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This commit is contained in:
Ozzie Gooen 2022-05-03 11:06:53 -04:00
parent f41f6617df
commit b28df258e1
2 changed files with 25 additions and 8 deletions

View File

@ -230,7 +230,7 @@ module Float = {
let inv = (p, t: t) => p < t ? 0.0 : 1.0
let mean = (t: t) => Ok(t)
let sample = (t: t) => t
let toString = Js.Float.toString
let toString = (t:t) => j`Delta($t)`
}
module From90thPercentile = {

View File

@ -220,9 +220,12 @@ Creates a [uniform distribution](<https://en.wikipedia.org/wiki/Uniform_distribu
Creates a discrete distribution with all of its probability mass at point `value`.
Numbers are often cast into delta distributions automatically. For example, in the function,
`mixture(1,2,normal(5,2))`, the first two arguments will get converted into delta distributions
with values at 1 and 2. Therefore, `mixture(1,2,normal(5,2))` is the same as `mixture(delta(1), delta(2),normal(5,2))`
Few Squiggle users call the function `delta()` directly. Numbers are converted into delta distributions automatically, when it is appropriate.
For example, in the function `mixture(1,2,normal(5,2))`, the first two arguments will get converted into delta distributions
with values at 1 and 2. Therefore, this is the same as `mixture(delta(1),delta(2),normal(5,2))`.
`Delta()` distributions are currently the only discrete distributions accessible in Squiggle.
<Tabs>
<TabItem value="ex1" label="delta(3)" default>
@ -234,8 +237,11 @@ with values at 1 and 2. Therefore, `mixture(1,2,normal(5,2))` is the same as `mi
<TabItem value="ex2" label="normal(5,2) * 6">
<SquiggleEditor initialSquiggleString="normal(5,2) * 6" />
</TabItem>
<TabItem value="ex4" label="normal(5,2) .* 6">
<SquiggleEditor initialSquiggleString="normal(5,2) .* 6" />
<TabItem value="ex4" label="dotAdd(normal(5,2), 6)">
<SquiggleEditor initialSquiggleString="dotAdd(normal(5,2), 6)" />
</TabItem>
<TabItem value="ex5" label="dotMultiply(normal(5,2), 6)">
<SquiggleEditor initialSquiggleString="dotMultiply(normal(5,2), 6)" />
</TabItem>
</Tabs>
@ -315,8 +321,6 @@ Creates an [exponential distribution](https://en.wikipedia.org/wiki/Exponential_
Creates a [triangular distribution](https://en.wikipedia.org/wiki/Triangular_distribution) with the given low, mode, and high values.
#### Validity
### Arguments
- `low`: Number
@ -336,3 +340,16 @@ Creates a sample set distribution using an array of samples.
### Arguments
- `samples`: An array of at least 5 numbers.
<Admonition type="caution" title="Caution!">
<p>
Samples are converted into{" "}
<a href="https://en.wikipedia.org/wiki/Probability_density_function">PDF</a>{" "}
shapes automatically using{" "}
<a href="https://en.wikipedia.org/wiki/Kernel_density_estimation">
kernel density estimation
</a>{" "}
and an approximated bandwidth. Eventually Squiggle will allow for more
specificity.
</p>
</Admonition>