153 lines
4.8 KiB
Markdown
153 lines
4.8 KiB
Markdown
# Simple Squiggle
|
|
|
|
## About
|
|
|
|
|
|
|
|
"Simple Squiggle" is a simple parser that manipulates multiplications and divisions between numbers and lognormal distributions. It uses an extremely restricted subset of [Squiggle](https://github.com/quantified-uncertainty/squiggle)'s syntax, and unlike it, the underlying code is not easily extensible.
|
|
|
|
It may be useful for testing correctness of limited features of the full Squiggle, or for sanity-checking the validity of some Squiggle models.
|
|
|
|
|
|
|
|
## Built with
|
|
|
|
- [Node.js](https://nodejs.org/en/)
|
|
- [Math.js](https://mathjs.org/)
|
|
- [Best Readme template](https://github.com/othneildrew/Best-README-Template/blob/master/README.md)
|
|
|
|
## Getting started
|
|
|
|
### Prerequisites
|
|
|
|
- npm
|
|
- nodejs
|
|
|
|
### Installation
|
|
|
|
#### For command line usage
|
|
|
|
```
|
|
git clone https://github.com/quantified-uncertainty/simple-squiggle.git
|
|
cd simple-squiggle
|
|
## npm install
|
|
```
|
|
|
|
The last line is not necessary, since I'm saving node_packages in the repository.
|
|
|
|
#### For use inside another node program
|
|
|
|
```
|
|
npm install @forecasting/simple-squiggle
|
|
```
|
|
|
|
## Usage
|
|
|
|
### General usage
|
|
|
|
Consider a squiggle model which only uses lognormals:
|
|
|
|
```
|
|
initialPrisonPopulation = 1.8M to 2.5M # Data for 2022 prison population has not yet been published, though this estimate is perhaps too wide.
|
|
reductionInPrisonPopulation = 0.25 to 0.75
|
|
badnessOfPrisonInQALYs = 0.2 to 5 # 80% as good as being alive to 5 times worse than living is good
|
|
accelerationInYears = 5 to 50
|
|
probabilityOfSuccess = 0.01 to 0.1 # 1% to 10%.
|
|
estimateQALYs = leftTruncate(
|
|
initialPrisonPopulation *
|
|
reductionInPrisonPopulation *
|
|
badnessOfPrisonInQALYs *
|
|
accelerationInYears *
|
|
probabilityOfSuccess
|
|
, 0)
|
|
cost = 2B to 20B
|
|
costEffectivenessPerQALY = leftTruncate(cost / estimateQALYs, 0)
|
|
costEffectivenessPerQALY
|
|
```
|
|
|
|
It can be simplified to the following simple squiggle model:
|
|
|
|
```
|
|
( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )
|
|
```
|
|
|
|
I provide both an exportable library and a command line interface (cli).
|
|
|
|
### Command line interface
|
|
|
|
After cloning this repository through github (see installation section), the cli can be run with `npm run cli`, which produces a prompt:
|
|
|
|
```
|
|
> npm run cli
|
|
|
|
Model:
|
|
```
|
|
|
|
After filling in the prompt
|
|
|
|
```
|
|
> npm run cli
|
|
|
|
Model: ( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )
|
|
```
|
|
|
|
the output looks as follows:
|
|
|
|
```
|
|
> npm run cli
|
|
|
|
Model: ( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )
|
|
|
|
= (lognormal(22.57, 0.70)) / ((lognormal(14.57, 0.10)) * (lognormal(-0.84, 0.33)) * (lognormal(0.00, 0.98)) * (lognormal(2.76, 0.70)) * (lognormal(-3.45, 0.70)))
|
|
-> lognormal(22.57, 0.70) / (lognormal(14.57, 0.10) * lognormal(-0.84, 0.33) * lognormal(0.00, 0.98) * lognormal(2.76, 0.70) * lognormal(-3.45, 0.70))
|
|
-> lognormal(22.57, 0.70) / (lognormal(13.73, 0.35) * lognormal(0.00, 0.98) * lognormal(2.76, 0.70) * lognormal(-3.45, 0.70))
|
|
-> lognormal(22.57, 0.70) / (lognormal(13.73, 1.04) * lognormal(2.76, 0.70) * lognormal(-3.45, 0.70))
|
|
-> lognormal(22.57, 0.70) / (lognormal(16.49, 1.25) * lognormal(-3.45, 0.70))
|
|
-> lognormal(22.57, 0.70) / (lognormal(13.04, 1.43))
|
|
-> lognormal(22.57, 0.70) / lognormal(13.04, 1.43)
|
|
-> lognormal(9.53, 1.60)
|
|
|
|
=> lognormal(9.530291704996749, 1.596443005980748)
|
|
( => ~996.6270585961881 to ~190271.4039258926 )
|
|
|
|
----------------------------------------------------
|
|
|
|
```
|
|
|
|
For ease of representation, the intermediary outputs are printed only to two decimal points. But this is just a display decision; the innards of the program work with the full set of decimals.
|
|
|
|
You can also run tests with `npm run test`
|
|
|
|
### Exportable library
|
|
|
|
I also provide an exportable library. After installing it with npm (see installation section), you can call it with:
|
|
|
|
```
|
|
import { transformer } from "@forecasting/simple-squiggle";
|
|
|
|
// Helpers
|
|
let printer = (_) => null;
|
|
let getSimpleSquiggleOutput = (string) => transformer(string, printer);
|
|
|
|
// Model
|
|
let model = "( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )"
|
|
let result = getSimpleSquiggleOutput(model);
|
|
console.log(result); /* [
|
|
'lognormal(-0.3465735902799725, 1.1485521838283161)', // lognormal expression
|
|
'~0.10690936969938292 to ~4.676858552304103' // 90% confidence interval expression
|
|
] */
|
|
|
|
|
|
```
|
|
|
|
## Roadmap
|
|
|
|
I consider this repository to be feature complete. As such, I may tinker with the code which wraps around the core logic, but I don't really intend to add further functionality.
|
|
|
|
- [ ] Make wrapper code less hacky
|
|
- [x] Display final lognormal as a 90% confidence interval as well
|
|
|
|
## License
|
|
|
|
Distributed under the MIT License
|