# axle

#### package axle

See spire.optional.unicode.SymbolicSetOps for ∩ ∪ etc

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### Type Members

12. #### trait HtmlFrom[T] extends AnyRef

Annotations
@implicitNotFound( ... )

14. #### case class IndexedPowerSet[E](all: IndexedSeq[E]) extends Iterable[Set[E]] with Product with Serializable

A ℘ (IndexedPowerSet) constructed with a collection with elements of type E can construct an Iterator which enumerates all possible subsets (of type Collection<E>) of the collection used to construct the PowerSet.

15. #### case class Permutations[E](pool: IndexedSeq[E], r: Int)(implicit evidence\$1: Manifest[E]) extends Iterable[IndexedSeq[E]] with Product with Serializable

Based on Python's itertools.permutations function

Based on Python's itertools.permutations function

http://docs.python.org/library/itertools.html#itertools.permutations

Permutations("ABCD".toIndexedSeq, 2) Permutations(0 until 3)

### Value Members

2. #### def ackermann(m: Long, n: Long): Long

http://en.wikipedia.org/wiki/Ackermann_function

26. #### def gaps[T](xs: Seq[T])(implicit ringT: Ring[T]): Seq[(T, T)]

gaps

gaps

assumes that the input xs are already sorted

34. #### def logisticMap[N](λ: N)(implicit arg0: Ring[N]): (N) ⇒ N

https://en.wikipedia.org/wiki/Logistic_map

36. #### def mandelbrotNext[N](R: N, I: N)(implicit rng: Rng[N]): ((N, N)) ⇒ (N, N)

https://en.wikipedia.org/wiki/Mandelbrot_set

37. #### def monteCarloPiEstimate[F, N, V, G](trials: F, n2v: (N) ⇒ V)(implicit arg0: ConvertableTo[V], finite: Finite[F, N], functor: Functor[F, N, V, G], agg: Aggregatable[G, V, V], field: Field[V]): V

Monte Carlo approximation of pi http://en.wikipedia.org/wiki/Monte_Carlo_method

Monte Carlo approximation of pi http://en.wikipedia.org/wiki/Monte_Carlo_method

TODO get n2v implicitly?

runs

runs

61. #### def wallisΠ(iterations: Int = 10000): Rational

Englishman John Wallis (1616 - 1703) approximation of π in 1655