clifford.randomMV¶

clifford.randomMV(layout, min=-2.0, max=2.0, grades=None, mvClass=<class 'clifford._multivector.MultiVector'>, uniform=None, n=1, normed=False)[source]¶

n Random MultiVectors with given layout.

Coefficients are between min and max, and if grades is a list of integers, only those grades will be non-zero.

Parameters

layout (Layout) – the layout
min (Number) – minimum of random range
max (Number) – maximum
grades (int, list) – number or list of grades to generate
mvClass (class) – the class of MultiVector
uniform (function) – a function like np.randome.uniform , but not limited to
n (int) – number of samples to generate
normed (bool) – should results be normalized?

Examples

>>> randomMV(layout, min=-2.0, max=2.0, grades=None, uniform=None, n=2)  