Merge branch 'develop' into Umur-develop

This commit is contained in:
Umur Ozkul 2022-04-29 18:26:09 +02:00
commit b8c06e0846
48 changed files with 1820 additions and 1211 deletions

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@ -1,12 +1,22 @@
# Squiggle # Squiggle
[![Packages check](https://github.com/quantified-uncertainty/squiggle/actions/workflows/ci.yml/badge.svg)](https://github.com/quantified-uncertainty/squiggle/actions/workflows/ci.yml) [![Packages check](https://github.com/quantified-uncertainty/squiggle/actions/workflows/ci.yml/badge.svg)](https://github.com/quantified-uncertainty/squiggle/actions/workflows/ci.yml)
[![npm version](https://badge.fury.io/js/@quri%2Fsquiggle-lang.svg)](https://www.npmjs.com/package/@quri/squiggle-lang) [![npm version - lang](https://badge.fury.io/js/@quri%2Fsquiggle-lang.svg)](https://www.npmjs.com/package/@quri/squiggle-lang)
[![npm version](https://badge.fury.io/js/@quri%2Fsquiggle-components.svg)](https://www.npmjs.com/package/@quri/squiggle-components) [![npm version - components](https://badge.fury.io/js/@quri%2Fsquiggle-components.svg)](https://www.npmjs.com/package/@quri/squiggle-components)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/quantified-uncertainty/squiggle/blob/develop/LICENSE) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/quantified-uncertainty/squiggle/blob/develop/LICENSE)
[![codecov](https://codecov.io/gh/quantified-uncertainty/squiggle/branch/develop/graph/badge.svg?token=QRLBL5CQ7C)](https://codecov.io/gh/quantified-uncertainty/squiggle) [![codecov](https://codecov.io/gh/quantified-uncertainty/squiggle/branch/develop/graph/badge.svg?token=QRLBL5CQ7C)](https://codecov.io/gh/quantified-uncertainty/squiggle)
This is an experimental DSL/language for making probabilistic estimates. The full story can be found [here](https://www.lesswrong.com/s/rDe8QE5NvXcZYzgZ3). _An estimation language_.
## Get started
- [Gallery](https://www.squiggle-language.com/docs/Discussions/Gallery)
- [Squiggle playground](https://squiggle-language.com/playground)
- [Language basics](https://www.squiggle-language.com/docs/Features/Language)
- [Squiggle functions source of truth](https://www.squiggle-language.com/docs/Features/Functions)
- [Known bugs](https://www.squiggle-language.com/docs/Discussions/Bugs)
- [Original lesswrong sequence](https://www.lesswrong.com/s/rDe8QE5NvXcZYzgZ3)
- [Author your squiggle models as Observable notebooks](https://observablehq.com/@hazelfire/squiggle)
## Our deployments ## Our deployments
@ -27,7 +37,7 @@ the packages can be found in `packages`.
- `@quri/squiggle-components` in `packages/components` contains React components that - `@quri/squiggle-components` in `packages/components` contains React components that
can be passed squiggle strings as props, and return a presentation of the result can be passed squiggle strings as props, and return a presentation of the result
of the calculation. of the calculation.
- `@quri/squiggle-website` in `packages/website` The main descriptive website for squiggle, - `packages/website` is the main descriptive website for squiggle,
it is hosted at `squiggle-language.com`. it is hosted at `squiggle-language.com`.
The playground depends on the components library which then depends on the language. This means that if you wish to work on the components library, you will need to build (no need to bundle) the language, and as of this writing playground doesn't really work. The playground depends on the components library which then depends on the language. This means that if you wish to work on the components library, you will need to build (no need to bundle) the language, and as of this writing playground doesn't really work.

20
examples/decay.squiggle Normal file
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# The following code was provided by Nuño Sempere, it comes directly from the post https://www.lesswrong.com/s/rDe8QE5NvXcZYzgZ3/p/j8o6sgRerE3tqNWdj
## Initial setup
yearly_probability_max = 0.95
yearly_probability_min = 0.66
period_probability_function(epsilon, yearly_probability) = 1 - (1 - yearly_probability) ^ (1 / epsilon)
probability_decayed(t, time_periods, period_probability) = 1 - (1 - period_probability) ^ (time_periods - t)
## Monthly decomposition
months_in_a_year=12
monthly_probability_min = period_probability_function(months_in_a_year, yearly_probability_min)
monthly_probability_max = period_probability_function(months_in_a_year, yearly_probability_max)
probability_decayed_monthly_min(t) = probability_decayed(t, months_in_a_year, monthly_probability_min)
probability_decayed_monthly_max(t) = probability_decayed(t, months_in_a_year, monthly_probability_max)
probability_decayed_monthly(t) = probability_decayed_monthly_min(t) to probability_decayed_monthly_max(t)
probability_decayed_monthly
## probability_decayed_monthly(6)
## mean(probability_decayed_monthly(6))

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@ -0,0 +1,38 @@
# This is a cost effectiveness analysis of givedirectly, originally done by givewell, and translated into Squiggle by Sam Nolan
donation_size = 10000
proportion_of_funding_available = beta(10, 2)
total_funding_available = donation_size * proportion_of_funding_available
household_size = 3.7 to 5.7
size_of_transfer = 800 to 1200
size_of_transfer_per_person = size_of_transfer / household_size
portion_invested = 0.3 to 0.5
amount_invested = portion_invested * size_of_transfer_per_person
amount_consumed = (1 - portion_invested) * size_of_transfer_per_person
return_on_investment = 0.08 to 0.12
increase_in_consumption_from_investments = return_on_investment * amount_invested
baseline_consumption = 200 to 350
log_increase_in_consumption = log(amount_consumed + baseline_consumption) + log(baseline_consumption)
log_increase_in_consumption_from_investment = log(increase_in_consumption_from_investments + baseline_consumption) + log(baseline_consumption)
investment_duration = 8 to 12
discount_rate = beta(1.004, 20)
present_value_excluding_last_year = log_increase_in_consumption_from_investment * (1 - (1 + discount_rate) ^ (-investment_duration)) / (log(1 + discount_rate))
percent_of_investment_returned = 0.15 to 0.25
pv_consumption_last_year = (log(baseline_consumption + amount_invested * (return_on_investment + percent_of_investment_returned)) - log(baseline_consumption)) / (1 + discount_rate)^investment_duration
total_pv_of_cash_transfer = pv_consumption_last_year + present_value_excluding_last_year + log_increase_in_consumption
discount_negative_spoiler = 0.03 to 0.07
value_discounting_spoiler = discount_negative_spoiler * total_pv_of_cash_transfer
consumption_increase_per_household = value_discounting_spoiler * household_size
amount_of_transfers_made = total_funding_available / size_of_transfer
total_increase_in_ln_consumption = amount_of_transfers_made * consumption_increase_per_household
total_increase_in_ln_consumption

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@ -0,0 +1,3 @@
xY1 = 99
aBa3 = xY1 * 2 + 1
aBa3 * xY1 + aBa3

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@ -1,8 +1,26 @@
[![npm version](https://badge.fury.io/js/@quri%2Fsquiggle-components.svg)](https://www.npmjs.com/package/@quri/squiggle-components)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/quantified-uncertainty/squiggle/blob/develop/LICENSE)
# Squiggle Components # Squiggle Components
This package contains all the components for squiggle. These can be used either as a library or hosted as a [storybook](https://storybook.js.org/). This package contains all the components for squiggle. These can be used either as a library or hosted as a [storybook](https://storybook.js.org/).
# Build for development # Usage in a `react` project
For example, in a fresh `create-react-app` project
```sh
yarn add @quri/squiggle-components
```
Add to `App.js`:
```jsx
import { SquiggleEditor } from "@quri/squiggle-components";
<SquiggleEditor initialSquiggleString="x = beta(3, 10); x + 20" />;
```
# Build storybook for development
We assume that you had run `yarn` at monorepo level, installing dependencies. We assume that you had run `yarn` at monorepo level, installing dependencies.
@ -24,6 +42,5 @@ yarn start
And build artefacts for production, And build artefacts for production,
```sh ```sh
yarn bundle # builds components library
yarn build # builds storybook app yarn build # builds storybook app
``` ```

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@ -1,12 +1,18 @@
{ {
"name": "@quri/squiggle-components", "name": "@quri/squiggle-components",
"version": "0.2.9", "version": "0.2.14",
"licence": "MIT", "license": "MIT",
"dependencies": { "dependencies": {
"antd": "^4.20.1",
"react-ace": "10.1.0", "react-ace": "10.1.0",
"@quri/squiggle-lang": "^0.2.7",
"react-dom": "^18.1.0", "react-dom": "^18.1.0",
"vega": "^5.22.1",
"vega-embed": "^6.20.6",
"vega-lite": "^5.2.0",
"react-vega": "^7.5.0",
"react": "^18.1.0",
"@react-hook/size": "^2.1.2", "@react-hook/size": "^2.1.2",
"lodash": "^4.17.21",
"styled-components": "^5.3.5" "styled-components": "^5.3.5"
}, },
"devDependencies": { "devDependencies": {
@ -26,31 +32,25 @@
"webpack": "^5.72.0", "webpack": "^5.72.0",
"webpack-cli": "^4.9.2", "webpack-cli": "^4.9.2",
"webpack-dev-server": "^4.8.1", "webpack-dev-server": "^4.8.1",
"@quri/squiggle-lang": "0.2.5",
"@testing-library/jest-dom": "^5.16.4", "@testing-library/jest-dom": "^5.16.4",
"@testing-library/react": "^13.1.1", "@testing-library/react": "^13.1.1",
"@testing-library/user-event": "^14.1.1", "@testing-library/user-event": "^14.1.1",
"@types/jest": "^27.4.0", "@types/jest": "^27.4.0",
"web-vitals": "^2.1.4",
"@types/lodash": "^4.14.182", "@types/lodash": "^4.14.182",
"@types/node": "^17.0.29", "@types/node": "^17.0.29",
"@types/react": "^18.0.3", "@types/react": "^18.0.3",
"@types/react-dom": "^18.0.2", "@types/react-dom": "^18.0.2",
"cross-env": "^7.0.3", "cross-env": "^7.0.3",
"lodash": "^4.17.21",
"react": "^18.1.0",
"react-scripts": "5.0.1", "react-scripts": "5.0.1",
"react-vega": "^7.5.0",
"tsconfig-paths-webpack-plugin": "^3.5.2", "tsconfig-paths-webpack-plugin": "^3.5.2",
"typescript": "^4.6.3", "typescript": "^4.6.3",
"vega": "^5.22.1",
"vega-embed": "^6.20.6",
"vega-lite": "^5.2.0",
"web-vitals": "^2.1.4",
"webpack-cli": "^4.9.2" "webpack-cli": "^4.9.2"
}, },
"scripts": { "scripts": {
"start": "cross-env REACT_APP_FAST_REFRESH=false && start-storybook -p 6006 -s public", "start": "cross-env REACT_APP_FAST_REFRESH=false && start-storybook -p 6006 -s public",
"build": "tsc -b && build-storybook -s public", "build": "tsc -b && build-storybook -s public",
"build:package": "tsc -b",
"bundle": "webpack", "bundle": "webpack",
"all": "yarn bundle && yarn build", "all": "yarn bundle && yarn build",
"lint": "prettier --check .", "lint": "prettier --check .",
@ -88,6 +88,7 @@
"@types/react": "17.0.43" "@types/react": "17.0.43"
}, },
"source": "./src/index.ts", "source": "./src/index.ts",
"main": "dist/bundle.js", "browser": "dist/bundle.js",
"main": "dist/src/index.js",
"types": "dist/src/index.d.ts" "types": "dist/src/index.d.ts"
} }

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@ -6,6 +6,7 @@ import { distributionErrorToString } from "@quri/squiggle-lang";
import { createClassFromSpec } from "react-vega"; import { createClassFromSpec } from "react-vega";
import * as chartSpecification from "../vega-specs/spec-distributions.json"; import * as chartSpecification from "../vega-specs/spec-distributions.json";
import { ErrorBox } from "./ErrorBox"; import { ErrorBox } from "./ErrorBox";
import styled from "styled-components";
let SquiggleVegaChart = createClassFromSpec({ let SquiggleVegaChart = createClassFromSpec({
spec: chartSpecification as Spec, spec: chartSpecification as Spec,
@ -24,19 +25,21 @@ export const DistributionChart: React.FC<DistributionChartProps> = ({
}: DistributionChartProps) => { }: DistributionChartProps) => {
let shape = distribution.pointSet(); let shape = distribution.pointSet();
if (shape.tag === "Ok") { if (shape.tag === "Ok") {
return ( let widthProp = width ? width - 20 : undefined;
var result = (
<SquiggleVegaChart <SquiggleVegaChart
data={{ con: shape.value.continuous, dis: shape.value.discrete }} data={{ con: shape.value.continuous, dis: shape.value.discrete }}
width={width - 20} width={widthProp}
height={height} height={height}
actions={false} actions={false}
/> />
); );
} else { } else {
return ( var result = (
<ErrorBox heading="Distribution Error"> <ErrorBox heading="Distribution Error">
{distributionErrorToString(shape.value)} {distributionErrorToString(shape.value)}
</ErrorBox> </ErrorBox>
); );
} }
return result;
}; };

