^jOdZddlZddlmZmZddlZddlZddlm Z ddl m Z gdZ ejejej ej"ej$ej&ej(ej*ej,ej.ej0ej2ej4ej6ej8ej:ej<gZiZ dZ!dZ"dZ#d Z$d Z%d-d Z&d.d ejNfd Z(ejRdfdZ*d/dZ+dejXd ejXe-ej\zfdZ/d e0fdZ1d e0fdZ2d0dddd e0fdZ3d e0fdZ4d e0fdZ5d e0fdZ6ddd e7e8dfdzfdZ9d1dd d e7e8dffd!Z:d"Z;d e0fd#Z< d-d$ed%ded&zd'ed d(fd)Z=d*Z>d1d+Z?d ejNfd,Z@y)2z, Utility functions for sparse matrix module N)AnyLiteral)prod) upcastgetdtypegetdata isscalarlike isintlikeisshape issequenceisdenseismatrix get_sum_dtypebroadcast_shapesctjt|}||Stj|}t D].}tj ||s|tt|<|cStd|)aReturns the nearest supported sparse dtype for the combination of one or more types. upcast(t0, t1, ..., tn) -> T where T is a supported dtype Examples -------- >>> from scipy.sparse._sputils import upcast >>> upcast('int32') >>> upcast('bool') >>> upcast('int32','float32') >>> upcast('bool',complex,float) z#no supported conversion for types: ) _upcast_memogethashnp result_typesupported_dtypescan_cast TypeError)argstrs N/opt/ringagent/.cad-venv/lib/python3.12/site-packages/scipy/sparse/_sputils.pyrrsu( d$A} ^^T "F  ;;vq !'(Ld $H 9$B CCctj|}||Stttj |}|t|<|S)z9Same as `upcast` but taking dtype.char as input (faster).)rrrmaprdtype)rrs r upcast_charr!:s@A}BHHd#$AL HrcLtjdg||zjS)z`Determine data type for binary operation between an array of type `dtype` and a scalar. rr )rarrayr )r scalars r upcast_scalarr&Ds" HHaS & / 6 66rc>|jjtjtjjkDr|jdk(r|j tjS|j }|j}|tjtjj kDs0|tjtjjkr td|j tjS|S)z Down-cast index array to np.intp dtype if it is of a larger dtype. Raise an error if the array contains a value that is too large for intp. rzzCannot deal with arrays with indices larger than the machine maximum address size (e.g. 64-bit indices on 32-bit machine).) r itemsizerintpsizeastypemaxminiinfo ValueError)arrmaxvalminvals rdowncast_intp_indexr3Ks yyBHHRWW-666 88q=::bgg& & BHHRWW%)) )Vbhhrww6G6K6K-KHI Izz"''"" Jrc|j}|jr|Stj||j dS)a Ensure that the data type of the NumPy array `A` has native byte order. `A` must be a NumPy array. If the data type of `A` does not have native byte order, a copy of `A` with a native byte order is returned. Otherwise `A` is returned. nativer#)r isnativerasarray newbyteorder)Adts r to_nativer;_s5 B {{ ::arx8 99rc0| |j}ntj|}|tvr.dj dtD}t d|d|d|S#t$r.}|tj|}n td|Yd}~jd}~wwxYw)aForm a supported numpy dtype based on input arguments. Returns a valid ``numpy.dtype`` from `dtype` if not None, or else ``a.dtype`` if possible, or else the given `default` if not None, or else raise a ``TypeError``. The resulting ``dtype`` must be in ``supported_dtypes``: bool_, int8, uint8, int16, uint16, int32, uint32, int64, uint64, longlong, ulonglong, float32, float64, longdouble, complex64, complex128, clongdouble Nzcould not interpret data typez, c34K|]}|jywN)__name__).0rs r zgetdtype..s(N(Nsz$scipy.sparse does not support dtype z . The only supported types are: .)r AttributeErrorrrrjoinr/)r adefaultnewdtypeesupported_dtypes_fmts rrros } HwwH88E?''#yy(N=M(NN?zJ::N9OqRS S O H"88G, ?@aG Hs A B'$BBreturnc`tj|||}t|j|S)z This is a wrapper of `np.array(obj, dtype=dtype, copy=copy)` that will generate a warning if the result is an object array. )r copy)rr$rr )objr rLdatas rrrs) 88Cu4 0D TZZ Krc|sd}tjj|jdvr|jdkDrt d|t|j kDr+|jkDjrt d||jjd}|jjd}||fS|jdk(r_t|j kDr,tfd |jDrt d |tfd |jDS|jd k(r_t|j kDr+|jkDjrt d ||jjd}|S|jdk(r|j\}}|jd|zkDr t dt|j kDr.