156 lines
4.9 KiB
Markdown
156 lines
4.9 KiB
Markdown
# Simple Squiggle
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## About
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"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.
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It may be useful for testing correctness of limited features of the full Squiggle, or for sanity-checking the validity of some Squiggle models.
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## Built with
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- [Node.js](https://nodejs.org/en/)
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- [Math.js](https://mathjs.org/)
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- [Best Readme template](https://github.com/othneildrew/Best-README-Template/blob/master/README.md)
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## Getting started
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### Prerequisites
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- npm
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- nodejs
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### Installation
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#### For command line usage
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```
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git clone https://github.com/quantified-uncertainty/simple-squiggle.git
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cd simple-squiggle
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## npm install
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```
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The last line is not necessary, since I'm saving node_packages in the repository.
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#### For use inside another node program
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```
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npm install @forecasting/simple-squiggle
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```
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## Usage
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### General usage
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Consider a squiggle model which only uses lognormals:
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```
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initialPrisonPopulation = 1.8M to 2.5M # Data for 2022 prison population has not yet been published, though this estimate is perhaps too wide.
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reductionInPrisonPopulation = 0.25 to 0.75
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badnessOfPrisonInQALYs = 0.2 to 5 # 80% as good as being alive to 5 times worse than living is good
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accelerationInYears = 5 to 50
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probabilityOfSuccess = 0.01 to 0.1 # 1% to 10%.
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estimateQALYs = leftTruncate(
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initialPrisonPopulation *
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reductionInPrisonPopulation *
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badnessOfPrisonInQALYs *
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accelerationInYears *
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probabilityOfSuccess
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, 0)
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cost = 2B to 20B
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costEffectivenessPerQALY = leftTruncate(cost / estimateQALYs, 0)
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costEffectivenessPerQALY
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```
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It can be simplified to the following simple squiggle model:
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```
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( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )
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```
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I provide both an exportable library and a command line interface (cli).
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### Command line interface
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After cloning this repository through github (see installation section), the cli can be run with `npm run cli`, which produces a prompt:
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```
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> npm run cli
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Model:
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```
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After filling in the prompt
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```
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> npm run cli
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Model: ( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )
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```
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the output looks as follows:
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```
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> npm run cli
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Model: ( 2000000000 to 20000000000 ) / ( (1800000 to 2500000) * (0.25 to 0.75) * (0.2 to 5) * (5 to 50) * (0.01 to 0.1) )
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= (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)))
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-> 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))
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-> 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))
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-> lognormal(22.57, 0.70) / (lognormal(13.73, 1.04) * lognormal(2.76, 0.70) * lognormal(-3.45, 0.70))
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-> lognormal(22.57, 0.70) / (lognormal(16.49, 1.25) * lognormal(-3.45, 0.70))
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-> lognormal(22.57, 0.70) / (lognormal(13.04, 1.43))
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-> lognormal(22.57, 0.70) / lognormal(13.04, 1.43)
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-> lognormal(9.53, 1.60)
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=> lognormal(9.530291704996749, 1.596443005980748)
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( => ~996.6270585961881 to ~190271.4039258926 )
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----------------------------------------------------
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```
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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.
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You can also run tests with `npm run test`
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### Exportable library
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I also provide an exportable library. After installing it with npm (see installation section), you can call it with:
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```
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import { transformer } from "@forecasting/simple-squiggle";
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// Helpers
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let printer = (_) => null;
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let getSimpleSquiggleOutput = (string) => transformer(string, printer);
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// Model
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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) )"
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let result = getSimpleSquiggleOutput(model);
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console.log(result); /* {
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squiggleString: 'lognormal(-0.3465735902799725, 1.1485521838283161)',
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lognormalParameters: [ -0.3465735902799725, 1.1485521838283161 ],
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shortGuesstimateString: '0.11 to 4.7',
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array90CI: [ 0.10690936969938292, 4.676858552304103 ]
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}
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*/
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```
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## Roadmap
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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.
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- [ ] Make wrapper code less hacky
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- [x] Display final lognormal as a 90% confidence interval as well
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## License
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Distributed under the MIT License
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