\MhڝRdZddlZddlZddlmZddlZgdZ d'dZ d(dZ d)dZ d'd Z d*d Z GddZ d+dZ d,dZ d-dZdZdZdZd Zd!Zd"Zd(d#Zd$Zd%Zd.d&ZdS)/a ********** Matplotlib ********** Draw networks with matplotlib. Examples -------- >>> G = nx.complete_graph(5) >>> nx.draw(G) See Also -------- - :doc:`matplotlib ` - :func:`matplotlib.pyplot.scatter` - :obj:`matplotlib.patches.FancyArrowPatch` N)Number)displayapply_matplotlib_colorsdraw draw_networkxdraw_networkx_nodesdraw_networkx_edgesdraw_networkx_labelsdraw_networkx_edge_labelsdraw_bipartite draw_circulardraw_kamada_kawai draw_random draw_spectral draw_spring draw_planar draw_shelldraw_forceatlas2TcV ddl}|r n?rd n ||1 fd D}|t |}|t |}|j| || fd |r8tj fdD|dStj fd  D|dS) a Apply colors from a matplotlib colormap to a graph. Reads values from the `src_attr` and use a matplotlib colormap to produce a color. Write the color to `dest_attr`. Parameters ---------- G : nx.Graph The graph to read and compute colors for. src_attr : str or other attribute name The name of the attribute to read from the graph. dest_attr : str or other attribute name The name of the attribute to write to on the graph. map : matplotlib.colormap The matplotlib colormap to use. vmin : float, default None The minimum value for scaling the colormap. If `None`, find the minimum value of `src_attr`. vmax : float, default None The maximum value for scaling the colormap. If `None`, find the maximum value of `src_attr`. nodes : bool, default True Whether the attribute names are edge attributes or node attributes. rNTkeysc,g|]}|Sr).0asrc_attr type_iters Y/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/networkx/drawing/nx_pylab.py z+apply_matplotlib_colors..[s":::1 ! X&:::cmapc\td|DS)Nc34K|]}t|VdSN)float)rxs r z:apply_matplotlib_colors..do_map..fs(99!U1XX999999r )tupleto_rgba)r'mappers rdo_mapz'apply_matplotlib_colors..do_mapds,99v~~a'8'8999999r cJi|]}|j| Sr)nodes)rnGr,rs r z+apply_matplotlib_colors..j0CCCA66!'!*X.//CCCr cJi|]}|j| Sr)edges)rer0r,rs rr1z+apply_matplotlib_colors..nr2r ) matplotlibr. is_multigraphr4minmaxcmScalarMappableset_climnxset_node_attributesset_edge_attributes) r0r dest_attrmapvminvmaxr.mplvalsr,r+rs `` @@@rrr/sD GGII   GGG&& GGII  |t|::::: ::: <t99D <t99D V " " " , ,F OOD$:::::    CCCCCCCCCY       CCCCCCCCCY     r c .&'()*+,-./012345ddlm}ddl.ddlm1ddl0iddddddd d d d d ddddddddddddddddddddd dd d dddddddddd dd! d"d#d$dd%|rd&nd#d'|rd(ndd)dddd**D]}|*vrtjd+|1  d,*d,r d-d-d.d.d.d./*/fd0}*.fd1),fd2'*+fd3}*+fd4,db*+/fd5 -.0fd630fd75+,-.235fd8}G01fd9d:.j j } dd;} t| tr| r|} n5g} n2d<tj|| dD} || / dd=2d>} t)2r'tj/2/| | 2| d<nHtj|2ikr/tj/tj/| | 2| d<t/| dkrJ dd?} |tj/| *dD]4*4fd@/| AD} 0|| d=}0)fdBt5|| dC|| dDD(0&(-fdEt7| D}|dddf|dddFf|| dG(4|| dH|dIJ d dK}||d.uri}t|t:r|}d}/|AD]\}}|d.ur t|t:sdK||n|i}| dK|}t|t<st=|}||/j|2\}} |||| dG*d dG| dC*d dC| dL*d dL| dM*d dM| dN*d dN| dO*d dOj | dP*d dPQ  dd;}t|tr|r|!}n5g}n2dRtj"||dD}|#|+tItj/2tj+tj/22S+%r"'fdT+!dUDn'fdV+!D}+%r"'fdW+!dUDn'fdX+!D}0-fdY|D}t/|dkr^.j&|||dC||dZ||d[||dDd\dF]}'|i}t/|dkr.|D]+}||||<(||, ddK}i}t|t:r|}dK}+%r+!|d^n+!|A} ||d.ur| D]ѐ^}}tS|}|d.us|t|t:sdK|i}||| dK}t|t<st=|} ||}!n#tT$r||}!YnwxYw|d|dFkr|!+}"j ,+j|d2}#|"|#|#}$j -.|$}%|%j/d\}} |||| dG*ddG| dC*ddC| dL*ddL| dM*ddM| dD*ddD| dN*ddN| dO*ddOdj | dP*ddPdF_r||!|| dG*ddG| dC*ddC| dL*ddL| dM*ddM| dD*ddD| dP*ddP| dN*ddN| dO*ddO| d=*dd=| d`*dd`j dFaӉ2| krtj0|| |S)ca6-Draw the graph G. Draw the graph as a collection of nodes connected by edges. The exact details of what the graph looks like are controled by the below attributes. All nodes and nodes at the end of visible edges must have a position set, but nearly all other node and edge attributes are options and nodes or edges missing the attribute will use the default listed below. A more complete discription of each parameter is given below this summary. .. list-table:: Default Visualization Attributes :widths: 25 25 50 :header-rows: 1 * - Parameter - Default Attribute - Default Value * - pos - `"pos"` - If there is not position, a layout will be calculated with `nx.spring_layout`. * - node_visible - `"visible"` - True * - node_color - `"color"` - #1f78b4 * - node_size - `"size"` - 300 * - node_label - `"label"` - Dict describing the node label. Defaults create a black text with the node name as the label. The dict respects these keys and defaults: * size : 12 * color : black * family : sans serif * weight : normal * alpha : 1.0 * h_align : center * v_align : center * bbox : Dict describing a `matplotlib.patches.FancyBboxPatch`. Default is None. * - node_shape - `"shape"` - "o" * - node_alpha - `"alpha"` - 1.0 * - node_border_width - `"border_width"` - 1.0 * - node_border_color - `"border_color"` - Matching node_color * - edge_visible - `"visible"` - True * - edge_width - `"width"` - 1.0 * - edge_color - `"color"` - Black (#000000) * - edge_label - `"label"` - Dict describing the edge label. Defaults create black text with a white bounding box. The dictionary respects these keys and defaults: * size : 12 * color : black * family : sans serif * weight : normal * alpha : 1.0 * bbox : Dict describing a `matplotlib.patches.FancyBboxPatch`. Default {"boxstyle": "round", "ec": (1.0, 1.0, 1.0), "fc": (1.0, 1.0, 1.0)} * h_align : "center" * v_align : "center" * pos : 0.5 * rotate : True * - edge_style - `"style"` - "-" * - edge_alpha - `"alpha"` - 1.0 * - arrowstyle - `"arrowstyle"` - ``"-|>"`` if `G` is directed else ``"-"`` * - arrowsize - `"arrowsize"` - 10 if `G` is directed else 0 * - edge_curvature - `"curvature"` - arc3 * - edge_source_margin - `"source_margin"` - 0 * - edge_target_margin - `"target_margin"` - 0 Parameters ---------- G : graph A networkx graph canvas : Matplotlib Axes object, optional Draw the graph in specified Matplotlib axes pos : string or function, default "pos" A string naming the node attribute storing the position of nodes as a tuple. Or a function to be called with input `G` which returns the layout as a dict keyed by node to position tuple like the NetworkX layout functions. If no nodes in the graph has the attribute, a spring layout is calculated. node_visible : string or bool, default visible A string naming the node attribute which stores if a node should be drawn. If `True`, all nodes will be visible while if `False` no nodes will be visible. If incomplete, nodes missing this attribute will be shown by default. node_color : string, default "color" A string naming the node attribute which stores the color of each node. Visible nodes without this attribute will use '#1f78b4' as a default. node_size : string or number, default "size" A string naming the node attribute which stores the size of each node. Visible nodes without this attribute will use a default size of 300. node_label : string or bool, default "label" A string naming the node attribute which stores the label of each node. The attribute value can be a string, False (no label for that node), True (the node is the label) or a dict keyed by node to the label. If a dict is specified, these keys are read to further control the label: * label : The text of the label; default: name of the node * size : Font size of the label; default: 12 * color : Font color of the label; default: black * family : Font family of the label; default: "sans-serif" * weight : Font weight of the label; default: "normal" * alpha : Alpha value of the label; default: 1.0 * h_align : The horizontal alignment of the label. one of "left", "center", "right"; default: "center" * v_align : The vertical alignment of the label. one of "top", "center", "bottom"; default: "center" * bbox : A dict of parameters for `matplotlib.patches.FancyBboxPatch`. Visible nodes without this attribute will be treated as if the value was True. node_shape : string, default "shape" A string naming the node attribute which stores the label of each node. The values of this attribute are expected to be one of the matplotlib shapes, one of 'so^>v"`` for directed graphs. See `matplotlib.patches.ArrowStyle` for more options arrowsize : string or int, default "arrow_size" A string naming the edge attribute which stores the size of the arrowhead for each edge. Visible edges without this attribute will use a default value of 10. edge_curvature : string, default "curvature" A string naming the edge attribute storing the curvature and connection style of each edge. Visible edges without this attribute will use "arc3" as a default value, resulting an a straight line between the two nodes. Curvature can be given as 'arc3,rad=0.2' to specify both the style and radius of curvature. Please see `matplotlib.patches.ConnectionStyle` and `matplotlib.patches.FancyArrowPatch` for more information. edge_source_margin : string or int, default "source_margin" A string naming the edge attribute which stores the minimum margin (gap) between the source node and the start of the edge. Visible edges without this attribute will use a default value of 0. edge_target_margin : string or int, default "target_margin" A string naming the edge attribute which stores the minimumm margin (gap) between the target node and the end of the edge. Visible edges without this attribute will use a default value of 0. hide_ticks : bool, default True Weather to remove the ticks from the axes of the matplotlib object. Raises ------ NetworkXError If a node or edge is missing a required parameter such as `pos` or if `display` receives an argument not listed above. ValueError If a node or edge has an invalid color format, i.e. not a color string, rgb tuple or rgba tuple. Returns ------- The input graph. This is potentially useful for dispatching visualization functions. r)CounterNnode_pos node_visibleT node_color#1f78b4 node_size, node_label z#000000 sans-serifnormal?center)sizecolorfamilyweightalphah_alignv_alignbbox node_shapeo node_alphanode_border_widthnode_border_colorface edge_visible edge_width edge_color edge_labelroundrRrRrRboxstyleecfc?) rTrUrVrWrXr[rYrZposrotate edge_style- edge_alphaedge_arrowstyle-|>edge_arrowsize arc3)edge_curvatureedge_source_marginedge_target_margin hide_ticksz-Unrecongized visualization keyword argument: rzbothFaxiswhichbottomleft labelbottom labelleftczd}||.|D]+}j|vrtjdd|,Ttjikr;t fdDrfd|DSfd|DS)FReturn a list of attribute values for `seq`, using a default if needednode_N Attribute 'z' missing for node c32K|]\}}d|v |kVdS)nodeNrrkvattrs rr(z:display..node_property_sequence../HH$!QFaKKDAIKKKKHHr cg|]}Srrr_rs rrz;display..node_property_sequence..