mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-07-14 01:10:34 +08:00
Kevin Johnson
117 lines
4.1 KiB
Python
117 lines
4.1 KiB
Python
from .config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
|
|
from .context import pandas_ta
|
|
|
|
from unittest import TestCase, skip
|
|
import pandas.util.testing as pdt
|
|
from pandas import DataFrame, Series
|
|
|
|
import talib as tal
|
|
|
|
|
|
|
|
class TestTrend(TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
cls.data = sample_data
|
|
cls.data.columns = cls.data.columns.str.lower()
|
|
cls.open = cls.data['open']
|
|
cls.high = cls.data['high']
|
|
cls.low = cls.data['low']
|
|
cls.close = cls.data['close']
|
|
if 'volume' in cls.data.columns: cls.volume = cls.data['volume']
|
|
|
|
@classmethod
|
|
def tearDownClass(cls):
|
|
del cls.open
|
|
del cls.high
|
|
del cls.low
|
|
del cls.close
|
|
if hasattr(cls, 'volume'): del cls.volume
|
|
del cls.data
|
|
|
|
|
|
def setUp(self): pass
|
|
def tearDown(self): pass
|
|
|
|
|
|
def test_adx(self):
|
|
result = pandas_ta.adx(self.high, self.low, self.close)
|
|
self.assertIsInstance(result, DataFrame)
|
|
self.assertEqual(result.name, 'ADX_14')
|
|
|
|
try:
|
|
expected = tal.ADX(self.high, self.low, self.close)
|
|
pdt.assert_series_equal(result.iloc[:,0], expected)
|
|
except AssertionError as ae:
|
|
try:
|
|
corr = pandas_ta.utils.df_error_analysis(result.iloc[:,0], expected, col=CORRELATION)
|
|
self.assertGreater(corr, CORRELATION_THRESHOLD)
|
|
except Exception as ex:
|
|
error_analysis(result, CORRELATION, ex)
|
|
|
|
def test_amat(self):
|
|
result = pandas_ta.amat(self.close)
|
|
self.assertIsInstance(result, DataFrame)
|
|
self.assertEqual(result.name, 'AMAT_EMA_8_21_2')
|
|
|
|
def test_aroon(self):
|
|
result = pandas_ta.aroon(self.close)
|
|
self.assertIsInstance(result, DataFrame)
|
|
self.assertEqual(result.name, 'AROON_14')
|
|
|
|
try:
|
|
expected = tal.AROON(self.high, self.low)
|
|
expecteddf = DataFrame({'AROOND_14': expected[0], 'AROONU_14': expected[1]})
|
|
pdt.assert_frame_equal(result, expecteddf)
|
|
except AssertionError as ae:
|
|
try:
|
|
aroond_corr = pandas_ta.utils.df_error_analysis(result.iloc[:,0], expecteddf.iloc[:,0], col=CORRELATION)
|
|
self.assertGreater(aroond_corr, CORRELATION_THRESHOLD)
|
|
except Exception as ex:
|
|
error_analysis(result.iloc[:,0], CORRELATION, ex)
|
|
|
|
try:
|
|
aroonu_corr = pandas_ta.utils.df_error_analysis(result.iloc[:,1], expecteddf.iloc[:,1], col=CORRELATION)
|
|
self.assertGreater(aroonu_corr, CORRELATION_THRESHOLD)
|
|
except Exception as ex:
|
|
error_analysis(result.iloc[:,1], CORRELATION, ex, newline=False)
|
|
|
|
def test_decreasing(self):
|
|
result = pandas_ta.decreasing(self.close)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'DEC_1')
|
|
|
|
def test_dpo(self):
|
|
result = pandas_ta.dpo(self.close)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'DPO_1')
|
|
|
|
def test_increasing(self):
|
|
result = pandas_ta.increasing(self.close)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'INC_1')
|
|
|
|
def test_linear_decay(self):
|
|
result = pandas_ta.linear_decay(self.close)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'LDECAY_5')
|
|
|
|
def test_long_run(self):
|
|
result = pandas_ta.long_run(self.close, self.open)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'LR_2')
|
|
|
|
def test_qstick(self):
|
|
result = pandas_ta.qstick(self.open, self.close)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'QS_10')
|
|
|
|
def test_short_run(self):
|
|
result = pandas_ta.short_run(self.close, self.open)
|
|
self.assertIsInstance(result, Series)
|
|
self.assertEqual(result.name, 'SR_2')
|
|
|
|
def test_vortex(self):
|
|
result = pandas_ta.vortex(self.high, self.low, self.close)
|
|
self.assertIsInstance(result, DataFrame)
|
|
self.assertEqual(result.name, 'VTX_14') |