a
    RG5d
                     @   sp   d dl mZ d dlmZ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)adjoint	conjugate)
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   sf   | j }|ddr,t|tr,|jf i |}t|dd }|d urZ| }|d urR|S t|S t|S d S )NdeepT_eval_transpose)argget
isinstancer   doitgetattrr   )selfhintsr	   r   result r   `/var/www/html/django/DPS/env/lib/python3.9/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   0   s    zTranspose.shapeFc                 K   s   | j j||fd|i|S )Nexpand)r	   _entry)r   ijr   kwargsr   r   r   r   4   s    zTranspose._entryc                 C   s
   t | jS N)r   r	   r   r   r   r   _eval_adjoint7   s    zTranspose._eval_adjointc                 C   s
   t | jS r   )r   r	   r   r   r   r   _eval_conjugate:   s    zTranspose._eval_conjugatec                 C   s   | j S r   )r	   r   r   r   r   r   =   s    zTranspose._eval_transposec                 C   s   ddl m} || jS )N   )Trace)tracer    r	   )r   r    r   r   r   _eval_trace@   s    zTranspose._eval_tracec                 C   s   ddl m} || jS )Nr   )det)&sympy.matrices.expressions.determinantr#   r	   )r   r#   r   r   r   _eval_determinantD   s    zTranspose._eval_determinantc                 C   s   | j |S r   )r	   _eval_derivative)r   xr   r   r   r&   H   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>N       z;Transpose._eval_derivative_matrix_lines.<locals>.<listcomp>)r   _eval_derivative_matrix_lines)r   r'   linesr   r   r   r,   L   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(   Q   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
    )r5   r6   	symmetricr	   )r4   assumptionsr   r   r   refine_TransposeZ   s    
r:   N)sympy.core.basicr   sympy.functionsr   r   "sympy.matrices.expressions.matexprr   r   r(   sympy.assumptions.askr5   r6   sympy.assumptions.refiner7   r:   r   r   r   r   <module>   s   J