&&&QD&&&r cRg|]#}j|$Sr)r.get)rr/rdefault node_subgraphs rrz;display..node_property_sequence..1GGGa #A&**499GGGr )rr.r= NetworkXErrorget_node_attributesanyitems)seqr param_namer/rdefaultskwargsrs ` @rnode_property_sequencez'display..node_property_sequences $T^^ :&zz*d++ ? W W}21555*+U+U+URS+U+UVVV6  &}d;;rAAHHHH&,,..HHHHHB'&&&#&&& &GGGGGG3GGGGr ct|trEjj|}|dkr|d|d|d|fS|St|t r+t |dkr|d|d|d|fSt|t rt |dkr|Std|)Nr^rzInvalid format for color: ) isinstancestrcolorscolorConverterr*r)len ValueError)rUrXrgbarrDs rcompute_colorszdisplay..compute_colorss eS ! ! :,44U;;D...Qa$q'599K eU # # 9E a!HeAha%8 8 eU # # E aL=e==>>>r c|ddkoA|ddko1|ddko!|ddko|d|dkS) N arrowstylerp curvaturerv source_marginr target_marginrr)r5 get_edge_attrs rcollection_compatiblez&display..collection_compatibles M!\ * *c 1  a--7  a11Q6  a11Q6  !!  r czd}||.|D]+}j|vrtjdd|,Ttjikr;t fdDrfd|DSfd|DS)redge_Nrz' missing for edge c32K|]\}}d|v |kVdS)edgeNrrs rr(z:display..edge_property_sequence..rr cg|]}Srrrs rrz;display..edge_property_sequence..rr cRg|]#}j|$Sr)r4r)rr5rr edge_subgraphs rrz;display..edge_property_sequence..rr )rr4r=rget_edge_attributesrr)rrrr5rrrrs ` @redge_property_sequencez'display..edge_property_sequences $T^^ :&zz*d++ ? W W}21555*+U+U+URS+U+UVVV6  &}d;;rAAHHHH&,,..HHHHHB'&&&#&&& &GGGGGG3GGGGr cHd|}|}||}|)|j|vrtjd|d||1tj|ikr|vr|Sj|||S)z@Return the final edge attribute value, using default if not NonerNrz' missing from edge )rr4r=rrvalues)r5rrrrrrs rrzdisplay..get_edge_attrs$T^^ :&zz*d++ ?t=+>q+AAA"#N#N#N1#N#NOO O  &}d;;rAA ''K"1%))$888r cT|rn }d|}|}||}|)||j|vrtjd|d||1tj||ikr|vr|S|j|||S)z@Return the final node attribute value, using default if not NonerNrz' missing from node )rr.r=rrr) r/ruse_edge_subgraphsubgraphrrrrrrs r get_node_attrzdisplay..get_node_attr.s$5H===#T^^ :&zz*d++ ?t8>!+<<<"#N#N#N1#N#NOO O  &x66"<< ''K~a $$T7333r cfd}|S)Nc B||kstjd j|}dz }|dz}d|g||g|dgddg| dg| |gd|gg} dzr@|j\}} t dzD]} | | } } || gj} j j||zgdS)ND`self_loop` connection style methodis only to be used for self-loopsHrlrrrrrrrrr) allr=r transDatainverted transformsqrtasarrayTrangearraypathPath)posAposBargsrdata_locv_shifth_shiftrr'yrcanvas edge_indexrDrLnps rself_loop_connectionz8display..self_loop..self_loop_connectionDs]66$$,'' &8 '0022<.self_loopCs;% % % % % % % % % N$#r cr|dvrd|zdz S|dz SNzs^>v.to_marker_edgems> X  771t8$$q( (774==1$ $r c  |dd|dd}t||d} |dd|dd}t||d}jj|dj|d|d|d|dkr |dn9t |d krdn |d d z|dd|d |d |d |d||d S)NrrTshaperrrrrrrrUstylewidth arrowsize) rconnectionstylerU linestyle linewidthmutation_scaleshrinkAshrinkBzorder)r9patchesFancyArrowPatchr.r) r5rrrrrrDrmrrs rbuild_fancy_arrowz"display..build_fancy_arrowss& M!A$ ' ' M!A$ ( (    M!_ - -  ' M!A$ ' ' M!A$ ( (    M!_ - -  {**  ! %c *  ! %c *$}Q 55Q41Q4<< a---YQ1AA!A$(!M!A$//  -7++#mAw//#mAw//(=K88!!%+   r cFeZdZddddfd ZdZfdZfdZxZS) display..CurvedArrowTextrlFN label_poslabels_horizontalaxcN||_||_||_|}||_||\|_|_|_tj |j|jg|Rd|ji||j |dSNrotation arrowrrgcar_update_text_pos_angler'ranglesuper__init__ add_artist selfrrrrrr __class__plts rrz)display..CurvedArrowText.__init__DJ'DN%6D "zWWYYDG)-)D)DU)K)K &DFDFDJ EGG TVTV Rd R R RTZ R6 R R R G  t $ $ $ $ $r c |j}|jj}|j||jd}||jd}|||f\}}||||j|j|j |z|j |z}n| |j }|S)U This is part of FancyArrowPatch._get_path_in_displaycoord It omits the second part of the method where path is converted to polygon based on width The transform is taken from ax, not the object, as the object has not been added yet, and doesn't have transform NrrpatchApatchBrr) _dpi_corrr _posA_posB_convert_xy_unitsrget_connectionstyler r rrtransform_path_path_originalrrdpi_cor trans_datarr_paths r_get_arrow_path_dispz5display..CurvedArrowText._get_arrow_path_dispsnG*J+..u/?/BCC..u/?/BCC)33T4LAA t31133 < <!MG3!MG3 #11%2FGGLr c<||}|j\\}}\}}\}}|j} d| z } | dz|zd| z| z|zz| dz|zz} | dz|zd| z| z|zz| dz|zz} |jrd} nhd| z||z zd| z||z zz}d| z||z zd| z||z zz}||djzz dz} | dkr| dz} | dkr| dz } |jj | | f\} } | | | fSNrrrihZi) rverticesrrarctan2pirrrr)rr path_dispx1y1cxcyx2y2tttr'rrchange_xchange_yrs rrz7display..CurvedArrowText._update_text_pos_anglest11%88I+4+= (HRhr2RAQBA QURZ"_,q!tby8AA QURZ"_,q!tby8A% !r6R"W-Ab0AAr6R"W-Ab0AAHh771ru9EL2::SLE3;;SLEW&//11;;QFCCFQa; r c||j\|_|_|_||j|jf||jt|dSr% rrr'rr set_position set_rotationrrrrendererrs rrz%display..CurvedArrowText.drawt)-)D)DTZ)P)P &DFDFDJ   tvtv. / / /   dj ) ) ) GGLL " " " " "r __name__ __module__ __qualname__rrrr __classcell__)rrrs@rCurvedArrowTextrs #  % % % % % % % %2   8     4 # # # # # # # # #r r6visiblecg|] \}}|| Srr)rr/rs rrzdisplay..2   !QST    r rmz!display's position attribute namercBg|]\}}|ks| dk|S)Nr\r)rr/srrs rrzdisplay..sC   Aq::!),9O0O0O0O0O0Or )datac.g|]\}}||Srr)rcrrs rrzdisplay..'s91#N1a((r rUrXcPg|]"\}}|ddxdkrn|#S) border_colorFrar)rir/r>rUrs rrzdisplay..0sj1"/ ! . %""A """#1Xr rrT border_widthr)r;r>r linewidths edgecolorsrlabelrVrWrYrZr[)rTrUrVrWhorizontalalignmentverticalalignmentrr[cg|] \}}|| Srr)rr5rs rrzdisplay..{r9r )namec*g|]}| |Srrrr5rs rrzdisplay..s*OOOq6K6KA6N6NOOOOr rc*g|]}| |SrrrKs rrzdisplay..s* K K KA2G2G2J2J Ka K K Kr c*g|]}| |SrrrKs rrzdisplay..s+SSSq:O:OPQ:R:RSSSSr c*g|]}| |SrrrKs rrzdisplay..s* O O OA6K6KA6N6N Oa O O Or cNg|]!^}}}|dd|ddf"S)rmT)rr)rurrrs rrzdisplay..s[   1q a$??? a$???    