_MhcNdZdZgdZddlZddlmZddlmZdd l m Z m Z m Z m Z dd lmZdd lmZmZmZmZmZmZdd lmZGd deZdZdZGddee ZGddeeZdS)zSparse DIAgonal formatzrestructuredtext en) dia_array dia_matrixisspmatrix_diaN)copy_if_needed)spmatrix)issparse_formats_spbasesparray) _data_matrix)isshape upcast_chargetdtype get_sum_dtype validateaxis check_shape) dia_matvecceZdZdZddddZdZdZddZejj e_ dd Z ej j e _ dd Z ej j e _ d Z d Z d ZddZddZejj e_ ddZejj e_ ddZejj e_ ddZejj e_ ddZejj e_ ddZdZejj e_ dS) _dia_basediaNFmaxprintctj|||t|r|jdkrI|r|}|j|_|j|_t|j|_ n|j|jkr|r|}n| }|j|_|j|_t|j|_ ndt|trzt|rt||_ tjdt!|t"|_|t'|j}tjd||_n |\}} |t)d|st*}tjtj|d|| |_tj|d |t'|| } tj| |_t||_ n#t2$r} d } t)| | d} ~ wwxYw tj|}n+#t2$r} t)d |jd | d} ~ wwxYwt|t6r#|jdkrt)d|jd|||| }|j|_|j|_t|j|_ |.t!|} |j| |_|jjd krt)d|jjdkrt)d|jjdt?|jkr6t)d|jjdt?|jfzt?tj |jt?|jkrt)ddS)Nrr)rr)defaultmaxvalrdtypezexpected a shape argument)r copyrz+unrecognized form for dia_array constructorzunrecognized form for z_matrix constructorrzDIA arrays don't support zD input. Use 2D)r shapezoffsets array must have rank 1zdata array must have rank 2zBnumber of diagonals (%d) does not match the number of offsets (%d)z&offset array contains duplicate values)!r__init__r formatr!dataoffsetsrr"_shapetodia isinstancetuplernpzerosrfloat_get_index_dtypemax ValueErrorr atleast_2darray atleast_1d Exceptionasarrayr ndim_coo_containerastypelenunique) selfarg1r"r r!rA idx_dtyper%r&emessagenewdtypes Q/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/scipy/sparse/_dia.pyr#z_dia_base.__init__s(dD8<<<< D>>5 /{e##'99;;D I #| )$*55 ;$+--$- AA AF  y )!'22 e $ $& /t}} 5*$// HUHUE,J,J,JKK  11TZ1II !x9=== 5$(MD' }()DEEE.- " bhtAweRV.W.W.W X XDI htAw-1-B-B#e**-B-U-U,0222G$&=#9#9DL"-e"4"4DKK!555KG$W--145  Mz$'' M M M "E$(K"E"E"EFFKLM M$(( YTY!^^ !WTY!W!W!WXXX##DU#CCIIKKADI9DL%ag..DK  H ((22DI <  ! !=>> > 9>Q  :;; ; 9?1 T\!2!2 2 2@yq)3t|+<+<=>?? ? ry&& ' '3t|+<+< < <EFF F = )r r$r)r r%r"r nnz)r;_fmt sparse_clsds rB__repr__z_dia_base.__repr__cs$+&3 *4 9 9GWWx IOA  Y Y YZ Y YDJ Y Yh Y Y23 Y YKO: Y Y Y c|j\}}tj|jjd}||jdddfz }|dk}|||kz}|||kz}|S)z~Returns a mask of the same shape as self.data, where mask[i,j] is True when data[i,j] corresponds to a stored element.rNr)r"r+aranger%r&)r;num_rowsnum_cols offset_indsrowmasks rB _data_maskz_dia_base._data_masklsl"Z(i  233 DL400q x  x'( rMc|td|}tj|j|S)Nz$, 6 6 ;??49uz#9:: :ju}== ?; ==OK?? #*"1% W  [!1!1S5F5F!F!Fyx!8!89H Y\ " " "ej 0 " " " " w  3{#3#3s5=7I7I#I#Iz- ":":;H Xqqq[ ! ! !TY . ! ! ! !DJqMKO3TZ]CCAx[!!1%nTY ;;H Xww& ' ' '49QQQU+; ; ' ' ' Y( ) ) )UZ2A2-> > ) ) )""Hk#:$*"MMMrMc<||j|zSN)rsr%)r;rys rB _mul_scalarz_dia_base._mul_scalarsty50111rMc t|}tj|jdt|jj|jj}|jjd}|j\}}t||t|j ||j |j| | |S)Nrrr) r+r,r"rr charr%rr9r&ravel)r;ryrjyLr]r^s rB_matmul_vectorz_dia_base._matmul_vectors  HTZ]+djo78w|+E+E F F F IOA j!1QDL))1dlDI7799aggii ) ) )rMrc|j\}}|jdkr tj}nt |}|dkrt ||z||}d}|}nt |||z |}|}||z}|jdkr |d|}|jj\} } ||jvrX|| kr9tj| |f|jj } |j| ddd| f<| |_||j|j|k||f<dStj |j|jj ||_t|| } tj| dz| f|jj } |j| ddd| f<|| d||f<| |_dS)Nrrrro) r"r6r+infr9r[r%r&r,r appendtyper/) r;valuesr_r]r^values_nn min_index max_index data_rows data_colsr%ms rB_setdiagz_dia_base._setdiagsz1 ;!  vHH6{{H q55AE1h''AIIIAq1uh''AIAI ;!  