IRandomUniformExtensions

Creates an array that contains a random permutation of the ints in the interval [0, count-1].

Creates an array that contains a random permutation of the numbers in the interval [0, count-1].

Returns a random subset of an array with a supplied number of elements (subsetCount). The elements in the subset are in the same order as in the original array. O(count). NOTE: this method needs to generate one random number for each element of the original array. If subsetCount is signficantly smaller than count, it is more efficient to use or or or .

Creates an ordered array of subsetCount int indices that constitute a subset of all ints in the range [0, count-1]. O(subsetCount * log(subsetCount)) for subsetCount << count. NOTE: It is assumed that subsetCount is significantly smaller than count. If this is not the case, use CreateRandomSubsetOfSize instead. WARNING: As subsetCount approaches count execution time increases significantly.

Creates an ordered array of subsetCount long indices that constitute a subset of all longs in the range [0, count-1]. O(subsetCount * log(subsetCount)) for subsetCount << count. NOTE: It is assumed that subsetCount is significantly smaller than count. If this is not the case, use CreateRandomSubsetOfSize instead. WARNING: As subsetCount approaches count execution time increases significantly.

Creates an unordered array of subsetCount int indices that constitute a subset of all ints in the range [0, count-1]. O(subsetCount) for subsetCount << count. NOTE: It is assumed that subsetCount is significantly smaller than count. If this is not the case, use CreateRandomSubsetOfSize instead. WARNING: As subsetCount approaches count execution time increases significantly.

Creates an unordered array of subsetCount long indices that constitute a subset of all longs in the range [0, count-1]. O(subsetCount) for subsetCount << count. NOTE: It is assumed that subsetCount is significantly smaller than count. If this is not the case, use CreateRandomSubsetOfSize instead. WARNING: As subsetCount approaches count execution time increases significantly.

Create a random array of doubles in the half-open interval [0.0, 1.0) of the specified length.

Create a random array of full doubles in the half-open interval [0.0, 1.0) of the specified length.

Fills the specified array with random ints in the interval [0, 2^31-1].

Fills the specified array with random floats in the half-open interval [0.0f, 1.0f).

Fills the specified array with random doubles in the half-open interval [0.0, 1.0).

Fills the specified array with fully random doubles (53 random bits) in the half-open interval [0.0, 1.0).

Supply random bits one at a time. The currently unused bits are maintained in the supplied reference parameter. Before the first call randomBits must be 0.

Randomly permute the first count elements of the supplied array. This does work with counts of up to about 2^50.

Randomly permute the elements of the supplied array. This does work with arrays up to a length of about 2^50.

Randomly permute the elements of the supplied list.

Randomly permute the specified number of elements in the supplied array starting at the specified index.

Randomly permute the specified number of elements in the supplied array starting at the specified index.

Randomly permute the specified number of elements in the supplied list starting at the specified index.

Returns a uniformly distributed double in the half-open interval [0.0, 1.0). Note, that two random values are used to make all 53 bits random. If you use this repeatedly, consider using a 64-bit random generator, which can provide such doubles directly using UniformDouble().

Returns a uniformly distributed double in the closed interval [0.0, 1.0]. Note, that two random values are used to make all 53 bits random.

Returns a uniformly distributed double in the open interval (0.0, 1.0). Note, that two random values are used to make all 53 bits random.

Returns a uniformly distributed int in the interval [0, count-1]. In order to avoid excessive aliasing, two random numbers are used when count is greater or equal 2^24 and the random generator delivers 32 random bits or less. The method thus works fairly decently for all integers.

Returns a uniform int which is guaranteed not to be zero.

Returns a uniformly distributed long in the interval [0, size-1]. NOTE: If count has more than about 48 bits, aliasing leads to noticeable (greater 5%) shifts in the probabilities (i.e. one long has a probability of x and the other a probability of x * (2^(52-b)-1)/(2^(52-b)), where b is log(size)/log(2)).

Returns a uniform long which is guaranteed not to be zero.

Uniform vector in the closed unit sphere (i.e vectors to the surface of the sphere may be generated).

Returns a uniformly distributed vector (corresponds to a uniformly distributed point on the surface of the unit sphere). Note however, that the returned vector will never be equal to [0, 0, -1].

Returns a fully uniformly distributed vector (corresponds to a uniformly distributed point on the surface of the unit sphere). Note however, that the returned vector will never be equal to [0, 0, -1].

Uniform vector inside the open unit sphere (i.e. no vector ends on the surface of the sphere).