Creates an array with random elements.

Parameters¶

shape: ShapeLike = ()¶

A NumPy-compliant shape tuple. The default is () which represents a scalar.

low: ElementLike = 0¶

The smallest element (inclusive). The default is 0.

high: ElementLike | None = None¶

The largest element (exclusive). The default is None which represents order.

seed: int | Generator | None = None¶

Non-negative integer used to initialize the PRNG. The default is None which means that unpredictable entropy will be pulled from the OS to be used as the seed. A numpy.random.Generator can also be passed.

dtype: DTypeLike | None = None¶

The numpy.dtype of the array elements. The default is None which represents the smallest unsigned data type for this FieldArray subclass (the first element in dtypes).

Returns¶

An array of random elements.

Examples¶

Generate a random matrix with an unpredictable seed.

In [1]: GF = galois.GF(31)

In [2]: GF.Random((2, 5))
Out[2]: 
GF([[ 0,  1,  5, 22,  7],
    [25, 23,  3, 14,  8]], order=31)

Generate a random array with a specified seed. This produces repeatable outputs.

In [3]: GF.Random(10, seed=123456789)
Out[3]: GF([ 7, 29, 20, 27, 18,  5,  2,  0, 24, 24], order=31)

In [4]: GF.Random(10, seed=123456789)
Out[4]: GF([ 7, 29, 20, 27, 18,  5,  2,  0, 24, 24], order=31)

Generate a group of random arrays using a single global seed.

In [5]: rng = np.random.default_rng(123456789)

In [6]: GF.Random(10, seed=rng)
Out[6]: GF([ 7, 29, 20, 27, 18,  5,  2,  0, 24, 24], order=31)

In [7]: GF.Random(10, seed=rng)
Out[7]: GF([20, 15,  3, 28, 22,  0,  5, 10,  1,  0], order=31)