Sliding Features

Modular sliding window with various signal processing functions and technical indicators including Normalization. Can be used for building low latency real-time trading systems. Values in window are updated at each time step. A View defines the function which processes the incoming values and provides and output value. Views can easily be added by implementing the View Trait which requires two functions: - update(&mut self, val: f64) - last(&self) -> f64

The Views can be parameterized as desired when created with new() function. Add Views to SlidingWindow by calling register_view(). SlidingWindows last() function returns a vector of all the latest observations of all views that are currently registered.

Example

```rust extern crate rusttimeseriesgenerator;

use slidingfeatures::*; use rusttimeseriesgenerator::gaussianprocess::gen;

fn main() { // new sliding window let mut sf = SlidingWindow::new();

let window_len: usize = 16
// register some normalized indicators so output range is [-1.0, 1.0] 
sf.register_view(Box::new(Normalizer::new(Box::new(RSI::new(window_len)), window_len)));
sf.register_view(Box::new(Normalizer::new(Box::new(ROC::new(window_len)), window_len)));
// register some variance stabilized indicators
sf.register_view(Box::new(VST::new(Box::new(TrendFlex::new(window_len)))));
sf.register_view(Box::new(VST::new(Box::new(CenterOfGravity::new(window_len)))));
sf.register_view(Box::new(VST::new(Box::new(CyberCycle::new(window_len)))));

// generate dummy values
let vals = gen(1024, 100.0);
for i in 0..vals.len() {
    // update all the sliding window features with a given value
    sf.update(vals[i]);
    // get the latest values from sliding window
    let last: Vec<f64> = sf.last();  
    println!("last: {:?}", last);
}

} ```

See examples folder. Run the examples using cargo run --example simple cargo run --example multiple cargo run --example multiple_normalized

Views

A View defines the function which processes value updates. They currently include: * Echo * Technical Indicators * Center of Gravity * Cyber Cycle * Laguerre RSI * Laguerre Filter * ReFlex * TrendFlex * ROC * RSI * Correlation Trend Indicator (CTI) * Normalization / variance / mean standardization * Normalizer * Variance Stabilizing Transform (VST) * Variance Stabilizing Centering Transform (VSCT) * Moving Averages * ALMA (Arnaux Legoux Moving Average)

Entropy (acts on a bit stream, thus does not impl View trait)

Images

Underlying data synthetically generated by MathisWellmann/rusttimeseriesgenerator Note that each run is differently seeded by default.

laguerrefilter centerofgravity centerofgravitynormalized cybercycle laguerrersi reflex trendflex roc rsi alma cti

TODOs:

SMA
EMA
FRAMA
MAMA
FAMA
Stochastic
Super Smoother
Zero Lag
gaussian filter
and so much more...

Contributing

If you have a sliding window function or indicator which you would like to integrate, feel free to create a pull request. Any help is highly appreciated. Let's build the greatest sliding window library together :handshake:

License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.

GNU AGPLv3