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@ -3,10 +3,12 @@ import _ from "lodash";
import styled from "styled-components"; import styled from "styled-components";
import { import {
run, run,
runPartial,
errorValueToString, errorValueToString,
squiggleExpression, squiggleExpression,
bindings,
samplingParams,
} from "@quri/squiggle-lang"; } from "@quri/squiggle-lang";
import type { samplingParams } from "@quri/squiggle-lang";
import { NumberShower } from "./NumberShower"; import { NumberShower } from "./NumberShower";
import { DistributionChart } from "./DistributionChart"; import { DistributionChart } from "./DistributionChart";
import { ErrorBox } from "./ErrorBox"; import { ErrorBox } from "./ErrorBox";
@ -44,6 +46,8 @@ export const VariableBox: React.FC<{
); );
}; };
let RecordKeyHeader = styled.h3``;
export interface SquiggleItemProps { export interface SquiggleItemProps {
/** The input string for squiggle */ /** The input string for squiggle */
expression: squiggleExpression; expression: squiggleExpression;
@ -104,6 +108,17 @@ const SquiggleItem: React.FC<SquiggleItemProps> = ({
))} ))}
</VariableBox> </VariableBox>
); );
case "record":
return (
<VariableBox heading="Record">
{Object.entries(expression.value).map(([key, r]) => (
<>
<RecordKeyHeader>{key}</RecordKeyHeader>
<SquiggleItem expression={r} width={width - 20} height={50} />
</>
))}
</VariableBox>
);
default: default:
return ( return (
<ErrorBox heading="No Viewer"> <ErrorBox heading="No Viewer">
@ -135,40 +150,43 @@ export interface SquiggleChartProps {
/** CSS width of the element */ /** CSS width of the element */
width?: number; width?: number;
height?: number; height?: number;
/** Bindings of previous variables declared */
bindings?: bindings;
} }
const ChartWrapper = styled.div`
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
"Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji",
"Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji";
`;
export const SquiggleChart: React.FC<SquiggleChartProps> = ({ export const SquiggleChart: React.FC<SquiggleChartProps> = ({
squiggleString = "", squiggleString = "",
sampleCount = 1000, sampleCount = 1000,
outputXYPoints = 1000, outputXYPoints = 1000,
onChange = () => {}, onChange = () => {},
height = 60, height = 60,
bindings = {},
width = NaN, width = NaN,
}: SquiggleChartProps) => { }: SquiggleChartProps) => {
const target = React.useRef(null);
const [componentWidth] = useSize(target);
// I would have wanted to just use componentWidth, but this created infinite loops with SquiggleChart.stories.
//So you can manually add a width, as an escape hatch.
let _width = width || componentWidth;
let samplingInputs: samplingParams = { let samplingInputs: samplingParams = {
sampleCount: sampleCount, sampleCount: sampleCount,
xyPointLength: outputXYPoints, xyPointLength: outputXYPoints,
}; };
let expressionResult = run(squiggleString, samplingInputs); let expressionResult = run(squiggleString, bindings, samplingInputs);
let internal: JSX.Element; let internal: JSX.Element;
if (expressionResult.tag === "Ok") { if (expressionResult.tag === "Ok") {
let expression = expressionResult.value; let expression = expressionResult.value;
onChange(expression); onChange(expression);
internal = ( internal = (
<SquiggleItem expression={expression} width={_width} height={height} /> <SquiggleItem expression={expression} width={width} height={height} />
); );
} else { } else {
// At this point, we came across an error. What was our error?
internal = ( internal = (
<ErrorBox heading={"Parse Error"}> <ErrorBox heading={"Parse Error"}>
{errorValueToString(expressionResult.value)} {errorValueToString(expressionResult.value)}
</ErrorBox> </ErrorBox>
); );
} }
return <div ref={target}>{internal}</div>; return <ChartWrapper>{internal}</ChartWrapper>;
}; };

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@ -3,7 +3,9 @@ import * as ReactDOM from "react-dom";
import { SquiggleChart } from "./SquiggleChart"; import { SquiggleChart } from "./SquiggleChart";
import { CodeEditor } from "./CodeEditor"; import { CodeEditor } from "./CodeEditor";
import styled from "styled-components"; import styled from "styled-components";
import type { squiggleExpression } from "@quri/squiggle-lang"; import type { squiggleExpression, bindings } from "@quri/squiggle-lang";
import { runPartial, errorValueToString } from "@quri/squiggle-lang";
import { ErrorBox } from "./ErrorBox";
export interface SquiggleEditorProps { export interface SquiggleEditorProps {
/** The input string for squiggle */ /** The input string for squiggle */
@ -26,6 +28,8 @@ export interface SquiggleEditorProps {
onChange?(expr: squiggleExpression): void; onChange?(expr: squiggleExpression): void;
/** The width of the element */ /** The width of the element */
width: number; width: number;
/** Previous variable declarations */
bindings: bindings;
} }
const Input = styled.div` const Input = styled.div`
@ -46,6 +50,7 @@ export let SquiggleEditor: React.FC<SquiggleEditorProps> = ({
diagramCount, diagramCount,
onChange, onChange,
environment, environment,
bindings = {},
}: SquiggleEditorProps) => { }: SquiggleEditorProps) => {
let [expression, setExpression] = React.useState(initialSquiggleString); let [expression, setExpression] = React.useState(initialSquiggleString);
return ( return (
@ -71,6 +76,7 @@ export let SquiggleEditor: React.FC<SquiggleEditorProps> = ({
diagramCount={diagramCount} diagramCount={diagramCount}
environment={environment} environment={environment}
onChange={onChange} onChange={onChange}
bindings={bindings}
/> />
</div> </div>
); );
@ -107,3 +113,76 @@ export function renderSquiggleEditorToDom(props: SquiggleEditorProps) {
); );
return parent; return parent;
} }
export interface SquigglePartialProps {
/** The input string for squiggle */
initialSquiggleString?: string;
/** If the output requires monte carlo sampling, the amount of samples */
sampleCount?: number;
/** The amount of points returned to draw the distribution */
outputXYPoints?: number;
kernelWidth?: number;
pointDistLength?: number;
/** If the result is a function, where the function starts */
diagramStart?: number;
/** If the result is a function, where the function ends */
diagramStop?: number;
/** If the result is a function, how many points along the function it samples */
diagramCount?: number;
/** when the environment changes. Used again for notebook magic*/
onChange?(expr: bindings): void;
/** The width of the element */
width: number;
/** Previously declared variables */
bindings: bindings;
}
export let SquigglePartial: React.FC<SquigglePartialProps> = ({
initialSquiggleString = "",
onChange,
bindings,
}: SquigglePartialProps) => {
let [expression, setExpression] = React.useState(initialSquiggleString);
let squiggleResult = runPartial(expression, bindings);
if (squiggleResult.tag == "Ok") {
if (onChange) onChange(squiggleResult.value);
}
return (
<div>
<Input>
<CodeEditor
value={expression}
onChange={setExpression}
oneLine={true}
showGutter={false}
height={20}
/>
</Input>
{squiggleResult.tag == "Error" ? (
<ErrorBox heading="Error">
{errorValueToString(squiggleResult.value)}
</ErrorBox>
) : (
<></>
)}
</div>
);
};
export function renderSquigglePartialToDom(props: SquigglePartialProps) {
let parent = document.createElement("div");
ReactDOM.render(
<SquigglePartial
{...props}
onChange={(bindings) => {
// @ts-ignore
parent.value = bindings;
parent.dispatchEvent(new CustomEvent("input"));
if (props.onChange) props.onChange(bindings);
}}
/>,
parent
);
return parent;
}

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@ -1,11 +1,9 @@
import _ from "lodash"; import _ from "lodash";
import React, { FC, useState } from "react"; import React, { FC, ReactElement, useState } from "react";
import ReactDOM from "react-dom"; import ReactDOM from "react-dom";
import { SquiggleChart } from "./SquiggleChart"; import { SquiggleChart } from "./SquiggleChart";
import CodeEditor from "./CodeEditor"; import CodeEditor from "./CodeEditor";
import { Form, Input, Row, Col } from "antd";
import styled from "styled-components"; import styled from "styled-components";
import "antd/dist/antd.css";
interface FieldFloatProps { interface FieldFloatProps {
label: string; label: string;
@ -14,10 +12,19 @@ interface FieldFloatProps {
onChange: (value: number) => void; onChange: (value: number) => void;
} }
const Input = styled.input``;
const FormItem = (props: { label: string; children: ReactElement }) => (
<div>
<label>{props.label}</label>
{props.children}
</div>
);
function FieldFloat(Props: FieldFloatProps) { function FieldFloat(Props: FieldFloatProps) {
let [contents, setContents] = useState(Props.value + ""); let [contents, setContents] = useState(Props.value + "");
return ( return (
<Form.Item label={Props.label}> <FormItem label={Props.label}>
<Input <Input
value={contents} value={contents}
className={Props.className ? Props.className : ""} className={Props.className ? Props.className : ""}
@ -29,7 +36,7 @@ function FieldFloat(Props: FieldFloatProps) {
} }
}} }}
/> />
</Form.Item> </FormItem>
); );
} }
@ -65,6 +72,12 @@ const Display = styled.div<TitleProps>`
max-height: ${(props) => props.maxHeight}px; max-height: ${(props) => props.maxHeight}px;
`; `;
const Row = styled.div`
display: grid;
grid-template-columns: 1fr 1fr;
`;
const Col = styled.div``;
let SquigglePlayground: FC<Props> = ({ let SquigglePlayground: FC<Props> = ({
initialSquiggleString = "", initialSquiggleString = "",
height = 300, height = 300,
@ -79,7 +92,7 @@ let SquigglePlayground: FC<Props> = ({
return ( return (
<ShowBox height={height}> <ShowBox height={height}>
<Row> <Row>
<Col span={12}> <Col>
<CodeEditor <CodeEditor
value={squiggleString} value={squiggleString}
onChange={setSquiggleString} onChange={setSquiggleString}
@ -88,7 +101,7 @@ let SquigglePlayground: FC<Props> = ({
height={height - 3} height={height - 3}
/> />
</Col> </Col>
<Col span={12}> <Col>
<Display maxHeight={height - 3}> <Display maxHeight={height - 3}>
<SquiggleChart <SquiggleChart
squiggleString={squiggleString} squiggleString={squiggleString}

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@ -1,7 +1,9 @@
export { SquiggleChart } from "./components/SquiggleChart"; export { SquiggleChart } from "./components/SquiggleChart";
export { export {
SquiggleEditor, SquiggleEditor,
SquigglePartial,
renderSquiggleEditorToDom, renderSquiggleEditorToDom,
renderSquigglePartialToDom,
} from "./components/SquiggleEditor"; } from "./components/SquiggleEditor";
import SquigglePlayground, { import SquigglePlayground, {
renderSquigglePlaygroundToDom, renderSquigglePlaygroundToDom,

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@ -3,6 +3,7 @@
"description": "A basic area chart example", "description": "A basic area chart example",
"width": 500, "width": 500,
"height": 100, "height": 100,
"autosize": "fit",
"padding": 5, "padding": 5,
"data": [ "data": [
{ {

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@ -2,7 +2,6 @@ node_modules
shell.nix shell.nix
.cache .cache
.direnv .direnv
src
__tests__ __tests__
lib lib
examples examples

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@ -1,3 +1,6 @@
[![npm version](https://badge.fury.io/js/@quri%2Fsquiggle-lang.svg)](https://www.npmjs.com/package/@quri/squiggle-lang)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/quantified-uncertainty/squiggle/blob/develop/LICENSE)
# Squiggle language # Squiggle language
## Build for development ## Build for development
@ -15,13 +18,16 @@ Other:
```sh ```sh
yarn start # listens to files and recompiles at every mutation yarn start # listens to files and recompiles at every mutation
yarn test yarn test
yarn test:watch # keeps an active session and runs all tests at every mutation
# where o := open in osx and o := xdg-open in linux, # where o := open in osx and o := xdg-open in linux,
yarn coverage; o _coverage/index.html # produces coverage report and opens it in browser yarn coverage:rescript; o _coverage/index.html # produces coverage report and opens it in browser
``` ```
## Information ## Distributing this package or using this package from other monorepo packages
As it says in the other `packages/*/README.md`s, building this package is an essential step of building other packages.
# Information
Squiggle is a language for representing probability distributions, as well as functions that return probability distributions. Its original intended use is for improving epistemics around EA decisions. Squiggle is a language for representing probability distributions, as well as functions that return probability distributions. Its original intended use is for improving epistemics around EA decisions.
@ -34,11 +40,3 @@ This package is mainly written in [ReScript](https://rescript-lang.org/), but ha
ReScript has an interesting philosophy of not providing much in the way of effective build tools. Every ReScript file is compiled into `.bs.js` and `.gen.ts` files with the same name and same location, and then you can use these files in other `.js` files to create your program. To generate these files to build the package, you run `yarn build`. ReScript has an interesting philosophy of not providing much in the way of effective build tools. Every ReScript file is compiled into `.bs.js` and `.gen.ts` files with the same name and same location, and then you can use these files in other `.js` files to create your program. To generate these files to build the package, you run `yarn build`.
`.gen.ts` files are created by the [`@genType`](https://rescript-lang.org/docs/gentype/latest/getting-started) decorator, which creates typescript typings for needed parts of the codebase so that they can be easily used in typescript. These .gen.ts files reference the .bs.js files generated by rescript. `.gen.ts` files are created by the [`@genType`](https://rescript-lang.org/docs/gentype/latest/getting-started) decorator, which creates typescript typings for needed parts of the codebase so that they can be easily used in typescript. These .gen.ts files reference the .bs.js files generated by rescript.
### Errors regarding the `rationale` package
You may notice sometimes, that there are errors about the `rationale` package. If you ever get these errors, `yarn build` should fix this issue. These errors occur because `yarn build` also needs to create build files that are in `node_modules`. So if you replace `node_modules` you may need to rebuild to get those files back.
## Distributing this package or using this package from other monorepo packages
As it says in the other `packages/*/README.md`s, building this package is an essential step of building other packages.

