# 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 rust_timeseries_generator;
use sliding_features::*;
use rust_timeseries_generator::gaussian_process::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/rust_timeseries_generator](https://www.github.com/MathisWellmann/rust_timeseries_generator)
Note that each run is differently seeded by default.
### 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
Copyright (C) 2020 <MathisWellmann wellmannmathis@gmail.com>
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/>.
