added Elders Thermometer 90%correlation

pandas_ta/__init__.py

@@ -51,7 +51,7 @@ Category = {
     "trend": ["adx", "amat", "aroon", "chop", "cksp", "decay", "decreasing", "dpo", "increasing", "long_run", "psar", "qstick", "short_run", "ttm_trend", "vortex"],
 
     # Volatility
-    "volatility": ["aberration", "accbands", "atr", "bbands", "donchian", "kc", "massi", "natr", "pdist", "rvi", "true_range", "ui"],
+    "volatility": ["aberration", "accbands", "atr", "bbands", "donchian", "kc", "massi", "natr", "pdist", "rvi", "thermo", "true_range", "ui"],
 
     # Volume, "vp" or "Volume Profile" is unique
     "volume": ["ad", "adosc", "aobv", "cmf", "efi", "eom", "mfi", "nvi", "obv", "pvi", "pvol", "pvt"],

pandas_ta/core.py

@@ -1366,6 +1366,13 @@ class AnalysisIndicators(BasePandasObject):
         result = rvi(high=high, low=low, close=close, length=length, scalar=scalar, refined=refined, thirds=thirds, mamode=mamode, drift=drift, offset=offset, **kwargs)
         return self._post_process(result, **kwargs)
 
+    def thermo(self, long=None, short= None, length=None, mamode=None, drift=None, offset=None, **kwargs):
+        high  = self._get_column(kwargs.pop("high", "high"))
+        low   = self._get_column(kwargs.pop("low", "low"))
+
+        result = thermo(high=high, low=low, long=long, short=short, length=length, mamode=mamode, drift=drift, offset=offset, **kwargs)
+        return self._post_process(result, **kwargs)
+
     def true_range(self, drift=None, offset=None, **kwargs):
         high  = self._get_column(kwargs.pop("high", "high"))
         low   = self._get_column(kwargs.pop("low", "low"))

pandas_ta/volatility/__init__.py

@@ -9,5 +9,6 @@ from .massi import massi
 from .pdist import pdist
 from .natr import natr
 from .rvi import rvi
+from .thermo import thermo
 from .true_range import true_range
 from .ui import ui