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@ -1,41 +0,0 @@
open Jest
open TestHelpers
describe("Continuous and discrete splits", () => {
makeTest(
"splits (1)",
SampleSetDist_ToPointSet.Internals.T.splitContinuousAndDiscrete([1.432, 1.33455, 2.0]),
([1.432, 1.33455, 2.0], E.FloatFloatMap.empty()),
)
makeTest(
"splits (2)",
SampleSetDist_ToPointSet.Internals.T.splitContinuousAndDiscrete([
1.432,
1.33455,
2.0,
2.0,
2.0,
2.0,
]) |> (((c, disc)) => (c, disc |> E.FloatFloatMap.toArray)),
([1.432, 1.33455], [(2.0, 4.0)]),
)
let makeDuplicatedArray = count => {
let arr = Belt.Array.range(1, count) |> E.A.fmap(float_of_int)
let sorted = arr |> Belt.SortArray.stableSortBy(_, compare)
E.A.concatMany([sorted, sorted, sorted, sorted]) |> Belt.SortArray.stableSortBy(_, compare)
}
let (_, discrete1) = SampleSetDist_ToPointSet.Internals.T.splitContinuousAndDiscrete(
makeDuplicatedArray(10),
)
let toArr1 = discrete1 |> E.FloatFloatMap.toArray
makeTest("splitMedium at count=10", toArr1 |> Belt.Array.length, 10)
let (_c, discrete2) = SampleSetDist_ToPointSet.Internals.T.splitContinuousAndDiscrete(
makeDuplicatedArray(500),
)
let toArr2 = discrete2 |> E.FloatFloatMap.toArray
makeTest("splitMedium at count=500", toArr2 |> Belt.Array.length, 500)
// makeTest("foo", [] |> Belt.Array.length, 500)
})

View File

@ -0,0 +1,48 @@
open Jest
open TestHelpers
let prepareInputs = (ar, minWeight) =>
E.A.Floats.Sorted.splitContinuousAndDiscreteForMinWeight(ar, ~minDiscreteWeight=minWeight) |> (
((c, disc)) => (c, disc |> E.FloatFloatMap.toArray)
)
describe("Continuous and discrete splits", () => {
makeTest(
"is empty, with no common elements",
prepareInputs([1.432, 1.33455, 2.0], 2),
([1.33455, 1.432, 2.0], []),
)
makeTest(
"only stores 3.5 as discrete when minWeight is 3",
prepareInputs([1.432, 1.33455, 2.0, 2.0, 3.5, 3.5, 3.5], 3),
([1.33455, 1.432, 2.0, 2.0], [(3.5, 3.0)]),
)
makeTest(
"doesn't store 3.5 as discrete when minWeight is 5",
prepareInputs([1.432, 1.33455, 2.0, 2.0, 3.5, 3.5, 3.5], 5),
([1.33455, 1.432, 2.0, 2.0, 3.5, 3.5, 3.5], []),
)
let makeDuplicatedArray = count => {
let arr = Belt.Array.range(1, count) |> E.A.fmap(float_of_int)
let sorted = arr |> Belt.SortArray.stableSortBy(_, compare)
E.A.concatMany([sorted, sorted, sorted, sorted]) |> Belt.SortArray.stableSortBy(_, compare)
}
let (_, discrete1) = E.A.Floats.Sorted.splitContinuousAndDiscreteForMinWeight(
makeDuplicatedArray(10),
~minDiscreteWeight=2,
)
let toArr1 = discrete1 |> E.FloatFloatMap.toArray
makeTest("splitMedium at count=10", toArr1 |> Belt.Array.length, 10)
let (_c, discrete2) = E.A.Floats.Sorted.splitContinuousAndDiscreteForMinWeight(
makeDuplicatedArray(500),
~minDiscreteWeight=2,
)
let toArr2 = discrete2 |> E.FloatFloatMap.toArray
makeTest("splitMedium at count=500", toArr2 |> Belt.Array.length, 500)
// makeTest("foo", [] |> Belt.Array.length, 500)
})

View File

@ -92,11 +92,11 @@ describe("eval on distribution functions", () => {
testEval("log(2, uniform(5,8))", "Ok(Sample Set Distribution)") testEval("log(2, uniform(5,8))", "Ok(Sample Set Distribution)")
testEval( testEval(
"log(normal(5,2), 3)", "log(normal(5,2), 3)",
"Error(Distribution Math Error: Logarithm of input error: First input must completely greater than 0)", "Error(Distribution Math Error: Logarithm of input error: First input must be completely greater than 0)",
) )
testEval( testEval(
"log(normal(5,2), normal(10,1))", "log(normal(5,2), normal(10,1))",
"Error(Distribution Math Error: Logarithm of input error: First input must completely greater than 0)", "Error(Distribution Math Error: Logarithm of input error: First input must be completely greater than 0)",
) )
testEval("log(uniform(5,8))", "Ok(Sample Set Distribution)") testEval("log(uniform(5,8))", "Ok(Sample Set Distribution)")
testEval("log10(uniform(5,8))", "Ok(Sample Set Distribution)") testEval("log10(uniform(5,8))", "Ok(Sample Set Distribution)")

View File

@ -1,23 +1,5 @@
import { import { Distribution, resultMap } from "../../src/js/index";
run, import { testRun, testRunPartial } from "./TestHelpers";
Distribution,
resultMap,
squiggleExpression,
errorValueToString,
} from "../../src/js/index";
let testRun = (x: string): squiggleExpression => {
let result = run(x, { sampleCount: 100, xyPointLength: 100 });
expect(result.tag).toEqual("Ok");
if (result.tag === "Ok") {
return result.value;
} else {
throw Error(
"Expected squiggle expression to evaluate but got error: " +
errorValueToString(result.value)
);
}
};
function Ok<b>(x: b) { function Ok<b>(x: b) {
return { tag: "Ok", value: x }; return { tag: "Ok", value: x };
@ -42,6 +24,50 @@ describe("Log function", () => {
}); });
}); });
describe("Array", () => {
test("nested Array", () => {
expect(testRun("[[1]]")).toEqual({
tag: "array",
value: [
{
tag: "array",
value: [
{
tag: "number",
value: 1,
},
],
},
],
});
});
});
describe("Record", () => {
test("Return record", () => {
expect(testRun("{a: 1}")).toEqual({
tag: "record",
value: {
a: {
tag: "number",
value: 1,
},
},
});
});
});
describe("Partials", () => {
test("Can pass variables between partials and cells", () => {
let bindings = testRunPartial(`x = 5`);
let bindings2 = testRunPartial(`y = x + 2`, bindings);
expect(testRun(`y + 3`, bindings2)).toEqual({
tag: "number",
value: 10,
});
});
});
describe("Distribution", () => { describe("Distribution", () => {
//It's important that sampleCount is less than 9. If it's more, than that will create randomness //It's important that sampleCount is less than 9. If it's more, than that will create randomness
//Also, note, the value should be created using makeSampleSetDist() later on. //Also, note, the value should be created using makeSampleSetDist() later on.

View File

@ -1,14 +1,16 @@
import { import {
run, run,
// Distribution, runPartial,
bindings,
squiggleExpression, squiggleExpression,
errorValueToString, errorValueToString,
// errorValue,
// result,
} from "../../src/js/index"; } from "../../src/js/index";
export function testRun(x: string): squiggleExpression { export function testRun(x: string, bindings = {}): squiggleExpression {
let squiggleResult = run(x, { sampleCount: 1000, xyPointLength: 100 }); let squiggleResult = run(x, bindings, {
sampleCount: 1000,
xyPointLength: 100,
});
// return squiggleResult.value // return squiggleResult.value
if (squiggleResult.tag === "Ok") { if (squiggleResult.tag === "Ok") {
return squiggleResult.value; return squiggleResult.value;
@ -21,6 +23,22 @@ export function testRun(x: string): squiggleExpression {
} }
} }
export function testRunPartial(x: string, bindings: bindings = {}): bindings {
let squiggleResult = runPartial(x, bindings, {
sampleCount: 1000,
xyPointLength: 100,
});
if (squiggleResult.tag === "Ok") {
return squiggleResult.value;
} else {
throw new Error(
`Expected squiggle expression to evaluate but got error: ${errorValueToString(
squiggleResult.value
)}`
);
}
}
export function failDefault() { export function failDefault() {
expect("be reached").toBe("codepath should never"); expect("be reached").toBe("codepath should never");
} }

View File

@ -18,7 +18,26 @@ let pointSetDist3: PointSetTypes.xyShape = {
ys: [0.2, 0.5, 0.8], ys: [0.2, 0.5, 0.8],
} }
let makeAndGetErrorString = (~xs, ~ys) =>
XYShape.T.make(~xs, ~ys)->E.R.getError->E.O2.fmap(XYShape.Error.toString)
describe("XYShapes", () => { describe("XYShapes", () => {
describe("Validator", () => {
makeTest(
"with no errors",
makeAndGetErrorString(~xs=[1.0, 4.0, 8.0], ~ys=[0.2, 0.4, 0.8]),
None,
)
makeTest("when empty", makeAndGetErrorString(~xs=[], ~ys=[]), Some("Xs is empty"))
makeTest(
"when not sorted, different lengths, and not finite",
makeAndGetErrorString(~xs=[2.0, 1.0, infinity, 0.0], ~ys=[3.0, Js.Float._NaN]),
Some(
"Multiple Errors: [Xs is not sorted], [Xs and Ys have different lengths. Xs has length 4 and Ys has length 2], [Xs is not finite. Example value: Infinity], [Ys is not finite. Example value: NaN]",
),
)
})
describe("logScorePoint", () => { describe("logScorePoint", () => {
makeTest("When identical", XYShape.logScorePoint(30, pointSetDist1, pointSetDist1), Some(0.0)) makeTest("When identical", XYShape.logScorePoint(30, pointSetDist1, pointSetDist1), Some(0.0))
makeTest( makeTest(
@ -32,16 +51,6 @@ describe("XYShapes", () => {
Some(210.3721280423322), Some(210.3721280423322),
) )
}) })
// describe("transverse", () => {
// makeTest(
// "When very different",
// XYShape.Transversal._transverse(
// (aCurrent, aLast) => aCurrent +. aLast,
// [|1.0, 2.0, 3.0, 4.0|],
// ),
// [|1.0, 3.0, 6.0, 10.0|],
// )
// });
describe("integrateWithTriangles", () => describe("integrateWithTriangles", () =>
makeTest( makeTest(
"integrates correctly", "integrates correctly",

View File

@ -20,7 +20,7 @@
], ],
"suffix": ".bs.js", "suffix": ".bs.js",
"namespace": true, "namespace": true,
"bs-dependencies": ["@glennsl/rescript-jest", "rationale", "bisect_ppx"], "bs-dependencies": ["@glennsl/rescript-jest", "bisect_ppx"],
"gentypeconfig": { "gentypeconfig": {
"language": "typescript", "language": "typescript",
"module": "commonjs", "module": "commonjs",

