BLD added sinwma indicator and tests

README.md

@@ -109,7 +109,7 @@ help(pd.DataFrame().ta.log_return)
 |:--------:|
 | ![Example MACD](/images/SPY_MACD.png) |
 
-## _Overlap_ (23)
+## _Overlap_ (24)
 
 * _Double Exponential Moving Average_: **dema**
 * _Exponential Moving Average_: **ema**
@@ -128,6 +128,7 @@ help(pd.DataFrame().ta.log_return)
 * _Pascal's Weighted Moving Average_: **pwma**
 * _William's Moving Average_: **rma**
 * _Simple Moving Average_: **sma**
+* _Sine Weighted Moving Average_: **sinwma**
 * _Symmetric Weighted Moving Average_: **swma**
 * _T3 Moving Average_: **t3**
 * _Triple Exponential Moving Average_: **tema**
@@ -229,6 +230,7 @@ Use parameter: cumulative=**True** for cumulative results.
 
 
 # Inspiration
+* TradingView: http://www.tradingview.com
 * Original TA-LIB: http://ta-lib.org/
 * Bukosabino: https://github.com/bukosabino/ta
 

pandas_ta/__init__.py

@@ -56,6 +56,7 @@ from .overlap.midprice import midprice
 from .overlap.ohlc4 import ohlc4
 from .overlap.pwma import pwma
 from .overlap.rma import rma
+from .overlap.sinwma import sinwma
 from .overlap.sma import sma
 from .overlap.swma import swma
 from .overlap.t3 import t3

pandas_ta/core.py

@@ -502,6 +502,13 @@ class AnalysisIndicators(BasePandasObject):
         self._append(result, **kwargs)
         return result
 
+    def sinwma(self, close=None, length=None, offset=None, **kwargs):
+        close = self._get_column(close, 'close')
+        from .overlap.sinwma import sinwma
+        result = sinwma(close=close, length=length, offset=offset, **kwargs)
+        self._append(result, **kwargs)
+        return result
+
     def sma(self, close=None, length=None, offset=None, **kwargs):
         close = self._get_column(close, 'close')
         from .overlap.sma import sma

pandas_ta/overlap/sinwma.py

@@ -0,0 +1,67 @@
+# -*- coding: utf-8 -*-
+from math import pi
+from math import sin
+from pandas import Series
+from ..utils import get_offset, pascals_triangle, verify_series, weights
+
+def sinwma(close, length=None, asc=None, offset=None, **kwargs):
+    """Indicator: Sine Weighted Moving Average (SINWMA) by Everget of TradingView"""
+    # Validate Arguments
+    close = verify_series(close)
+    length = int(length) if length and length > 0 else 14
+    min_periods = int(kwargs['min_periods']) if 'min_periods' in kwargs and kwargs['min_periods'] is not None else length
+    offset = get_offset(offset)
+
+    # Calculate Result
+    sines = Series([sin((i + 1) * pi / (length + 1)) for i in range(0, length)])
+    w = sines / sines.sum()
+
+    sinwma = close.rolling(length, min_periods=length).apply(weights(w), raw=True)
+
+    # Offset
+    if offset != 0:
+        sinwma = sinwma.shift(offset)
+
+    # Name & Category
+    sinwma.name = f"SINWMA_{length}"
+    sinwma.category = 'overlap'
+
+    return sinwma
+
+
+
+sinwma.__doc__ = \
+"""Sine Weighted Moving Average (SWMA)
+
+A weighted average using sine cycles.  The middle term(s) of the average have the highest
+weight(s).
+
+Source:
+    https://www.tradingview.com/script/6MWFvnPO-Sine-Weighted-Moving-Average/
+    Author: Everget (https://www.tradingview.com/u/everget/)
+
+Calculation:
+    Default Inputs:
+        length=10
+
+    def weights(w):
+        def _compute(x):
+            return np.dot(w * x)
+        return _compute
+
+    sines = Series([sin((i + 1) * pi / (length + 1)) for i in range(0, length)])
+    w = sines / sines.sum()
+    SINWMA = close.rolling(length, min_periods=length).apply(weights(w), raw=True)
+
+Args:
+    close (pd.Series): Series of 'close's
+    length (int): It's period.  Default: 10
+    offset (int): How many periods to offset the result.  Default: 0
+
+Kwargs:
+    fillna (value, optional): pd.DataFrame.fillna(value)
+    fill_method (value, optional): Type of fill method
+
+Returns:
+    pd.Series: New feature generated.
+"""

setup.py

@@ -6,7 +6,7 @@ long_description = "An easy to use Python 3 Pandas Extension with 80+ Technical
 setup(
     name ="pandas_ta",
     packages =['pandas_ta', 'pandas_ta.momentum', 'pandas_ta.overlap', 'pandas_ta.performance', 'pandas_ta.statistics', 'pandas_ta.trend', 'pandas_ta.volatility', 'pandas_ta.volume'],
-    version ="0.1.33b",
+    version ="0.1.34b",
     description =long_description,
     long_description =long_description,
     author ="Kevin Johnson",

tests/test_indicator_overlap.py

@@ -218,6 +218,11 @@ class TestOverlap(TestCase):
         self.assertIsInstance(result, Series)
         self.assertEqual(result.name, 'RMA_10')
 
+    def test_sinwma(self):
+        result = pandas_ta.sinwma(self.close)
+        self.assertIsInstance(result, Series)
+        self.assertEqual(result.name, 'SINWMA_14')
+
     def test_sma(self):
         result = pandas_ta.sma(self.close)
         self.assertIsInstance(result, Series)

tests/test_indicator_overlap_ext.py

@@ -93,6 +93,11 @@ class TestOverlapExtension(TestCase):
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(self.data.columns[-1], 'RMA_10')
 
+    def test_sinwma_ext(self):
+        self.data.ta.sinwma(append=True)
+        self.assertIsInstance(self.data, DataFrame)
+        self.assertEqual(self.data.columns[-1], 'SINWMA_14')
+
     def test_sma_ext(self):
         self.data.ta.sma(append=True)
         self.assertIsInstance(self.data, DataFrame)