Merge branch 'pr/106' into development

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,36 @@
+---
+name: Bug report
+about: Create a report to help us improve.
+title: ''
+labels: bug
+assignees: twopirllc
+
+---
+
+**Which version are you running? The lastest version is on Github. Pip is for major releases.**
+```python
+import pandas_ta as ta
+print(ta.version)
+```
+
+**Upgrade.**
+```sh
+$ pip install -U git+https://github.com/twopirllc/pandas-ta
+```
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Provide sample code.
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Screenshots**
+If applicable, add screenshots to help explain your problem.
+
+**Additional context**
+Add any other context about the problem here.
+
+Thanks for using Pandas TA!

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,33 @@
+---
+name: Feature request
+about: Suggest an idea for this project.
+title: ''
+labels: enhancement
+assignees: ''
+
+---
+
+**Which version are you running? The lastest version is Github. Pip is for major releases.**
+```python
+import pandas_ta as ta
+print(ta.version)
+```
+
+**Upgrade.**
+```sh
+$ pip install -U git+https://github.com/twopirllc/pandas-ta
+```
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.
+
+Thanks for using Pandas TA!

.github/ISSUE_TEMPLATE/indicator-request.md

@@ -0,0 +1,33 @@
+---
+name: Indicator Request
+about: Be as detailed as possible with links please.
+title: ''
+labels: enhancement
+assignees: twopirllc
+
+---
+
+**Which version are you running? The lastest version is on Github. Pip is for major releases.**
+```python
+import pandas_ta as ta
+print(ta.version)
+```
+
+**Upgrade.**
+```sh
+$ pip install -U git+https://github.com/twopirllc/pandas-ta
+```
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context, web links, or screenshots about the feature request here.
+
+Thanks for using Pandas TA!

.gitignore

@@ -122,8 +122,8 @@ data/SPY_5min.csv
 data/SPY_1min.csv
 data/SPY_D_adxfish.csv
 data/SPY_D_lbsz.csv
-data/TV_5min.csv
 data/similang-ch.csv
+data/TV_5min.csv
 data/tulip.csv
 
 examples/cache.sqlite
@@ -141,6 +141,7 @@ doc.py
 bt.ipynb
 scratch.ipynb
 ta_extension.ipynb
+scratch.ipynb
 kerasmodeller.ipynb
 Charts.ipynb
 pandas_pips

README.md

@@ -56,10 +56,11 @@ and _Weighted Moving Average_.
 
 
 ## __New Indicators__
-_Squeeze_ (**squeeze**). A Momentum indicator. Both John Carter's TTM **and** Lazybear's TradingView versions are implemented. The default is John Carter's, or ```lazybear=False```. Set ```lazybear=True``` to enable Lazybear's.
+* _Squeeze_ (**squeeze**). A Momentum indicator. Both John Carter's TTM **and** Lazybear's TradingView versions are implemented. The default is John Carter's, or ```lazybear=False```. Set ```lazybear=True``` to enable Lazybear's.
+
 ## __Updated Indicators__
-_Fisher Transform_ **fisher**: Added Fisher's default **ema** signal line. To change the length of the signal line, use the argument: ```signal=5```. Default: 5
-_Fisher Transform_ **fisher** and _Kaufman's Adaptive Moving Average_ **kama**: Fixed a bug where their columns were not added to final DataFrame when using the _strategy_ method.
+* _Fisher Transform_ **fisher**: Added Fisher's default **ema** signal line. To change the length of the signal line, use the argument: ```signal=5```. Default: 5
+* _Fisher Transform_ **fisher** and _Kaufman's Adaptive Moving Average_ **kama**: Fixed a bug where their columns were not added to final DataFrame when using the _strategy_ method.
 
 
 ## What is a Pandas DataFrame Extension?

pandas_ta/core.py

@@ -838,6 +838,15 @@ class AnalysisIndicators(BasePandasObject):
         result = stoch(high=high, low=low, close=close, fast_k=fast_k, slow_k=slow_k, slow_d=slow_d, offset=offset, **kwargs)
         return result
 