View File

@ -1,13 +1,13 @@
{ {
"name": "@quri/squiggle-lang", "name": "@quri/squiggle-lang",
"version": "0.2.5", "version": "0.2.7",
"homepage": "https://squiggle-language.com", "homepage": "https://squiggle-language.com",
"licence": "MIT", "license": "MIT",
"scripts": { "scripts": {
"build": "rescript build -with-deps", "build": "rescript build -with-deps && tsc",
"bundle": "webpack", "bundle": "webpack",
"start": "rescript build -w -with-deps", "start": "rescript build -w -with-deps",
"clean": "rescript clean", "clean": "rescript clean && rm -r dist",
"test:reducer": "jest __tests__/Reducer*/", "test:reducer": "jest __tests__/Reducer*/",
"benchmark": "ts-node benchmark/conversion_tests.ts", "benchmark": "ts-node benchmark/conversion_tests.ts",
"test": "jest", "test": "jest",
@ -31,34 +31,28 @@
], ],
"author": "Quantified Uncertainty Research Institute", "author": "Quantified Uncertainty Research Institute",
"license": "MIT", "license": "MIT",
"dependencies": {
"rescript": "^9.1.4",
"jstat": "^1.9.5",
"pdfast": "^0.2.0",
"mathjs": "10.5.0"
},
"devDependencies": { "devDependencies": {
"bisect_ppx": "^2.7.1", "bisect_ppx": "^2.7.1",
"jstat": "^1.9.5",
"lodash": "4.17.21", "lodash": "4.17.21",
"mathjs": "10.5.0",
"pdfast": "^0.2.0",
"rationale": "0.2.0",
"rescript": "^9.1.4",
"rescript-fast-check": "^1.1.1", "rescript-fast-check": "^1.1.1",
"@glennsl/rescript-jest": "^0.9.0", "@glennsl/rescript-jest": "^0.9.0",
"@istanbuljs/nyc-config-typescript": "^1.0.2", "@istanbuljs/nyc-config-typescript": "^1.0.2",
"@types/jest": "^27.4.0", "@types/jest": "^27.4.0",
"babel-plugin-transform-es2015-modules-commonjs": "^6.26.2", "babel-plugin-transform-es2015-modules-commonjs": "^6.26.2",
"bisect_ppx": "^2.7.1", "chalk": "^5.0.1",
"chalk": "^4.1.2",
"codecov": "3.8.3", "codecov": "3.8.3",
"fast-check": "2.25.0", "fast-check": "2.25.0",
"gentype": "^4.3.0", "gentype": "^4.3.0",
"jest": "^27.5.1", "jest": "^27.5.1",
"jstat": "^1.9.5",
"lodash": "4.17.21",
"mathjs": "10.5.0",
"moduleserve": "0.9.1", "moduleserve": "0.9.1",
"nyc": "^15.1.0", "nyc": "^15.1.0",
"pdfast": "^0.2.0",
"rationale": "0.2.0",
"reanalyze": "^2.19.0", "reanalyze": "^2.19.0",
"rescript": "^9.1.4",
"ts-jest": "^27.1.4", "ts-jest": "^27.1.4",
"ts-loader": "^9.2.8", "ts-loader": "^9.2.8",
"ts-node": "^10.7.0", "ts-node": "^10.7.0",
@ -67,6 +61,6 @@
"webpack-cli": "^4.9.2" "webpack-cli": "^4.9.2"
}, },
"source": "./src/js/index.ts", "source": "./src/js/index.ts",
"main": "./dist/bundle.js", "main": "./dist/src/js/index.js",
"types": "./dist/js/index.d.ts" "types": "./dist/src/js/index.d.ts"
} }

View File

@ -2,7 +2,9 @@ import * as _ from "lodash";
import { import {
genericDist, genericDist,
samplingParams, samplingParams,
evaluate, evaluateUsingExternalBindings,
evaluatePartialUsingExternalBindings,
externalBindings,
expressionValue, expressionValue,
errorValue, errorValue,
distributionError, distributionError,
@ -10,6 +12,9 @@ import {
continuousShape, continuousShape,
discreteShape, discreteShape,
distributionErrorToString, distributionErrorToString,
mixedShape,
sampleSetDist,
symbolicDist,
} from "../rescript/TypescriptInterface.gen"; } from "../rescript/TypescriptInterface.gen";
export { export {
makeSampleSetDist, makeSampleSetDist,
@ -43,7 +48,7 @@ import {
Constructors_pointwiseLogarithm, Constructors_pointwiseLogarithm,
Constructors_pointwisePower, Constructors_pointwisePower,
} from "../rescript/Distributions/DistributionOperation/DistributionOperation.gen"; } from "../rescript/Distributions/DistributionOperation/DistributionOperation.gen";
export type { samplingParams, errorValue }; export type { samplingParams, errorValue, externalBindings as bindings };
export let defaultSamplingInputs: samplingParams = { export let defaultSamplingInputs: samplingParams = {
sampleCount: 10000, sampleCount: 10000,
@ -90,26 +95,67 @@ export type squiggleExpression =
| tagged<"distribution", Distribution> | tagged<"distribution", Distribution>
| tagged<"number", number> | tagged<"number", number>
| tagged<"record", { [key: string]: squiggleExpression }>; | tagged<"record", { [key: string]: squiggleExpression }>;
export function run( export function run(
squiggleString: string, squiggleString: string,
bindings?: externalBindings,
samplingInputs?: samplingParams samplingInputs?: samplingParams
): result<squiggleExpression, errorValue> { ): result<squiggleExpression, errorValue> {
let b = bindings ? bindings : {};
let si: samplingParams = samplingInputs let si: samplingParams = samplingInputs
? samplingInputs ? samplingInputs
: defaultSamplingInputs; : defaultSamplingInputs;
let result: result<expressionValue, errorValue> = evaluate(squiggleString);
let result: result<expressionValue, errorValue> =
evaluateUsingExternalBindings(squiggleString, b);
return resultMap(result, (x) => createTsExport(x, si)); return resultMap(result, (x) => createTsExport(x, si));
} }
// Run Partial. A partial is a block of code that doesn't return a value
export function runPartial(
squiggleString: string,
bindings: externalBindings,
_samplingInputs?: samplingParams
): result<externalBindings, errorValue> {
return evaluatePartialUsingExternalBindings(squiggleString, bindings);
}
function createTsExport( function createTsExport(
x: expressionValue, x: expressionValue,
sampEnv: samplingParams sampEnv: samplingParams
): squiggleExpression { ): squiggleExpression {
switch (x.tag) { switch (x.tag) {
case "EvArray": case "EvArray":
// genType doesn't convert anything more than 2 layers down into {tag: x, value: x}
// format, leaving it as the raw values. This converts the raw values
// directly into typescript values.
//
// The casting here is because genType is about the types of the returned
// values, claiming they are fully recursive when that's not actually the
// case
return tag( return tag(
"array", "array",
x.value.map((x) => createTsExport(x, sampEnv)) x.value.map((arrayItem): squiggleExpression => {
switch (arrayItem.tag) {
case "EvRecord":
return tag(
"record",
_.mapValues(arrayItem.value, (recordValue: unknown) =>
convertRawToTypescript(recordValue as rescriptExport, sampEnv)
)
);
case "EvArray":
let y = arrayItem.value as unknown as rescriptExport[];
return tag(
"array",
y.map((childArrayItem) =>
convertRawToTypescript(childArrayItem, sampEnv)
)
);
default:
return createTsExport(arrayItem, sampEnv);
}
})
); );
case "EvBool": case "EvBool":
return tag("boolean", x.value); return tag("boolean", x.value);
@ -120,10 +166,14 @@ function createTsExport(
case "EvNumber": case "EvNumber":
return tag("number", x.value); return tag("number", x.value);
case "EvRecord": case "EvRecord":
return tag( // genType doesn't support records, so we have to do the raw conversion ourself
let result: tagged<"record", { [key: string]: squiggleExpression }> = tag(
"record", "record",
_.mapValues(x.value, (x) => createTsExport(x, sampEnv)) _.mapValues(x.value, (x: unknown) =>
convertRawToTypescript(x as rescriptExport, sampEnv)
)
); );
return result;
case "EvString": case "EvString":
return tag("string", x.value); return tag("string", x.value);
case "EvSymbol": case "EvSymbol":
@ -131,6 +181,118 @@ function createTsExport(
} }
} }
// Helper functions to convert the rescript representations that genType doesn't
// cover
function convertRawToTypescript(
result: rescriptExport,
sampEnv: samplingParams
): squiggleExpression {
switch (result.TAG) {
case 0: // EvArray
return tag(
"array",
result._0.map((x) => convertRawToTypescript(x, sampEnv))
);
case 1: // EvBool
return tag("boolean", result._0);
case 2: // EvCall
return tag("call", result._0);
case 3: // EvDistribution
return tag(
"distribution",
new Distribution(
convertRawDistributionToGenericDist(result._0),
sampEnv
)
);
case 4: // EvNumber
return tag("number", result._0);
case 5: // EvRecord
return tag(
"record",
_.mapValues(result._0, (x) => convertRawToTypescript(x, sampEnv))
);
case 6: // EvString
return tag("string", result._0);
case 7: // EvSymbol
return tag("symbol", result._0);
}
}
function convertRawDistributionToGenericDist(
result: rescriptDist
): genericDist {
switch (result.TAG) {
case 0: // Point Set Dist
switch (result._0.TAG) {
case 0: // Mixed
return tag("PointSet", tag("Mixed", result._0._0));
case 1: // Discrete
return tag("PointSet", tag("Discrete", result._0._0));
case 2: // Continuous
return tag("PointSet", tag("Continuous", result._0._0));
}
case 1: // Sample Set Dist
return tag("SampleSet", result._0);
case 2: // Symbolic Dist
return tag("Symbolic", result._0);
}
}
// Raw rescript types.
type rescriptExport =
| {
TAG: 0; // EvArray
_0: rescriptExport[];
}
| {
TAG: 1; // EvBool
_0: boolean;
}
| {
TAG: 2; // EvCall
_0: string;
}
| {
TAG: 3; // EvDistribution
_0: rescriptDist;
}
| {
TAG: 4; // EvNumber
_0: number;
}
| {
TAG: 5; // EvRecord
_0: { [key: string]: rescriptExport };
}
| {
TAG: 6; // EvString
_0: string;
}
| {
TAG: 7; // EvSymbol
_0: string;
};
type rescriptDist =
| { TAG: 0; _0: rescriptPointSetDist }
| { TAG: 1; _0: sampleSetDist }
| { TAG: 2; _0: symbolicDist };
type rescriptPointSetDist =
| {
TAG: 0; // Mixed
_0: mixedShape;
}
| {
TAG: 1; // Discrete
_0: discreteShape;
}
| {
TAG: 2; // ContinuousShape
_0: continuousShape;
};
export function resultExn<a, c>(r: result<a, c>): a | c { export function resultExn<a, c>(r: result<a, c>): a | c {
return r.value; return r.value;
} }

View File

@ -19,6 +19,7 @@ type error =
| RequestedStrategyInvalidError(string) | RequestedStrategyInvalidError(string)
| LogarithmOfDistributionError(string) | LogarithmOfDistributionError(string)
| OtherError(string) | OtherError(string)
| XYShapeError(XYShape.error)
@genType @genType
module Error = { module Error = {
@ -39,6 +40,7 @@ module Error = {
| PointSetConversionError(err) => SampleSetDist.pointsetConversionErrorToString(err) | PointSetConversionError(err) => SampleSetDist.pointsetConversionErrorToString(err)
| SparklineError(err) => PointSetTypes.sparklineErrorToString(err) | SparklineError(err) => PointSetTypes.sparklineErrorToString(err)
| RequestedStrategyInvalidError(err) => `Requested strategy invalid: ${err}` | RequestedStrategyInvalidError(err) => `Requested strategy invalid: ${err}`
| XYShapeError(err) => `XY Shape Error: ${XYShape.Error.toString(err)}`
| OtherError(s) => s | OtherError(s) => s
} }

