matrix_props.has_same_dimension

Checks if the dimensions of list of vectors or matrices are equal.

Functions

has_same_dimension(items)

Check if all vectors or matrices in a list have the same dimension.

Module Contents

matrix_props.has_same_dimension.has_same_dimension(items)

Check if all vectors or matrices in a list have the same dimension.

For a vector (1D array), the dimension is its length. For a matrix, the dimension can be considered as the total number of elements (rows x columns) for non-square matrices, or simply the number of rows (or columns) for square matrices. The function iterates through the provided list and ensures that every item has the same dimension.

Examples

Check a list of vectors with the same dimension:

>>> import numpy as np
>>> from toqito.matrix_props import has_same_dimension
>>> vectors = [np.array([1, 2, 3]), np.array([4, 5, 6]), np.array([7, 8, 9])]
>>> has_same_dimension(vectors)
True

Check a list of matrices with the same dimension:

>>> import numpy as np
>>> from toqito.matrix_props import has_same_dimension
>>> matrices = [np.array([[1, 0], [0, 1]]), np.array([[2, 3], [4, 5]]), np.array([[6, 7], [8, 9]])]
>>> has_same_dimension(matrices)
True

Check a list containing items of different dimensions:

>>> import numpy as np
>>> from toqito.matrix_props import has_same_dimension
>>> mixed = [np.array([1, 2, 3]), np.array([[1, 0], [0, 1]])]
>>> has_same_dimension(mixed)
False
Parameters:

items (list[numpy.ndarray]) – A list containing vectors or matrices. Vectors are represented as 1D numpy arrays, and matrices are represented as 2D numpy arrays.

Returns:

Returns True if all items in the list have the same dimension, False otherwise.

Raises:

ValueError – If the input list is empty.

Return type:

bool