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This differs from numpy for computational efficiency. .. seealso:: min : The minimum value of a sparse matrix along a given axis. .. seealso:: numpy.matrix.max : NumPy's implementation of ``max`` for matrices z%explicit of cupyx.scipy.sparse.{}.max)format __class__r0r experimentalrar$r_rr+r,rVZapi_namerrrr_  z_minmax_mixin.maxcCrg)aReturns the minimum of the matrix or maximum along an axis. Args: axis (int): {-2, -1, 0, 1, ``None``} (optional) Axis along which the sum is computed. The default is to compute the minimum over all the matrix elements, returning a scalar (i.e. ``axis`` = ``None``). out (None): (optional) This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used. explicit (bool): Return the minimum value explicitly specified and ignore all implicit zero entries. If the dimension has no explicit values, a zero is then returned to indicate that it is the only implicit value. This parameter is experimental and may change in the future. Returns: (cupy.ndarray or float): Minimum of ``a``. If ``axis`` is None, the result is a scalar value. If ``axis`` is given, the result is an array of dimension ``a.ndim - 1``. This differs from numpy for computational efficiency. .. seealso:: max : The maximum value of a sparse matrix along a given axis. .. seealso:: numpy.matrix.min : NumPy's implementation of 'min' for matrices z%explicit of cupyx.scipy.sparse.{}.min)rhrir0rrjrar$r^rkrrrr^&rlz_minmax_mixin.mincC|||tjtjS)aReturns indices of maximum elements along an axis. Implicit zero elements are taken into account. If there are several maximum values, the index of the first occurrence is returned. If ``NaN`` values occur in the matrix, the output defaults to a zero entry for the row/column in which the NaN occurs. Args: axis (int): {-2, -1, 0, 1, ``None``} (optional) Axis along which the argmax is computed. If ``None`` (default), index of the maximum 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: (cupy.narray or int): Indices of maximum elements. If array, its size along ``axis`` is 1. )rfr$r;Zgreaterrr+r,rrrr;Jsz_minmax_mixin.argmaxcCrm)a Returns indices of minimum elements along an axis. Implicit zero elements are taken into account. If there are several minimum values, the index of the first occurrence is returned. If ``NaN`` values occur in the matrix, the output defaults to a zero entry for the row/column in which the NaN occurs. Args: axis (int): {-2, -1, 0, 1, ``None``} (optional) Axis along which the argmin is computed. If ``None`` (default), index of the minimum element in the flatten data is returned. out (None): (optional) This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used. Returns: (cupy.narray or int): Indices of minimum elements. If matrix, its size along ``axis`` is 1. )rfr$argminlessrnrrrrobsz_minmax_mixin.argmin)NN) r0r1r2r5r[rarcrfr_r^r;rorrrrrLs  $ $rLcs,fdd}d|_|_tt|dS)Ncstt}||j}||Sr)getattrr$rr)rZufuncresult func_namerrf~s   z_install_ufunc..fzElementwise %s.)r5r0setattrr)rtrurrsr_install_ufunc|s  rwcCstD]}t|qdSr)_ufuncsrwrsrrr_install_ufuncss ry)r$numpyrAZ cupy._corerrZcupyx.scipy.sparserrrrxr4rr?rKobjectrLrwryrrrrs      k  k