:vjz dZddlZddlZddlmZmZmZddlm Z m Z ddl m Z ddl mZmZmZmZmZmZmZ ddlmZmZdd lmZ ddlZd+d Zd eefd Z d Z!dZ"dZ#dZ$d,dededzfdZ% d-de&de&dedzded e'f dZ( d.dedefdZ)d/dZ*ded e'efdZ+deded eezfdZ,d0d Z-d,d!Z.d1d"Z/d2d#edzd$edzfd%Z0 d/ded&edzd e1e&e&ffd'Z2d(Z3d/d)Z4d/d*Z5y#e$r@Zej8eZej8eZej8eZYdZ[dZ[wwxYw#e$rZej8eZYdZ[dZ[wwxYw)3z graph.py ------------- Deal with graph operations. Primarily deal with graphs in (n, 2) edge list form, and abstract the backend graph library being used. Currently uses networkx or scipy.sparse.csgraph backend. N) exceptionsgroupingutil)logtol)faces_to_edges) ArrayLikeGraphEngineTypeIntegerNDArrayNumberSequenceint64) coo_matrixcsgraph)cKDTreec|#t|d\}}|jdn|j}|j}t j |d}t |dk(rtjd ||}|dddf|dddfk7}||}|jd|r,||dddf|}t |t |k(sJ||fS|S) a Returns an (n, 2) list of face indices. Each pair of faces in the list shares an edge, making them adjacent. Parameters ----------- faces : (n, 3) int, or None Vertex indices representing triangles mesh : Trimesh object If passed will used cached edges instead of generating from faces return_edges : bool Return the edges shared by adjacent faces Returns ---------- adjacency : (m, 2) int Indexes of faces that are adjacent edges: (m, 2) int Only returned if return_edges is True Indexes of vertices which make up the edges shared by the adjacent faces Examples ---------- This is useful for lots of things such as finding face- connected components: ```python >>> graph = nx.Graph() >>> graph.add_edges_from(mesh.face_adjacency) >>> groups = nx.connected_components(graph_connected) ``` NT) return_indexraxis require_countrz3No adjacent faces detected! Did you merge vertices?) r sort edges_sorted edges_facer group_rowslenrdebug) facesmesh return_edgesedgesr edge_groups adjacency nondegenerateadjacency_edgess ^/workspace/moltex-experiments/.pixi/envs/default/lib/python3.12/site-packages/trimesh/graph.pyface_adjacencyr*-sH |+5tDz  !!__ %%e1=K ;1 GH ;'IadOyA6M-(INNN AqD 1- @A?#s9~555/)) returnc2|j}|j|z}|jd|j|j }t j |jdddf|jdddffdt j}|S)a Find faces that share a vertex i.e. 'neighbors' faces. Relies on the fact that an adjacency matrix at a power p contains the number of paths of length p connecting two nodes. Here we take the bipartite graph from mesh.faces_sparse to the power 2. The non-zeros are the faces connected by one vertex. Returns ---------- neighborhood : (n, 2) int Pairs of faces which share a vertex rN)rdtype) faces_sparseTsetdiageliminate_zerostocoonp concatenaterowcolr)r"VTTT neighborhoods r)face_neighborhoodr<{s|   B BJJqM B>> 4"&&D/*288L r+c tj|jtjdz }|j}t |jj D]\}}|j|}tjtj||dddfjdk(||dddfjdk(}|jddk(}d||ddf<|||||f<|S)a Return the vertex index of the two vertices not in the shared edge between two adjacent faces Parameters ---------- mesh : Trimesh object Input mesh Returns ----------- vid_unshared : (len(mesh.face_adjacency), 2) int Indexes of mesh.vertices for degenerate faces without exactly one unshared vertex per face it will be -1 r/rNrr.rrF) r5 zeros_liker*rface_adjacency_edges enumerater1r! logical_not logical_orreshapesum)r" vid_unsharedr$ifidr!unsharedrow_oks r)face_adjacency_unsharedrLs(==!4!4BHHEIL  % %ED//1123 3>> MMq!t,,W55q!t,,W55  1%*$&!"'