r rrr)rrCrrX antialiasedsr)r<r) rTrUrVrWrXrFrGrrr[rrn) rTrUrVrWrXr[rFrGrrrrr)T)1 collectionsrGr6matplotlib.pyplotpyplotnumpy is_directedr=rrr tick_paramstextTextrboolr.rrrcallabler> spring_layoutrrrzip enumeratescatterdictrupdaterr4rrprintr7LineCollectionadd_collection add_patchr)KeyErrorrrrrrremove_node_attributes)6r0rrrGkwargrrrr6rI visible_nodesdefault_display_pos_attrr\nodes_with_shapepositionr@rN default_dictr/lbllbl_textr'rrb visible_edgescollection_edgesnon_collection_edges edge_positionedge_collection fancy_arrowsr5reedge_label_datarconnectionstyle_objrr path_datar>rrUrrrrrrDrrrrmrrrs6 `` @@@@@@@@@@@@@@@@rrrrsU\$###########*D** i* S * "   * c* c!*" S#*$ V%*& '*( c)** i+*, "!(WW   -*D cE*F cG*H AMMOO<55I*J  6""QK*L!S***HZ  "GGG  ! ~ zz, 677     HHHHHHH4??????2     HHHHHHH,9999999&444444444*($($($($($($($T%%%%% % % % % % % % % % % % NV#V#V#V#V#V#V#V##(-V#V#V#r::ni88L,%%  GGIIMMMM  0L$GGMMOO   JJ}--M **Z ' 'CB}} 6  33}--/G   '5z 3 ' '2 - -  2+M::www**Hh,, )x== JJ| $ $ $ &q)#.DAq KKWWVXl%;F%CDDgggx '=g'FGGwwx,)?)IJJwwx,)?)IJJ$'GGx 5i@%%#&'')Xl5KI5V"W"W *WWVXl%;F%CDD     $::ni88L,%%  GGIIMMMM  0L$GGMMOO   OOM22M "  4 4555r-mSAA  & & ( ( LOOOOM''T'22OOOO K K K K,,.. K K K  & & ( ( PSSSSM''T'22SSSS O O O O,,.. O O O JJ    -    M q  /88 ))*:GDD--.>HH,,-=wGG(()97CC9   o...L   1$$% . .A//22LO   \!_ - - - -L'22JL*d##!   & & ( ( 2 $777  j 1 1 *E"9"9&E E GQaAe||s{c4(( %n JJ| $ $ $www''Hh,, )x==  -$Q - - -))!,, -tqt||&+&?&?&A&A#'11-2Ead2KC2PQQ//d;; ",5577FFyQQ  )!,1 ,)?)GHH'''8L+A'+JKK778Xl-CH-MNN778Xl-CH-MNN'''8L+A'+JKK(+!8L#9)#D))'*gg!8L#9)#D''$.,)?)GHH%( OWWVXl%;F%CDDgggx '=g'FGGwwx,)?)IJJwwx,)?)IJJgggx '=g'FGGWWVXl%;F%CDD$'GGx 5i@%%#&'')Xl5KI5V"W"W''%,)?)FGG"%''(H\4J84T"U"U *#     * &&& !!%=>>> Hs+d44e  e c ~ddlm}||}n|}|d|1|jr|}n|d}d|vrd|v|d<t|f||d|| | dS)aIDraw the graph G with Matplotlib. Draw the graph as a simple representation with no node labels or edge labels and using the full Matplotlib figure area and no axis labels by default. See draw_networkx() for more full-featured drawing that allows title, axis labels etc. Parameters ---------- G : graph A networkx graph pos : dictionary, optional A dictionary with nodes as keys and positions as values. If not specified a spring layout positioning will be computed. See :py:mod:`networkx.drawing.layout` for functions that compute node positions. ax : Matplotlib Axes object, optional Draw the graph in specified Matplotlib axes. kwds : optional keywords See networkx.draw_networkx() for a description of optional keywords. Examples -------- >>> G = nx.dodecahedral_graph() >>> nx.draw(G) >>> nx.draw(G, pos=nx.spring_layout(G)) # use spring layout See Also -------- draw_networkx draw_networkx_nodes draw_networkx_edges draw_networkx_labels draw_networkx_edge_labels Notes ----- This function has the same name as pylab.draw and pyplot.draw so beware when using `from networkx import *` since you might overwrite the pylab.draw function. With pyplot use >>> import matplotlib.pyplot as plt >>> G = nx.dodecahedral_graph() >>> nx.draw(G) # networkx draw() >>> plt.draw() # pyplot draw() Also see the NetworkX drawing examples at https://networkx.org/documentation/latest/auto_examples/index.html rNw)rrrr with_labelslabels)rmr) rTrUgcf get_figure set_facecoloraxesradd_axesr set_axis_offdraw_if_interactive)r0rmrkwdsrcfs rrr sr$##### z WWYY ]]__S z 7 +BB\**BD  &$.]!,,,t,,,OO Fr c L ddlm}ddlm}|tj|tj |tj  z zhdz t fd|Dr3d fd|D}td|fd | D} fd | D} fd | D} |tj|}t ||fi|t||fd |i| |rt||fi| |dS) aCDraw the graph G using Matplotlib. Draw the graph with Matplotlib with options for node positions, labeling, titles, and many other drawing features. See draw() for simple drawing without labels or axes. Parameters ---------- G : graph A networkx graph pos : dictionary, optional A dictionary with nodes as keys and positions as values. If not specified a spring layout positioning will be computed. See :py:mod:`networkx.drawing.layout` for functions that compute node positions. arrows : bool or None, optional (default=None) If `None`, directed graphs draw arrowheads with `~matplotlib.patches.FancyArrowPatch`, while undirected graphs draw edges via `~matplotlib.collections.LineCollection` for speed. If `True`, draw arrowheads with FancyArrowPatches (bendable and stylish). If `False`, draw edges using LineCollection (linear and fast). For directed graphs, if True draw arrowheads. Note: Arrows will be the same color as edges. arrowstyle : str (default='-\|>' for directed graphs) For directed graphs, choose the style of the arrowsheads. For undirected graphs default to '-' See `matplotlib.patches.ArrowStyle` for more options. arrowsize : int or list (default=10) For directed graphs, choose the size of the arrow head's length and width. A list of values can be passed in to assign a different size for arrow head's length and width. See `matplotlib.patches.FancyArrowPatch` for attribute `mutation_scale` for more info. with_labels : bool (default=True) Set to True to draw labels on the nodes. ax : Matplotlib Axes object, optional Draw the graph in the specified Matplotlib axes. nodelist : list (default=list(G)) Draw only specified nodes edgelist : list (default=list(G.edges())) Draw