tensorflow-technical-indicators 0.1.2

Technical Indicators as TensorFlow Graph Functions

tensorflow-technical-indicators

Technical Indicators as TF Graph Functions!

- Compatible with the rest of the tensorflow ecosystem
- Super fast as tensorflow graph code

pip install tensorflow-technical-indicators

(Coverage % is bad because tf graphs are not traced, only the @tf.function)

Usage

import tensorflow_technical_indicators as tfti

# assuming your tensors have dimensions: (time step, features[ohlcv])
# where candles[:, 0] is open, candles[:, 1] high, etc..

candles = [...]
# you can get
c = tfti.features.close(candles)
rsi = tfti.rsi(candles=c, window_size=7, method='ema')

# you can also pass multidimensional tensors with (time step, features)
# where features = open, close
# to calculate some indicator for both open and close
result = tfti.indicator(candles, ..params..)

# in general
# tfti.<indicator>(parameters)
# check the list below to find indicator names

List of Indicators

from tensorflow_technical_indicators import <indicator>

Indicator	Implementation
SMA	simple_moving_average
EMA	exponential_moving_average
RSI	rsi
MACD	macd
Stochastic Oscillator
Bolliger Bands
Fibonacci Retractment
Ichimoku Cloud
Standard Deviation
Average Directional Index
More	To Come

Need more indicators? Open up a pull request or open an issue :).