Merge pull request #873 from quantified-uncertainty/homepage-changes

Docs improvements - July 23
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Ozzie Gooen 2022-07-23 11:54:16 -07:00 committed by GitHub
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14 changed files with 140 additions and 102 deletions

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@ -43,7 +43,7 @@ could be continuous, discrete or mixed.
<Story
name="Continuous Pointset"
args={{
code: "toPointSet(normal(5,2))",
code: "PointSet.fromDist(normal(5,2))",
width,
}}
>
@ -57,7 +57,7 @@ could be continuous, discrete or mixed.
<Story
name="Continuous SampleSet"
args={{
code: "toSampleSet(normal(5,2), 1000)",
code: "SampleSet.fromDist(normal(5,2))",
width,
}}
>

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@ -339,7 +339,7 @@ A log loss score. Often that often acts as a [scoring rule](https://en.wikipedia
Note that it is fairly slow.
```
logScore: ({estimate: distribution, ?prior: distribution, answer: distribution|number}) => number
Dist.logScore: ({estimate: distribution, ?prior: distribution, answer: distribution|number}) => number
```
**Examples**

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@ -38,7 +38,7 @@ Gets the internal samples of a sampleSet distribution. This is separate from the
**Examples**
```
toList(toSampleSet(normal(5,2)))
toList(SampleSet.fromDist(normal(5,2)))
```
### map

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@ -31,6 +31,6 @@ The means of sample set distributions can vary dramatically, especially as the n
<SquiggleEditor
defaultCode={`symbolicDist = 5 to 50333333
sampleSetDist = toSampleSet(symbolicDist)
sampleSetDist = SampleSet.fromDist(symbolicDist)
[mean(symbolicDist), mean(sampleSetDist), symbolicDist, sampleSetDist]`}
/>

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@ -23,12 +23,6 @@ Squiggle is still very early. The main first goal is to become stable. This mean
## Distribution Features
`Distribution.fromSamples([])`
Converts a list of samples, for example, from Guesstimate, into a distribution shape. Maybe takes a list of optional parameters.
`Distribution.fromCoordinates({xs, ys})`
Convert XY coordinates into a distribution. Figure out a good way to do this for continuous, discrete, and mixed distributions.
[Metalog Distribution](https://en.wikipedia.org/wiki/Metalog_distribution)
Add the Metalog distribution, and some convenient methods for generating these distributions. This might be a bit tricky because we might need or build a library to fit data. There's no Metalog javascript library yet, this would be pretty useful. There's already a Metalog library in Python, so that one could be used for inspiration.

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@ -343,13 +343,13 @@ Creates a [triangular distribution](https://en.wikipedia.org/wiki/Triangular_dis
<SquiggleEditor defaultCode="triangular(1, 2, 4)" />
## FromSamples
## FromList
`fromSamples(samples:number[])`
`SampleSet.fromList(samples:number[])`
Creates a sample set distribution using an array of samples.
<SquiggleEditor defaultCode="fromSamples([1,2,3,4,6,5,5,5])" />
<SquiggleEditor defaultCode="SampleSet.fromList([1,2,3,4,6,5,5,5])" />
### Arguments

