API at a glance
The tti.indicators package implements 62 Trading Technical indicators. The constructor for each indicator is like the one below:
<indicator_object>(input_data, **kwargs, fill_missing_values=True)
input_data (pandas.DataFrame): Index is of DateTimeIndex type, and contains some or all of the following columns, depending the indicator (high, low, open, close, volume)
fill_missing_values (bool): If set to True, missing values in the input data are being filled.
**kwargs (args or None): Additional input arguments which required for some indicators.
An example of a valid input_data pandas.DataFrame is the one below:
date open high low close volume
2012-09-12 140.92 141.28 140.14 140.41 488800
2012-09-11 142.57 142.57 140.53 140.95 443500
2012-09-10 143.27 144.08 141.22 141.25 1000800
2012-09-07 144 144.92 143.81 144.36 340100
... ... ... ... ... ...
Each indicator provides an implementation for the below methods:
getTiData(): Returns a pandas.DataFrame object with the calculated indicator.
getTiValue(date=None): Returns a list(numeric) with the indicator values of the given date. If date is None, then the latest values are being returned.
getTiSignal(): Returns a tuple (string, integer), the Trading signal for the calculated indicator. Possible values are ('hold', 0), ('buy', -1), ('sell', 1).
getTiGraph(): Returns a matplotlib.pyplot object with a graph, customized for each indicator.
getTiSimulation(close_values, max_exposure=None, short_exposure_factor=1.5): Returns a pandas.DataFrame, a dictionary object and a matplotlib.pyplot graph with details about the executed simulation.