only specified edges node_size : scalar or array (default=300) Size of nodes. If an array is specified it must be the same length as nodelist. node_color : color or array of colors (default='#1f78b4') Node color. Can be a single color or a sequence of colors with the same length as nodelist. Color can be string or rgb (or rgba) tuple of floats from 0-1. If numeric values are specified they will be mapped to colors using the cmap and vmin,vmax parameters. See matplotlib.scatter for more details. node_shape : string (default='o') The shape of the node. Specification is as matplotlib.scatter marker, one of 'so^>v>> G = nx.dodecahedral_graph() >>> nx.draw(G) >>> nx.draw(G, pos=nx.spring_layout(G)) # use spring layout >>> import matplotlib.pyplot as plt >>> limits = plt.axis("off") # turn off axis Also see the NetworkX drawing examples at https://networkx.org/documentation/latest/auto_examples/index.html See Also -------- draw draw_networkx_nodes draw_networkx_edges draw_networkx_labels draw_networkx_edge_labels r) signatureN>r0rmarrowsr|c3 K|]}|vV dSr%rrr valid_kwdss rr(z draw_networkx..s( - -11J  - - - - - -r z, cg|]}|v| Srrrs rrz!draw_networkx..s#!I!I!IQj5H5H!5H5H5Hr zReceived invalid argument(s): c$i|] \}}|v || Srr)rrrvalid_node_kwdss rr1z!draw_networkx..)GGG$!Q!2F2FA2F2F2Fr c$i|] \}}|v || Srr)rrrvalid_edge_kwdss rr1z!draw_networkx.. rr c$i|] \}}|v || Srr)rrrvalid_label_kwdss rr1z!draw_networkx.. s*III41a18H3H3H!Q3H3H3Hr r)inspectrrTrUr parametersrr r rjoinrrr=drawingr]r)r0rmrr|rrr invalid_args node_kwds edge_kwds label_kwdsrrrrs @@@@rrrYsn"!!!!!######  i 344?DDFFOi 344?DDFFO y!566AFFHH"O36FFKKKJ - - - - - - ---Jyy!I!I!I!IT!I!I!IJJ H,HHIIIGGGG$**,,GGGIGGGG$**,,GGGIIIII4::<<IIIJ {j&&q))3,,),,,3;;v;;;;3Q22z222r rMrKr]cddlm}ddl}ddl}ddlm}ddl}| |} |t|}t|dkr|j dS | fd|D}n+#t$r}tjd|d|d}~wwxYwt!||rt#|||||| }d}t!|jsPt!ts;|fdt)t|D|D];}| ||kdf||kdf|||||| || | | }<|r| d d d d d d |0t!||r | j|n| ||d |S)a Draw the nodes of the graph G. This draws only the nodes of the graph G. Parameters ---------- G : graph A networkx graph pos : dictionary A dictionary with nodes as keys and positions as values. Positions should be sequences of length 2. ax : Matplotlib Axes object, optional Draw the graph in the specified Matplotlib axes. nodelist : list (default list(G)) Draw only specified nodes node_size : scalar or array (default=300) Size of nodes. If an array it must be the same length as nodelist. node_color : color or array of colors (default='#1f78b4') Node color. Can be a single color or a sequence of colors with the same length as nodelist. Color can be string or rgb (or rgba) tuple of floats from 0-1. If numeric values are specified they will be mapped to colors using the cmap and vmin,vmax parameters. See matplotlib.scatter for more details. node_shape : string (default='o') The shape of the node. Specification is as matplotlib.scatter marker, one of 'so^>v>> G = nx.dodecahedral_graph() >>> nodes = nx.draw_networkx_nodes(G, pos=nx.spring_layout(G)) Also see the NetworkX drawing examples at https://networkx.org/documentation/latest/auto_examples/index.html See Also -------- draw draw_networkx draw_networkx_edges draw_networkx_labels draw_networkx_edge_labels r)IterableNc g|] }| Srr)rrrms rrz'draw_networkx_nodes..s222AQ222r zNode z has no position.cg|]}Srr)rrr\s rrz'draw_networkx_nodes..sHHHazHHHr r) r;r>rr"rBrCrXrCrDrEr{Fr|r)collections.abcrr6matplotlib.collectionsrTrUrVrlistrrSPathCollectionrrgr=rr apply_alphandarrayrruniquer`rXmargins set_zorder)r0rmnodelistrLrJr\rXr"rBrCrrCrDrErrzrrDr6rrxyerrrnode_collections ` ` rrrsV)(((((!!!!###### z WWYY77 8}}--d333H ZZ2222222 3 3 HHH=s===>>CGH%"" UHdD$OO  j"* - -JjT6R6RJXXHHHH5X3G3GHHHII :&&  ** zU"A% & zU"A% &!!%          gx ( ( BJ JJw   q!!! s0!B B:B55B:cVeZdZdZGddZ dd ZdZdZd S)FancyArrowFactoryz5Draw arrows with `matplotlib.patches.FancyarrowPatch`c"eZdZddZdZdZdS)(FancyArrowFactory.ConnectionStyleFactoryNcddlddl}ddl}||_|_||_fd|D|_t|j|_||_ dS)NrcDg|]}j|Sr)rConnectionStyle)rcsrDs rrzEFancyArrowFactory.ConnectionStyleFactory.__init__..s6+++46 ++B//+++r ) r6matplotlib.pathrVrrDrbase_connection_stylesrr/selfloop_height)rconnectionstylesrrr6rrDs @rrz1FancyArrowFactory.ConnectionStyleFactory.__init__s $ $ $ $ " " " "    DGDHDG++++:J+++D '455DF#2D r c,|j||jzSr%)rr/)rrs rcurvedz/FancyArrowFactory.ConnectionStyleFactory.curveds.zDF/BC Cr cfd}|S)Nc b j||kstjd jj|}d jz}|dz} j d|g||g|dgddg| dg| |gd|gg} dzrE|j \}} t dzD]} | | } } j || gj } j j jj||zgdS)Nrg?rlrrr)rrr=rrrrrrrrrrrDrr) rrrrrrrrr'rrrrs rrzPFancyArrowFactory.ConnectionStyleFactory.self_loop..self_loop_connections`w{{44<00*<  7,5577AA$GG 44!C-wG  '* ! A!1 !7+G     >36DAq":>22%% 1"17==!Q002Dx}))G%//4@@BWBWBWr r)rrrs`` rrz2FancyArrowFactory.ConnectionStyleFactory.self_loops+# # # # # # J( 'r r%)r2r3r4rrrrr rConnectionStyleFactoryrsI 3 3 3 3 D D D& (& (& (& (& (r rrvr]rprurNrRsolidrcddl}ddl}ddlm}ddl}t |t r|g}n;||rt|}nd}tj |||_ ||_ ||_ ||_||_||_||_||_||_||_||_|||||_| |_| |_|jj| | |_| |_||_t | tr/tA| tA|krtCddSdS)NrzDConnectionStyleFactory arg `connectionstyle` must be str or iterablez1arrowsize should have the same length as edgelist)"r6matplotlib.patchesrTrUrVrriterablerr=rrrDredge_posedgelistrr\min_source_marginmin_target_margin edge_indicesrLrconnectionstyle_factoryrrrr to_rgba_array arrow_colorsrrrr)rrrrrrLrrr\rrrdrXrrrrrrDr6rrmsgs rrzFancyArrowFactory.