Shuffle! - Netflix

Thu 27 June 2019

In present times, Gods and Demons coexist together with Humans after the door between each of these worlds had opened. Tsuchimi Rin is a normal young high school student attending Verbena Academy, spending his days living peacefully with his childhood friend Kaede. Unexpectedly, one day the King of Gods, the King of Demons and their families move into be Rin's next door neighbors. Apparently the daughter of the Gods, Sia, and the daughter of the demons, Nerine, are both deeply in love with Rin after having met him in the past. Along with his playful friendship with upperclassmen Asa and his encounter with the silent but cute Primula, Rin has much on his hands dealing with the affections of each of these girls. Based on the eroge by Navel.

Shuffle! - Netflix

Type: Animation

Languages: Japanese

Status: Ended

Runtime: 25 minutes

Premier: 2005-07-08

Shuffle! - Shuffling - Netflix

Shuffling is a procedure used to randomize a deck of playing cards to provide an element of chance in card games. Shuffling is often followed by a cut, to help ensure that the shuffler has not manipulated the outcome.

Shuffle! - Shuffling algorithms - Netflix

If a computer has access to purely random numbers, it is capable of generating a “perfect shuffle”, a random permutation of the cards; beware that this terminology (an algorithm that perfectly randomizes the deck) differs from “a perfectly executed single shuffle”, notably a perfectly interleaving faro shuffle. The Fisher–Yates shuffle, popularized by Donald Knuth, is simple (a few lines of code) and efficient (O(n) on an n-card deck, assuming constant time for fundamental steps) algorithm for doing this. Shuffling can be seen as the opposite of sorting. There are other, less-desirable algorithms in common use. For example, one can assign a random number to each card, and then sort the cards in order of their random numbers. This will generate a random permutation, unless any of the random numbers generated are the same as any others (i.e. pairs, triplets etc.). This can be eliminated either by adjusting one of the pair's values randomly up or down by a small amount, or reduced to an arbitrarily low probability by choosing a sufficiently wide range of random number choices. If using efficient sorting such as mergesort or heapsort this is an O(n log n) average and worst-case algorithm.

Shuffle! - References - Netflix