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([[13, 19,  6,  3,  7],
    [13,  7, 17,  9,  9]], 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)