e!hcNdZdZgdZddlZddlmZddlmZdd l m Z m Z m Z m Z dd lmZdd lmZmZmZmZmZmZdd lmZGd deZdZdZGddee ZGddeeZy)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_matveccxeZdZdZddddZdZdZddZejje_ ddZ ejje _ dd Z ejje _ d Z d Z d Zdd ZddZej je_ ddZej"je_ ddZej$je_ ddZej&je_ ddZej(je_ ddZdZej,je_ y) _dia_basediaNmaxprintctj|||t|r|jdk(rP|r|j }|j |_|j |_t|j|_ nl|j|jk(r|r|j }n|j}|j |_|j |_t|j|_ nt|tr5t|r}t||_ tjdt!|t"|_|j%t'|j}tjd||_nY |\}} | t)d|st*}tj,tj.|d|| |_tj.|d |j%t'|| } tj0| |_t||_ n tj4|}t|t6r(|j8dk7rt)d|j8d|j;|||j}|j |_|j |_t|j|_ |+t!|} |j j=| |_|j j8d k7r t)d|j j8dk7r t)d|j jdt?|j k7r:t)d|j jdt?|j fzt?tj@|j t?|j k7r t)dy#t2$r} d } t)| | d} ~ wwxYw#t2$r} t)d |jd | d} ~ wwxYw)Nrr)rr)defaultmaxvalrdtypezexpected a shape argument)r copyrz+unrecognized form for dia_array constructorzunrecognized form for z_matrix constructorrzDIA arrays don't support zD input. Use 2D)r shapezoffsets array must have rank 1zdata array must have rank 2zBnumber of diagonals (%d) does not match the number of offsets (%d)z&offset array contains duplicate values)!r__init__r formatr!dataoffsetsrr"_shapetodia isinstancetuplernpzerosrfloat_get_index_dtypemax ValueErrorr atleast_2darray atleast_1d Exceptionasarrayr ndim_coo_containerastypelenunique) selfarg1r"r r!rA idx_dtyper%r&emessagenewdtypes Y/var/www/html/diagnosisapp-backend/venv/lib/python3.12/site-packages/scipy/sparse/_dia.pyr#z_dia_base.__init__svdD8< D>{{e#99;D II #|| )$**5 ;;$++-$ A AFF  yy )!''2 e $t}*$/ HHUHUE,JK  11TZZ1I !xx9= 5$(MD' }()DEE- " bhhtAweRV.W XDI hhtAw-1-B-B#e*-B-U,02G$&==#9DL"-e"4DK Mzz$'$(TYY!^ # > 99>>Q :; ; 99??1 T\\!2 2@yyq)3t||+<=>? ? ryy& '3t||+< <EF F =Y!5KG$W-145$ M !9$(KK=0C"EFKLM Ms0PP6 P3 P..P36 Q?QQc t|j\}}t|trdnd}|jj d}d|d|d|j d|jd|d |j d S) Nr2matrixr)r r$r)r r%r"r nnz)r;_fmt sparse_clsds rB__repr__z_dia_base.__repr__cs|$++&3 *4 9Wx IIOOA uHZL DJJ<@hhZ1!4J4::,VW Y c|j\}}tj|jjd}||jdddfz }|dk\}|||kz}|||kz}|S)z~Returns a mask of the same shape as self.data, where mask[i,j] is True when data[i,j] corresponds to a stored element.rNr)r"r+aranger%r&)r;num_rowsnum_cols offset_indsrowmasks rB _data_maskz_dia_base._data_masklso"ZZ(ii  23 DLL400q x  x'( rMc| td|j}tj|j|S)Nz>$,, 6??499uzz#9: :jju}}= ??; =OOK? #**""1% W [!1S5F!Fyyx!89H Y\ "ejj 0 " w 3{#3s5==7I#Izz- ":;H Xq[ !TYY . !DJJqMKO3TZZ]CAxx[!1%nnTYY ;H Xww& '499QU+; ; ' Y( )UZZ2A2-> > )""Hk#:$**"MMrMc>|j|j|zSN)rsr%)r;rys rB _mul_scalarz_dia_base._mul_scalarstyy5011rMc |}tj|jdt|jj |jj }|j jd}|j\}}t||t|j||j|j |j|j|S)Nrrr) r+r,r"rr charr%rr9r&ravel)r;ryrjyLr]r^s rB_matmul_vectorz_dia_base._matmul_vectors  HHTZZ]+djjoo78ww||+E F IIOOA jj!1QDLL)1dllDII779aggi )rMc|j\}}|jdk(rtj}n t |}|dkrt ||z||}d}|}nt |||z |}|}||z}|jdk7r|d|}|j j\} } ||jvro|| kDrItj| |f|j j} |j | ddd| f<| |_||j |j|k(||f<ytj|j|jjj||_t|| } tj| dz| f|j j} |j | ddd| f<|| d||f<| |_y)Nrrrro) r"r6r+infr9r[r%r&r,r appendtyper/) r;valuesr_r]r^values_nn min_index max_index data_rows data_colsr%ms rB_setdiagz_dia_base._setdiagszz1 ;;! vvH6{H q5AE1h'AIIAq1uh'AIAI ;;! BQZF#yy 9  9$xxI 6diiooN&*iiQ  ]#  @FDIIdlla'9)<< =99T\\4<<3E3E3J3J13MNDLIy)A88Y]A.diiooFD$(IID"jyj !,2DYy(( )DIrMc*|r|jS|Srr!)r;r!s rBr(z_dia_base.todias 99; KrMc||dk7r td|j\}}t|j}|j }t j t |tjdddf}t j |tj||zdddfz }td||jjdz } t j|jt j|jjd| f|jjf} | ||f} |j| |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.transposes3  LM M"ZZ(djj/<<- IIc'l"'' 21d7 ; IIhbgg .'G2CQW1M MGDIIOOA$667 yy$))RXXtyyq/A:.N48IIOO&EFGAqDz""D'? h; &*#, ,rMc|j\}}|| ks||k\r+tjd|jjStj |j |k(\}td|}t||z|}||z }|jdk(r+tj||jjS|j|d||f}|t|z } | dkDrtj|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.diagonal1sZZ d :d88ATYY__5 5zz$,,!+,1I tax&* 88q=88Ktyy? ?3q69X#556F + Q;VVFQLzBF rMcL|jdk(r'|j|j|jS|j\}}|jj\}}t j |}||jdddfz }|dk\}|||kz}|||kz}||jdk7z}|jt|j} t j|dz| } t j|jdd|| d|dz||kr | || |dzd|j|jj| d} |jj|j} |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 88q=&&tzz&D D!ZZ("&))// Zii + DLL400q x  x'( a ))TZZ)A (Q,i8!#4888+;IX+F!GqA  $*:$6F:a<= !%%-&&yu&=yy{{466"""D'6#:$**)-#5 5rMct|j\}}|jj\}}tj|}||jdddfz }|dk\}|||kz}|||kz}||jdk7z}||}tj |||j } |j|jft|j} |j| d}| j| d} |j|} |j| || ff|j|jdS)Nr)arraysrFr)r"r r!) r"r%r+rOr&tilerr.r/r8r7r ) r;r!rPrQrrrRrSrTcolr>r%s rBtocooz_dia_base.tocoo]s2!ZZ("&))// Zii + DLL400q x  x'( a $iggk;/ =))LL?3tzz?* jjj/jjj/yy"" C: djj #  rMc|r7|j||jjf|jS|j||jf|jS)zReturns a matrix with the same sparsity structure as self, but with different data. By default the structure arrays are copied. rp)rxr&r!r")r;r%r!s rBrsz_dia_base._with_dataxsf &&t||((*+4::' &&t||$DJJ' rMct|}|\}}|jddd|f|_||jdkDrtj|j |jdz|jjdkr_|j dddf|jdztj |jjdk}d|j|<||_y)Nrr)rr%r"r+anyr&rOr')r;r"r]r^rTs rBresizez_dia_base.resizesE"1IIa!e$  1 t||djjm3diiooa6HHILLD)DJJqM9IIdiiooa012DDIIdO rM)NNFr)NNN)r)F)NF)T)__name__ __module__ __qualname___formatr#rLrUrXr __doc__r`rerqrrrr(rrrrrsrrdrMrBrrs GKGTKGZ  1$1199M oo--GO!6F++%%CK#NJ2 #J MM))EM,, ))11I ''//H50MM))EM 0MM))EM  ^^++FNrMrcrtj|}tjt|||<|S)z)Helper function to invert an index array.)r+ zeros_likerOr9)rinvs rBrvrvs+ -- CyyS"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 $$rMceZdZdZy)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.]]) NrrrrrdrMrBrrHrMrceZdZdZy)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 _sparsetoolsrrrvrrrrdrMrBrsm% 7'77%A, A,H %6I 7IXI9IrM