View File

@ -6,6 +6,24 @@ type toSampleSetFn = t => result<SampleSetDist.t, error>
type scaleMultiplyFn = (t, float) => result<t, error> type scaleMultiplyFn = (t, float) => result<t, error>
type pointwiseAddFn = (t, t) => result<t, error> type pointwiseAddFn = (t, t) => result<t, error>
let isPointSet = (t: t) =>
switch t {
| PointSet(_) => true
| _ => false
}
let isSampleSetSet = (t: t) =>
switch t {
| SampleSet(_) => true
| _ => false
}
let isSymbolic = (t: t) =>
switch t {
| Symbolic(_) => true
| _ => false
}
let sampleN = (t: t, n) => let sampleN = (t: t, n) =>
switch t { switch t {
| PointSet(r) => PointSetDist.sampleNRendered(n, r) | PointSet(r) => PointSetDist.sampleNRendered(n, r)
@ -150,144 +168,147 @@ let truncate = Truncate.run
of a new variable that is the result of the operation on A and B. of a new variable that is the result of the operation on A and B.
For instance, normal(0, 1) + normal(1, 1) -> normal(1, 2). For instance, normal(0, 1) + normal(1, 1) -> normal(1, 2).
In general, this is implemented via convolution. In general, this is implemented via convolution.
TODO: It would be useful to be able to pass in a paramater to get this to run either with convolution or monte carlo.
*/ */
module AlgebraicCombination = { module AlgebraicCombination = {
let runConvolution = ( module InputValidator = {
toPointSet: toPointSetFn, /*
arithmeticOperation: Operation.convolutionOperation,
t1: t,
t2: t,
) =>
E.R.merge(toPointSet(t1), toPointSet(t2))->E.R2.fmap(((a, b)) =>
PointSetDist.combineAlgebraically(arithmeticOperation, a, b)
)
let runMonteCarlo = (
toSampleSet: toSampleSetFn,
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): result<t, error> => {
let fn = Operation.Algebraic.toFn(arithmeticOperation)
E.R.merge(toSampleSet(t1), toSampleSet(t2))
->E.R.bind(((t1, t2)) => {
SampleSetDist.map2(~fn, ~t1, ~t2)->E.R2.errMap(x => DistributionTypes.OperationError(x))
})
->E.R2.fmap(r => DistributionTypes.SampleSet(r))
}
/*
It would be good to also do a check to make sure that probability mass for the second It would be good to also do a check to make sure that probability mass for the second
operand, at value 1.0, is 0 (or approximately 0). However, we'd ideally want to check operand, at value 1.0, is 0 (or approximately 0). However, we'd ideally want to check
that both the probability mass and the probability density are greater than zero. that both the probability mass and the probability density are greater than zero.
Right now we don't yet have a way of getting probability mass, so I'll leave this for later. Right now we don't yet have a way of getting probability mass, so I'll leave this for later.
*/ */
let getLogarithmInputError = (t1: t, t2: t, ~toPointSetFn: toPointSetFn): option<error> => { let getLogarithmInputError = (t1: t, t2: t, ~toPointSetFn: toPointSetFn): option<error> => {
let firstOperandIsGreaterThanZero = let firstOperandIsGreaterThanZero =
toFloatOperation( toFloatOperation(
t1, t1,
~toPointSetFn, ~toPointSetFn,
~distToFloatOperation=#Cdf(MagicNumbers.Epsilon.ten), ~distToFloatOperation=#Cdf(MagicNumbers.Epsilon.ten),
) |> E.R.fmap(r => r > 0.) ) |> E.R.fmap(r => r > 0.)
let secondOperandIsGreaterThanZero = let secondOperandIsGreaterThanZero =
toFloatOperation( toFloatOperation(
t2, t2,
~toPointSetFn, ~toPointSetFn,
~distToFloatOperation=#Cdf(MagicNumbers.Epsilon.ten), ~distToFloatOperation=#Cdf(MagicNumbers.Epsilon.ten),
) |> E.R.fmap(r => r > 0.) ) |> E.R.fmap(r => r > 0.)
let items = E.A.R.firstErrorOrOpen([ let items = E.A.R.firstErrorOrOpen([
firstOperandIsGreaterThanZero, firstOperandIsGreaterThanZero,
secondOperandIsGreaterThanZero, secondOperandIsGreaterThanZero,
]) ])
switch items { switch items {
| Error(r) => Some(r) | Error(r) => Some(r)
| Ok([true, _]) => | Ok([true, _]) =>
Some(LogarithmOfDistributionError("First input must completely greater than 0")) Some(LogarithmOfDistributionError("First input must be completely greater than 0"))
| Ok([false, true]) => | Ok([false, true]) =>
Some(LogarithmOfDistributionError("Second input must completely greater than 0")) Some(LogarithmOfDistributionError("Second input must be completely greater than 0"))
| Ok([false, false]) => None | Ok([false, false]) => None
| Ok(_) => Some(Unreachable) | Ok(_) => Some(Unreachable)
}
}
let run = (t1: t, t2: t, ~toPointSetFn: toPointSetFn, ~arithmeticOperation): option<error> => {
if arithmeticOperation == #Logarithm {
getLogarithmInputError(t1, t2, ~toPointSetFn)
} else {
None
}
} }
} }
let getInvalidOperationError = ( module StrategyCallOnValidatedInputs = {
t1: t, let convolution = (
t2: t, toPointSet: toPointSetFn,
~toPointSetFn: toPointSetFn, arithmeticOperation: Operation.convolutionOperation,
t1: t,
t2: t,
): result<t, error> =>
E.R.merge(toPointSet(t1), toPointSet(t2))
->E.R2.fmap(((a, b)) => PointSetDist.combineAlgebraically(arithmeticOperation, a, b))
->E.R2.fmap(r => DistributionTypes.PointSet(r))
let monteCarlo = (
toSampleSet: toSampleSetFn,
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): result<t, error> => {
let fn = Operation.Algebraic.toFn(arithmeticOperation)
E.R.merge(toSampleSet(t1), toSampleSet(t2))
->E.R.bind(((t1, t2)) => {
SampleSetDist.map2(~fn, ~t1, ~t2)->E.R2.errMap(x => DistributionTypes.OperationError(x))
})
->E.R2.fmap(r => DistributionTypes.SampleSet(r))
}
let symbolic = (
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): SymbolicDistTypes.analyticalSimplificationResult => {
switch (t1, t2) {
| (DistributionTypes.Symbolic(d1), DistributionTypes.Symbolic(d2)) =>
SymbolicDist.T.tryAnalyticalSimplification(d1, d2, arithmeticOperation)
| _ => #NoSolution
}
}
}
module StrategyChooser = {
type specificStrategy = [#AsSymbolic | #AsMonteCarlo | #AsConvolution]
//I'm (Ozzie) really just guessing here, very little idea what's best
let expectedConvolutionCost: t => int = x =>
switch x {
| Symbolic(#Float(_)) => MagicNumbers.OpCost.floatCost
| Symbolic(_) => MagicNumbers.OpCost.symbolicCost
| PointSet(Discrete(m)) => m.xyShape->XYShape.T.length
| PointSet(Mixed(_)) => MagicNumbers.OpCost.mixedCost
| PointSet(Continuous(_)) => MagicNumbers.OpCost.continuousCost
| _ => MagicNumbers.OpCost.wildcardCost
}
let hasSampleSetDist = (t1: t, t2: t): bool => isSampleSetSet(t1) || isSampleSetSet(t2)
let convolutionIsFasterThanMonteCarlo = (t1: t, t2: t): bool =>
expectedConvolutionCost(t1) * expectedConvolutionCost(t2) < MagicNumbers.OpCost.monteCarloCost
let preferConvolutionToMonteCarlo = (t1, t2, arithmeticOperation) => {
!hasSampleSetDist(t1, t2) &&
Operation.Convolution.canDoAlgebraicOperation(arithmeticOperation) &&
convolutionIsFasterThanMonteCarlo(t1, t2)
}
let run = (~t1: t, ~t2: t, ~arithmeticOperation): specificStrategy => {
switch StrategyCallOnValidatedInputs.symbolic(arithmeticOperation, t1, t2) {
| #AnalyticalSolution(_)
| #Error(_) =>
#AsSymbolic
| #NoSolution =>
preferConvolutionToMonteCarlo(t1, t2, arithmeticOperation) ? #AsConvolution : #AsMonteCarlo
}
}
}
let runStrategyOnValidatedInputs = (
~t1: t,
~t2: t,
~arithmeticOperation, ~arithmeticOperation,
): option<error> => { ~strategy: StrategyChooser.specificStrategy,
if arithmeticOperation == #Logarithm {
getLogarithmInputError(t1, t2, ~toPointSetFn)
} else {
None
}
}
//I'm (Ozzie) really just guessing here, very little idea what's best
let expectedConvolutionCost: t => int = x =>
switch x {
| Symbolic(#Float(_)) => MagicNumbers.OpCost.floatCost
| Symbolic(_) => MagicNumbers.OpCost.symbolicCost
| PointSet(Discrete(m)) => m.xyShape->XYShape.T.length
| PointSet(Mixed(_)) => MagicNumbers.OpCost.mixedCost
| PointSet(Continuous(_)) => MagicNumbers.OpCost.continuousCost
| _ => MagicNumbers.OpCost.wildcardCost
}
type calculationStrategy = MonteCarloStrat | ConvolutionStrat(Operation.convolutionOperation)
let chooseConvolutionOrMonteCarloDefault = (
op: Operation.algebraicOperation,
t2: t,
t1: t,
): calculationStrategy =>
switch op {
| #Divide
| #Power
| #Logarithm =>
MonteCarloStrat
| (#Add | #Subtract | #Multiply) as convOp =>
expectedConvolutionCost(t1) * expectedConvolutionCost(t2) > MagicNumbers.OpCost.monteCarloCost
? MonteCarloStrat
: ConvolutionStrat(convOp)
}
let tryAnalyticalSimplification = (
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): option<SymbolicDistTypes.analyticalSimplificationResult> => {
switch (t1, t2) {
| (DistributionTypes.Symbolic(d1), DistributionTypes.Symbolic(d2)) =>
Some(SymbolicDist.T.tryAnalyticalSimplification(d1, d2, arithmeticOperation))
| _ => None
}
}
let runDefault = (
t1: t,
~toPointSetFn: toPointSetFn, ~toPointSetFn: toPointSetFn,
~toSampleSetFn: toSampleSetFn, ~toSampleSetFn: toSampleSetFn,
~arithmeticOperation,
~t2: t,
): result<t, error> => { ): result<t, error> => {
switch tryAnalyticalSimplification(arithmeticOperation, t1, t2) { switch strategy {
| Some(#AnalyticalSolution(symbolicDist)) => Ok(Symbolic(symbolicDist)) | #AsMonteCarlo =>
| Some(#Error(e)) => Error(OperationError(e)) StrategyCallOnValidatedInputs.monteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
| Some(#NoSolution) | #AsSymbolic =>
| None => switch StrategyCallOnValidatedInputs.symbolic(arithmeticOperation, t1, t2) {
switch getInvalidOperationError(t1, t2, ~toPointSetFn, ~arithmeticOperation) { | #AnalyticalSolution(symbolicDist) => Ok(Symbolic(symbolicDist))
| Some(e) => Error(e) | #Error(e) => Error(OperationError(e))
| None => | #NoSolution => Error(Unreachable)
switch chooseConvolutionOrMonteCarloDefault(arithmeticOperation, t1, t2) { }
| MonteCarloStrat => runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2) | #AsConvolution =>
| ConvolutionStrat(convOp) => switch Operation.Convolution.fromAlgebraicOperation(arithmeticOperation) {
runConvolution(toPointSetFn, convOp, t1, t2)->E.R2.fmap(r => DistributionTypes.PointSet( | Some(convOp) => StrategyCallOnValidatedInputs.convolution(toPointSetFn, convOp, t1, t2)
r, | None => Error(Unreachable)
))
}
} }
} }
} }
@ -300,27 +321,38 @@ module AlgebraicCombination = {
~arithmeticOperation: Operation.algebraicOperation, ~arithmeticOperation: Operation.algebraicOperation,
~t2: t, ~t2: t,
): result<t, error> => { ): result<t, error> => {
switch strategy { let invalidOperationError = InputValidator.run(t1, t2, ~arithmeticOperation, ~toPointSetFn)
| AsDefault => runDefault(t1, ~toPointSetFn, ~toSampleSetFn, ~arithmeticOperation, ~t2) switch (invalidOperationError, strategy) {
| AsSymbolic => | (Some(e), _) => Error(e)
switch tryAnalyticalSimplification(arithmeticOperation, t1, t2) { | (None, AsDefault) => {
| Some(#AnalyticalSolution(symbolicDist)) => Ok(Symbolic(symbolicDist)) let chooseStrategy = StrategyChooser.run(~arithmeticOperation, ~t1, ~t2)
| Some(#NoSolution) => Error(RequestedStrategyInvalidError(`No analytical solution`)) runStrategyOnValidatedInputs(
| None => Error(RequestedStrategyInvalidError("Inputs were not even symbolic")) ~t1,
| Some(#Error(err)) => Error(OperationError(err)) ~t2,
~strategy=chooseStrategy,
~arithmeticOperation,
~toPointSetFn,
~toSampleSetFn,
)
} }
| AsConvolution => { | (None, AsMonteCarlo) =>
let errString = opString => `Can't convolve on ${opString}` StrategyCallOnValidatedInputs.monteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
switch arithmeticOperation { | (None, AsSymbolic) =>
| (#Add | #Subtract | #Multiply) as convOp => switch StrategyCallOnValidatedInputs.symbolic(arithmeticOperation, t1, t2) {
runConvolution(toPointSetFn, convOp, t1, t2)->E.R2.fmap(r => DistributionTypes.PointSet( | #AnalyticalSolution(symbolicDist) => Ok(Symbolic(symbolicDist))
r, | #NoSolution => Error(RequestedStrategyInvalidError(`No analytic solution for inputs`))
)) | #Error(err) => Error(OperationError(err))
| (#Divide | #Power | #Logarithm) as op => }
op->Operation.Algebraic.toString->errString->RequestedStrategyInvalidError->Error | (None, AsConvolution) =>
switch Operation.Convolution.fromAlgebraicOperation(arithmeticOperation) {
| None => {
let errString = `Convolution not supported for ${Operation.Algebraic.toString(
arithmeticOperation,
)}`
Error(RequestedStrategyInvalidError(errString))
} }
| Some(convOp) => StrategyCallOnValidatedInputs.convolution(toPointSetFn, convOp, t1, t2)
} }
| AsMonteCarlo => runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
} }
} }
} }