/ VQY!3$ r+c |jtjdkD}tjdtj|j|z}|j |j }tj|djd}|j}tjtj|j |djd}tj|tj||jd|z}tj|}tjt!|j"tj$z} |||z | |<| |fS)a Compute an approximate radius between adjacent faces. Parameters -------------- mesh : trimesh.Trimesh Returns ------------- radii : (len(self.face_adjacency),) float Approximate radius between faces Parallel faces will have a value of np.inf span : (len(self.face_adjacency),) float Perpendicular projection distance of two unshared vertices onto the shared edge g{Gz?g@rr)r.r?)face_adjacency_anglesr5radiansabssinverticesrLdiffrErArunitizesubtract diagonal_dotrow_normonesrr*inf) r"nonzero denominator point_pairsvectorsr$ edges_vecperpspanradiis r)face_adjacency_radiusrcs1,((2::d+;;G&&rvvd&@&@&IJJKK-- < <=Kggk*227;G  % %E RWWT]]5%9BJJ7STI ;;$##GY7??H9T D == D GGC++, - 6E'][0E'N $;r+cdtj}|j|j|S)a/ Returns a networkx graph representing the vertices and their connections in the mesh. Parameters ---------- mesh : Trimesh object Returns --------- graph : networkx.Graph Graph representing vertices and edges between them where vertices are nodes and edges are edges Examples ---------- This is useful for getting nearby vertices for a given vertex, potentially for some simple smoothing techniques. >>> graph = mesh.vertex_adjacency_graph >>> graph.neighbors(0) > [1, 3, 4] )nxGraphadd_edges_from edges_unique)r"gs r)vertex_adjacency_graphrjs(.  AT&&' Hr+ctjt|d}tjt|d}tj||tj }|S)a Given two sets of faces, find the edges which are in both sets. Parameters --------- faces_a : (n, 3) int Array of faces faces_b : (m, 3) int Array of faces Returns --------- shared : (p, 2) int Edges shared between faces rr operation)r5rr r boolean_rows intersect1d)faces_afaces_be_ae_bshareds r) shared_edgesrusK ''.) 2C ''.) 2C  " "3r~~ FF Mr+enginefacet_thresholdc|tj}|j}|j}t j t |t}t j|tjkD}||||z dz|kD||<t|j|t jt |jd|}|S)an Find the list of parallel adjacent faces. Parameters ----------- mesh : trimesh.Trimesh engine Which graph engine to use facet_threshold : float Threshold for two facets to be considered coplanar Returns --------- facets : sequence of (n,) int Groups of face indexes of parallel adjacent faces. r>r)nodesmin_lenrv)rrwrcface_adjacency_spanr5rYrboolrQzeroconnected_componentsr*aranger!)r"rvrwrbraparallelr[ componentss r)facetsr%s$--  & &E  # #Dwws5z.HffTlSXX%Gw$w-7A=OHW& H%iiDJJ( J r+only_watertightrepairr&c | |j}|rd}nd}t|tjt |j ||}|j |f||d|S)a3 Split a mesh into multiple meshes from face connectivity. If only_watertight is true it will only return watertight meshes and will attempt to repair single triangle or quad holes. Parameters ---------- mesh : trimesh.Trimesh The source multibody mesh to split only_watertight Only return watertight components and discard any connected component that isn't fully watertight. repair If set try to fill small holes in a mesh, before the discard step in `only_watertight. adjacency : (n, 2) int If passed will be used instead of `mesh.face_adjacency` engine Which graph engine to use for the connected components. Returns ---------- meshes : (m,) trimesh.Trimesh Results of splitting based on