DistributeLib

A single-source-file library for converting 32-bit integer inputs into various 1D, 2D, and 3D distributions and types. The intended use is to convert the output of an RNG into various more useful forms.

Features:

• Generation of int, float, 2D and 3D samples over various shapes
• Cheap routines that only take one input number, but may be less accurate or controllable
• More accurate routines that take a full number of input samples, e.g., three for a cube
• Pre-modulation of inputs into triangular, gaussian-like, and weighted forms
• Gaussian (normal) distribution as both a cheap approximation and via full Box-Muller transform
• Optional generators supplying LCG/PCG/XorShift/Hash/Halton/Golden/'R' sequences.

To build and run the test app:

c++ --std=c++11 Distribute.cpp DistributeTest.cpp -o distribute && ./distribute 200

Or add those files to your favourite IDE.

Examples

Assuming 'rng' returns the next sample via operator uint32_t(), usage can be as simple as below, otherwise substitute rng() or whatever other syntax is appropriate for your sample generator.

1D:

float score     = ToFloat(rng, 1.0f, 100.0f);
int   modifier  = ToInt32Signed(rng, 5);
int   dayOfYear = ToInt32Inclusive(rng, 1, 365);
float weightKG  = ToFloat(ModGaussLike(rng), 50.0f, 130.0f);

2D/3D:

Vec2f circleLoc     = ToCircle(rng);
Vec2f pixTentSample = ToSquare(ModTriangle(rng), ModTriangle(rng));
Vec3f rayDir        = ToDirection3(rng);

Warning: do not simply use rand() to feed these functions, as, in addition to its low quality, its range is not guaranteed to be a full 32 bits.

If you don't already have your own preferred RNG routines, the additional files Generate.h/cpp provide LCG, PCG, Halton, "Golden" (Spiral), and "R" generators, in a form that interoperates cleanly with Distribute.h.

Output

• 1D: float [-1, 1], integer [-10, 10], with a simple LCG input.

  

• 2D: square, ring, triangle

  

• Triangle Modifier: integer, float, square in both dimensions

  

• Gauss-like Modifier: integer, square, and full gaussian for comparison.

  

• Weighted Modifier: float and circle weighted by [1, 8, 0, 4, 1]

  

• Non-random inputs: Halton 100, 1000, 5000 samples

  

• Non-random inputs: Golden ratio square, circle, and sphere surface

  

• Progressively adding samples from the PCG, Halton, and Golden sequences

  

• Progressively adding samples from the Rd sequence: square, circle, cube