a aH2@sdZddlZddlmZmZddlmZmZm Z gZ GdddeZ eD]"Z e j Zdd Zee eee qHd d ZGd d d ZdS)zBase class for sparse matrice with a .data attribute subclasses must provide a _with_data() method that creates a new matrix with the same sparsity pattern as self but with a different data array N)spmatrix _ufuncs_with_fixed_point_at_zero) isscalarlike validateaxismatrixc@seZdZddZddZddZeeedZdd Zd d Z d(d dZ ddZ ddZ ddZ ddZddZd)ddZejje_d*ddZejje_dd Zejje_d!d"Zejje_d+d$d%Zd&d'Zd#S), _data_matrixcCst|dSN)r__init__selfr a/Users/vegardjervell/Documents/master/model/venv/lib/python3.9/site-packages/scipy/sparse/data.pyr sz_data_matrix.__init__cCs|jjSr datadtyper r r r _get_dtypesz_data_matrix._get_dtypecCs ||j_dSr r)r Znewtyper r r _set_dtypesz_data_matrix._set_dtype)fgetfsetcCst|dr||jS)Nsum_duplicates)hasattrrrr r r r _deduped_datas z_data_matrix._deduped_datacCs|t|Sr ) _with_dataabsrr r r r__abs__#sz_data_matrix.__abs__rcCs|tj||dS)N)Zdecimals)rnpZaroundr)r ndigitsr r r __round__&sz_data_matrix.__round__cCs||jjSr )rrrealr r r r_real)sz_data_matrix._realcCs||jjSr )rrimagr r r r_imag,sz_data_matrix._imagcCs"|jjdkrtd||j S)Nbz1negating a sparse boolean matrix is not supported)rkindNotImplementedErrorrrr r r r__neg__/s z_data_matrix.__neg__cCs"t|r|j|9_|StSdSr rrNotImplementedr otherr r r__imul__5sz_data_matrix.__imul__cCs*t|r"d|}|j|9_|StSdS)Ng?r')r r*Zrecipr r r __itruediv__<s z_data_matrix.__itruediv__unsafeTcCsFt|}|j|kr2|j|j|||d|dS|r>|S|SdS)N)castingcopyr/)rrrrastyper/)r rr.r/r r rr1Ds  z_data_matrix.astypecCs8t|jtjr$|j|j|dS|r0|S|SdS)Nr0)rZ issubdtyperZcomplexfloatingrrconjr/)r r/r r rr2Qs z_data_matrix.conjcCs|j|jddSNTr0)rrr/r r r rr/[sz_data_matrix.copycCst|Sr )r count_nonzerorr r r rr4`sz_data_matrix.count_nonzeroNcCs8t|std|}|dur*||}|||S)z This function performs element-wise power. 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These are not implemented for dia_matrix, hence the separate class. c Cs|j|}|dkrtd|jd|}|dkr8|n|}|||\}}t|j||k}|||d||<|dk} t | |}t | |}ddl m } |dkr| |t t ||ff|jd|fdS| ||t t |ff|j|dfdSdS)Nr&zero-size array to reduction operationr) coo_matrix)rshape)rL ValueErrortocsctocsrrZ _minor_reducerdiffindptrcompressrKzeroslenr) r axis min_or_maxNMmatZ major_indexvaluenot_fullmaskrKr r r_min_or_max_axiss(      z_minmax_mixin._min_or_max_axiscCs|durtdt||dur~d|jvr2td|jd}|jdkrL|S||}|jt |jkrz|||}|S|dkr|d7}|dks|dkr| ||StddS)N2Sparse matrices do not support an 'out' parameter.rrJrzaxis out of range) rMrrLrtypennzreducerZravelrprodr^)r rVoutrWzeromr r r _min_or_maxs$     z_minmax_mixin._min_or_maxcCs>|j|dkrtd|dkr&|d7}|jd}|dkrB|n|}|||j\}}tj |t d}t t |j \} | D]} |j | | d\} } |j| | } |j| | }|| }| |}|||s| | |kr|||| <qt||}||krt|||| <q||| <q|dkr6|dd}t|S)Nrz7Can't apply the operation along a zero-sized dimension.r`)rrrC)rLrMrrarNrOrZ_swaprrTintZnonzerorPrQrindicesrHminZreshaper)r rVr?comparerfrZZret_sizeZ line_sizeretZnz_linesipqrrjamrgzero_indr r r_arg_min_or_max_axiss2      z"_minmax_mixin._arg_min_or_max_axisc Cs|durtdt||durd|jvr2td|jdkr@dS|jd}|}|||j}|j|}|||rt |j ||jdt |j |St |j} | |jkr|S|j |jd|j } t| | } ||krt| |S| S||||S)Nr_rz-Can't apply the operation to an empty matrix.r)rMrrLrbrraZtocoorrrirowcolrrdrHrkrs) r rVrer?rlrfrZrqrgsizerErrr r r_arg_min_or_maxs0      &    z_minmax_mixin._arg_min_or_maxNcCs|||tjS)a6 Return the maximum of the matrix or maximum along an axis. This takes all elements into account, not just the non-zero ones. Parameters ---------- axis : {-2, -1, 0, 1, None} optional Axis along which the sum is computed. The default is to compute the maximum over all the matrix elements, returning a scalar (i.e., `axis` = `None`). out : None, optional This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used. Returns ------- amax : coo_matrix or scalar Maximum of `a`. If `axis` is None, the result is a scalar value. If `axis` is given, the result is a sparse.coo_matrix of dimension ``a.ndim - 1``. See Also -------- min : The minimum value of a sparse matrix along a given axis. numpy.matrix.max : NumPy's implementation of 'max' for matrices )rhrmaximumr rVrer r rmax#sz_minmax_mixin.maxcCs|||tjS)a6 Return the minimum of the matrix or maximum along an axis. This takes all elements into account, not just the non-zero ones. Parameters ---------- axis : {-2, -1, 0, 1, None} optional Axis along which the sum is computed. The default is to compute the minimum over all the matrix elements, returning a scalar (i.e., `axis` = `None`). out : None, optional This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used. Returns ------- amin : coo_matrix or scalar Minimum of `a`. If `axis` is None, the result is a scalar value. If `axis` is given, the result is a sparse.coo_matrix of dimension ``a.ndim - 1``. See Also -------- max : The maximum value of a sparse matrix along a given axis. numpy.matrix.min : NumPy's implementation of 'min' for matrices )rhrZminimumryr r rrkCsz_minmax_mixin.mincCs|||tjtjS)a.Return indices of maximum elements along an axis. Implicit zero elements are also taken into account. If there are several maximum values, the index of the first occurrence is returned. 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If None (default), index of the minimum element in the flatten data is returned. out : None, optional This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used. Returns ------- ind : numpy.matrix or int Indices of minimum elements. If matrix, its size along `axis` is 1. )rwrargminZlessryr r rr|zsz_minmax_mixin.argmin)NN)NN)NN)NN) r8r9r:r<r^rhrsrwrzrkr{r|r r r rrIs%' rI)r<ZnumpyrbaserrZsputilsrrr__all__rZnpfuncr8rArBsetattrrHrIr r r rsm