Python talib.WMA Examples

The following are 9 code examples of talib.WMA(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module talib , or try the search function .
Example #1
Source File: wma.py    From jesse with MIT License 6 votes vote down vote up 
def wma(candles: np.ndarray, period=30, source_type="close", sequential=False) -> Union[float, np.ndarray]:
    """
    WMA - Weighted Moving Average

    :param candles: np.ndarray
    :param period: int - default: 30
    :param source_type: str - default: "close"
    :param sequential: bool - default=False

    :return: float | np.ndarray
    """
    if not sequential and len(candles) > 240:
        candles = candles[-240:]

    source = get_candle_source(candles, source_type=source_type)
    res = talib.WMA(source, timeperiod=period)

    return res if sequential else res[-1]
Example #2
Source File: talib_numpy.py    From QUANTAXIS with MIT License 5 votes vote down vote up 
def TA_HMA(close, period):
    """
    赫尔移动平均线(HMA) 
    Hull Moving Average.
    Formula:
    HMA = WMA(2*WMA(n/2) - WMA(n)), sqrt(n)
    """
    hma = talib.WMA(2 * talib.WMA(close, int(period / 2)) - talib.WMA(close, period), int(np.sqrt(period)))
    return hma
Example #3
Source File: ta_indicator_mixin.py    From strategy with Apache License 2.0 5 votes vote down vote up 
def wma_close(self, sym, frequency, period=30):
        if not self.kbars_ready(sym, frequency):
            return []

        closes = self.close(sym, frequency)
        ma = ta.WMA(closes, timeperiod=period)

        return ma
Example #4
Source File: ta.py    From dash-technical-charting with MIT License 5 votes vote down vote up 
def add_WMA(self, timeperiod=20,
            type='line', color='secondary', **kwargs):
    """Weighted Moving Average."""

    if not self.has_close:
        raise Exception()

    utils.kwargs_check(kwargs, VALID_TA_KWARGS)
    if 'kind' in kwargs:
        type = kwargs['kind']

    name = 'WMA({})'.format(str(timeperiod))
    self.pri[name] = dict(type=type, color=color)
    self.ind[name] = talib.WMA(self.df[self.cl].values,
                               timeperiod)
Example #5
Source File: __init__.py    From ebisu with MIT License 5 votes vote down vote up 
def wma(src, length):
    return talib.WMA(src, length)
Example #6
Source File: indicator_helpers.py    From technical with GNU General Public License v3.0 5 votes vote down vote up 
def fishers_inverse(series: Series, smoothing: float = 0) -> np.ndarray:
    """ Does a smoothed fishers inverse transformation.
        Can be used with any oscillator that goes from 0 to 100 like RSI or MFI """
    v1 = 0.1 * (series - 50)
    if smoothing > 0:
        v2 = ta.WMA(v1.values, timeperiod=smoothing)
    else:
        v2 = v1
    return (np.exp(2 * v2)-1) / (np.exp(2 * v2) + 1)
Example #7
Source File: test_reg.py    From finta with GNU Lesser General Public License v3.0 5 votes vote down vote up 
def test_wma():
    '''test TA.WVMA'''

    ma = TA.WMA(ohlc, period=20)
    talib_ma = talib.WMA(ohlc['close'], timeperiod=20)

    # assert round(talib_ma[-1], 5) == round(ma.values[-1], 5)
    # assert 1511.96547 == 1497.22193
    pass  # close enough
Example #8
Source File: test_indicator_overlap.py    From pandas-ta with MIT License 5 votes vote down vote up 
def test_wma(self):
        result = pandas_ta.wma(self.close)
        self.assertIsInstance(result, Series)
        self.assertEqual(result.name, 'WMA_10')

        try:
            expected = tal.WMA(self.close, 10)
            pdt.assert_series_equal(result, expected, check_names=False)
        except AssertionError as ae:
            try:
                corr = pandas_ta.utils.df_error_analysis(result, expected, col=CORRELATION)
                self.assertGreater(corr, CORRELATION_THRESHOLD)
            except Exception as ex:
                error_analysis(result, CORRELATION, ex)
Example #9
Source File: talib_indicators.py    From qtpylib with Apache License 2.0 5 votes vote down vote up 
def WMA(data, **kwargs):
    _check_talib_presence()
    prices = _extract_series(data)
    return talib.WMA(prices, **kwargs)


# ---------------------------------------------
# Momentum Indicators
# ---------------------------------------------