U
    ?hU>                     @   sf   d dl Z d dlZd dlmZ d dlmZmZmZm	Z	m
Z
mZ d dlmZ dgZddd	ZdddZdS )    N)LinAlgError)get_blas_funcsqrsolvesvd	qr_insertlstsq)make_systemgcrotmk Fc	           "   
   C   s  |dkrdd }|dkr dd }t ddddg|f\}	}
}}|g}g }d}tj}|t| }tjt||f|jd	}tjd
|jd	}tjd|jd	}t|jj}d}t	|D ]j}|r|t|k r|| \}}n`|r|t|kr||}d}nB|s"||t| kr"|||t|   \}}n||d }d}|dkrJ|| |}n|
 }||}t|D ]6\}}|
||}||||f< |	|||jd | }qbtj|d |jd	}t|D ]2\}}|
||}|||< |	|||jd | }q||||d < tjddd d|d  }W 5 Q R X t|r6|||}|d || ksLd}|| || tj|d |d f|jdd}||d|d d|d f< d||d |d f< tj|d |f|jdd} || d|d ddf< t|| ||dddd\}}t|d }||k s|r qqt|||f s6t t|d|d d|d f |dd|d f  \}}!}!}!|ddd|d f }|||||||fS )a  
    FGMRES Arnoldi process, with optional projection or augmentation

    Parameters
    ----------
    matvec : callable
        Operation A*x
    v0 : ndarray
        Initial vector, normalized to nrm2(v0) == 1
    m : int
        Number of GMRES rounds
    atol : float
        Absolute tolerance for early exit
    lpsolve : callable
        Left preconditioner L
    rpsolve : callable
        Right preconditioner R
    cs : list of (ndarray, ndarray)
        Columns of matrices C and U in GCROT
    outer_v : list of ndarrays
        Augmentation vectors in LGMRES
    prepend_outer_v : bool, optional
        Whether augmentation vectors come before or after
        Krylov iterates

    Raises
    ------
    LinAlgError
        If nans encountered

    Returns
    -------
    Q, R : ndarray
        QR decomposition of the upper Hessenberg H=QR
    B : ndarray
        Projections corresponding to matrix C
    vs : list of ndarray
        Columns of matrix V
    zs : list of ndarray
        Columns of matrix Z
    y : ndarray
        Solution to ||H y - e_1||_2 = min!
    res : float
        The final (preconditioned) residual norm

    Nc                 S   s   | S Nr   xr   r   V/var/www/html/venv/lib/python3.8/site-packages/scipy/sparse/linalg/_isolve/_gcrotmk.py<lambda>@       z_fgmres.<locals>.<lambda>c                 S   s   | S r   r   r   r   r   r   r   B   r   axpydotscalnrm2)dtype)   r   )r   r   Fr      r   ignore)ZoverdivideTFr   ordercol)whichZoverwrite_qruZcheck_finite)r   r   )r   npnanlenZzerosr   ZonesZfinfoepsrangecopy	enumerateshapeZerrstateisfiniteappendr   absr   r   Zconj)"matvecZv0matolZlpsolverpsolvecsZouter_vZprepend_outer_vr   r   r   r   vszsyresBQRr$   Z	breakdownjzwZw_normicalphaZhcurvZQ2ZR2_r   r   r   _fgmres   s    1





 
>r@   h㈵>     oldestc           A   
   C   s0  t | |||\} }}}}t| s.td|dkrDtd|f |dkr`tjdtdd |}| j}|j}|	dkrxg }	|dkr|}d\}}}|dkr|	 }n||| }t
d	d
ddg||f\}}}}||}|dkr|}||dfS |
rdd |	D |	dd< |	rt|	jdd d tj| jd t|	f|jdd}g }d}|	r|	d\}}|dkrj||}||dd|f< |d7 }|| qDt|dddd\}}}~t|j}g } tt|D ]}|||  }t|D ],}!||||!  ||jd ||!|f  }qt|||f dt|d  k r0 qT|d|||f  |}| | qtt|| ddd |	dd< |	rt
d	d
g|f\}}|	D ]>\}}|||}"||||jd |"}||||jd |" }qt|D ]}#|dk	r|| ||}$t||| }%|$|%kr6|#dks"|	r6||| }||}$|$|%krJd}# q|t|t|	 d }&dd |	D }z@t|||$ |&|t||| |$ |d\}}}'}(})}*}+|*|$9 }*W n tk
r   Y  qY nX |)d |*d  },t|)dd |*dd D ]\}-}"||-|,|,jd |"},q|'|*}.t|	|.D ](\}/}0|/\}}|||,|,jd |0 },q,|||*}1|(d |1d  }2t|(dd |1dd D ]\}3}4||3|2|2jd |4}2qz"d||2 }5t|5st W n  ttfk
r   Y qY nX ||5|2}2||5|,},||2|}6||2||jd |6 }||,||jd |6}|dkrht|	|kr|	r|	d= qFnx|d krt|	|kr|	rt|ddddf j|'jj}7t|7\}8}9}:g };t |8ddd|d f jD ]\}}<|	d \}}||<d  }||<d  }t|	dd |<dd D ]:\}=}>|=\}?}@||?||jd |>}||@||jd |>}q|;D ]@\}?}@||?|}5||?||jd |5 }||@||jd |5 }q\||}5|d|5 |}|d|5 |}|;||f q|;|	dd< |	|2|,f q|	d|	 f |
r d!d |	D |	dd< |||#d fS )"a,  
    Solve a matrix equation using flexible GCROT(m,k) algorithm.

