Like Array.prototype.find, but for finding the closest match.
npm install find-closestThis module provides functions equivalent to Array.prototype.find and Array.prototype.findIndex, but for finding the closest value where an exact match may not exist.
npm install find-closest
The default behaviour is to compare numbers in an array to the target number provided. The closest match is returned:
``javascript
import { findClosest, findClosestIndex } from 'find-closest'
findClosest([0, 10, 20, 30], 12)
// => 10
findClosestIndex([0, 10, 20, 30], 12)
// => 1
`
#### Mapping
An optional filterMapFn function can be passed to compare non-number values to the target:
`javascript
const pets = [
{ name: 'Fluffy', age: 10 },
{ name: 'Biscuit', age: 6 },
{ name: 'Wilbur', age: 12 },
]
findClosest(pets, 7, ({ age }) => age)
// => { name: 'Biscuit', age: 6 }
`
#### Filtering
Additionally, returning false from this function omits the value:
`javascript
const isGreaterThan10 = (n) => n > 10
findClosest([0, 10, 20, 30], 12)
// => 10
findClosest([0, 10, 20, 30], 12, isGreaterThan10)
// => 20
`
#### Mapping _and_ filtering
The mapping and filtering can be performed by the same function:
`javascript
const pets = [
{ name: 'Fluffy', age: 10 },
{ name: 'Biscuit', age: 6 },
{ name: 'Wilbur', age: 12 },
]
findClosest(pets, 7, ({ age }) => {
if (age < 7) {
return false
}
return age
})
// => { name: 'Fluffy', age: 10 }
`
Note that, unless all the values in the array are numbers, the filterMapFn cannot return true - attempting to do so will cause an error to be thrown.
#### context argument
filterMapFn also receives a second argument with context information, allowing the last example to be rewritten like this:
`javascript`
findClosest(pets, 7, (pet, context) => {
if (pet.age < context.target) {
return false
}
return pet.age
})
The context argument also has context.index and context.array properties.
#### Performance
The filterMapFn argument has potential performance gains over manually calling .map().filter()` on the input array:
- Mapping _and_ filtering happens in a single pass.
- The mapping is executed lazily. If a perfect match is found before reaching the end of the array, unnecessary calculations are avoided.