_-Ph&XdZddlZddlZddlmZmZmZddlm Z m Z  d dZ d d Z d d Z dS)a#Visualization tools for coarse grids, both C/F splittings and aggregation. Output is either to file (VTK) or to the screen (matplotlib). vis_splitting: visualize C/F splittings through vertex elements vis_aggregate_groups: visualize aggregation through groupins of edges, elements N) csr_matrix coo_matrixtriu)write_basic_mesh write_vtu output.vtuc t||||ddddd}||vrtd|||}t|}||jdkr+||d |jdk}t |j|jdkr|jd d |jd d z dkd}tj | d t  }|j||d k<|jd ||dk<||} n |j|} tjttj| d dkd} || d d f} | jd} | } tjtjd|jdtj|jd ft }tjt | f}t |t | krtdt)||| ff|jd|d zf}|j|z}t-|d }tj|j|jfj}||j|j|j|jk}|jd}tj | d  }tjtj|jtj|d kd }t |}dtj| fz}dtj|fz}d tj|fz}d |d||| i}d |d|||i}t;||||d S)aCoarse grid visualization of aggregate groups. Create .vtu files for use in Paraview or display with Matplotlib. Parameters ---------- V : {array} coordinate array (N x D) E2V : {array} element index array (Nel x Nelnodes) AggOp : {csr_matrix} sparse matrix for the aggregate-vertex relationship (N x Nagg) mesh_type : {string} type of elements: vertex, tri, quad, tet, hex (all 3d) fname : {string, file object} file to be written, e.g. 'output.vtu' Returns ------- Writes data to .vtu file for use in paraview (xml 0.1 format) or displays to screen using matplotlib Notes ----- Works for both 2d and 3d elements. Element groupings are colored with data equal to 2.0 and stringy edges in the aggregate are colored with 3.0 Examples -------- >>> from pyamg.aggregation import standard_aggregation >>> from pyamg.vis.vis_coarse import vis_aggregate_groups >>> from pyamg.gallery import load_example >>> data = load_example('unit_square') >>> A = data['A'].tocsr() >>> V = data['vertices'] >>> E2V = data['elements'] >>> AggOp = standard_aggregation(A)[0] >>> vis_aggregate_groups(V=V, E2V=E2V, AggOp=AggOp, ... mesh_type='tri', fname='output.vtu') >>> from pyamg.aggregation import standard_aggregation >>> from pyamg.vis.vis_coarse import vis_aggregate_groups >>> from pyamg.gallery import load_example >>> data = load_example('unit_cube') >>> A = data['A'].tocsr() >>> V = data['vertices'] >>> E2V = data['elements'] >>> AggOp = standard_aggregation(A)[0] >>> vis_aggregate_groups(V=V, E2V=E2V, AggOp=AggOp, ... mesh_type='tet', fname='output.vtu') )VE2VAggOp mesh_type )triquadtethexzUnknown mesh_type=rr)axisNdtypez)Problem constructing vertex-to-vertex map)shape)r cellsfnamecdata) check_input ValueErrorrmaxrlenindicesindptrnonzeronparraysumintravelwhereabsdiffkronarangeonesrTrtocoovstackrowcolargwhereisinr)r r r rrmap_type_to_keykey full_aggsnew_aggs ElementAggsmaskE2V_aNel_ar7r6dataV2VedgesE2V_bNel_bsumsE2V_cNel_ccolors_acolors_bcolors_crr s T/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/pyamg/vis/vis_coarse.pyvis_aggregate_groupsrNsl!EY????2bAAO''9i99::: ) $C u  E wwyyEKN""#''q'//EKN23  5=U[^++l122&crc)::q@IIKKAN 8EII1I--S999??AA#(=a #(;q>a sm mC( 8C ,,--11q199Q> ? ? BD aaaLE KNE ))++C '")Asy|,,'39Q1, they are assumed ordered [...dof1..., ...dof2..., etc] Examples -------- >>> import numpy as np >>> from pyamg.vis.vis_coarse import vis_splitting >>> V = np.array([[0.0,0.0], ... [1.0,0.0], ... [0.0,1.0], ... [1.0,1.0]]) >>> splitting = np.array([0,1,0,1,1,0,1,0]) # two variables >>> vis_splitting(V,splitting,output='vtk',fname='output.vtu') >>> from pyamg.classical.split import RS >>> from pyamg.vis.vis_coarse import vis_splitting >>> from pyamg.gallery import load_example >>> data = load_example('unit_square') >>> A = data['A'].tocsr() >>> V = data['vertices'] >>> E2V = data['elements'] >>> splitting = RS(A) >>> vis_splitting(V=V,splitting=splitting,output='vtk', fname='output.vtu') rr.rz.vtuNrr_)rP matplotlibzproblem with outputtyperPvertex)r r rr rrUzr.zb.T)clip_onz%C/F splitting (red=coarse, blue=fine)xyoffz) Note: matplotlib is needed for plotting.)r!rr+r$r(r1splitjoinranger"rmatplotlib.pyplotpyplotr-figureplottitlexlabelylabelrshow ImportErrorprint)r splittingoutputrNNdofr afname1fname2 new_fnamedr pltcdataFcdataCxCyCxFyFs rM vis_splittingrxsr9  A s9~~! " "D )Aq $ $ $C  CA 1vvzz13B32I 1d^^DD !88!22AaC22&22I1Q3!A#q/* . . .677 7 U?? qcX#(  ; ; ; ; ; | # # D//////%1*--a0%1*--a0vqy\vqy\vqy\vqy\ Rr2tTBBB ABBB 3 3  D D DBCCCCC D!$DDs"DH&&IIcd|3tj|jtjst d|vtj|jtjst d|dkr+tjd|d|+|j d|j dkrt d ||t d |I|G|j d|j dks|j d|j dkrt d ||t d |F| }|0t||j dzdkrt d |d }||vrt d|dSdS)z Check input for local functions.NzV should be of type floatzE2V should be of type integerrzElement indices begin at r) stacklevelrz AggOp should be of size N x Naggzproblem with check_inputz2expected square matrix A and compatible with AggOpz!splitting must be a multiple of N)rVrrrrzmesh_type should one of ) r( issubdtyperfloatingr"integerminwarningswarnrr,r$)r r r Arhrvalid_mesh_typess rMr!r!s}R]17BK@@}4555 }SY 33 ><== = 7799>> MAcggiiAAa P P P P U[^ek!n<<;<<<}3444 %+ WQZ171: % %171:Q+G+GMNNN3444OO%% =c)nnqwqz9a??@AA AB , , ,J8HJJKK K , ,rO)r )rPr )NNNNNN)__doc__rnumpyr( scipy.sparserrr vtk_writerrrrNrxr!rOrMrs555555555533333333 ,z:z:z:z:ziDiDiDiDX L L L L L LrO