    Parameters
    ----------
    A : {sparse matrix, ndarray, LinearOperator}
        The real or complex N-by-N matrix of the linear system.
        Alternatively, ``A`` can be a linear operator which can
        produce ``Ax`` using, e.g.,
        ``scipy.sparse.linalg.LinearOperator``.
    b : ndarray
        Right hand side of the linear system. Has shape (N,) or (N,1).
    x0 : ndarray
        Starting guess for the solution.
    tol, atol : float, optional
        Tolerances for convergence, ``norm(residual) <= max(tol*norm(b), atol)``.
        The default for ``atol`` is `tol`.

        .. warning::

           The default value for `atol` will be changed in a future release.
           For future compatibility, specify `atol` explicitly.
    maxiter : int, optional
        Maximum number of iterations.  Iteration will stop after maxiter
        steps even if the specified tolerance has not been achieved.
    M : {sparse matrix, ndarray, LinearOperator}, optional
        Preconditioner for A.  The preconditioner should approximate the
        inverse of A. gcrotmk is a 'flexible' algorithm and the preconditioner
        can vary from iteration to iteration. Effective preconditioning
        dramatically improves the rate of convergence, which implies that
        fewer iterations are needed to reach a given error tolerance.
    callback : function, optional
        User-supplied function to call after each iteration.  It is called
        as callback(xk), where xk is the current solution vector.
    m : int, optional
        Number of inner FGMRES iterations per each outer iteration.
        Default: 20
    k : int, optional
        Number of vectors to carry between inner FGMRES iterations.
        According to [2]_, good values are around m.
        Default: m
    CU : list of tuples, optional
        List of tuples ``(c, u)`` which contain the columns of the matrices
        C and U in the GCROT(m,k) algorithm. For details, see [2]_.
        The list given and vectors contained in it are modified in-place.
        If not given, start from empty matrices. The ``c`` elements in the
        tuples can be ``None``, in which case the vectors are recomputed
        via ``c = A u`` on start and orthogonalized as described in [3]_.
    discard_C : bool, optional
        Discard the C-vectors at the end. Useful if recycling Krylov subspaces
        for different linear systems.
    truncate : {'oldest', 'smallest'}, optional
        Truncation scheme to use. Drop: oldest vectors, or vectors with
        smallest singular values using the scheme discussed in [1,2].
        See [2]_ for detailed comparison.
        Default: 'oldest'

    Returns
    -------
    x : ndarray
        The solution found.
    info : int
        Provides convergence information:

        * 0  : successful exit
        * >0 : convergence to tolerance not achieved, number of iterations

    Examples
    --------
    >>> import numpy as np
    >>> from scipy.sparse import csc_matrix
    >>> from scipy.sparse.linalg import gcrotmk
    >>> R = np.random.randn(5, 5)
    >>> A = csc_matrix(R)
    >>> b = np.random.randn(5)
    >>> x, exit_code = gcrotmk(A, b)
    >>> print(exit_code)
    0
    >>> np.allclose(A.dot(x), b)
    True

    References
    ----------
    .. [1] E. de Sturler, ''Truncation strategies for optimal Krylov subspace
           methods'', SIAM J. Numer. Anal. 36, 864 (1999).
    .. [2] J.E. Hicken and D.W. Zingg, ''A simplified and flexible variant
           of GCROT for solving nonsymmetric linear systems'',
           SIAM J. Sci. Comput. 32, 172 (2010).
    .. [3] M.L. Parks, E. de Sturler, G. Mackey, D.D. Johnson, S. Maiti,
           ''Recycling Krylov subspaces for sequences of linear systems'',
           SIAM J. Sci. Comput. 28, 1651 (2006).

    z$RHS must contain only finite numbers)rD   smallestz Invalid value for 'truncate': %rNzscipy.sparse.linalg.gcrotmk called without specifying `atol`. The default value will change in the future. To preserve current behavior, set ``atol=tol``.r   )category
stacklevel)NNNr   r   r   r   r   c                 S   s   g | ]\}}d |fqS r   r   .0r<   ur   r   r   
<listcomp>=  s     zgcrotmk.<locals>.<listcomp>c                 S   s   | d d k	S )Nr   r   )cur   r   r   r   B  r   zgcrotmk.<locals>.<lambda>)keyr   r   r   TZeconomic)Zoverwrite_amodeZpivotingg-q=)r   r   g      ?r   c                 S   s   g | ]\}}|qS r   r   rH   r   r   r   rK     s     )r/   r.   r0   rD   rE   c                 S   s   g | ]\}}d |fqS r   r   )rI   czuzr   r   r   rK     s     )!r	   r!   r)   all
ValueErrorwarningswarnDeprecationWarningr,   r&   r   sortemptyr(   r#   r   popr*   r   listTr%   r+   zipmaxr@   r   r   FloatingPointErrorZeroDivisionErrorr   r   r'   )AAbZx0ZtolmaxiterMcallbackr-   kZCUZ	discard_Ctruncater.   r   postprocessr,   Zpsolver   r   r   rr   Zb_normCusr8   r<   rJ   r6   r7   Pr0   Znew_usr;   ZycZj_outerbetaZbeta_tolmlr5   r1   r2   r3   ZpresZuxr9   ZbyrL   ZbychyZcxr>   Zhycr=   gammaDWsigmaVZnew_CUr:   cupZwpcpupr   r   r   r
      s   ` 

 

*" 



"
"





 &"
)NNr   r   F)NrA   rB   NNrC   NNFrD   N)rS   numpyr!   Znumpy.linalgr   Zscipy.linalgr   r   r   r   r   r   Z!scipy.sparse.linalg._isolve.utilsr	   __all__r@   r
   r   r   r   r   <module>   s"      
 )           