zonopy.batchMatPolyZonotope

class zonopy.batchMatPolyZonotope(Z, n_dep_gens=0, expMat=None, id=None, copy_Z=True, dtype=None, device=None)

Bases: object

Batched 2D Matrix Polynomial Zonotopes

Batched form of the matPolyZonotope class. This class is designed to represent a batch of 2D matrix polynomial zonotopes over the same domain with arbitrary batch dimensions, extending the concept of polynomial zonotopes to matrix forms and allowing for batch processing. It adheres to a formulation similar to the polyZonotope and batchPolyZonotope classes, enabling efficient representation and manipulation of sets of matrix polynomial zonotopes.

This results in a $\mathbf{Z} \in \mathbb{R}^{B_1 \times B_2 \times \cdots \times B_b \times (N+M+1) \times dx \times dy}$ tensor, where $dx$ and $dy$ are the dimensions of the matrices.

Refer to the matPolyZonotope class for more detailed information on matrix polynomial zonotopes.

__init__(Z, n_dep_gens=0, expMat=None, id=None, copy_Z=True, dtype=None, device=None)

Constructor for the batchMatPolyZonotope class

Initializes a batch of 2D matrix polynomial zonotopes with specified characteristics.

Parameters:

• Z (torch.Tensor) – The center and generator tensor for the batch of matrix polynomial zonotopes. The shape of Z should be $(B_1, B_2, \cdots, B_b, N+M+1, dx, dy)$, where $B_1, B_2, \cdots, B_b$ are the batch dimensions, $N$ is the number of dependent generators, $M$ is the number of independent generators, and $dx, dy$ are the dimensions of the matrices.

• n_dep_gens (int, optional) – The number of dependent generators in the matrix polynomial zonotope. Default: 0.

• expMat (torch.Tensor, optional) – The exponent matrix for the dependent generators. If None, it will be assumed to be the identity matrix. Default: None.

• id (torch.Tensor, optional) – The integer identifiers for the dependent generators. If None, it will be the range of the number of dependent generators. Default: None.

• copy_Z (bool, optional) – If True, a copy of the input Z tensor will be made. Default: True.

• dtype (torch.dtype, optional) – The data type for the elements of the matrix polynomial zonotope. If None, it will be inferred from Z. Default: None.

• device (torch.device, optional) – The device on which the matrix polynomial zonotope is to be stored. If None, it will be inferred from Z. Default: None.

Raises:

• AssertionError – If the dimension of the Z input is not 5 or more, indicating incorrect batch dimensions or matrix dimensions.

• AssertionError – If the exponent matrix does not seem to be valid for the given number of dependent generators or ids.

• AssertionError – If the number of dependent generators does not match the number of ids provided.

• AssertionError – If the exponent matrix is not a non-negative integer matrix.

Methods

__init__(Z[, n_dep_gens, expMat, id, ...])	Constructor for the batchMatPolyZonotope class
combine_bmpz(bmpzlist, idxs)
compress(compression_level)
cpu()
eye(batch_size, dim[, dtype, device])
from_mpzlist(mpzlist)
ones(batch_size, dim1[, dim2, dtype, device])
reduce_indep(order[, option])
to([dtype, itype, device])
to_batchMatZonotope()
zeros(batch_size, dim1[, dim2, dtype, device])

Attributes

C
G
Grest
T
batch_shape
device
dtype
input_pairs
itype
n_cols
n_generators
n_indep_gens
n_rows
shape

property C

property G

property Grest

property T

property batch_shape

static combine_bmpz(bmpzlist, idxs)

compress(compression_level)

cpu()

property device

property dtype

static eye(batch_size, dim, dtype=None, device=None)

static from_mpzlist(mpzlist)

property input_pairs

property itype

property n_cols

property n_generators

property n_indep_gens

property n_rows

static ones(batch_size, dim1, dim2=None, dtype=None, device=None)

reduce_indep(order, option='girard')

property shape

to(dtype=None, itype=None, device=None)

to_batchMatZonotope()

static zeros(batch_size, dim1, dim2=None, dtype=None, device=None)