View File

@ -69,3 +69,6 @@ let mixture: (
~scaleMultiplyFn: scaleMultiplyFn, ~scaleMultiplyFn: scaleMultiplyFn,
~pointwiseAddFn: pointwiseAddFn, ~pointwiseAddFn: pointwiseAddFn,
) => result<t, error> ) => result<t, error>
let isSymbolic: t => bool
let isPointSet: t => bool

View File

@ -263,4 +263,4 @@ let combineShapesContinuousDiscrete = (
) )
} }
let isOrdered = (a: XYShape.T.t): bool => E.A.Sorted.Floats.isSorted(a.xs) let isOrdered = (a: XYShape.T.t): bool => E.A.Floats.isSorted(a.xs)

View File

@ -39,28 +39,6 @@ module Internals = {
module T = { module T = {
type t = array<float> type t = array<float>
let splitContinuousAndDiscrete = (sortedArray: t) => {
let continuous = []
let discrete = E.FloatFloatMap.empty()
Belt.Array.forEachWithIndex(sortedArray, (index, element) => {
let maxIndex = (sortedArray |> Array.length) - 1
let possiblySimilarElements = switch index {
| 0 => [index + 1]
| n if n == maxIndex => [index - 1]
| _ => [index - 1, index + 1]
} |> Belt.Array.map(_, r => sortedArray[r])
let hasSimilarElement = Belt.Array.some(possiblySimilarElements, r => r == element)
hasSimilarElement
? E.FloatFloatMap.increment(element, discrete)
: {
let _ = Js.Array.push(element, continuous)
}
()
})
(continuous, discrete)
}
let xWidthToUnitWidth = (samples, outputXYPoints, xWidth) => { let xWidthToUnitWidth = (samples, outputXYPoints, xWidth) => {
let xyPointRange = E.A.Sorted.range(samples) |> E.O.default(0.0) let xyPointRange = E.A.Sorted.range(samples) |> E.O.default(0.0)
let xyPointWidth = xyPointRange /. float_of_int(outputXYPoints) let xyPointWidth = xyPointRange /. float_of_int(outputXYPoints)
@ -85,7 +63,11 @@ let toPointSetDist = (
(), (),
): Internals.Types.outputs => { ): Internals.Types.outputs => {
Array.fast_sort(compare, samples) Array.fast_sort(compare, samples)
let (continuousPart, discretePart) = E.A.Sorted.Floats.split(samples) let minDiscreteToKeep = MagicNumbers.ToPointSet.minDiscreteToKeep(samples)
let (continuousPart, discretePart) = E.A.Floats.Sorted.splitContinuousAndDiscreteForMinWeight(
samples,
~minDiscreteWeight=minDiscreteToKeep,
)
let length = samples |> E.A.length |> float_of_int let length = samples |> E.A.length |> float_of_int
let discrete: PointSetTypes.discreteShape = let discrete: PointSetTypes.discreteShape =
discretePart discretePart

View File

@ -22,3 +22,16 @@ module OpCost = {
let wildcardCost = 1000 let wildcardCost = 1000
let monteCarloCost = Environment.defaultSampleCount let monteCarloCost = Environment.defaultSampleCount
} }
module ToPointSet = {
/*
This function chooses the minimum amount of duplicate samples that need
to exist in order for this to be considered discrete. The tricky thing
is that there are some operations that create duplicate continuous samples,
so we can't guarantee that these only will occur because the fundamental
structure is meant to be discrete. I chose this heuristic because I think
it would strike a reasonable trade-off, but Im really unsure whats
best right now.
*/
let minDiscreteToKeep = samples => max(20, E.A.length(samples) / 50)
}

View File

@ -13,6 +13,12 @@ type samplingParams = DistributionOperation.env
@genType @genType
type genericDist = DistributionTypes.genericDist type genericDist = DistributionTypes.genericDist
@genType
type sampleSetDist = SampleSetDist.t
@genType
type symbolicDist = SymbolicDistTypes.symbolicDist
@genType @genType
type distributionError = DistributionTypes.error type distributionError = DistributionTypes.error
@ -34,6 +40,12 @@ let evaluate = Reducer.evaluate
@genType @genType
let evaluateUsingExternalBindings = Reducer.evaluateUsingExternalBindings let evaluateUsingExternalBindings = Reducer.evaluateUsingExternalBindings
@genType
let evaluatePartialUsingExternalBindings = Reducer.evaluatePartialUsingExternalBindings
@genType
type externalBindings = Reducer.externalBindings
@genType @genType
type expressionValue = ReducerInterface_ExpressionValue.expressionValue type expressionValue = ReducerInterface_ExpressionValue.expressionValue

