*Last updated: 2023-03-16.*
# tf_quant_finance.math.qmc.scramble_generating_matrices
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Scrambles a generating matrix.
```python
tf_quant_finance.math.qmc.scramble_generating_matrices(
generating_matrices, scrambling_matrices, num_digits, validate_args=False,
dtype=None, name=None
)
```
#### Examples
```python
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`.