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@ -47,7 +47,7 @@ dist1 * dist2`}
We also provide concatenation of two distributions as a syntax sugar for `*`
<SquiggleEditor defaultCode="(0.1 to 1) triangular(1,2,3)" />
<SquiggleEditor defaultCode="(0.1 to 1) * triangular(1,2,3)" />
### Division
@ -87,18 +87,11 @@ A projection over a stretched x-axis.
log(dist)`}
/>
<SquiggleEditor
defaultCode={`dist = beta(1,2)
log10(dist)`}
/>
<SquiggleEditor defaultCode={`log10(5 to 10)`} />
Base `x`
<SquiggleEditor
defaultCode={`x = 2
dist = beta(2,3)
log(dist, x)`}
/>
<SquiggleEditor defaultCode={`log(5 to 10, 2)`} />
#### Validity
@ -113,45 +106,25 @@ For every point on the x-axis, operate the corresponding points in the y axis of
TODO: this isn't in the new interpreter/parser yet.
<SquiggleEditor
defaultCode={`dist1 = 1 to 10
dist2 = triangular(1,2,3)
dist1 .+ dist2`}
/>
<SquiggleEditor defaultCode={`(1 to 10) .+ triangular(1,2,3)`} />
### Pointwise subtraction
TODO: this isn't in the new interpreter/parser yet.
<SquiggleEditor
defaultCode={`dist1 = 1 to 10
dist2 = triangular(1,2,3)
dist1 .- dist2`}
/>
<SquiggleEditor defaultCode={`(1 to 10) .- triangular(1,2,3)`} />
### Pointwise multiplication
<SquiggleEditor
defaultCode={`dist1 = 1 to 10
dist2 = triangular(1,2,3)
dist1 .* dist2`}
/>
<SquiggleEditor defaultCode={`(1 to 10) .* triangular(1,2,3)`} />
### Pointwise division
<SquiggleEditor
defaultCode={`dist1 = uniform(0,20)
dist2 = normal(10,8)
dist1 ./ dist2`}
/>
<SquiggleEditor defaultCode={`(uniform(0,10)) ./ normal(10,4)`} />
### Pointwise exponentiation
<SquiggleEditor
defaultCode={`dist1 = 1 to 10
dist2 = triangular(1,2,3)
dist1 .^ dist2`}
/>
<SquiggleEditor defaultCode={`(1 to 10) .^ triangular(1,2,3)`} />
## Standard functions on distributions
@ -208,21 +181,15 @@ The `sample(distribution)` samples a given distribution.
Recall the [three formats of distributions](https://develop--squiggle-documentation.netlify.app/docs/Discussions/Three-Types-Of-Distributions). We can force any distribution into `SampleSet` format
<SquiggleEditor defaultCode="toSampleSet(normal(5, 10))" />
<SquiggleEditor defaultCode="PointSet.fromDist(normal(5, 10))" />
Or `PointSet` format
<SquiggleEditor defaultCode="toPointSet(normal(5, 10))" />
### `toSampleSet` has two signatures
Above, we saw the unary `toSampleSet`, which uses an internal hardcoded number of samples. If you'd like to provide the number of samples, it has a binary signature as well (floored)
<SquiggleEditor defaultCode="[toSampleSet(0.1 to 1, 100.1), toSampleSet(0.1 to 1, 5000), toSampleSet(0.1 to 1, 20000)]" />
<SquiggleEditor defaultCode="PointSet.fromDist(normal(5, 10))" />
#### Validity
- Second argument to `toSampleSet` must be a number.
- Second argument to `SampleSet.fromDist` must be a number.
## Normalization
@ -246,7 +213,7 @@ We provide a predicate `isNormalized`, for when we have simple control flow
You may like to debug by right clicking your browser and using the _inspect_ functionality on the webpage, and viewing the _console_ tab. Then, wrap your squiggle output with `inspect` to log an internal representation.
<SquiggleEditor defaultCode="inspect(toSampleSet(0.1 to 1, 100))" />
<SquiggleEditor defaultCode="inspect(SampleSet.fromDist(0.1 to 1))" />
Save for a logging side effect, `inspect` does nothing to input and returns it.

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@ -7,46 +7,46 @@ import { SquiggleEditor } from "../../src/components/SquiggleEditor";
## Expressions
### Distributions
<SquiggleEditor defaultCode={`mixture(1 to 2, 3, [0.3, 0.7])`} />
### Numbers
<SquiggleEditor defaultCode="4.32" />
### Arrays
### Distributions
<SquiggleEditor
defaultCode={`[beta(1,10), 4, isNormalized(toSampleSet(1 to 2))]`}
defaultCode={`a = normal(4,2)
b = 30 to 50
c = lognormal({mean:90, stdev: 7})
d = mixture(a,b,c, [0.3, 0.3, .4])
{a:a, b:b, c:c, d:d}`}
/>
### Records
### Lists
<SquiggleEditor
defaultCode={`[beta(1,10), 4, isNormalized(SampleSet.fromDist(1 to 2))]`}
/>
<SquiggleEditor defaultCode={`List.make(5,1)`} />
### Dictionaries
<SquiggleEditor
defaultCode={`d = {dist: triangular(0, 1, 2), weight: 0.25}
d.dist`}
/>
## Statements
A statement assigns expressions to names. It looks like `<symbol> = <expression>`
<SquiggleEditor
defaultCode={`value_of_work = 10 to 70
5 + value_of_work / 75`}
/>
### Functions
We can define functions
<SquiggleEditor
defaultCode={`ozzie_estimate(t) = lognormal(t^(1.1), 0.5)
nuno_estimate(t, m) = mixture(normal(-5, 1), lognormal(m, t / 1.25))
ozzie_estimate(1) * nuno_estimate(1, 1)`}
defaultCode={`f(t) = normal(t^2, t^1.2+.01)
f`}
/>
### Anonymous Functions
<SquiggleEditor defaultCode={`{|t| normal(t^2, t^1.2+.01)}`} />
## See more
- [Distribution creation](./DistributionCreation)

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@ -3,7 +3,21 @@ sidebar_position: 1
title: Introduction
---
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 simple programming language for intuitive probabilistic estimation. It's meant for quantitative forecasting and evaluations.
The basics of Squiggle can be pretty simple and intuitive. The more advanced functionality can take some time to learn.
## What Squiggle Is
- A simple programming language for doing math with probability distributions
- An embeddable language that can be used in Javascript applications
- A tool to embed functions as forecasts that can be embedded in other applications
## What Squiggle Is Not
- A complete replacement for enterprise Risk Analysis tools (See Crystal Ball, @Risk, Lumina Analytica)
- A Probabilistic Programming Language with backwards inference and sophisticated sampling algorithms. (See [PPLs](https://en.wikipedia.org/wiki/Probabilistic_programming))
- A visual tool aimed at casual users (see Guesstimate, Causal)
## Get started