+    @finalize
+    def ttm_trend(self, high=None, low=None, close=None, offset=None, length=None, **kwargs):
+        high = self._get_column(high, "high")
+        low = self._get_column(low, "low")
+        close = self._get_column(close, "close")
+
+        result = ttm_trend(high=high, low=low, close=close, length=length, offset=offset, **kwargs)
+        return result
+
     @finalize
     def trix(self, close=None, length=None, signal=None, scalar=None, drift=None, offset=None, **kwargs):
         close = self._get_column(close, "close")
@@ -1588,4 +1597,4 @@ class AnalysisIndicators(BasePandasObject):
         volume = self._get_column(volume, 'volume')
 
         result = vp(close=close, volume=volume, width=width, percent=percent, **kwargs)
-        return result
+        return result

pandas_ta/trend/__init__.py

@@ -12,4 +12,5 @@ from .long_run import long_run
 from .psar import psar
 from .qstick import qstick
 from .short_run import short_run
-from .vortex import vortex
+from .ttm_trend import ttm_trend
+from .vortex import vortex

pandas_ta/trend/ttm_trend.py

@@ -0,0 +1,77 @@
+# -*- coding: utf-8 -*-
+from pandas import DataFrame
+from pandas_ta.utils import get_offset, verify_series
+
+def ttm_trend(high, low, close, length=None, offset=None, **kwargs):
+    """Indicator: TTM Trend"""
+    # Validate arguments
+    high = verify_series(high)
+    low = verify_series(low)
+    close = verify_series(close)
+    length = int(length) if length and length > 0 else 6
+    offset = get_offset(offset)
+
+    # Calculate Result
+    trend_avg = ((high + low)/2)
+    for i in range(1, length):
+        trend_avg = trend_avg + ((high.shift(i) + low.shift(i))/2)
+
+    trend_avg = trend_avg / length
+
+    tm_trend = (close > trend_avg).astype(int)
+    tm_trend.replace(0, -1, inplace=True)
+
+    # Offset
+    if offset != 0:
+        tm_trend = tm_trend.shift(offset)
+
+    # Handle fills
+    if 'fillna' in kwargs:
+        tm_trend.fillna(kwargs['fillna'], inplace=True)
+    if 'fill_method' in kwargs:
+        tm_trend.fillna(method=kwargs['fill_method'], inplace=True)
+
+    # Name and Categorize it
+    tm_trend.name = f"TTM_TRND_{length}"
+    tm_trend.category = "momentum"
+
+    # Prepare DataFrame to return
+    data = {tm_trend.name: tm_trend}
+    df = DataFrame(data)
+    df.name = f"TTMTREND_{length}"
+    df.category = tm_trend.category
+
+    return df
+
+
+
+ttm_trend.__doc__ = \
+"""This indicator is from John Carters book “Mastering the trade” an plots the bars green or red.
+It checks if the price is above or under the average price of the previous 5 bars.
+The indicator should hep you stay in a trade until the colors chance.
+Two bars of the opposite color is the signal to get in or out.
+Sources:
+    https://www.prorealcode.com/prorealtime-indicators/ttm-trend-price/
+Calculation:
+    Default Inputs:
+        length=6
+    averageprice = (((high[5]+low[5])/2)+((high[4]+low[4])/2)+((high[3]+low[3])/2)+((high[2]+low[2])/2)+((high[1]+low[1])/2)+((high[6]+low[6])/2))/6
+    if close > averageprice then
+     drawcandle(open,high,low,close) coloured(0,255,0)
+    endif
+
+    if close < averageprice then
+     drawcandle(open,high,low,close) coloured(255,0,0)
+    endif
+Args:
+    high (pd.Series): Series of 'high's
+    low (pd.Series): Series of 'low's
+    close (pd.Series): Series of 'close's
+    length (int): It's period.  Default: 6
+    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: ttm_trend.
+"""

tests/test_indicator_trend.py

@@ -154,7 +154,12 @@ class TestTrend(TestCase):
         self.assertIsInstance(result, Series)
         self.assertEqual(result.name, "SR_2")
 
+    def test_ttm_trend(self):
+        result = pandas_ta.ttm_trend(self.high, self.low, self.close)
+        self.assertIsInstance(result, DataFrame)
+        self.assertEqual(result.name, "TTMTREND_6")
+
     def test_vortex(self):
         result = pandas_ta.vortex(self.high, self.low, self.close)
         self.assertIsInstance(result, DataFrame)
-        self.assertEqual(result.name, "VTX_14")
+        self.assertEqual(result.name, "VTX_14")

tests/test_indicator_trend_ext.py

@@ -98,6 +98,11 @@ class TestTrendExtension(TestCase):
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(self.data.columns[-1], "SR_2")
 
+    def test_ttm_trend_ext(self):
+        self.data.ta.ttm_trend(append=True)
+        self.assertIsInstance(self.data, DataFrame)
+        self.assertEqual(list(self.data.columns[-1:]), ["TTM_TRND_6"])
+
     def test_vortext_ext(self):
         self.data.ta.vortex(append=True)
         self.assertIsInstance(self.data, DataFrame)