parameters. r)r$ryrzrv)rr)r*r~r5rrr!submesh)r"rrr&rvkwargsrzrs r)splitrVstH'' %ryyTZZ97SYJ 4<< $3F FL r+rzc fd} fd}tjtjtjt dk(rgSt dk(r+dkr$tj dj SgStjds tddg}t dkDr|jjt dkDr|jjtj|dz tj t}d |<|jd }|tj d |fd |ff} || vr | |S| j#D] } | cSt'd #t$$rY$wxYw)a Find groups of connected nodes from an edge list. Parameters ----------- edges : (n, 2) int Edges between nodes nodes : (m, ) int or None List of nodes that exist min_len : int Minimum length of a component group to return engine : str or None Which graph engine to use (None for automatic): (None, 'networkx', 'scipy') Returns ----------- components : (n,) sequence of (*,) int Nodes which are connected ctj}dkr|jtj|Dcgc] }t |c}Scc}w)z: Find connected components using networkx r)re from_edgelistadd_nodes_fromr~list)graphrHr$rzrys r)components_networkxz1connected_components..components_networkxsU  ' a<   '!#!8!8!?@!?AQ!?@@@sAct}tjt}d|<tjtj |}t j||}|Dcgc]}|| c}Scc}w)zF Find connected components using scipy.sparse.csgraph ) node_countr>T)rz)connected_component_labelsr5zerosr|rrrgroup) labels containedindexrcr$rzrrys r)components_csgraphz0connected_components..components_csgraphsw ,EjIHHZt4  % *BHH5i@^^F9$5wG ",-*Qa*---s5 Br>rrr?r.redges must be (n, 2)!Trscipynetworkxzno graph engines available!)r5 asanyarrayruniquerrEtolistris_shape ValueErrorappendmaxrr|all collections OrderedDictvalues BaseException ImportError) r$rzryrvrrcountsmaskedges_okenginesfunctionrs ``` @r)r~r~s2 A$ MM%rxx 0E } %  5zQ Uq a<::eW-446 6I == (011SF 5zA~ eiik" 5zA~ eiik"!#J 88Jd +DDKE{A&H (OE%% % &5H(IJG wv  NN$ : % 3 44   s&F;; GGcvt||}tj|d\}}|t||k(sJ|S)a? Label graph nodes from an edge list, using scipy.sparse.csgraph Parameters ----------- edges : (n, 2) int Edges of a graph node_count : int, or None The largest node in the graph. Returns ---------- labels : (node_count,) int Component labels for each node F)directed) edges_to_coorr~r)r$rmatrix _body_countrs r)rrsD % ,F!66vNK6{j((( Mr+ traversalc tj|dd|ddf}|jtj|dddk}|j r|g}nOt j |dd}|Dcgc],}tj|dddf|||dddg.}}tj|Dcgc]G}t|d kDxr5|d|dk7xr(|jt|d|dgddkIc}}|jr@tj|dD]%} tj|| || ddg|| <'tjr`|D][}tjtj|dd|ddfd} |j| ddkj r[J|Scc}wcc}w) a Given a traversal as a list of nodes split the traversal if a sequential index pair is not in the given edges. Useful since the implementation of DFS we're using will happily return disconnected values in a flat traversal. Parameters -------------- traversal : (m,) int Traversal through edges edges_tree : cKDTree A way to reconstruct original edge indices from sorted (n, 2) edge values. This is a slight misuse of a kdtree since one could just hash the tuples of the integer edges, but that isn't possible with numpy arrays easily and this allows a vectorized reconstruction. Returns --------------- split : sequence of (p,) int Traversals split into only connected paths. Nr.rrrg|=T)rz only_nonzeror)r5 column_stackqueryrrrblocksr6arrayrsortedanyr[rstrict) r edges_tree trav_edgeexistsrrbs needs_closerH check_edges r)_split_traversalrs23B12 ?