BQBZF#y 9   9$$xI 6dioNNN&*iQQQ  ]#  @FDIdla'9)<< = = =9T\4<3E3J3J13M3MNNDLIy))A8Y]A.dioFFFD$(ID"jyj !,2DYy(( )DIIIrMc2|r|S|Srr!)r;r!s rBr(z_dia_base.todias  99;; KrMcr||dkrtd|j\}}t|j}|j }t jt |tjdddf}t j|tj||zdddfz }td||jjdz } t j |jt j |jjd| f|jj f} | ||f} | | |f||f|S)N)rrzvSparse arrays/matrices do not support an 'axes' parameter because swapping dimensions is the only logical permutation.rrr)r"r!) r0r"r/r&r+rOr9intcr%hstackr,r rx) r;axesr!rPrQmax_dimr&rc pad_amountr%s rB transposez_dia_base.transposesM  LMM M"Z(dj//<- Ic'll"' 2 2 2111d7 ; Ihbg . . .'G2CQQQW1M MGDIOA$6677 y$)RXtyq/A:.N48IO&E&E&EFGGAqDz""D'? h; &*#,, ,rMc|j\}}|| ks||kr tjd|jjStj|j|k\}td|}t||z|}||z }|j dkr tj ||jjS|j|d||f}|t|z } | dkrtj |d| fd}|S)Nrrconstant)mode) r"r+emptyr%r nonzeror&r/r[sizer,r9pad) r;r_rowscolsidx first_collast_col result_sizeresultpaddings rBdiagonalz_dia_base.diagonal1sZ d ::d8ATY_555 5z$,!+,,1II tax&&* 8q==8Kty??? ?3q69X#556F + Q;;VFQLzBBBF rMc |jdkr!||j|jS|j\}}|jj\}}t j|}||jdddfz }|dk}|||kz}|||kz}||jdkz}|t|j} t j |dz| } t j | dd|| d|dz<||kr| || |dzd<|j |j | d} |jj |j } || | | f|j|jS) NrrrrrbFr)r"r )rG_csc_containerr"r r%r+rOr&r.r/r,cumsumreTr8) r;r!rPrQ num_offsets offset_lenrRrSrTr>indptrindicesr%s rBtocscz_dia_base.tocscCs 8q==&&tz&DD D!Z("&)/ Zi ++ DL400q x  x'( a ))TZ)AA (Q,i888!#4888+;+;IXI+F!G!GqA~  $*:$6F:a<== !%-&&yu&==y{46"""D'6#:$*)-#55 5rMc\|j\}}|jj\}}tj|}||jdddfz }|dk}|||kz}|||kz}||jdkz}||}tj|||} ||jft|j} | | d}| | d} |j|} | | || ff|j|j dS)Nr)arraysrFr)r"r r!) r"r%r+rOr&tilerr.r/r8r7r ) r;r!rPrQrrrRrSrTcolr>r%s rBtocooz_dia_base.tocoo]s8!Z("&)/ Zi ++ DL400q x  x'( a $igk;// =))L?3tz??*  jjj//jjj//y"" C: dj #   rMTc|r5|||jf|jS|||jf|jS)zReturns a matrix with the same sparsity structure as self, but with different data. By default the structure arrays are copied. rp)rxr&r!r")r;r%r!s rBrsz_dia_base._with_dataxsp  &&t|((**+4:' &&t|$DJ' rMct|}|\}}|jddd|f|_||jdkrtj|j|jdz|jjdkrO|jdddf|jdztj|jjdk}d|j|<||_dS)Nrr)rr%r"r+anyr&rOr')r;r"r]r^rTs rBresizez_dia_base.resizesE""1Iaaa!e$  1  t|djm3dioa6HHII LD)DJqM9Idioa0112DDIdO rM)NNFr)NNN)r)F)NF)T)__name__ __module__ __qualname___formatr#rLrUrXr __doc__r`rerqrrrr(rrrrrsrrdrMrBrrsGKGTKGKGKGKGKGZ      1111$19M    o-GO!6!6!6!6F+%CK#N#N#NJ222   ####J M)EM,,,,, )1I '/H55550M)EM    0M)EM       ^+FNNNrMrcvtj|}tjt|||<|S)z)Helper function to invert an index array.)r+ zeros_likerOr9)rinvs rBrvrvs/ -  CyS""CH JrMc,t|tS)aIs `x` of dia_matrix type? Parameters ---------- x object to check for being a dia matrix Returns ------- bool True if `x` is a dia matrix, False otherwise Examples -------- >>> from scipy.sparse import dia_array, dia_matrix, coo_matrix, isspmatrix_dia >>> isspmatrix_dia(dia_matrix([[5]])) True >>> isspmatrix_dia(dia_array([[5]])) False >>> isspmatrix_dia(coo_matrix([[5]])) False )r)r)rjs rBrrs. a $ $$rMceZdZdZdS)ra< Sparse array with DIAgonal storage. This can be instantiated in several ways: dia_array(D) where D is a 2-D ndarray dia_array(S) with another sparse array or matrix S (equivalent to S.todia()) dia_array((M, N), [dtype]) to construct an empty array with shape (M, N), dtype is optional, defaulting to dtype='d'. dia_array((data, offsets), shape=(M, N)) where the ``data[k,:]`` stores the diagonal