True), array_5w)
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npt.assert_array_equal(self.utils.pascals_triangle(n=5, weighted=True, inverse=True), array_5iw)
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def test_symmetric_triangle(self):
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npt.assert_array_equal(self.utils.symmetric_triangle(), np.array([1,1]))
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npt.assert_array_equal(self.utils.symmetric_triangle(weighted=True), np.array([0.5, 0.5]))
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array_4 = self.utils.symmetric_triangle(n=4) # or np.array([1, 2, 2, 1])
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array_4w = array_4 / np.sum(array_4)
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npt.assert_array_equal(self.utils.symmetric_triangle(n=4), array_4)
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npt.assert_array_equal(self.utils.symmetric_triangle(n=4, weighted=True), array_4w)
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array_5 = self.utils.symmetric_triangle(n=5) # or np.array([1, 2, 3, 2, 1])
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array_5w = array_5 / np.sum(array_5)
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npt.assert_array_equal(self.utils.symmetric_triangle(n=5), array_5)
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npt.assert_array_equal(self.utils.symmetric_triangle(n=5, weighted=True), array_5w)
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def test_tal_ma(self):
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self.assertEqual(self.utils.tal_ma("sma"), 0)
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self.assertEqual(self.utils.tal_ma("Sma"), 0)
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self.assertEqual(self.utils.tal_ma("ema"), 1)
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self.assertEqual(self.utils.tal_ma("wma"), 2)
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self.assertEqual(self.utils.tal_ma("dema"), 3)
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self.assertEqual(self.utils.tal_ma("tema"), 4)
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self.assertEqual(self.utils.tal_ma("trima"), 5)
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self.assertEqual(self.utils.tal_ma("kama"), 6)
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self.assertEqual(self.utils.tal_ma("mama"), 7)
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self.assertEqual(self.utils.tal_ma("t3"), 8)
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def test_zero(self):
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self.assertEqual(self.utils.zero(-0.0000000000000001), 0)
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self.assertEqual(self.utils.zero(0), 0)
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self.assertEqual(self.utils.zero(0.0), 0)
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self.assertEqual(self.utils.zero(0.0000000000000001), 0)
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self.assertNotEqual(self.utils.zero(-0.000000000000001), 0)
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self.assertNotEqual(self.utils.zero(0.000000000000001), 0)
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self.assertNotEqual(self.utils.zero(1), 0)
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def test_get_drift(self):
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for s in [0, None, "", [], {}]:
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self.assertIsInstance(self.utils.get_drift(s), int)
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self.assertEqual(self.utils.get_drift(0), 1)
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self.assertEqual(self.utils.get_drift(1.1), 1)
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self.assertEqual(self.utils.get_drift(-1.1), 1)
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def test_get_offset(self):
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for s in [0, None, "", [], {}]:
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self.assertIsInstance(self.utils.get_offset(s), int)
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self.assertEqual(self.utils.get_offset(0), 0)
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self.assertEqual(self.utils.get_offset(-1.1), 0)
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self.assertEqual(self.utils.get_offset(1), 1)
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def test_to_utc(self):
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result = self.utils.to_utc(self.data.copy())
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self.assertTrue(is_datetime64_ns_dtype(result.index))
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self.assertTrue(is_datetime64tz_dtype(result.index))
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def test_total_time(self):
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result = self.utils.total_time(self.data)
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self.assertEqual(30.182539682539684, result)
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result = self.utils.total_time(self.data, "months")
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self.assertEqual(250.05753361606995, result)
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result = self.utils.total_time(self.data, "weeks")
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self.assertEqual(1086.5714285714287, result)
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result = self.utils.total_time(self.data, "days")
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self.assertEqual(7606, result)
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result = self.utils.total_time(self.data, "hours")
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self.assertEqual(182544, result)
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result = self.utils.total_time(self.data, "minutes")
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self.assertEqual(10952640.0, result)
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result = self.utils.total_time(self.data, "seconds")
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self.assertEqual(657158400.0, result)
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def test_version(self):
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result = pandas_ta.version
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self.assertIsInstance(result, str)
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print(f"\nPandas TA v{result}") |