__init__s( !   !!!!'''''' os + + (./OO [[ ) ) ("?33OOXC"3'' '      $!2!2("'+'B'B _b( ( $%"J5CCJPUVV" i & & R3y>>S]]+J+JPQQ Q R R+J+Jr c  |j|\\}}\}}d}d}|j|jrBt |jt s(t |jt s|j|}n|j}|j|jrBt |jt s(t |jt s|j|} n|j} |j|jr|j |dd\} } |j|j | } |j|j | } | | |j }| | |j }n"| |j|j }|}t||}t|| }t |jt r|j|}n|j}t#|j|kr|j|}nHt#|jdkr|jd}n"|j|t#|jz}|j|jrIt#|j|kr|j|}n*|j|t#|jz}n|j}|j|jr}t |jt sct |jt sIt#|j|kr|j|}n*|j|t#|jz}n|j}||kr,||kr&|j|j|}n%|j|j|}|j|jrBt |jt s(t |jt s|j|}n|j}|jj||f||f||||||||d S)Nrrr) rrrrrUrrrr)rrrrrrr)rrLrrindexrr\r9rrrrrrrrrrrrDrr)rrAr r!r$r% shrink_source shrink_targetrrsourcetargetsource_node_sizetarget_node_sizer arrow_colorrrrrs r__call__zFancyArrowFactory.__call__3sF!]1-R(2r  G  T3 4 4 7t5s;; 7t5u== 7 !% 6q 9   $ 6  G  T3 4 4 7t5s;; 7t5u== 7 !% 6q 9   $ 6  7  DN + + *!]1-bqb1NFF#~dm.A.A&.I.IJ #~dm.A.A&.I.IJ  //0@$/RRM //0@$/RRMM //PPM)MM+<== M+<==  dnd + + ,!^A.NN!^N t ! !A % %+A.KK " # #q ( (+A.KK+AD4E0F0F,FGK 7  DN + + '4>""Q&& N1-  N1s4>/B/B+BC I G  TZ ( ( #tz3// #tz511 # 4:"" JqM  Jq3tz??':;  I 88b":DD!!$OO#:AA$BSTUBVWWO G  T_ - - )t44 )t66 ) +JJJx// H H!!!)+0   r c|dvr |jd|zdz S|j|dz Sr)rr)r marker_sizers rrz FancyArrowFactory.to_marker_edgesC X  7<<K0014 47<< ,,q0 0r ) rvr]rprurNrRrrrN)r2r3r4__doc__rrrrrr rrrs??8(8(8(8(8(8(8(8(D %4R4R4R4Rl_ _ _ B11111r rrRrrrurvcr  23ddl}ddl}ddl}ddl}ddlm}ddl}| *|p| }n't| tstd| }t|tr|g}n;| |rt|}nd}tj||rd}|0||dt&d|d kr0||d t&d|dkr0||d t&d|dkr0||d t&dt)d |Dr0||dt&d||rdnd}| |} t|jt/rL|r$t1jd33fdD}ndgt/z}ngS|!t|}|d}|fdD}| |rt/|t/|kr|d|Dr t |jjsJn| | tA|} | tC|} |j"| | 22 fd|D}|#|$|dddddf}|%|$|dddddf} |#|$|dddddf}!|%|$|dddddf}"| |z }#|"|!z }$|$dkr|$n)d|&|!z}%tO|||||%||||||||||| }&|r"|j(|||d||}'|') |'*| | |'+d|',|| -|'|'}(fdtj.|D})|)rstt_t`}*g}+|)D]L},|*1|,}-|&|-}.|+2|.| 3|.MnVg}(tit/D]7}-|&|-}.| 3|.|(2|.8d|#zd|$z}0}/||/z |!|0z f| |/z|"|0zff}1| 5|1| 6|r| 7ddd d d d !|(S)"aDraw the edges of the graph G. This draws only the edges of the graph G. Parameters ---------- G : graph A networkx graph pos : dictionary A dictionary with nodes as keys and positions as values. Positions should be sequences of length 2. edgelist : collection of edge tuples (default=G.edges()) Draw only specified edges width : float or array of floats (default=1.0) Line width of edges edge_color : color or array of colors (default='k') Edge color. Can be a single color or a sequence of colors with the same length as edgelist. Color can be string or rgb (or rgba) tuple of floats from 0-1. If numeric values are specified they will be mapped to colors using the edge_cmap and edge_vmin,edge_vmax parameters. style : string or array of strings (default='solid') Edge line style e.g.: '-', '--', '-.', ':' or words like 'solid' or 'dashed'. Can be a single style or a sequence of styles with the same length as the edge list. If less styles than edges are given the styles will cycle. If more styles than edges are given the styles will be used sequentially and not be exhausted. Also, `(offset, onoffseq)` tuples can be used as style instead of a strings. (See `matplotlib.patches.FancyArrowPatch`: `linestyle`) alpha : float or array of floats (default=None) The edge transparency. This can be a single alpha value, in which case it will be applied to all specified edges. Otherwise, if it is an array, the elements of alpha will be applied to the colors in order (cycling through alpha multiple times if necessary). edge_cmap : Matplotlib colormap, optional Colormap for mapping intensities of edges edge_vmin,edge_vmax : floats, optional Minimum and maximum for edge colormap scaling ax : Matplotlib Axes object, optional Draw the graph in the specified Matplotlib axes. arrows : bool or None, optional (default=None) If `None`, directed graphs draw arrowheads with `~matplotlib.patches.FancyArrowPatch`, while undirected graphs draw edges via `~matplotlib.collections.LineCollection` for speed. If `True`, draw arrowheads with FancyArrowPatches (bendable and stylish). If `False`, draw edges using LineCollection (linear and fast). Note: Arrowheads will be the same color as edges. arrowstyle : str or list of strs (default='-\|>' for directed graphs) For directed graphs and `arrows==True` defaults to '-\|>', For undirected graphs default to '-'. See `matplotlib.patches.ArrowStyle` for more options. arrowsize : int or list of ints(default=10) For directed graphs, choose the size of the arrow head's length and width. See `matplotlib.patches.FancyArrowPatch` for attribute `mutation_scale` for more info. connectionstyle : string or iterable of strings (default="arc3") Pass the connectionstyle parameter to create curved arc of rounding radius rad. For example, connectionstyle='arc3,rad=0.2'. See `matplotlib.patches.ConnectionStyle` and `matplotlib.patches.FancyArrowPatch` for more info. If Iterable, index indicates i'th edge key of MultiGraph node_size : scalar or array (default=300) Size of nodes. Though the nodes are not drawn with this function, the node size is used in determining edge positioning. nodelist : list, optional (default=G.nodes()) This provides the node order