pandas_ta/volatility/thermo.py

@@ -0,0 +1,126 @@
+# -*- coding: utf-8 -*-
+import numpy as np
+from pandas import DataFrame, Series
+from pandas_ta.overlap import ema
+from pandas_ta.utils import get_offset, verify_series, get_drift
+
+def thermo(high, low, long=None, short=None, length=None, mamode=None, drift=None, offset=None, **kwargs):
+    """Indicator: Elders Thermometer (THERMO)"""
+    # Validate arguments
+    high = verify_series(high)
+    low = verify_series(low)
+    drift = get_drift(drift)
+    offset = get_offset(offset)
+
+    length = int(length) if length and length > 0 else 20
+    long = float(long) if long and long > 0 else 2
+    short = float(short) if short and short > 0 else 0.5
+    mamode = mamode.lower() if mamode else "ema"
+   
+    asint = kwargs.pop("asint", True)
+    lazybear = kwargs.pop("lazybear", False)
+
+
+    # Calculate Result
+    thermoL = (low.shift(drift) - low).abs()
+    thermoH = (high - high.shift(drift)).abs()
+    if lazybear:
+        thermo = (high < high.shift(drift)) & (low > low.shift(drift))
+        if thermo.any():
+            thermo = thermoL
+            thermo = thermo.where(thermoH < thermoL, thermoH)
+            thermo.index = high.index
+
+        thermoma = ema(thermo,length)
+
+    else:
+        thermo = thermoL
+        thermo = thermo.where(thermoH < thermoL, thermoH)
+        thermo.index = high.index
+
+        thermoma = ema(thermo, length)
+
+    # Create signals
+    thermo_long = thermo < (thermoma * long) # Returns T/F
+    thermo_short = thermo > (thermoma * short) # Returns T/F
+
+    # Binary output, useful for signals
+    if asint:
+        thermo_long = thermo_long.astype(int)  
+        thermo_short = thermo_short.astype(int)
+
+    # Offset
+    if offset != 0:
+        thermo = thermo.shift(offset)
+        thermoma = thermoma.shift(offset)
+
+    # Handle fills
+    if "fillna" in kwargs:
+        thermo.fillna(kwargs["fillna"], inplace=True)
+        thermoma.fillna(kwargs["fillna"], inplace=True)
+    if "fill_method" in kwargs:
+        thermo.fillna(method=kwargs["fill_method"], inplace=True)
+        thermoma.fillna(method=kwargs["fill_method"], inplace=True)
+
+    # Name and Categorize it
+    _props = f"_{length}_{long}_{short}"
+    thermo.name = f"THERMO{_props}"
+    thermoma.name = f"THERMOma{_props}"
+    thermo_long.name = f"THERMOl{_props}"
+    thermo_short.name = f"THERMOs{_props}"
+    
+    thermo.category = thermo_long.category = thermo_short.category = thermoma.category = "volatility"
+
+    # Prepare Dataframe to return
+    data = {thermo.name: thermo, thermoma.name: thermoma, thermo_long.name: thermo_long, thermo_short.name: thermo_short}
+    df = DataFrame(data)
+    df.name = f"THERMO_{length}"
+    df.category = thermo.category
+
+    return df
+
+thermo.__doc__ = \
+"""Elders Thermometer (THERMO)
+
+Elder's Thermometer measures price volatility.
+
+Sources:
+    https://www.motivewave.com/studies/elders_thermometer.htm
+    https://www.tradingview.com/script/HqvTuEMW-Elder-s-Market-Thermometer-LazyBear/
+
+Calculation:
+    Default Inputs:
+    length=20, drift=1, mamode=EMA, long=2 short=0.5
+
+    EMA = Exponential Moving Average
+
+    thermoL = (low.shift(drift) - low).abs()
+    thermoH = (high - high.shift(drift)).abs()
+    thermo = np.where(thermoH > thermoL, thermoH, thermoL)
+
+    thermoma = ema(thermo, length)
+
+    thermo_long = thermo < (thermoma * long) # Returns T/F
+    thermo_short = thermo > (thermoma * short) # Returns T/F
+
+    Binary output
+    thermo_long = thermo_long.astype(int)  
+    thermo_short = thermo_short.astype(int)
+
+Args:
+    high (pd.Series): Series of 'high's
+    low (pd.Series): Series of 'low's
+    long(int): The buy factor
+    short(float): The sell factor
+    length (int): The  period.  Default: 20
+    drift (int): The diff period.   Default: 1
+    mamode (str): Two options: None or "sma".  Default: ema
+    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.DataFrame: thermo, thermoma, thermo_long, thermo_short columns.
+"""

tests/test_ext_indicator_volatility.py

@@ -79,6 +79,11 @@ class TestVolatilityExtension(TestCase):
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(self.data.columns[-1], "RVIt_14")
 
+    def test_thermo_ext(self):
+        self.data.ta.thermo(append=True)
+        self.assertIsInstance(self.data, DataFrame)
+        self.assertEqual(list(self.data.columns[-4:]), ["THERMO_20_2_0.5", "THERMOma_20_2_0.5", "THERMOl_20_2_0.5", "THERMOs_20_2_0.5"])
+
     def test_true_range_ext(self):
         self.data.ta.true_range(append=True)
         self.assertIsInstance(self.data, DataFrame)

tests/test_indicator_volatility.py

@@ -144,6 +144,11 @@ class TestVolatility(TestCase):
         self.assertIsInstance(result, Series)
         self.assertEqual(result.name, "RVIt_14")
 
+    def test_thermo(self):
+        result = pandas_ta.thermo(self.high, self.low)
+        self.assertIsInstance(result, DataFrame)
+        self.assertEqual(result.name, "THERMO_20_2_0.5")
+    
     def test_true_range(self):
         result = pandas_ta.true_range(self.high, self.low, self.close)
         self.assertIsInstance(result, Series)