a ij$@shdZdZddlZddlZddlmZddlmZddl m Z m Z ddl m Z ddlmZdd lmZmZmZeefZddlZd d ZGd d d ejZejejejejejejej ej!ej"ej#ej$ej%ej&ej'ej(ej)ej*ej+i Z,ejejejejejejej!ej ej#ej"ej%ej$ej'ej&ej)ej(ej+ej*dejdejdejdej dej"dej$dej(dej*dej&iZ-dS)aLists/tuples as data-format for storage Note: This implementation is *far* less efficient than using Numpy to support lists/tuples, as the code here is all available in C-level code there. This implementation is required to allow for usage without numpy installed. listsN)_types)_arrayconstants)constanterror) ERROR_ON_COPY) formathandler)bytesunicodeas_8_bitcCs&ts|Sdd}t|dd|_|SdS)zNDecorator which raises informative error if we try to copy while ERROR_ON_COPYc_std|jjfdS)Nz%s passed, cannot copy with ERROR_ON_COPY set, please use an array type which has native data-pointer support (e.g. numpy or ctypes arrays))rZ CopyError __class____name__)selfvalueargsnamedrQ/home/ghrups/robot-bench/.venv/lib/python3.9/site-packages/OpenGL/arrays/lists.pyraiseErrorOnCopys z%err_on_copy..raiseErrorOnCopyr rN)rgetattrr )funcrrrr err_on_copys rc@seZdZdZedddZeejZ e Z dZ ee ddZ e dd Ze d d Ze d d Ze dddZe ddZe ddZee dddZee dddZee d ddZe d!ddZdS)" ListHandleraStorage of array data in Python lists/arrays This mechanism, unlike multi-dimensional arrays, is not necessarily uniform in type or dimension, so we have to do a lot of extra checks to make sure that we get a correctly-structured array. That, as well as the need to copy the arrays in Python code, makes this a far less efficient implementation than the numpy implementation, which does all the same things, but does them all in C code. Note: as an *output* format, this format handler produces ctypes arrays, not Python lists, this is done for convenience in coding the implementation, mostly. Nc Csbz t|WSttfy\}z4|||}tt|}|f|_|WYd}~Sd}~00dS)N)ctypesbyref TypeErrorAttributeErrorasArrayZc_void_p addressofZ_temporary_array_)rinstancetypeCodeerrarraypprrr from_param8s  zListHandler.from_paramTcCs t|S)zCGiven value in a known data-pointer type, return void_p for pointer)rr)clsrrrrvoidDataPointerFszListHandler.voidDataPointercCs t|}|D] }||9}q |S)z#Return array of zeros in given size)GL_TYPE_TO_ARRAY_MAPPING)r%dimsr typedimrrrzerosLs zListHandler.zerosc Cs|zt|g}Wn.tttfy<}zgWYd}~Sd}~00d}|D]0}||}|durF||krFtd||f|qFdS)zCalculate total dimension-set of the elements in x This is *extremely* messy, as it has to track nested arrays where the arrays could be different sizes on all sorts of levels... Nz+Non-uniform array encountered: %s versus %s)lenrr ValueErrordimsOf)r%x_r!ZchildDimensionchildZ newDimensionrrrr.Ts" zListHandler.dimsOfcCs8t|j}|dur|Std|jtt|fdS)z=Given a value, guess OpenGL type of the corresponding pointerNzADon't know GL type for array of type %r, known types: %s value:%s)ARRAY_TO_GL_TYPE_MAPPINGget_type_rlistkeys)r%rresultrrr arrayToGLTypeos  zListHandler.arrayToGLTypecCs4d}||D] }t|dd}|dur||9}q|S)z6Given a data-value, calculate dimensions for the array_length_Ntypesr)r%rr r(baselengthrrr arraySizes   zListHandler.arraySizeccs6|}|dur2|Vt|dd}t|ttfrd}qdS)z.Produce iterable producing all composite typesNr4)r isinstancer r )r%rZ dimObjectrrrr<s  zListHandler.typesccs.||D]}t|dd}|dur |Vq dS)z"Produce iterable of all dimensionsr:Nr;)r%rr=r>rrrr(s zListHandler.dimscsdurtdt}t|ttfrfdd|D}|r|ddddD] }||9}qV|t|9}|}||dd<|Sn||SdS)zConvert given value to a ctypes array value of given typeCode This does a *lot* of work just to get the data into the correct format. It's not going to be anywhere near as fast as a numpy or similar approach! Nz0Haven't implemented type-inference for lists yetcsg|]}|qSr)r).0itemr%r rr z'ListHandler.asArray..r)NotImplementedErrorr'r@r5tuple dimensionsr,)r%rr Z arrayTypeZsubItemsr*r7rrCrrs    zListHandler.asArraycCst||dS)z-Determine unit size of an array (if possible)rFrHr(r%rr rrrunitSizeszListHandler.unitSizecCst||S)zsT