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@ -10,7 +10,8 @@ const path = require("path");
/** @type {import('@docusaurus/types').Config} */
const config = {
title: "Squiggle",
tagline: "An estimation language for forecasters",
tagline:
"A simple programming language for intuitive probabilistic estimation",
url: "https://squiggle-language.com",
baseUrl: "/",
onBrokenLinks: "throw",
@ -72,6 +73,11 @@ const config = {
},
{ to: "/blog", label: "Blog", position: "left" },
{ to: "/playground", label: "Playground", position: "left" },
{
href: "https://github.com/quantified-uncertainty/squiggle/discussions",
label: "Issues & Discussion",
position: "right",
},
{
href: "https://github.com/quantified-uncertainty/squiggle",
label: "GitHub",

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@ -5,6 +5,11 @@
width: 100%;
}
.features h3 {
font-family: "Lora", serif;
font-size: 1.5em;
}
.featureSvg {
height: 200px;
width: 200px;

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@ -4,27 +4,29 @@
* work well for content-centric websites.
*/
@import url("https://fonts.googleapis.com/css2?family=Inter:wght@300;400;600&family=Lato:wght@100;400;700;900&family=Lora:wght@400;500;600&display=swap");
/* You can override the default Infima variables here. */
:root {
--ifm-color-primary: #2488df;
--ifm-color-primary-dark: #176fcd;
--ifm-color-primary-darker: #1f58cb;
--ifm-color-primary-darkest: #1e2672;
--ifm-color-primary-light: #49acd3;
--ifm-color-primary-lighter: #4fb1c7;
--ifm-color-primary-lightest: #3dbfd3;
--ifm-color-primary: #e74c0f;
--ifm-color-primary-dark: #bb4b05;
--ifm-color-primary-darker: #9d0c02;
--ifm-color-primary-darkest: #5d2200;
--ifm-color-primary-light: #e6a036;
--ifm-color-primary-lighter: #e79d1d;
--ifm-color-primary-lightest: #f5e191;
--ifm-code-font-size: 95%;
}
/* For readability concerns, you should choose a lighter palette in dark mode. */
html[data-theme="dark"] {
--ifm-color-primary: #25c2a0;
--ifm-color-primary-dark: #21af90;
--ifm-color-primary-darker: #1fa588;
--ifm-color-primary-darkest: #1a8870;
--ifm-color-primary-light: #29d5b0;
--ifm-color-primary-lighter: #32d8b4;
--ifm-color-primary-lightest: #4fddbf;
--ifm-color-primary: #df774d;
--ifm-color-primary-dark: #db8651;
--ifm-color-primary-darker: #d7584f;
--ifm-color-primary-darkest: #b3693e;
--ifm-color-primary-light: #edb25a;
--ifm-color-primary-lighter: #ebd489;
--ifm-color-primary-lightest: #faf2d4;
}
.docusaurus-highlight-code-line {
@ -37,3 +39,55 @@ html[data-theme="dark"] {
html[data-theme="dark"] .docusaurus-highlight-code-line {
background-color: rgba(0, 0, 0, 0.3);
}
.hero h1 {
font-size: 4em;
font-weight: 900;
margin-bottom: 0.5rem;
color: rgb(230, 72, 79);
font-family: "Lato", sans-serif;
}
.navbar__title {
font-family: "Lato", sans-serif;
font-weight: 900;
color: rgb(205, 88, 53);
}
.hero__subtitle {
color: #888;
font-size: 1.25em;
}
.hero__subtitle2 {
color: #ba3e3e;
font-size: 1.5em;
font-family: "Lora";
font-weight: 500;
margin-top: 1em;
margin-left: auto;
margin-right: auto;
max-width: 500px;
}
h1 {
font-family: "Lora", serif;
font-size: 2.5em;
}
h2 {
font-weight: 600;
}
.menu__link,
.navbar__item {
font-family: "Lora", serif;
}
.navbar__item {
font-weight: 700;
}
:root {
/* --ifm-font-family-base: 'Lora'; */
}

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@ -12,11 +12,8 @@ function HomepageHeader() {
<header className={clsx("hero hero--primary", styles.heroBanner)}>
<div className="container">
<h1 className="hero__title">{siteConfig.title}</h1>
<p className="hero__subtitle">
<i>Early access</i>
</p>
<p className="hero__subtitle">{siteConfig.tagline}</p>
<div className={styles.buttons}></div>
<p className="hero__subtitle">Early Access</p>
<p className="hero__subtitle2">{siteConfig.tagline}</p>
</div>
</header>
);

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@ -4,10 +4,11 @@
*/
.heroBanner {
padding: 4rem 0;
padding: 2rem 0;
text-align: center;
position: relative;
overflow: hidden;
background: rgb(255, 246, 237);
}
@media screen and (max-width: 966px) {