@I  bggia8 9! ?E!H, zzA!CR&!AB%!AJJ$$Z03e;@@B BB L1  s :1GA G traversalsr$c $tj|d}t|}t|dk(r|j Sg}|D]}|j t || tj|Dcgc]}tj|dd|ddf!c}}t|dkDrI|jd|j tj||tj|S|j }|Scc}w)a Convert a traversal of a list of edges into a sequence of traversals where every pair of consecutive node indexes is an edge in a passed edge list Parameters ------------- traversals : sequence of (m,) int Node indexes of traversals of a graph edges : (n, 2) int Pairs of connected node indexes Returns -------------- splits : sequence of (p,) int Node indexes of connected traversals rrr)rrNr.rl) r5rrrcopyextendrr vstack_emptyrrrn setdiff1d)rr$rsplitsryrHincludeds r)fill_traversalsrMs& GGE "EJ :!zz| F &:NO   F!SFq"//1Sb61QR5/"BF!STH 8}q 1   h++E8r||TU M M"Ts9$D ctj|tj}t|dk(rgSt j |ds t dt|jj}|dk(rtj}n!|dk(rtj}n t d|jd t|}tj|j!}tj"|dk(d}tj"|dkDd}g}tj$t|dztj&}tj(||fD]G} || r ||| d d j+tj} |j-| d || <I|S) a Given an edge list generate a sequence of ordered depth first search traversals using scipy.csgraph routines. Parameters ------------ edges : (n, 2) int Undirected edges of a graph mode : str Traversal type, 'bfs' or 'dfs' Returns ----------- traversals : (m,) sequence of (p,) int Ordered DFS or BFS traversals of the graph. r>rrzedges are not (n, 2)!bfsdfsz(traversal mode must be either dfs or bfsrrF)i_startreturn_predecessorsrT)r5rrrrrrstrlowerstriprbreadth_first_orderdepth_first_orderrrbincountravelr[rbool_r6astyper) r$modefuncrr nodes_leafryrvisitedstartordereds r)rr|s}" HHU"(( +E 5zQ ]]5' *011 t9??  " " $D u}** ((CDD JJAJ  E{{5;;=)HHM*1-J JJx!| $Q 'EJhhs8}q(9G U 34 5>  5ee &   '"5 r+ctj|tj}t|dk(s!t j |ds t d||jdz}t|}|$tjt|t}t||jf|j||fS)a Given an edge list, return a boolean scipy.sparse.coo_matrix representing the edges in matrix form. Parameters ------------ edges : (n, 2) int Edges of a graph count : int The total number of nodes in the graph if None: count = edges.max() + 1 data : (n,) any Assign data to each edge, if None will be bool True for each specified edge Returns ------------ matrix: (count, count) scipy.sparse.coo_matrix Sparse COO r>rrrr)r/shape)r5rrrrrrrintrYr|rr1r/)r$countdatas r)rrs* MM%rxx 0E J!Ot}}UG<011 } a JE |wws5z. tUWWoTZZu~ NNr+ctjt}|r)|Dcgc]}||dj|dc}nB|Dcgc]6}||dj|d||dj|df8c}||j dz}t |Dcgc]}t ||}}|Scc}wcc}wcc}w)a Find the neighbors for each node in an edgelist graph. TODO : re-write this with sparse matrix operations Parameters ------------ edges : (n, 2) int Connected nodes directed : bool If True, only connect edges in one direction Returns --------- neighbors : sequence Vertex index corresponds to set of other vertex indices rr)r defaultdictsetaddrranger)r$ max_indexr neighborsedgerHrs r)rrs$'',I5:;UT47   Q (U; tAw  # #DG ,iQ.@.D.DT!W.M N IIK!O ).y)9 :)9AT)A, )9E : L <  ;s!C ;C)C angle facet_minareacd|tjd}t|jdk(r|j S|j |k}|j|}g}d}||j }|j|z } |jD cgc]} || j|kDs| }} t|dkDrstjt|jt} d| tj|<|| |jd}tj|}t'|d | } t|dkDr| j)|t| dk(r|j Stjtj| } t| t|jk7r\tj*tj,t|j| } | j)| j/d |j1| dd }| |j2d<t|jt|jk7rt#j$d|Scc} w#t $rt#j$dd Y}wxYw)az Return a non-watertight version of the mesh which will render nicely with smooth shading by disconnecting faces at sharp angles to each other. Parameters ----------- mesh : trimesh.Trimesh Source geometry angle : float or None Angle in radians face pairs with angles smaller than this will