for the `node_size` array (if it is an array). node_shape : string (default='o') The marker used for nodes, used in determining edge positioning. Specification is as a `matplotlib.markers` marker, e.g. one of 'so^>v>> G = nx.dodecahedral_graph() >>> edges = nx.draw_networkx_edges(G, pos=nx.spring_layout(G)) >>> G = nx.DiGraph() >>> G.add_edges_from([(1, 2), (1, 3), (2, 3)]) >>> arcs = nx.draw_networkx_edges(G, pos=nx.spring_layout(G)) >>> alphas = [0.3, 0.4, 0.5] >>> for i, arc in enumerate(arcs): # change alpha values of arcs ... arc.set_alpha(alphas[i]) The FancyArrowPatches corresponding to self-loops are not always returned, but can always be accessed via the ``patches`` attribute of the `matplotlib.Axes` object. >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots() >>> G = nx.Graph([(0, 1), (0, 0)]) # Self-loop at node 0 >>> edge_collection = nx.draw_networkx_edges(G, pos=nx.circular_layout(G), ax=ax) >>> self_loop_fap = ax.patches[0] Also see the NetworkX drawing examples at https://networkx.org/documentation/latest/auto_examples/index.html See Also -------- draw draw_networkx draw_networkx_nodes draw_networkx_labels draw_networkx_edge_labels rNz.Argument `arrows` must be of type bool or NonezAdraw_networkx_edges arg `connectionstyle` must be str or iterablea The {0} keyword argument is not applicable when drawing edges with LineCollection. To make this warning go away, either specify `arrows=True` to force FancyArrowPatches or use the default values. Note that using FancyArrowPatches may be slow for large graphs. rr)category stacklevelrurrrc3"K|] }|dkV dS)rvNr)rrs rr(z&draw_networkx_edges..s&66rV|666666r rrsrpc*tjdSNr itertoolscountrr rz%draw_networkx_edges..s 8J8Jr c dg|],}tt|dd-SNrnextr)rr5 key_counts rrz'draw_networkx_edges..s4LLLaD52A2<..DDDaC!Is1Q4y1DDDr c8g|]}t|tSr)rr)rr>s rrz'draw_networkx_edges..s">>>aJq&))>>>r )rBrCc8g|]}|Srr)rr5 color_normal edge_cmaps rrz'draw_networkx_edges..s+EEEQii Q00EEEr r{Gzt?rrQ)rrCrRrrXcg|]}|v| Srr)rlooprs rrz'draw_networkx_edges..s#WWWddhFVFVTFVFVFVr g?r{Fr|)8warningsr6rmatplotlib.colorsrTrUrVrWr7rr[ TypeErrorrrrr=rwarnformat UserWarningrrr4rrS defaultdictr.rrrColormapget_cmapr8r9 Normalizeaminravelamaxrrrdset_cmapr<r set_labelreselfloop_edgesrAr)rappendrfrupdate_datalimautoscale_viewrX)4r0rmrrrdrrXrrr edge_vmin edge_vmaxrrrErLrr\rrrrzrrDr6rruse_linecollectionrrrminxmaxxminymaxyr{hrfancy_arrow_factoryru edge_viz_objselfloops_to_drawedgelist_tuplearrow_collectionrrArpadxpadycornersrrs4 `` ` @@rr r srOOO!!!!###### ~"#--//"FQ__5F5FG&$'' NLMM M!'Z/3''$*+ _ % %$//Qs###  P   ! MM#**\22[UVM W W W ?? MM#**[11KTUM V V V  ! ! MM .//+RS      ! ! MM .//+RS     66o666 6 6  MM ,-- PQ     mmoo6UU3  z WWYY== 8}} ??   /#/0J0JKKILLLL8LLLLL3X.LL  ?? zzDDDD8DDDEEH JF __H - - FF>>:>>> ? ?.  i)<== = = = = I  JI  JIz+++KK EEEEE*EEE  77288HQQQ1W-.. / /D 77288HQQQ1W-.. / /D 77288HQQQ1W-.. / /D 77288HQQQ1W-.. / /D t A t A 66aaurxx /B/B/F/F/H/H'HO+    #* '/88  9     +++  I666""1%%%!!%((( /***& XWWWb.?.B.BWWW  $!#eX"6"677N! ) $ $"((..++A.. ''... U#### s8}}%% ' 'A''**E LL       & & & &4!8$Dd{D4K(4$;t *DDGg       r rOrPrQrScddlm}| |} d|Dt fd}fd}||d||d||d||d ||d i}D]\}}||\}}t |tst|}| ||||||d|||d|||d |||d|||d | | | j || }|||<| r| d d d d d d |S)a Draw node labels on the graph G. Parameters ---------- G : graph A networkx graph pos : dictionary A dictionary with nodes as keys and positions as values. Positions should be sequences of length 2. labels : dictionary (default={n: n for n in G}) Node labels in a dictionary of text labels keyed by node. Node-keys in labels should appear as keys in `pos`. If needed use: `{n:lab for n,lab in labels.items() if n in pos}` font_size : int or dictionary of nodes to ints (default=12) Font size for text labels. font_color : color or dictionary of nodes to colors (default='k' black) Font color string. Color can be string or rgb (or rgba) tuple of floats from 0-1. font_weight : string or dictionary of nodes to strings (default='normal') Font weight. font_family : string or dictionary of nodes to strings (default='sans-serif') Font family. alpha : float or None or dictionary of nodes to floats (default=None) The text transparency. bbox : Matplotlib bbox, (default is Matplotlib's ax.text default) Specify text box properties (e.g. shape, color etc.) for node labels. horizontalalignment : string or array of strings (default='center') Horizontal alignment {'center', 'right', 'left'}. If an array is specified it must be the same length as `nodelist`. verticalalignment : string (default='center') Vertical alignment {'center', 'top', 'bottom', 'baseline', 'center_baseline'}. If an array is specified it must be the same length as `nodelist`. ax : Matplotlib Axes object, optional Draw the graph in the specified Matplotlib axes. clip_on : bool (default=True) Turn on clipping of node labels at axis boundaries hide_ticks : bool, optional Hide ticks of axes. When `True` (the default), ticks and ticklabels are removed from the axes. To set ticks and tick labels to the pyplot default, use ``hide_ticks=False``. Returns ------- dict `dict` of labels keyed on the nodes Examples -------- >>> G = nx.dodecahedral_graph() >>> labels = nx.draw_networkx_labels(G, pos=nx.spring_layout(G)) Also see the NetworkX drawing examples at https://networkx.org/documentation/latest/auto_examples/index.html See Also -------- draw draw_networkx draw_networkx_nodes draw_networkx_edges draw_networkx_edge_labels rNci|]}||Srr)rr/s rr1z(draw_networkx_labels..qs***1!Q***r ct|trIt|tkrt|d|dSdS)Nz% must have the same length as labels.)rrarradd)p_valuep_nameindividual_paramsr}s rcheck_individual_paramsz5draw_networkx_labels..check_individual_paramsusg gt $ $ *7||s6{{** F!Q!Q!QRRR  ! !