Last updated: 2023-03-16.

tf_quant_finance.math.qmc.scramble_generating_matrices

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Scrambles a generating matrix.

tf_quant_finance.math.qmc.scramble_generating_matrices(
    generating_matrices, scrambling_matrices, num_digits, validate_args=False,
    dtype=None, name=None
)

Examples

import tf_quant_finance as tff

# Example: Scrambling the 2D Sobol generating matrices.

dim = 2
num_results = 1000
num_digits = 10
seed = (2, 3)

tff.math.qmc.scramble_generating_matrices(
    tff.math.qmc.sobol_generating_matrices(dim, num_results, num_digits),
    tff.math.qmc.random_scrambling_matrices(dim, num_digits, seed=seed),
    num_digits)
# ==> tf.Tensor([
#             [586, 505, 224, 102,  34,  31,  13,   6,   2,   1],
#             [872, 695, 945, 531, 852, 663, 898, 568, 875, 693],
#         ], shape=(2, 10), dtype=int32)

Args:

• generating_matrices: Positive scalar Tensor of integers.

• scrambling_matrices: Positive Scalar Tensor of integers with the same shape as generating_matrices.

• num_digits: Positive scalar Tensor of integers with rank 0. The base-2 precision of the points which can be sampled from generating_matrices.

• validate_args: Python bool indicating whether to validate arguments. Default value: False.

• dtype: Optional dtype. The dtype of the output Tensor (either int32 or int64). Default value: None which maps to generating_matrices.dtype.

• name: Python str name prefixed to ops created by this function. Default value: None which maps to scramble_generating_matrices.

Returns:

A Tensor with the same shape and dtype as generating_matrices.