class TestKAMAIndicator(unittest.TestCase):
"""
https://school.stockcharts.com/doku.php?id=technical_indicators:kaufman_s_adaptive_moving_average
"""
_filename = 'ta/tests/data/cs-kama.csv'
def setUp(self):
self._df = pd.read_csv(self._filename, sep=',')
self._indicator = KAMAIndicator(close=self._df['Close'], n=10, pow1=2, pow2=30, fillna=False)
def tearDown(self):
del(self._df)
def test_kama(self):
target = 'KAMA'
result = self._indicator.kama()
pd.testing.assert_series_equal(self._df[target].tail(), result.tail(), check_names=False)
from google.cloud import storage
import shutil
if len(sys.argv) > 1:
batch_size = 31
symbol = sys.argv[1]
end = datetime.today()
start = datetime(2000, 9, 1)
ETH = pdr.DataReader(symbol,'yahoo',start,end)
df = pd.DataFrame(data=ETH)
kama_indicator = KAMAIndicator(close = df["Close"], window = 10, pow1 = 2, pow2 = 30, fillna = False)
df['kama'] = kama_indicator.kama()
ppo_indicator = PercentagePriceOscillator(close = df["Close"], window_slow = 20, window_fast = 10, window_sign = 9, fillna = False)
df['ppo'] = ppo_indicator.ppo()
roc_indicator = ROCIndicator(close = df["Close"], window = 12, fillna = False)
df['roc'] = roc_indicator.roc()
macd_indicator = MACD(close = df["Close"], window_slow = 20, window_fast = 12, window_sign = 9, fillna = False)
df['macd'] = macd_indicator.macd()
rsi_indicator = RSIIndicator(close = df["Close"], window = 14, fillna = False)
df['rsi'] = rsi_indicator.rsi()
aroon_indicator = AroonIndicator(close = df["Close"], window = 20, fillna = False)
df['aroon'] = aroon_indicator.aroon_indicator()
