nengolib.stats.Rd¶

class nengolib.stats.Rd[source]¶

Rd sequence for quasi Monte Carlo sampling the [0, 1]–cube.

This is similar to np.random.uniform(0, 1, size=(num, d)), but with the additional property that each d–dimensional point is uniformly scattered.

This is based on the tutorial and code from [1]. For d=2 this is often called the Padovan sequence. [2]

References

[1]	http://extremelearning.com.au/unreasonable-effectiveness-of-quasirandom-sequences/

[2]	http://oeis.org/A000931

Examples

>>> from nengolib.stats import Rd
>>> rd = Rd().sample(10000, 2)

>>> import matplotlib.pyplot as plt
>>> plt.figure(figsize=(6, 6))
>>> plt.scatter(*rd.T, c=np.arange(len(rd)), cmap='Blues', s=7)
>>> plt.show()

Methods

sample(n[, d, rng]) Samples n points in d dimensions.

nengolib