Files
pandas-ta/tests/test_indicator_performance_ext.py
T

49 lines
1.5 KiB
Python

from unittest import TestCase
import numpy.testing as npt
import pandas.util.testing as pdt
from pandas import DataFrame, read_csv, Series
import pandas_ta as ta
class TestPerformaceExtension(TestCase):
@classmethod
def setUpClass(cls):
cls.data = read_csv('data/sample.csv', index_col=0, parse_dates=True, infer_datetime_format=False, keep_date_col=True)
cls.close = cls.data['close']
@classmethod
def tearDownClass(cls):
del cls.data
del cls.close
def setUp(self):
pass
def tearDown(self):
pass
def test_log_return_ext(self):
self.data.ta.log_return(append=True)
self.assertIsInstance(self.data, DataFrame)
self.assertEqual(self.data.columns[-1], 'LOGRET_1')
self.data.ta.log_return(append=True, cumulative=True)
self.assertIsInstance(self.data, DataFrame)
self.assertEqual(self.data.columns[-1], 'CUMLOGRET_1')
def test_percent_return_ext(self):
self.data.ta.percent_return(append=True)
self.assertIsInstance(self.data, DataFrame)
self.assertEqual(self.data.columns[-1], 'PCTRET_1')
self.data.ta.percent_return(append=True, cumulative=True)
self.assertIsInstance(self.data, DataFrame)
self.assertEqual(self.data.columns[-1], 'CUMPCTRET_1')
# Example
# pta_sma = self.data[self.data.columns[-1]]
# tal_sma = tal.SMA(self.close)
# pdt.assert_series_equal(pta_sma, tal_sma)