|j|zkDjrt d||jjd}|jjd}||fStd|jd)a3 Safely cast sparse array indices to `idx_dtype`. Check the shape of `A` to determine if it is safe to cast its index arrays to dtype `idx_dtype`. If any dimension in shape is larger than fits in the dtype, casting is unsafe so raise ``ValueError``. If safe, cast the index arrays to `idx_dtype` and return the result without changing the input `A`. The caller can assign results to `A` attributes if desired or use the recast index arrays directly. Unless downcasting is needed, the original index arrays are returned. You can test e.g. ``A.indptr is new_indptr`` to see if downcasting occurred. .. versionadded:: 1.15.0 Parameters ---------- A : sparse array or matrix The array for which index arrays should be downcast. idx_dtype : dtype Desired dtype. Should be an integer dtype (default: ``np.int32``). Most of scipy.sparse uses either int64 or int32. msg : str, optional A string to be added to the end of the ValueError message if the array shape is too big to fit in `idx_dtype`. The error message is ``f" values too large for {msg}"`` It should indicate why the downcasting is needed, e.g. "SuperLU", and defaults to f"dtype {idx_dtype}". Returns ------- idx_arrays : ndarray or tuple of ndarrays Based on ``A.format``, index arrays are returned after casting to `idx_dtype`. For CSC/CSR, returns ``(indices, indptr)``. For COO, returns ``coords``. For DIA, returns ``offsets``. For BSR, returns ``(indices, indptr)``. Raises ------ ValueError If the array has shape that would not fit in the new dtype, or if the sparse format does not use index arrays. Examples -------- >>> import numpy as np >>> from scipy import sparse >>> data = [3] >>> coords = (np.array([3]), np.array([1])) # Note: int64 arrays >>> A = sparse.coo_array((data, coords)) >>> A.coords[0].dtype dtype('int64') >>> # rescast after construction, raising exception if shape too big >>> coords = sparse.safely_cast_index_arrays(A, np.int32) >>> A.coords[0] is coords[0] # False if casting is needed False >>> A.coords = coords # set the index dtype of A >>> A.coords[0].dtype dtype('int32') zdtype csccsrzindptr values too large for zindices values too large for FrLcooc3DK|]}|kDjywr>)any)r@co max_values rrAz+safely_cast_index_arrays..s=bBN'')= zcoords values too large for c3DK|]}|jdyw)FrUN)r+)r@rY idx_dtypes rrAz+safely_cast_index_arrays..sI"RYYyuY5Ir[diazoffsets values too large for bsrz!indptr values too large for {msg}zFormat zP is not associated with index arrays. DOK and LIL have dict and list, not array.)rr.r,formatindptrr/shapeindicesrXr+coordstupleoffsets blocksizer) r9r]msgrcrarfRCrZs ` @rsafely_cast_index_arraysrksY| yk"#''Ixx>! 88B<) #;C5AB B =9 $ I%**, #@!FGG))""95"97 U  =9 $=AHH== #?u!EFFIIII U  =9 $ I%**, #@!FGG))""95"9 U {{1 88B>> import numpy as np >>> from scipy import sparse >>> # select index dtype based on shape >>> shape = (3, 3) >>> idx_dtype = sparse.get_index_dtype(maxval=max(shape)) >>> data = [1.1, 3.0, 1.5] >>> indices = np.array([0, 1, 0], dtype=idx_dtype) >>> indptr = np.array([0, 2, 3, 3], dtype=idx_dtype) >>> A = sparse.csr_array((data, indices, indptr), shape=shape) >>> A.indptr.dtype dtype('int32') >>> # select based on larger of existing arrays and shape >>> shape = (3, 3) >>> idx_dtype = sparse.get_index_dtype(A.indptr, maxval=max(shape)) >>> idx_dtype r)rintcr(int64int32r.r-r, isinstancendarrayr7rr r* issubdtypeinteger)arraysr1check_contentsint32minint32maxr0r2s rget_index_dtyperys3R wwyQxxxx*../Hxx*../H &! H 88O&"**% jjo{{399bhh/88q=]]399bjj9 WWYF WWYF)f.@ 88O  88Orr c|jdk(r4tj|tjrtjStj|tjrtjS|S)z Mimic numpy's casting for np.sumu)kindrruintint_r#s rrrOsH zzSR[[8ww {{5"''"ww Lrchtj|xst|xr|jdk(S)z8Is x either a scalar, an array scalar, or a 0-dim array?r)risscalarr ndimxs rr r Xs& ;;q> 9gaj8QVVq[9rc tj|dk7ry tj|y#tt f$rC t t||k(}n#tt f$rYYywxYw|r d}t ||cYSwxYw)zsIs x appropriate as an index into a sparse matrix? Returns True if it can be cast safely to a machine int. rFz4Inexact indices into sparse matrices are not allowedT)rroperatorindexrr/boolint)r loose_intrhs rr r ]s  wwqzQ q  z " SVq[)I:&   HCS/ !s31BABA,(B+A,,BB)T)allow_ndcheck_ndcdt|}|r||vry|D]}t|sy|s|dksyy)zIs x a valid tuple of dimensions? If nonneg, also checks that the dimensions are non-negative. Shapes of length in the tuple allow_nd are allowed. FrT)lenr )rnonnegrrrds rr r ssD q6DD( | a!e  rct|ttzxr(t|dk(xst j |dxs+t|tj xr|jdk(S)Nr)rqlistrerrrrrrrs rr r sW 4%< (/ Vq[ -BKK!