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    !?h  ć                   @   s>   d dl Zd dlZd dlZdd Zdd Zdd ZdddZdS )é    Nc                 C   s@  | \}}|| }|d }|d }|| }t  dddddddddg	”d }t  t  t  |”|”d”}t  t  t  |”|”d”}	|d t  dddddddddg	|” }
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k|
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csr_matrixŚT)ŚshapeŚhŚwŚnZh2Zw2Zn2ŚweightsZx2Śy2ŚxŚyŚmaskZi_indsZj_indsŚvaluesŚ
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t  |”}t|D ]}||||  |”  |  }q8|S )Nr   r   )r   Z
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
r#   c              	   C   sę   |\}}	||	 }
|
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   r   ZlinalgZspsolver   r   Zdiagonalr#   Ś_vcycle_step)r   r    r   ŚcacheŚnum_pre_iterŚnum_post_iterr!   Śdirect_solve_sizer   r   r   r   r   Zcoarse_Ar   r   ZresidualZcoarse_residualZcoarse_xr   r   r   r$   .   s4    

ųr$   r   ēé?é@   c                    s(   dkri  fdd}|S )aę  
    Implements the V-Cycle preconditioner.
    The V-Cycle solver was recommended by :cite:`lee2014scalable` to solve the alpha matting problem.

    Parameters
    ----------
    A: numpy.ndarray
        Input matrix
    shape: tuple of ints
        Describing the height and width of the image
    num_pre_iter: int
        Number of Jacobi iterations before each V-Cycle, defaults to 1
    num_post_iter: int
        Number of Jacobi iterations after each V-Cycle, defaults to 1
    omega: float
        Weight parameter for the Jacobi method. If method fails to converge, try different values.

    Returns
    -------
    precondition: function
        Function which applies the V-Cycle preconditioner to a vector

    Example
    -------
    >>> from pymatting import *
    >>> import numpy as np
    >>> from scipy.sparse import csc_matrix
    >>> A = np.array([[2, 3], [3, 5]])
    >>> preconditioner = vcycle(A, (2, 2))
    >>> preconditioner(np.array([1, 2]))
    array([-1.,  1.])
    Nc              	      s   t  | S )N)r$   )Śr©r   r%   r(   r'   r&   r!   r   r   r   Śprecondition   s           ’zvcycle.<locals>.preconditionr   )r   r   r&   r'   r!   r(   r%   r-   r   r,   r   Śvcycleg   s    *r.   )r   r   r)   r*   N)	Śnumpyr   Zscipy.sparser
   Zscipy.sparse.linalgr   r#   r$   r.   r   r   r   r   Ś<module>   s   <     ł