Fixing bug: hard-coded values

setup.py

@@ -3,7 +3,7 @@
 setup(
     name = 'ta',
     packages = ['ta'],
-    version = '0.5.12',
+    version = '0.5.13',
     description='Technical Analysis Library in Python',
     long_description='It is a Technical Analysis library to financial time series datasets. You can use to do feature engineering. It is builded on Python Pandas library.',
     author = 'Dario Lopez Padial (Bukosabino)',
@@ -15,7 +15,7 @@
         'numpy',
         'pandas',
     ],
-    download_url = 'https://github.com/bukosabino/ta/tarball/0.5.12',
+    download_url = 'https://github.com/bukosabino/ta/tarball/0.5.13',
     keywords = ['technical analysis', 'python3', 'pandas'],
     license='The MIT License (MIT)',
     classifiers = [

ta/momentum.py

@@ -609,10 +609,10 @@ def uo(high, low, close, s=7, m=14, len=28, ws=4.0, wm=2.0, wl=1.0, fillna=False
 
     """
     return UltimateOscillator(
-        high=high, low=low, close=close, s=7, m=14, len=28, ws=4.0, wm=2.0, wl=1.0, fillna=fillna).uo()
+        high=high, low=low, close=close, s=s, m=m, len=len, ws=ws, wm=wm, wl=wl, fillna=fillna).uo()
 
 
-def stoch(high, low, close, n=14, fillna=False):
+def stoch(high, low, close, n=14, d_n=3, fillna=False):
     """Stochastic Oscillator
 
     Developed in the late 1950s by George Lane. The stochastic
@@ -627,13 +627,14 @@ def stoch(high, low, close, n=14, fillna=False):
         low(pandas.Series): dataset 'Low' column.
         close(pandas.Series): dataset 'Close' column.
         n(int): n period.
+        d_n(int): sma period over stoch_k
         fillna(bool): if True, fill nan values.
 
     Returns:
         pandas.Series: New feature generated.
     """
 
-    return StochasticOscillator(high=high, low=low, close=close, n=n, d_n=3, fillna=fillna).stoch()
+    return StochasticOscillator(high=high, low=low, close=close, n=n, d_n=d_n, fillna=fillna).stoch()
 
 
 def stoch_signal(high, low, close, n=14, d_n=3, fillna=False):
@@ -737,7 +738,7 @@ def ao(high, low, s=5, len=34, fillna=False):
     Returns:
         pandas.Series: New feature generated.
     """
-    return AwesomeOscillatorIndicator(high=high, low=low, s=s, len=34, fillna=fillna).ao()
+    return AwesomeOscillatorIndicator(high=high, low=low, s=s, len=len, fillna=fillna).ao()
 
 
 def kama(close, n=10, pow1=2, pow2=30, fillna=False):
@@ -792,4 +793,4 @@ def roc(close, n=12, fillna=False):
         pandas.Series: New feature generated.
 
     """
-    return ROCIndicator(close=close, n=12, fillna=fillna).roc()
+    return ROCIndicator(close=close, n=n, fillna=fillna).roc()

ta/volatility.py

@@ -446,7 +446,7 @@ def keltner_channel_central(high, low, close, n=10, fillna=False):
     Returns:
         pandas.Series: New feature generated.
     """
-    indicator = KeltnerChannel(high=high, low=low, close=close, n=10, fillna=False)
+    indicator = KeltnerChannel(high=high, low=low, close=close, n=n, fillna=False)
     return indicator.keltner_channel_central()
 
 
@@ -467,7 +467,7 @@ def keltner_channel_hband(high, low, close, n=10, fillna=False):
     Returns:
         pandas.Series: New feature generated.
     """
-    indicator = KeltnerChannel(high=high, low=low, close=close, n=10, fillna=False)
+    indicator = KeltnerChannel(high=high, low=low, close=close, n=n, fillna=False)
     return indicator.keltner_channel_hband()
 
 
@@ -488,7 +488,7 @@ def keltner_channel_lband(high, low, close, n=10, fillna=False):
     Returns:
         pandas.Series: New feature generated.
     """
-    indicator = KeltnerChannel(high=high, low=low, close=close, n=10, fillna=False)
+    indicator = KeltnerChannel(high=high, low=low, close=close, n=n, fillna=False)
     return indicator.keltner_channel_lband()
 
 
@@ -510,7 +510,7 @@ def keltner_channel_hband_indicator(high, low, close, n=10, fillna=False):
     Returns:
         pandas.Series: New feature generated.
     """
-    indicator = KeltnerChannel(high=high, low=low, close=close, n=10, fillna=False)
+    indicator = KeltnerChannel(high=high, low=low, close=close, n=n, fillna=False)
     return indicator.keltner_channel_hband_indicator()
 
 
@@ -531,7 +531,7 @@ def keltner_channel_lband_indicator(high, low, close, n=10, fillna=False):
     Returns:
         pandas.Series: New feature generated.
     """
-    indicator = KeltnerChannel(high=high, low=low, close=close, n=10, fillna=False)
+    indicator = KeltnerChannel(high=high, low=low, close=close, n=n, fillna=False)
     return indicator.keltner_channel_lband_indicator()