- : 2:: & 8AFFaK;rct|ttzxrt|dkDxrt |dxs+t|t j xr|jdk(S)Nrr)rqrrerr rrrrrs rrrsV 4%< (- VaZ-&qt, 8 2:: & 6166Q;9rc6t|tjSr>)rqrrrrs rr r s a $$rr)r.c>|y|dk(r tdt|tsZtjtj t |tjstdt ||f}g}|D]L}t|std|d|dkr||z }|dks||k\r td|j|Nt|}|tt|k7r td||kDr td ||k(ryt|S) NzWsparse does not accept 0D axis (). Either use toarray (for dense) or copy (for sparse).z+axis must be an integer/tuple of ints, not z axis must be an integer. (given )rzaxis out of range for ndimzduplicate value in axisz axis tuple has too many elements) r/rqrerrsr typertrr appendrset)axisr canon_axisaxlen_axiss r validateaxisrs& | rz $  dE "}}RXXd4j12::>I$t*VW WwJ}>rd!DE E 6 $JB 6R4Z9: :":H3s:''233 D;<< T Z  r)rcpt|dk(r tdt|dk(r" t|d}td|D}ntd|D}|;t||vrt d|d|td |Drt d t|}t|Dcgc] \}}|dks |}}}|s!t|} | |k7rt d |d |t|dk(rf|d} t|d| || dzdz} t|| \} } | dk7r#td |D}t d |d ||d| | fz|| dzdz}n t dt||vrt d|d||S#t$rt j |df}YRwxYwcc}}w)a@Imitate numpy.matrix handling of shape arguments Parameters ---------- args : array_like Data structures providing information about the shape of the sparse array. current_shape : tuple, optional The current shape of the sparse array or matrix. If None (default), the current shape will be inferred from args. allow_nd : tuple of ints, optional default: (2,) If shape does not have a length in the tuple allow_nd an error is raised. Returns ------- new_shape: tuple The new shape after validation. rz8function missing 1 required positional argument: 'shape'rc3FK|]}tj|ywr>rrr@args rrAzcheck_shape..sHchnnS1H!c3FK|]}tj|ywr>rrs rrAzcheck_shape..s>#(..->rNzshape must have length in z. Got new_shape=c3&K|] }|dk yw)rNr)r@rs rrAzcheck_shape..s(q1u(sz#'shape' elements cannot be negativezcannot reshape array of size z into shape c3.K|] }|dkrdn|yw)rnewshapeNr)r@rs rrAzcheck_shape..s!PA*1">>  y> )9(CT)VW W (i( (BC CM* +4I*>H$!Q!a%AHHIH<' #@#/ {"<== ! "a '#A&DYu- $q&'0BBCI%+L)%D "KA~!!Pi!PP  #@#/ {"<==!%4(K>9Id1fg QF Q&c"G w-C '> c#c(3 DAqAv!s1v+q6Q;$%TUUA   S7NRs#B czttjjddd}|duxr t ||S)zV Check whether object is pydata/sparse matrix, avoiding importing the module. sparse SparseArrayN)getattrsysmodulesrrq)mbase_clss ris_pydata_spmatrixrs6s{{x0-FH 4  ;Jq($;;rr target_formatrQ accept_fvzsp.spmatrix | Anyct|rF |j|}||j|}|S|jdvr|j }|S#t$r|j}YPwxYw)z_ Convert a pydata/sparse array to scipy sparse matrix, pass through anything else. )rrQ)rto_scipy_sparserasformatr`tocsc)rrrs rconvert_pydata_sparse_to_scipyr$s~# (%% %:C  $,,}-C JZZ~ -))+C J  (%%'C (sAA0/A0cftj|i|jtjSr>)rr$viewmatrix)rkwargss rrrAs% 88T $V $ ) )")) 44rct|tjr||j|k(r|Stj||j tjS)Nr#)rqrrr r7r)rNr s rasmatrixrEsD$ " u9L ::d% ( - -bii 88rc0t|tjjr|j St|tj r:t j|j|j|jSt|tjrWt j|j|j}tjj|j||S|j!j S)zAccess nonzero values, possibly after summing duplicates. Parameters ---------- s : sparse array Input sparse array. Returns ------- data: ndarray Nonzero values of the array, with shape (s.nnz,) )r countr#)rqsp_data _data_matrix _deduped_data dok_arrayrfromitervaluesr nnz lil_arrayempty _csparsetoolslil_flatten_to_arrayrNtocoo)srNs r_todatarMs!RXX**+  !R\\"{{188:QWWAEEBB!R\\"xxQWW- --affd; 779 " " $$r)NN)NF)rNF)Fr>)A__doc__rtypingrrrnumpyrmathr scipy.sparserr__all__bool_byteubyteshortushortrnuintclongulonglonglong ulonglongfloat32float64 longdouble complex64 complex128 clongdoublerrrr!r&r3r;rrrrrprkryr rgenericrrr r r r rr rerrrrrrrrrrrrrs  HHbggrxx299bggHHbggrxxbllJJ BMMLL"--A  DD 7( : < BJJ +-((kF\EPbhhbjj1A&A:t: D,$;T; 949 %$% !#!U38_t%;#!L=d=uS#X=@B