numpy.bmat()

numpy.bmat(obj, ldict=None, gdict=None) [source]

Build a matrix object from a string, nested sequence, or array.

Parameters:

Parameters:	obj : str or array_like Input data. Names of variables in the current scope may be referenced, even if `obj` is a string. ldict : dict, optional A dictionary that replaces local operands in current frame. Ignored if `obj` is not a string or `gdict` is `None`. gdict : dict, optional A dictionary that replaces global operands in current frame. Ignored if `obj` is not a string.
Returns:	out : matrix Returns a matrix object, which is a specialized 2-D array.

obj : str or array_like

Input data. Names of variables in the current scope may be referenced, even if obj is a string.

ldict : dict, optional

A dictionary that replaces local operands in current frame. Ignored if obj is not a string or gdict is None.

gdict : dict, optional

A dictionary that replaces global operands in current frame. Ignored if obj is not a string.

Returns:

out : matrix

Returns a matrix object, which is a specialized 2-D array.

Examples

>>> A = np.mat('1 1; 1 1')
>>> B = np.mat('2 2; 2 2')
>>> C = np.mat('3 4; 5 6')
>>> D = np.mat('7 8; 9 0')

All the following expressions construct the same block matrix:

>>> np.bmat([[A, B], [C, D]])
matrix([[1, 1, 2, 2],
        [1, 1, 2, 2],
        [3, 4, 7, 8],
        [5, 6, 9, 0]])
>>> np.bmat(np.r_[np.c_[A, B], np.c_[C, D]])
matrix([[1, 1, 2, 2],
        [1, 1, 2, 2],
        [3, 4, 7, 8],
        [5, 6, 9, 0]])
>>> np.bmat('A,B; C,D')
matrix([[1, 1, 2, 2],
        [1, 1, 2, 2],
        [3, 4, 7, 8],
        [5, 6, 9, 0]])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.bmat.html

doc_NumPy

2025-01-10 15:47:30

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