View File

@ -1,4 +1,7 @@
open Rationale.Function.Infix /*
Some functions from modules `L`, `O`, and `R` below were copied directly from
running `rescript convert -all` on Rationale https://github.com/jonlaing/rationale
*/
module FloatFloatMap = { module FloatFloatMap = {
module Id = Belt.Id.MakeComparable({ module Id = Belt.Id.MakeComparable({
type t = float type t = float
@ -8,7 +11,7 @@ module FloatFloatMap = {
type t = Belt.MutableMap.t<Id.t, float, Id.identity> type t = Belt.MutableMap.t<Id.t, float, Id.identity>
let fromArray = (ar: array<(float, float)>) => Belt.MutableMap.fromArray(ar, ~id=module(Id)) let fromArray = (ar: array<(float, float)>) => Belt.MutableMap.fromArray(ar, ~id=module(Id))
let toArray = (t: t) => Belt.MutableMap.toArray(t) let toArray = (t: t): array<(float, float)> => Belt.MutableMap.toArray(t)
let empty = () => Belt.MutableMap.make(~id=module(Id)) let empty = () => Belt.MutableMap.make(~id=module(Id))
let increment = (el, t: t) => let increment = (el, t: t) =>
Belt.MutableMap.update(t, el, x => Belt.MutableMap.update(t, el, x =>
@ -20,6 +23,10 @@ module FloatFloatMap = {
let get = (el, t: t) => Belt.MutableMap.get(t, el) let get = (el, t: t) => Belt.MutableMap.get(t, el)
let fmap = (fn, t: t) => Belt.MutableMap.map(t, fn) let fmap = (fn, t: t) => Belt.MutableMap.map(t, fn)
let partition = (fn, t: t) => {
let (match, noMatch) = Belt.Array.partition(toArray(t), fn)
(fromArray(match), fromArray(noMatch))
}
} }
module Int = { module Int = {
@ -51,17 +58,59 @@ module O = {
| None => rFn() | None => rFn()
} }
() ()
let fmap = Rationale.Option.fmap let fmap = (f: 'a => 'b, x: option<'a>): option<'b> => {
let bind = Rationale.Option.bind switch x {
let default = Rationale.Option.default | None => None
let isSome = Rationale.Option.isSome | Some(x') => Some(f(x'))
let isNone = Rationale.Option.isNone }
let toExn = Rationale.Option.toExn }
let some = Rationale.Option.some let bind = (o, f) =>
let firstSome = Rationale.Option.firstSome switch o {
let toExt = Rationale.Option.toExn // wanna flag this-- looks like a typo but `Rationale.OptiontoExt` doesn't exist. | None => None
let flatApply = (fn, b) => Rationale.Option.apply(fn, Some(b)) |> Rationale.Option.flatten | Some(a) => f(a)
let flatten = Rationale.Option.flatten }
let default = (d, o) =>
switch o {
| None => d
| Some(a) => a
}
let isSome = o =>
switch o {
| Some(_) => true
| _ => false
}
let isNone = o =>
switch o {
| None => true
| _ => false
}
let toExn = (err, o) =>
switch o {
| None => raise(Failure(err))
| Some(a) => a
}
let some = a => Some(a)
let firstSome = (a, b) =>
switch a {
| None => b
| _ => a
}
let toExt = toExn
let flatten = o =>
switch o {
| None => None
| Some(x) => x
}
let apply = (o, a) =>
switch o {
| Some(f) => bind(a, b => some(f(b)))
| _ => None
}
let flatApply = (fn, b) => apply(fn, Some(b)) |> flatten
let toBool = opt => let toBool = opt =>
switch opt { switch opt {
@ -109,6 +158,11 @@ module O2 = {
/* Functions */ /* Functions */
module F = { module F = {
let pipe = (f, g, x) => g(f(x))
let compose = (f, g, x) => f(g(x))
let flip = (f, a, b) => f(b, a)
let always = (x, _y) => x
let apply = (a, e) => a |> e let apply = (a, e) => a |> e
let flatten2Callbacks = (fn1, fn2, fnlast) => let flatten2Callbacks = (fn1, fn2, fnlast) =>
@ -156,10 +210,31 @@ exception Assertion(string)
/* R for Result */ /* R for Result */
module R = { module R = {
let result = Rationale.Result.result open Belt.Result
let result = (okF, errF, r) =>
switch r {
| Ok(a) => okF(a)
| Error(err) => errF(err)
}
let id = e => e |> result(U.id, U.id) let id = e => e |> result(U.id, U.id)
let fmap = Rationale.Result.fmap let isOk = Belt.Result.isOk
let bind = Rationale.Result.bind let getError = (r: result<'a, 'b>) =>
switch r {
| Ok(_) => None
| Error(e) => Some(e)
}
let fmap = (f: 'a => 'b, r: result<'a, 'c>): result<'b, 'c> => {
switch r {
| Ok(r') => Ok(f(r'))
| Error(err) => Error(err)
}
}
let bind = (r, f) =>
switch r {
| Ok(a) => f(a)
| Error(err) => Error(err)
}
let toExn = (msg: string, x: result<'a, 'b>): 'a => let toExn = (msg: string, x: result<'a, 'b>): 'a =>
switch x { switch x {
| Ok(r) => r | Ok(r) => r
@ -186,14 +261,17 @@ module R = {
let errorIfCondition = (errorCondition, errorMessage, r) => let errorIfCondition = (errorCondition, errorMessage, r) =>
errorCondition(r) ? Error(errorMessage) : Ok(r) errorCondition(r) ? Error(errorMessage) : Ok(r)
let ap = Rationale.Result.ap let ap = (r, a) =>
switch r {
| Ok(f) => Ok(f(a))
| Error(err) => Error(err)
}
let ap' = (r, a) => let ap' = (r, a) =>
switch r { switch r {
| Ok(f) => fmap(f, a) | Ok(f) => fmap(f, a)
| Error(err) => Error(err) | Error(err) => Error(err)
} }
// (a1 -> a2 -> r) -> m a1 -> m a2 -> m r // not in Rationale
let liftM2: (('a, 'b) => 'c, result<'a, 'd>, result<'b, 'd>) => result<'c, 'd> = (op, xR, yR) => { let liftM2: (('a, 'b) => 'c, result<'a, 'd>, result<'b, 'd>) => result<'c, 'd> = (op, xR, yR) => {
ap'(fmap(op, xR), yR) ap'(fmap(op, xR), yR)
} }
@ -243,7 +321,7 @@ module S = {
} }
module J = { module J = {
let toString = \"||>"(Js.Json.decodeString, O.default("")) let toString = F.pipe(Js.Json.decodeString, O.default(""))
let fromString = Js.Json.string let fromString = Js.Json.string
let fromNumber = Js.Json.number let fromNumber = Js.Json.number
@ -256,7 +334,7 @@ module J = {
let toString = (str: option<'a>) => let toString = (str: option<'a>) =>
switch str { switch str {
| Some(str) => Some(str |> \"||>"(Js.Json.decodeString, O.default(""))) | Some(str) => Some(str |> F.pipe(Js.Json.decodeString, O.default("")))
| _ => None | _ => None
} }
} }
@ -271,34 +349,132 @@ module JsDate = {
/* List */ /* List */
module L = { module L = {
module Util = {
let eq = (a, b) => a == b
}
let fmap = List.map let fmap = List.map
let get = Belt.List.get let get = Belt.List.get
let toArray = Array.of_list let toArray = Array.of_list
let fmapi = List.mapi let fmapi = List.mapi
let concat = List.concat let concat = List.concat
let drop = Rationale.RList.drop let concat' = (xs, ys) => List.append(ys, xs)
let remove = Rationale.RList.remove
let rec drop = (i, xs) =>
switch (i, xs) {
| (_, list{}) => list{}
| (i, _) if i <= 0 => xs
| (i, list{_, ...b}) => drop(i - 1, b)
}
let append = (a, xs) => List.append(xs, list{a})
let take = {
let rec loop = (i, xs, acc) =>
switch (i, xs) {
| (i, _) if i <= 0 => acc
| (_, list{}) => acc
| (i, list{a, ...b}) => loop(i - 1, b, append(a, acc))
}
(i, xs) => loop(i, xs, list{})
}
let takeLast = (i, xs) => List.rev(xs) |> take(i) |> List.rev
let splitAt = (i, xs) => (take(i, xs), takeLast(List.length(xs) - i, xs))
let remove = (i, n, xs) => {
let (a, b) = splitAt(i, xs)
\"@"(a, drop(n, b))
}
let find = List.find let find = List.find
let filter = List.filter let filter = List.filter
let for_all = List.for_all let for_all = List.for_all
let exists = List.exists let exists = List.exists
let sort = List.sort let sort = List.sort
let length = List.length let length = List.length
let filter_opt = Rationale.RList.filter_opt
let uniqBy = Rationale.RList.uniqBy let filter_opt = xs => {
let join = Rationale.RList.join let rec loop = (l, acc) =>
let head = Rationale.RList.head switch l {
let uniq = Rationale.RList.uniq | list{} => acc
| list{hd, ...tl} =>
switch hd {
| None => loop(tl, acc)
| Some(x) => loop(tl, list{x, ...acc})
}
}
List.rev(loop(xs, list{}))
}
let containsWith = f => List.exists(f)
let uniqWithBy = (eq, f, xs) =>
List.fold_left(
((acc, tacc), v) =>
containsWith(eq(f(v)), tacc) ? (acc, tacc) : (append(v, acc), append(f(v), tacc)),
(list{}, list{}),
xs,
) |> fst
let uniqBy = (f, xs) => uniqWithBy(Util.eq, f, xs)
let join = j => List.fold_left((acc, v) => String.length(acc) == 0 ? v : acc ++ (j ++ v), "")
let head = xs =>
switch List.hd(xs) {
| exception _ => None
| a => Some(a)
}
let uniq = xs => uniqBy(x => x, xs)
let flatten = List.flatten let flatten = List.flatten
let last = Rationale.RList.last let last = xs => xs |> List.rev |> head
let append = List.append let append = List.append
let getBy = Belt.List.getBy let getBy = Belt.List.getBy
let dropLast = Rationale.RList.dropLast let dropLast = (i, xs) => take(List.length(xs) - i, xs)
let contains = Rationale.RList.contains let containsWith = f => List.exists(f)
let without = Rationale.RList.without let contains = x => containsWith(Util.eq(x))
let update = Rationale.RList.update
let reject = pred => List.filter(x => !pred(x))
let tail = xs =>
switch List.tl(xs) {
| exception _ => None
| a => Some(a)
}
let init = xs => {
O.fmap(List.rev, xs |> List.rev |> tail)
}
let singleton = (x: 'a): list<'a> => list{x}
let adjust = (f, i, xs) => {
let (a, b) = splitAt(i + 1, xs)
switch a {
| _ if i < 0 => xs
| _ if i >= List.length(xs) => xs
| list{} => b
| list{a} => list{f(a), ...b}
| a =>
O.fmap(
concat'(b),
O.bind(init(a), x =>
O.fmap(F.flip(append, x), O.fmap(fmap(f), O.fmap(singleton, last(a))))
),
) |> O.default(xs)
}
}
let without = (exclude, xs) => reject(x => contains(x, exclude), xs)
let update = (x, i, xs) => adjust(F.always(x), i, xs)
let iter = List.iter let iter = List.iter
let findIndex = Rationale.RList.findIndex
let findIndex = {
let rec loop = (pred, xs, i) =>
switch xs {
| list{} => None
| list{a, ...b} => pred(a) ? Some(i) : loop(pred, b, i + 1)
}
(pred, xs) => loop(pred, xs, 0)
}
let headSafe = Belt.List.head let headSafe = Belt.List.head
let tailSafe = Belt.List.tail let tailSafe = Belt.List.tail
let headExn = Belt.List.headExn let headExn = Belt.List.headExn
@ -360,7 +536,7 @@ module A = {
Belt.Array.getUnsafe(a, index), Belt.Array.getUnsafe(a, index),
Belt.Array.getUnsafe(a, index + 1), Belt.Array.getUnsafe(a, index + 1),
)) ))
|> Rationale.Result.return |> (x => Ok(x))
} }
let tail = Belt.Array.sliceToEnd(_, 1) let tail = Belt.Array.sliceToEnd(_, 1)
@ -424,8 +600,8 @@ module A = {
module O = { module O = {
let concatSomes = (optionals: array<option<'a>>): array<'a> => let concatSomes = (optionals: array<option<'a>>): array<'a> =>
optionals optionals
|> Js.Array.filter(Rationale.Option.isSome) |> Js.Array.filter(O.isSome)
|> Js.Array.map(Rationale.Option.toExn("Warning: This should not have happened")) |> Js.Array.map(O.toExn("Warning: This should not have happened"))
let defaultEmpty = (o: option<array<'a>>): array<'a> => let defaultEmpty = (o: option<array<'a>>): array<'a> =>
switch o { switch o {
| Some(o) => o | Some(o) => o
@ -475,76 +651,8 @@ module A = {
} }
} }
module Sorted = {
let min = first
let max = last
let range = (~min=min, ~max=max, a) =>
switch (min(a), max(a)) {
| (Some(min), Some(max)) => Some(max -. min)
| _ => None
}
let floatCompare: (float, float) => int = compare
let binarySearchFirstElementGreaterIndex = (ar: array<'a>, el: 'a) => {
let el = Belt.SortArray.binarySearchBy(ar, el, floatCompare)
let el = el < 0 ? el * -1 - 1 : el
switch el {
| e if e >= length(ar) => #overMax
| e if e == 0 => #underMin
| e => #firstHigher(e)
}
}
let concat = (t1: array<'a>, t2: array<'a>) => {
let ts = Belt.Array.concat(t1, t2)
ts |> Array.fast_sort(floatCompare)
ts
}
let concatMany = (t1: array<array<'a>>) => {
let ts = Belt.Array.concatMany(t1)
ts |> Array.fast_sort(floatCompare)
ts
}
module Floats = {
let isSorted = (ar: array<float>): bool =>
reduce(zip(ar, tail(ar)), true, (acc, (first, second)) => acc && first < second)
let makeIncrementalUp = (a, b) =>
Array.make(b - a + 1, a) |> Array.mapi((i, c) => c + i) |> Belt.Array.map(_, float_of_int)
let makeIncrementalDown = (a, b) =>
Array.make(a - b + 1, a) |> Array.mapi((i, c) => c - i) |> Belt.Array.map(_, float_of_int)
let split = (sortedArray: array<float>) => {
let continuous = []
let discrete = FloatFloatMap.empty()
Belt.Array.forEachWithIndex(sortedArray, (_, element) => {
// let maxIndex = (sortedArray |> Array.length) - 1
// let possiblySimilarElements = switch index {
// | 0 => [index + 1]
// | n if n == maxIndex => [index - 1]
// | _ => [index - 1, index + 1]
// } |> Belt.Array.map(_, r => sortedArray[r])
// let hasSimilarElement = Belt.Array.some(possiblySimilarElements, r => r == element)
let hasSimilarElement = false
hasSimilarElement
? FloatFloatMap.increment(element, discrete)
: {
let _ = Js.Array.push(element, continuous)
}
()
})
(continuous, discrete)
}
}
}
module Floats = { module Floats = {
type t = array<float>
let mean = Jstat.mean let mean = Jstat.mean
let geomean = Jstat.geomean let geomean = Jstat.geomean
let mode = Jstat.mode let mode = Jstat.mode
@ -553,14 +661,31 @@ module A = {
let sum = Jstat.sum let sum = Jstat.sum
let random = Js.Math.random_int let random = Js.Math.random_int
let floatCompare: (float, float) => int = compare
let sort = t => {
let r = t
r |> Array.fast_sort(floatCompare)
r
}
let getNonFinite = (t: t) => Belt.Array.getBy(t, r => !Js.Float.isFinite(r))
let getBelowZero = (t: t) => Belt.Array.getBy(t, r => r < 0.0)
let isSorted = (t: t): bool =>
if Array.length(t) < 1 {
true
} else {
reduce(zip(t, tail(t)), true, (acc, (first, second)) => acc && first < second)
}
//Passing true for the exclusive parameter excludes both endpoints of the range. //Passing true for the exclusive parameter excludes both endpoints of the range.
//https://jstat.github.io/all.html //https://jstat.github.io/all.html
let percentile = (a, b) => Jstat.percentile(a, b, false) let percentile = (a, b) => Jstat.percentile(a, b, false)
// Gives an array with all the differences between values // Gives an array with all the differences between values
// diff([1,5,3,7]) = [4,-2,4] // diff([1,5,3,7]) = [4,-2,4]
let diff = (arr: array<float>): array<float> => let diff = (t: t): array<float> =>
Belt.Array.zipBy(arr, Belt.Array.sliceToEnd(arr, 1), (left, right) => right -. left) Belt.Array.zipBy(t, Belt.Array.sliceToEnd(t, 1), (left, right) => right -. left)
exception RangeError(string) exception RangeError(string)
let range = (min: float, max: float, n: int): array<float> => let range = (min: float, max: float, n: int): array<float> =>
@ -578,18 +703,104 @@ module A = {
let min = Js.Math.minMany_float let min = Js.Math.minMany_float
let max = Js.Math.maxMany_float let max = Js.Math.maxMany_float
module Sorted = {
let min = first
let max = last
let range = (~min=min, ~max=max, a) =>
switch (min(a), max(a)) {
| (Some(min), Some(max)) => Some(max -. min)
| _ => None
}
let binarySearchFirstElementGreaterIndex = (ar: array<'a>, el: 'a) => {
let el = Belt.SortArray.binarySearchBy(ar, el, floatCompare)
let el = el < 0 ? el * -1 - 1 : el
switch el {
| e if e >= length(ar) => #overMax
| e if e == 0 => #underMin
| e => #firstHigher(e)
}
}
let concat = (t1: array<'a>, t2: array<'a>) => Belt.Array.concat(t1, t2)->sort
let concatMany = (t1: array<array<'a>>) => Belt.Array.concatMany(t1)->sort
let makeIncrementalUp = (a, b) =>
Array.make(b - a + 1, a) |> Array.mapi((i, c) => c + i) |> Belt.Array.map(_, float_of_int)
let makeIncrementalDown = (a, b) =>
Array.make(a - b + 1, a) |> Array.mapi((i, c) => c - i) |> Belt.Array.map(_, float_of_int)
/*
This function goes through a sorted array and divides it into two different clusters:
continuous samples and discrete samples. The discrete samples are stored in a mutable map.
Samples are thought to be discrete if they have any duplicates.
*/
let _splitContinuousAndDiscreteForDuplicates = (sortedArray: array<float>) => {
let continuous: array<float> = []
let discrete = FloatFloatMap.empty()
Belt.Array.forEachWithIndex(sortedArray, (index, element) => {
let maxIndex = (sortedArray |> Array.length) - 1
let possiblySimilarElements = switch index {
| 0 => [index + 1]
| n if n == maxIndex => [index - 1]
| _ => [index - 1, index + 1]
} |> Belt.Array.map(_, r => sortedArray[r])
let hasSimilarElement = Belt.Array.some(possiblySimilarElements, r => r == element)
hasSimilarElement
? FloatFloatMap.increment(element, discrete)
: {
let _ = Js.Array.push(element, continuous)
}
()
})
(continuous, discrete)
}
/*
This function works very similarly to splitContinuousAndDiscreteForDuplicates. The one major difference
is that you can specify a minDiscreteWeight. If the min discreet weight is 4, that would mean that
at least four elements needed from a specific value for that to be kept as discrete. This is important
because in some cases, we can expect that some common elements will be generated by regular operations.
The final continous array will be sorted.
*/
let splitContinuousAndDiscreteForMinWeight = (
sortedArray: array<float>,
~minDiscreteWeight: int,
) => {
let (continuous, discrete) = _splitContinuousAndDiscreteForDuplicates(sortedArray)
let keepFn = v => Belt.Float.toInt(v) >= minDiscreteWeight
let (discreteToKeep, discreteToIntegrate) = FloatFloatMap.partition(
((_, v)) => keepFn(v),
discrete,
)
let newContinousSamples =
discreteToIntegrate->FloatFloatMap.toArray
|> fmap(((k, v)) => Belt.Array.makeBy(Belt.Float.toInt(v), _ => k))
|> Belt.Array.concatMany
let newContinuous = concat(continuous, newContinousSamples)
newContinuous |> Array.fast_sort(floatCompare)
(newContinuous, discreteToKeep)
}
}
} }
module Sorted = Floats.Sorted
} }
module A2 = { module A2 = {
let fmap = (a, b) => A.fmap(b, a) let fmap = (a, b) => A.fmap(b, a)
let joinWith = (a, b) => A.joinWith(b, a) let joinWith = (a, b) => A.joinWith(b, a)
let filter = (a, b) => A.filter(b, a)
} }
module JsArray = { module JsArray = {
let concatSomes = (optionals: Js.Array.t<option<'a>>): Js.Array.t<'a> => let concatSomes = (optionals: Js.Array.t<option<'a>>): Js.Array.t<'a> =>
optionals optionals
|> Js.Array.filter(Rationale.Option.isSome) |> Js.Array.filter(O.isSome)
|> Js.Array.map(Rationale.Option.toExn("Warning: This should not have happened")) |> Js.Array.map(O.toExn("Warning: This should not have happened"))
let filter = Js.Array.filter let filter = Js.Array.filter
} }

View File

@ -29,6 +29,18 @@ type distToFloatOperation = [
module Convolution = { module Convolution = {
type t = convolutionOperation type t = convolutionOperation
//Only a selection of operations are supported by convolution.
let fromAlgebraicOperation = (op: algebraicOperation): option<convolutionOperation> =>
switch op {
| #Add => Some(#Add)
| #Subtract => Some(#Subtract)
| #Multiply => Some(#Multiply)
| #Divide | #Power | #Logarithm => None
}
let canDoAlgebraicOperation = (op: algebraicOperation): bool =>
fromAlgebraicOperation(op)->E.O.isSome
let toFn: (t, float, float) => float = x => let toFn: (t, float, float) => float = x =>
switch x { switch x {
| #Add => \"+." | #Add => \"+."

