o
    ohU
                     @   s`   d dl mZ d dlmZ G dd deZdd Zd dlmZmZ d dl	m
Z
 d	d
 Zee
d< dS )    )Basic)
MatrixExprc                   @   sv   e Zd ZdZdZdd Zedd Zedd Zdd
dZ	dd Z
dd Zdd Zdd Zdd Zdd Zdd ZdS )	Transposea1  
    The transpose of a matrix expression.

    This is a symbolic object that simply stores its argument without
    evaluating it. To actually compute the transpose, use the ``transpose()``
    function, or the ``.T`` attribute of matrices.

    Examples
    ========

    >>> from sympy import MatrixSymbol, Transpose, transpose
    >>> A = MatrixSymbol('A', 3, 5)
    >>> B = MatrixSymbol('B', 5, 3)
    >>> Transpose(A)
    A.T
    >>> A.T == transpose(A) == Transpose(A)
    True
    >>> Transpose(A*B)
    (A*B).T
    >>> transpose(A*B)
    B.T*A.T

    Tc                 K   sb   | j }|ddrt|tr|jdi |}t|dd }|d ur-| }|d ur)|S t|S t|S )NdeepT_eval_transpose )argget
isinstancer   doitgetattrr   )selfhintsr   r   resultr   r   x/var/www/html/construction_image-detection-poc/venv/lib/python3.10/site-packages/sympy/matrices/expressions/transpose.pyr      s   zTranspose.doitc                 C   s
   | j d S )Nr   )argsr   r   r   r   r   *   s   
zTranspose.argc                 C   s   | j jd d d S )N)r   shaper   r   r   r   r   .   s   zTranspose.shapeFc                 K   s   | j j||fd|i|S )Nexpand)r   _entry)r   ijr   kwargsr   r   r   r   2   s   zTranspose._entryc                 C   
   | j  S N)r   	conjugater   r   r   r   _eval_adjoint5      
zTranspose._eval_adjointc                 C   r   r   )r   adjointr   r   r   r   _eval_conjugate8   r   zTranspose._eval_conjugatec                 C   s   | j S r   )r   r   r   r   r   r   ;   s   zTranspose._eval_transposec                 C      ddl m} || jS )N   )Trace)tracer#   r   )r   r#   r   r   r   _eval_trace>      
zTranspose._eval_tracec                 C   r!   )Nr   )det)&sympy.matrices.expressions.determinantr'   r   )r   r'   r   r   r   _eval_determinantB   r&   zTranspose._eval_determinantc                 C   s   | j |S r   )r   _eval_derivative)r   xr   r   r   r*   F   s   zTranspose._eval_derivativec                 C   s   | j d |}dd |D S )Nr   c                 S   s   g | ]}|  qS r   )	transpose).0r   r   r   r   
<listcomp>L   s    z;Transpose._eval_derivative_matrix_lines.<locals>.<listcomp>)r   _eval_derivative_matrix_lines)r   r+   linesr   r   r   r/   J   s   z'Transpose._eval_derivative_matrix_linesN)F)__name__
__module____qualname____doc__is_Transposer   propertyr   r   r   r   r    r   r%   r)   r*   r/   r   r   r   r   r      s     


r   c                 C   s   t | jddS )zMatrix transposeF)r   )r   r   )exprr   r   r   r,   O   s   r,   )askQ)handlers_dictc                 C   s   t t| |r| jS | S )z
    >>> from sympy import MatrixSymbol, Q, assuming, refine
    >>> X = MatrixSymbol('X', 2, 2)
    >>> X.T
    X.T
    >>> with assuming(Q.symmetric(X)):
    ...     print(refine(X.T))
    X
    )r8   r9   	symmetricr   )r7   assumptionsr   r   r   refine_TransposeX   s   
r=   N)sympy.core.basicr   "sympy.matrices.expressions.matexprr   r   r,   sympy.assumptions.askr8   r9   sympy.assumptions.refiner:   r=   r   r   r   r   <module>   s    J