ó |£*^c@sñdZdjdddgƒZddddgZd d lmZd d lmZd d lm Z d d l Z d d l Z d d l Z d d l Zdd d„Zddd d d„Zdd„Zddd dd„Zddddd d„Zd S(s" Generators for geometric graphs. s sAric Hagberg (hagberg@lanl.gov)s Dan Schult (dschult@colgate.edu)s!Ben Edwards (BJEdwards@gmail.com)trandom_geometric_grapht waxman_graphtgeographical_threshold_graphtnavigable_small_world_graphiÿÿÿÿ(t bisect_left(treduce(tproductNicCs0tjƒ}d|_|jt|ƒƒ|dkr{xW|D]9}gtd|ƒD]}tjƒ^qQ|j|d>> G = nx.random_geometric_graph(20, 0.1) Notes ----- This algorithm currently only supports Euclidean distance. This uses an `O(n^2)` algorithm to build the graph. A faster algorithm is possible using k-d trees. The ``pos`` keyword argument can be used to specify node positions so you can create an arbitrary distribution and domain for positions. For example, to use a 2D Gaussian distribution of node positions with mean (0, 0) and standard deviation 2:: >>> import random >>> n = 20 >>> p = {i: (random.gauss(0, 2), random.gauss(0, 2)) for i in range(n)} >>> G = nx.random_geometric_graph(n, 0.2, pos=p) References ---------- .. [1] Penrose, Mathew, Random Geometric Graphs, Oxford Studies in Probability, 5, 2003. sRandom Geometric Graphitpostdatacss#|]\}}||dVqdS(iN((t.0tatb((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pys dsiN(tnxtGraphtnametadd_nodes_fromtrangetNonetrandomtnodetset_node_attributestnodestTruetpoptsumtziptadd_edge(tntradiustdimRtGtiRtutdutputvtdvtpvtd((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pyRs"4    :   c Cstjƒ}|jgt|ƒD] }|^qƒ|dkrlx>|D] }tjdƒ|j|d>> G = nx.geographical_threshold_graph(20, 50) Notes ----- If weights are not specified they are assigned to nodes by drawing randomly from the exponential distribution with rate parameter `\lambda=1`. To specify weights from a different distribution, use the ``weight`` keyword argument:: >>> import random >>> n = 20 >>> w = {i: random.expovariate(5.0) for i in range(n)} >>> G = nx.geographical_threshold_graph(20, 50, weight=w) If node positions are not specified they are randomly assigned from the uniform distribution. References ---------- .. [1] Masuda, N., Miwa, H., Konno, N.: Geographical threshold graphs with small-world and scale-free properties. Physical Review E 71, 036108 (2005) .. [2] Milan Bradonjić, Aric Hagberg and Allon G. Percus, Giant component and connectivity in geographical threshold graphs, in Algorithms and Models for the Web-Graph (WAW 2007), Antony Bonato and Fan Chung (Eds), pp. 209--216, 2007 gð?tweightiRN( R R RRRRt expovariateRRtadd_edges_fromtgeographical_threshold_edges( RtthetatalphaRRR'RR#R((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pyRjsA &  !  :c csÂ|jdtƒ}x©|r½|jƒ\}}|d}|d}xv|D]n\}} | d} | d} tjtd„t|| ƒDƒƒƒ} || || |krH||fVqHqHWqWdS(s¡Generates edges for a geographical threshold graph given a graph with positions and weights assigned as node attributes ``'pos'`` and ``'weight'``. RR'Rcss#|]\}}||dVqdS(iN((R R R ((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pys ÌsN(RRRtmathtsqrtRR( RR+R,RR R!twuR"R#R$twvR%tr((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pyR*¾s     (gš™™™™™Ù?gš™™™™™¹?iicCsttjƒ}|jt|ƒƒ|\}}}} xI|D]A}|||tjƒ|| |tjƒf|j|d= 1isq must be >= 0sr must be >= 1trepeatcss%|]\}}t||ƒVqdS(N(tabs(R R R ((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pys bsiÿÿÿÿN(R tNetworkXExceptionRRtseedtDiGraphR2RRRRRtappendtutilst accumulateRtuniform(RtptqR1RRFRRtp1tprobstp2R&tcdft_ttarget((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pyR)s0*          #(iiii(t__doc__tjoint __author__t__all__tbisectRt functoolsRt itertoolsRR-RtsystnetworkxR RRRR*RR(((sq/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/generators/geometric.pyts$   $ K  S X