View File

@ -4,6 +4,42 @@ type xyShape = {
ys: array<float>, ys: array<float>,
} }
type propertyName = string
@genType
type rec error =
| NotSorted(propertyName)
| IsEmpty(propertyName)
| NotFinite(propertyName, float)
| DifferentLengths({p1Name: string, p2Name: string, p1Length: int, p2Length: int})
| MultipleErrors(array<error>)
@genType
module Error = {
let mapErrorArrayToError = (errors: array<error>): option<error> => {
switch errors {
| [] => None
| [error] => Some(error)
| _ => Some(MultipleErrors(errors))
}
}
let rec toString = (t: error) =>
switch t {
| NotSorted(propertyName) => `${propertyName} is not sorted`
| IsEmpty(propertyName) => `${propertyName} is empty`
| NotFinite(propertyName, exampleValue) =>
`${propertyName} is not finite. Example value: ${E.Float.toString(exampleValue)}`
| DifferentLengths({p1Name, p2Name, p1Length, p2Length}) =>
`${p1Name} and ${p2Name} have different lengths. ${p1Name} has length ${E.I.toString(
p1Length,
)} and ${p2Name} has length ${E.I.toString(p2Length)}`
| MultipleErrors(errors) =>
`Multiple Errors: ${E.A2.fmap(errors, toString)->E.A2.fmap(r => `[${r}]`)
|> E.A.joinWith(", ")}`
}
}
@genType @genType
type interpolationStrategy = [ type interpolationStrategy = [
| #Stepwise | #Stepwise
@ -60,6 +96,44 @@ module T = {
let fromZippedArray = (pairs: array<(float, float)>): t => pairs |> Belt.Array.unzip |> fromArray let fromZippedArray = (pairs: array<(float, float)>): t => pairs |> Belt.Array.unzip |> fromArray
let equallyDividedXs = (t: t, newLength) => E.A.Floats.range(minX(t), maxX(t), newLength) let equallyDividedXs = (t: t, newLength) => E.A.Floats.range(minX(t), maxX(t), newLength)
let toJs = (t: t) => {"xs": t.xs, "ys": t.ys} let toJs = (t: t) => {"xs": t.xs, "ys": t.ys}
module Validator = {
let fnName = "XYShape validate"
let notSortedError = (p: string): error => NotSorted(p)
let notFiniteError = (p, exampleValue): error => NotFinite(p, exampleValue)
let isEmptyError = (propertyName): error => IsEmpty(propertyName)
let differentLengthsError = (t): error => DifferentLengths({
p1Name: "Xs",
p2Name: "Ys",
p1Length: E.A.length(xs(t)),
p2Length: E.A.length(ys(t)),
})
let areXsSorted = (t: t) => E.A.Floats.isSorted(xs(t))
let areXsEmpty = (t: t) => E.A.length(xs(t)) == 0
let getNonFiniteXs = (t: t) => t->xs->E.A.Floats.getNonFinite
let getNonFiniteYs = (t: t) => t->ys->E.A.Floats.getNonFinite
let validate = (t: t) => {
let xsNotSorted = areXsSorted(t) ? None : Some(notSortedError("Xs"))
let xsEmpty = areXsEmpty(t) ? Some(isEmptyError("Xs")) : None
let differentLengths =
E.A.length(xs(t)) !== E.A.length(ys(t)) ? Some(differentLengthsError(t)) : None
let xsNotFinite = getNonFiniteXs(t)->E.O2.fmap(notFiniteError("Xs"))
let ysNotFinite = getNonFiniteYs(t)->E.O2.fmap(notFiniteError("Ys"))
[xsNotSorted, xsEmpty, differentLengths, xsNotFinite, ysNotFinite]
->E.A.O.concatSomes
->Error.mapErrorArrayToError
}
}
let make = (~xs: array<float>, ~ys: array<float>) => {
let attempt: t = {xs: xs, ys: ys}
switch Validator.validate(attempt) {
| Some(error) => Error(error)
| None => Ok(attempt)
}
}
} }
module Ts = { module Ts = {

View File

@ -0,0 +1,7 @@
---
sidebar_position: 6
title: Gallery
---
- [Adjusting probabilities for the passage of time](https://www.lesswrong.com/s/rDe8QE5NvXcZYzgZ3/p/j8o6sgRerE3tqNWdj) by Nuño Sempere
- [GiveWell's GiveDirectly cost effectiveness analysis](https://observablehq.com/@hazelfire/givewells-givedirectly-cost-effectiveness-analysis) by Sam Nolan

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@ -1,12 +1,10 @@
--- ---
sidebar_position: 5 sidebar_position: 5
title: Three Formats of Distributions
author: Ozzie Gooen
date: 02-19-2022
--- ---
# Three Formats of Distributions
_Author: Ozzie Gooen_
_Written on: Feb 19, 2022_
Probability distributions have several subtle possible formats. Three important ones that we deal with in Squiggle are symbolic, sample set, and graph formats. Probability distributions have several subtle possible formats. Three important ones that we deal with in Squiggle are symbolic, sample set, and graph formats.
_Symbolic_ formats are just the math equations. `normal(5,3)` is the symbolic representation of a normal distribution. _Symbolic_ formats are just the math equations. `normal(5,3)` is the symbolic representation of a normal distribution.

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@ -1,39 +1,53 @@
--- ---
sidebar_position: 2 sidebar_position: 2
title: Language Basics
--- ---
import { SquiggleEditor } from "../../src/components/SquiggleEditor"; import { SquiggleEditor } from "../../src/components/SquiggleEditor";
# Squiggle Language ## Expressions
The squiggle language has a very simple syntax. The best way to get to understand A distribution
it is by simply looking at examples.
## Basic Language <SquiggleEditor initialSquiggleString={`mixture(1 to 2, 3, [0.3, 0.7])`} />
As an example: A number
<SquiggleEditor initialSquiggleString="4.321e-3" />
Arrays
<SquiggleEditor
initialSquiggleString={`[beta(1,10), 4, isNormalized(toSampleSet(1 to 2))]`}
/>
Records
<SquiggleEditor
initialSquiggleString={`d = {dist: triangular(0, 1, 2), weight: 0.25}
d.dist`}
/>
## Statements
A statement assigns expressions to names. It looks like `<symbol> = <expression>`
<SquiggleEditor <SquiggleEditor
initialSquiggleString={`value_of_work = 10 to 70 initialSquiggleString={`value_of_work = 10 to 70
value_of_work`} 5 + value_of_work / 75`}
/> />
Squiggle can declare variables (`value_of_work = 10 to 70`) and declare exports ### Functions
(the lone `value_of_work` line). Variables can be used later in a squiggle program
and even in other notebooks!
An export is rendered to the output view so you can see your result. We can define functions
the exports can be expressions, such as:
<SquiggleEditor initialSquiggleString="normal(0,1)" />
## Functions
Squiggle supports functions, including the rendering of functions:
<SquiggleEditor <SquiggleEditor
initialSquiggleString={`ozzie_estimate(t) = lognormal({mean: 3 + (t+.1)^2.5, stdev: 8}) initialSquiggleString={`ozzie_estimate(t) = lognormal(1, t ^ 1.01)
ozzie_estimate nuño_estimate(t, m) = mixture(0.5 to 2, normal(m, t ^ 1.25))
`} ozzie_estimate(5) * nuño_estimate(5.01, 1)`}
/> />
## See more
- [Functions reference](https://squiggle-language.com/docs/Features/Functions)
- [Gallery](https://squiggle-language.com/docs/Discussions/Gallery)

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@ -1,13 +1,12 @@
--- ---
sidebar_position: 3 sidebar_position: 3
title: Node Packages
--- ---
# Javascript Libraries
There are two JavaScript packages currently available for Squiggle: There are two JavaScript packages currently available for Squiggle:
- [`@quri/squiggle-lang`](https://www.npmjs.com/package/@quri/squiggle-lang) - [`@quri/squiggle-lang`](https://www.npmjs.com/package/@quri/squiggle-lang) ![npm version](https://badge.fury.io/js/@quri%2Fsquiggle-lang.svg)
- [`@quri/squiggle-components`](https://www.npmjs.com/package/@quri/squiggle-components) - [`@quri/squiggle-components`](https://www.npmjs.com/package/@quri/squiggle-components) ![npm version](https://badge.fury.io/js/@quri%2Fsquiggle-components.svg)
Types are available for both packages. Types are available for both packages.
@ -23,8 +22,8 @@ argument allows you to pass an environment previously created by another `run`
call. Passing this environment will mean that all previously declared variables call. Passing this environment will mean that all previously declared variables
in the previous environment will be made available. in the previous environment will be made available.
The return type of `run` is a bit complicated, and comes from auto generated js The return type of `run` is a bit complicated, and comes from auto generated `js`
code that comes from rescript. I highly recommend using typescript when using code that comes from rescript. We highly recommend using typescript when using
this library to help navigate the return type. this library to help navigate the return type.
## Squiggle Components ## Squiggle Components

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@ -1,6 +1,9 @@
# Processing confidence intervals ---
title: Processing Confidence Intervals
author: Nuño Sempere
---
This page explains what we are doing when we take a 95% confidence interval, and we get a mean and a standard deviation from it This page explains what we are doing when we take a 90% confidence interval, and we get a mean and a standard deviation from it.
## For normals ## For normals
@ -19,10 +22,7 @@ module Normal = {
We know that for a normal with mean $\mu$ and standard deviation $\sigma$, We know that for a normal with mean $\mu$ and standard deviation $\sigma$,
$$ $$
a \cdot Normal(\mu, \sigma) = Normal(a \cdot \mu, |a| \cdot \sigma)
a \cdot Normal(\mu, \sigma) = Normal(a\cdot \mu, |a|\cdot \sigma)
$$ $$
We can now look at the inverse cdf of a $Normal(0,1)$. We find that the 95% point is reached at $1.6448536269514722$. ([source](https://stackoverflow.com/questions/20626994/how-to-calculate-the-inverse-of-the-normal-cumulative-distribution-function-in-p)) This means that the 90% confidence interval is $[-1.6448536269514722, 1.6448536269514722]$, which has a width of $2 \cdot 1.6448536269514722$. We can now look at the inverse cdf of a $Normal(0,1)$. We find that the 95% point is reached at $1.6448536269514722$. ([source](https://stackoverflow.com/questions/20626994/how-to-calculate-the-inverse-of-the-normal-cumulative-distribution-function-in-p)) This means that the 90% confidence interval is $[-1.6448536269514722, 1.6448536269514722]$, which has a width of $2 \cdot 1.6448536269514722$.
@ -30,3 +30,5 @@ We can now look at the inverse cdf of a $Normal(0,1)$. We find that the 95% poin
So then, if we take a $Normal(0,1)$ and we multiply it by $\frac{(high -. low)}{(2. *. 1.6448536269514722)}$, it's 90% confidence interval will be multiplied by the same amount. Then we just have to shift it by the mean to get our target normal. So then, if we take a $Normal(0,1)$ and we multiply it by $\frac{(high -. low)}{(2. *. 1.6448536269514722)}$, it's 90% confidence interval will be multiplied by the same amount. Then we just have to shift it by the mean to get our target normal.
## For lognormals ## For lognormals
TODO

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@ -1,10 +1,16 @@
--- ---
sidebar_position: 1 sidebar_position: 1
title: Introduction
--- ---
# Squiggle Squiggle is an _estimation language_, and a syntax for _calculating and expressing beliefs_ involving uncertainty. It has use cases in forecasting and writing evaluations.
Squiggle is a language for writing calculations under uncertainty. It has use ## Get started
cases in forecasting and writing better evaluations.
The best way to get started with Squiggle is to [try it out yourself](https://playground.squiggle-language.com/). - [Gallery](https://www.squiggle-language.com/docs/Discussions/Gallery)
- [Squiggle playground](https://squiggle-language.com/playground)
- [Language basics](https://www.squiggle-language.com/docs/Features/Language)
- [Squiggle functions source of truth](https://www.squiggle-language.com/docs/Features/Functions)
- [Known bugs](https://www.squiggle-language.com/docs/Discussions/Bugs)
- [Original lesswrong sequence](https://www.lesswrong.com/s/rDe8QE5NvXcZYzgZ3)
- [Author your squiggle models as Observable notebooks](https://observablehq.com/@hazelfire/squiggle)

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