appear smoothed facet_minarea : float or None Minimum area fraction to consider IE for `facets_minarea=25` only facets larger than `mesh.area / 25` will be considered. Returns --------- smooth : trimesh.Trimesh Geometry with disconnected face patches Nrr>Frrzfailed to calculate facetsT)exc_infor)rzryr?)rroriginal_componentszface count in smooth wrong!)r5rPrr*rrO area_facesarearrFrYr!r|hstackrrrrwarningr~rrrrErmetadata)r"rrangle_okr&rryareasmin_areafrrrbrokesmooths r) smooth_shader s=. } 2 4  1$yy{))E1H##H-IF E 99}, E"&JAa 0IaFJ6{Qwws4::d;*/RYYv&'%d9o&9&9q&9&AB  ),&i%HJ 6{Q&! :!yy{YYryy, -F 6{c$**o% RYYs4::7@%--01\\*eD\ IF-7FOO)* 6<<C O+ 12 MOK E KK4t D D Es+J J*J.BJ J J/.J/rcP|tj|d}tj|d}t t |dzt |k(}||j dddddfj}t tj|j}||fS)ah Parameters ----------- edges : (n, 2) int List of vertex indices edges_sorted : (n, 2) int Pass vertex indices sorted on axis 1 as a speedup Returns --------- watertight : boolean Whether every edge is shared by an even number of faces winding : boolean Whether every shared edge is reversed Nrrrr)r.rrN) r5rrrr|rrEr1equalr)r$rgroups watertightopposingwindings r) is_watertightr cs(wwu1-  Q ?Fs6{Q3u:56JV}$$W-a1f577H288X&**,-G w r+cddl}ddl}|j5}tjj j ||j|jd|jdg}ddd|S#1swYSxYw)z Turn a networkx graph into an SVG string using graphviz `dot`. Parameters ---------- graph: networkx graph Returns --------- svg: string, pictoral layout in SVG format rNdotz-Tsvg) subprocesstempfileNamedTemporaryFileredrawing nx_agraph write_dotname check_output)rr rdot_filesvgs r) graph_to_svgrsj  $ $ &( &&uhmm<%%uhmmW&EF ' J ' Js AA66Bc|6t|jt|jzdz}|dfg}g}g}t|D]}|dd}||}t|dk(r3|j |t|dk(r|S|j }Qd} |j D]L} || j D]4} | r|j | | fd} |j |dd| | fgz6N|S)a* For a networkx MultiDiGraph, find all paths from a source node to leaf nodes. This function returns edge instance numbers in addition to nodes, unlike networkx.all_simple_paths. Parameters --------------- G : networkx.MultiDiGraph Graph to evaluate source : hashable Node to start traversal at cutoff : int Number of nodes to visit If None will visit all nodes Returns ---------- traversals : (n,) list of [(node, edge instance index), ] paths Traversals of the multigraph Nrrr.TF)rr$ryrrpopkeys) Gsourcecutoffcurrentqueuer_ current_nodechildrnodeinstances r)multigraph_pathsr%s*~aggi.3qwwy>1Q6{mG EJ 6]r{1~ , u:?   g &5zQ* %iikGE  %d 0 0 2H h'78 %  WSb\dH5E4F%FG!3%+D r+cg}tj|D]A\}}||d|d|d}||j|.|j||C|S)a\ Given a MultiDiGraph traversal, collect attributes along it. Parameters ------------- G: networkx.MultiDiGraph traversal: (n) list of (node, instance) tuples attrib: dict key, name to collect. If None, will return all Returns ------------- collected: (len(traversal) - 1) list of attributes rr)rpairwiser)rrattrib collecteduvattribss r)multigraph_collectr-skI i(1AaD'!A$-!% >   W %   WV_ - ) r+)NNF)NN)TTNN)rNN)N)r)NF)Ng$@)6__doc__rnumpyr5rrr constantsrrgeometryr typedr r r r rrr scipy.sparserr scipy.spatialrrEExceptionWrapperrrer*r<rLrcrjrurr|rrr~rrrrrrrtupler rr%r-r+r)r:s(($00%(K\wu~2+\.b 8,..&4-.f!"&" 33 34 3  3 3nHLf5f55Df5R2<<W <~,,,x'?Q,^DN$ONDTftmT6D=Tp8<" "$-$4" 4:"J.AHI0)j))!,G)j))!,G,,,Q/J 0( % $ $Q 'B(s/C%D-%D**6D%%D*-E2E  E