Merge branch 'pr/246' into development

README.md

@@ -601,6 +601,7 @@ help(ta.yf)
     * Default is John Carter's. Enable Lazybear's with ```lazybear=True```
 * _Stochastic Oscillator_: **stoch**
 * _Stochastic RSI_: **stochrsi**
+* _TD Sequential_: **td**
 * _Trix_: **trix**
 * _True strength index_: **tsi**
 * _Ultimate Oscillator_: **uo**

pandas_ta/core.py

@@ -1043,6 +1043,12 @@ def stochrsi(self, length=None, rsi_length=None, k=None, d=None, offset=None, **
         result = stochrsi(high=high, low=low, close=close, length=length, rsi_length=rsi_length, k=k, d=d, offset=offset, **kwargs)
         return self._post_process(result, **kwargs)
 
+    def td(self, offset=None, show_all=True, **kwargs):
+        close = self._get_column(kwargs.pop("close", "close"))
+
+        result = td(close=close, offset=offset, show_all=show_all, **kwargs)
+        return self._post_process(result, **kwargs)
+
     def trix(self, length=None, signal=None, scalar=None, drift=None, offset=None, **kwargs):
         close = self._get_column(kwargs.pop("close", "close"))
         result = trix(close=close, length=length, signal=signal, scalar=scalar, drift=drift, offset=offset, **kwargs)

pandas_ta/momentum/__init__.py

@@ -31,6 +31,7 @@
 from .squeeze import squeeze
 from .stoch import stoch
 from .stochrsi import stochrsi
+from .td import td
 from .trix import trix
 from .tsi import tsi
 from .uo import uo

pandas_ta/momentum/td.py

@@ -0,0 +1,67 @@
+# -*- coding: utf-8 -*-
+import numpy as np
+from pandas import DataFrame, Series
+from pandas_ta.utils import get_offset, verify_series
+
+def true_sequence_count(s):
+    index = s.where(s == False).last_valid_index()
+
+    if index is None:
+        return s.count()
+    else:
+        s = s[s.index > index]
+        return s.count()
+
+def calc_td(close, direction, show_all):
+    td_bool = close.diff(4) > 0 if direction=='up' else close.diff(4) < 0
+    td_num = np.where(td_bool, td_bool.rolling(13, min_periods=0).apply(true_sequence_count), 0)
+    td_num = Series(td_num)
+
+    if show_all:
+        td_num = td_num.mask(td_num == 0)
+    else:
+        td_num = td_num.mask(~td_num.between(6,9))
+
+    return td_num       
+
+def td(close, offset=None, show_all=True, **kwargs):
+    up = calc_td(close, 'up', show_all)
+    down = calc_td(close, 'down', show_all)
+    df = DataFrame({'TD_up': up, 'TD_down': down})
+
+     # Offset
+    if offset and offset != 0:
+        df = df.shift(offset)
+
+    if "fillna" in kwargs:
+        df.fillna(kwargs["fillna"], inplace=True)
+
+    # Name & Category
+    df.name = "TD"
+    df.category = "momentum"
+
+    return df
+
+td.__doc__ = \
+"""TD Sequential (TD)
+
+TD Sequential indicator.
+
+Sources:
+    https://tradetrekker.wordpress.com/tdsequential/
+
+Calculation:
+    compare current close price with 4 days ago price, up to 13 days.
+    for the consecutive ascending or descending price sequence, display 6th to 9th day value.
+
+Args:
+    close (pd.Series): Series of 'close's
+    offset (int): How many periods to offset the result. Default: 0
+    show_all (bool): default True, show 1 - 13. If set to false, only show 6 - 9
+
+Kwargs:
+    fillna (value, optional): pd.DataFrame.fillna(value)
+
+Returns:
+    pd.DataFrame: New feature generated.
+"""

tests/test_ext_indicator_momentum.py

@@ -207,6 +207,11 @@ def test_stochrsi_ext(self):
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(list(self.data.columns[-2:]), ["STOCHRSIk_14_14_3_3", "STOCHRSId_14_14_3_3"])
 
+    def test_td_ext(self):
+        self.data.ta.td(append=True)
+        self.assertIsInstance(self.data, DataFrame)
+        self.assertEqual(list(self.data.columns[-2:]), ["TD_up", "TD_down"])
+
     def test_trix_ext(self):
         self.data.ta.trix(append=True)
         self.assertIsInstance(self.data, DataFrame)

tests/test_indicator_momentum.py

@@ -362,6 +362,12 @@ def test_stochrsi(self):
         self.assertIsInstance(result, DataFrame)
         self.assertEqual(result.name, "STOCHRSI_14_14_3_3")
 
+    def test_td(self):
+        # TD Sequential
+        result = pandas_ta.td(self.close)
+        self.assertIsInstance(result, DataFrame)
+        self.assertEqual(result.name, "TD")
+
     def test_trix(self):
         result = pandas_ta.trix(self.close)
         self.assertIsInstance(result, DataFrame)