entries for diagonal ``offsets[k]`` (See example below) Attributes ---------- dtype : dtype Data type of the array shape : 2-tuple Shape of the array ndim : int Number of dimensions (this is always 2) nnz size data DIA format data array of the array offsets DIA format offset array of the array T Notes ----- Sparse arrays can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power. Sparse arrays with DIAgonal storage do not support slicing. Examples -------- >>> import numpy as np >>> from scipy.sparse import dia_array >>> dia_array((3, 4), dtype=np.int8).toarray() array([[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], dtype=int8) >>> data = np.array([[1, 2, 3, 4]]).repeat(3, axis=0) >>> offsets = np.array([0, -1, 2]) >>> dia_array((data, offsets), shape=(4, 4)).toarray() array([[1, 0, 3, 0], [1, 2, 0, 4], [0, 2, 3, 0], [0, 0, 3, 4]]) >>> from scipy.sparse import dia_array >>> n = 10 >>> ex = np.ones(n) >>> data = np.array([ex, 2 * ex, ex]) >>> offsets = np.array([-1, 0, 1]) >>> dia_array((data, offsets), shape=(n, n)).toarray() array([[2., 1., 0., ..., 0., 0., 0.], [1., 2., 1., ..., 0., 0., 0.], [0., 1., 2., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 2., 1., 0.], [0., 0., 0., ..., 1., 2., 1.], [0., 0., 0., ..., 0., 1., 2.]]) NrrrrrdrMrBrr"HHHHrMrceZdZdZdS)raO Sparse matrix with DIAgonal storage. This can be instantiated in several ways: dia_matrix(D) where D is a 2-D ndarray dia_matrix(S) with another sparse array or matrix S (equivalent to S.todia()) dia_matrix((M, N), [dtype]) to construct an empty matrix with shape (M, N), dtype is optional, defaulting to dtype='d'. dia_matrix((data, offsets), shape=(M, N)) where the ``data[k,:]`` stores the diagonal entries for diagonal ``offsets[k]`` (See example below) Attributes ---------- dtype : dtype Data type of the matrix shape : 2-tuple Shape of the matrix ndim : int Number of dimensions (this is always 2) nnz size data DIA format data array of the matrix offsets DIA format offset array of the matrix T Notes ----- Sparse matrices can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power. Sparse matrices with DIAgonal storage do not support slicing. Examples -------- >>> import numpy as np >>> from scipy.sparse import dia_matrix >>> dia_matrix((3, 4), dtype=np.int8).toarray() array([[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], dtype=int8) >>> data = np.array([[1, 2, 3, 4]]).repeat(3, axis=0) >>> offsets = np.array([0, -1, 2]) >>> dia_matrix((data, offsets), shape=(4, 4)).toarray() array([[1, 0, 3, 0], [1, 2, 0, 4], [0, 2, 3, 0], [0, 0, 3, 4]]) >>> from scipy.sparse import dia_matrix >>> n = 10 >>> ex = np.ones(n) >>> data = np.array([ex, 2 * ex, ex]) >>> offsets = np.array([-1, 0, 1]) >>> dia_matrix((data, offsets), shape=(n, n)).toarray() array([[2., 1., 0., ..., 0., 0., 0.], [1., 2., 1., ..., 0., 0., 0.], [0., 1., 2., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 2., 1., 0.], [0., 0., 0., ..., 1., 2., 1.], [0., 0., 0., ..., 0., 1., 2.]]) NrrdrMrBrrrrMr)r __docformat____all__numpyr+ _lib._utilr_matrixr _baser r r r _datar_sputilsrrrrrr _sparsetoolsrrrvrrrrdrMrBrs% 7 7 7''''''777777777777%$$$$$A,A,A,A,A, A,A,A,H %%%6IIIII 7IIIXIIIII9IIIIIrM