bidZddlmZmZddlZddlmZddl m cm Z ddl m cmZddlmZddlmZddlmZddlmZddlmZdd lmZd ed ed ej:fd ZGddeeZy)a, Copyright 2013 Steven Diamond Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. )ListTupleN)AffAtom) MulExpression)AxisAtom) Constraint) Expression)Variabledimaxisreturnctjtj|tj|dz  gddg||fd}|dk(r|S|jS)aKReturn a sparse matrix representation of first order difference operator. Parameters ---------- dim : int The length of the matrix dimensions. axis : int The axis to take the difference along. Returns ------- sp.csc_array A square matrix representing first order difference. rcsc)offsetsshapeformat)sp diags_arraynponesT)r r mats T/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/cvxpy/atoms/affine/cumsum.py get_diff_matrsX .."''#,q)9(9:QGs !C!)3&&ceZdZdZddededdffd ZejdZ dZ de ed ffd Z d Z d Z dd e ed fde ej eeffdZxZS)cumsumz Cumulative sum of the elements of an expression. Attributes ---------- expr : CVXPY expression The expression being summed. axis : int The axis to sum across if 2D. exprr r Nc.tt| ||yN)superr__init__)selfr r __class__s rr$zcumsum.__init__?s fd$T40rcJtj|d|jS)zW Returns the cumulative sum of elements of an expression over an axis. rr )rrr )r%valuess rnumericzcumsum.numericBs yy33rcR|jdjdkDr tdy)Nrzdcumsum is only implemented for 1D or 2D arrays and might not work as expected for higher dimensions.)argsndim UserWarningr%s rvalidate_argumentszcumsum.validate_argumentsIs/ 99Q<  q :  !r.c4|jdjS)zThe same as the input.r)r-rr0s rshape_from_argszcumsum.shape_from_argsPsyy|!!!rc|dj|j}tjt j t j ||f}t|jdj}|jdk(r!t||j|d}|gSt||jj|d}|gS)a+Gives the (sub/super)gradient of the atom w.r.t. each argument. Matrix expressions are vectorized, so the gradient is a matrix. Args: values: A list of numeric values for the arguments. Returns: A list of SciPy CSC sparse matrices or None. rr) rr r csc_arrayrtrilrr r-r_gradr)r%r)r rvargrads rr7z cumsum._gradTsQioodii(ll277277C:#678tyy|))* 99> c*008;Dv !cee,226:1=Dv rc|jgS)zReturns the axis being summed.r(r0s rget_datazcumsum.get_datahs {rrc(tj|}|d}||}t||}tj|||fd}|dk(rtj||}ntj ||}|tj |d|gfS)aCumulative sum via difference matrix. Parameters ---------- arg_objs : list LinExpr for each argument. shape : tuple The shape of the resulting expression. data : Additional data required by the atom. Returns ------- tuple (LinOp for objective, list of constraints) rT)sparse)lu create_varr create_constmul_expr rmul_expr create_eq) r%arg_objsrdataYr r diff_matdiffs rgraph_implementationzcumsum.graph_implementationls* MM% AwDkT*??8c3ZE 19;;x+D<<8,DBLL!d3455r)rr")__name__ __module__ __qualname____doc__r intr$r numpy_numericr*r1rr3r7r;loLinOprrrI __classcell__)r&s@rrr4s 1Z1s141 44 "sCx"( 6:6$S#X6 rxxj)) *6rr) rMtypingrrnumpyr scipy.sparser=rcvxpy.lin_ops.lin_oplin_opslin_oprPcvxpy.lin_ops.lin_utils lin_utilsr>cvxpy.atoms.affine.affine_atomr#cvxpy.atoms.affine.binary_operatorsrcvxpy.atoms.axis_atomrcvxpy.constraints.constraintrcvxpy.expressions.expressionr cvxpy.expressions.variabler rNr5rrrrrbsa!!$$2=*33/'c'''*V6WhV6r