& ) ) ) ) ) * *r c |vr||S|Sr%r)rrrrs rget_param_valuez-draw_networkx_labels..get_param_value{s & & &4= r font_size font_color font_weight font_familyrX) rTrUrVrWrXrFrGrr[clip_onr{Fr|) rTrUrr.setrrrrYrrX)r0rmr}r"r#r%r$rXr[rFrGrr&rzrrr! text_itemsr/rEr'rr&rs ` @rr r sv$##### z WWYY ~** *********  I{333J 555K777K777E7+++JLLNN5QA%%% JJE GG  I{;;!/!Z>>"?1k=AA"?1k=AA!/!UG44 3/l    1        r rlcT ,-./01ddl/ddlm1ddl0G/01fdd/jj}| dddd} t |tr|g}n90|rt|}ntj d| 1 } |3| rd d ini}d |jd$d d i|D}|siSt|\,}|!t|}0fd ,D}| r$t'jd..fd,D}ndgt+,z}d}|ro00|dddddf}00|dddddf}||z }|dkr|n)d0|z}t7|,|||||| }i-,-fd}-fd}||d||d||d||d|| d|| d|| d||di}t9t,|D]\} \}!}"t |"tst|"}"|!dd\}#}$|| }%|#|$kr|%}&| j|#}'|&|'|'}(| j !|(})|)j"d\}*}+| |*|+|"||d||d||d||d||d|| d|| dd| j| d|||!<;||%|"||d||d||d||d||d|| d|| d| j| d|||d|| d | ||!<|r| #d!d!d"d"d"d"#|S)%a Draw edge labels. Parameters ---------- G : graph A networkx graph pos : dictionary A dictionary with nodes as keys and positions as values. Positions should be sequences of length 2. edge_labels : dictionary (default=None) Edge labels in a dictionary of labels keyed by edge two-tuple. Only labels for the keys in the dictionary are drawn. label_pos : float (default=0.5) Position of edge label along edge (0=head, 0.5=center, 1=tail) font_size : int (default=10) Font size for text labels font_color : color (default='k' black) Font color string. Color can be string or rgb (or rgba) tuple of floats from 0-1. font_weight : string (default='normal') Font weight font_family : string (default='sans-serif') Font family alpha : float or None (default=None) The text transparency bbox : Matplotlib bbox, optional Specify text box properties (e.g. shape, color etc.) for edge labels. Default is {boxstyle='round', ec=(1.0, 1.0, 1.0), fc=(1.0, 1.0, 1.0)}. horizontalalignment : string (default='center') Horizontal alignment {'center', 'right', 'left'} verticalalignment : string (default='center') Vertical alignment {'center', 'top', 'bottom', 'baseline', 'center_baseline'} ax : Matplotlib Axes object, optional Draw the graph in the specified Matplotlib axes. rotate : bool (default=True) Rotate edge labels to lie parallel to edges clip_on : bool (default=True) Turn on clipping of edge labels at axis boundaries node_size : scalar or array (default=300) Size of nodes. If an array it must be the same length as nodelist. nodelist : list, optional (default=G.nodes()) This provides the node order for the `node_size` array (if it is an array). connectionstyle : string or iterable of strings (default="arc3") Pass the connectionstyle parameter to create curved arc of rounding radius rad. For example, connectionstyle='arc3,rad=0.2'. See `matplotlib.patches.ConnectionStyle` and `matplotlib.patches.FancyArrowPatch` for more info. If Iterable, index indicates i'th edge key of MultiGraph hide_ticks : bool, optional Hide ticks of axes. When `True` (the default), ticks and ticklabels are removed from the axes. To set ticks and tick labels to the pyplot default, use ``hide_ticks=False``. Returns ------- dict `dict` of labels keyed by edge Examples -------- >>> G = nx.dodecahedral_graph() >>> edge_labels = nx.draw_networkx_edge_labels(G, pos=nx.spring_layout(G)) Also see the NetworkX drawing examples at https://networkx.org/documentation/latest/auto_examples/index.html See Also -------- draw draw_networkx draw_networkx_nodes draw_networkx_edges draw_networkx_labels rNcHeZdZddddfd ZdZfdZfdZxZS) 2draw_networkx_edge_labels..CurvedArrowTextrlFNrcN||_||_||_|}||_||\|_|_|_tj |j|jg|Rd|ji||j |dSrrrs rrz;draw_networkx_edge_labels..CurvedArrowText.__init__ rr c |j}|jj}|jt d||jd}||jd}|||f\}}||||j|j |j |z|j |z}|S)r NzPCan only draw labels for fancy arrows with posA and posB inputs, not custom pathrrr ) r rrrrrrrr r rrrs rrzGdraw_networkx_edge_labels..CurvedArrowText._get_arrow_path_disp8 snG*J' <**5+;A+>??D**5+;A+>??D%//t ==LT4/E--//|| / / ELr c|j}d|z }||}t|jjj}|r)|j\}\}}\} } }||z| |zz} ||z| |zz} nN|j\\} }\}}\}}|dz| zd|z|z|zz|dz|zz} |dz|zd|z|z|zz|dz|zz} |jrd}n||r| |z dz }| |z dz }n.d|z|| z zd|z||z zz}d|z||z zd|z||z zz} ||dj zz dz}|dkr|dz}n |dkr|dz }|j j | | f\} } | | |fSr)rrrrrrBarrrrrrrrr)rrr&r'r is_bar_stylercx1cy1cx2cy2r'rr r!r"r#r$r%rr(r)rDrs rrzIdraw_networkx_edge_labels..CurvedArrowText._update_text_pos_angleU sAQB11%88I%))++S[-H-LL =/8/A,:CzS1"HsQw&"HsQw&09/A,R(2rHREBJQb01a4"9<EBJQb01a4"9<% ! F #c QH #c QHH 2vb1AER"W4EEH 2vb1AER"W4EEH 8X66!be)DsJ2::SLEES[[SLEW&//11;;QFCCFQa; r c||j\|_|_|_||j|jf||jt|dSr%r+r.s rrz7draw_networkx_edge_labels..CurvedArrowText.draw r0r r1)rrDrrs@rr6r+ s #  % % % % % % % %2   :( ( ( ( ( ( T # # # # # # # # #r r6rfrgrhzNdraw_networkx_edges arg `connectionstyle` must bestring or iterable of stringsrTc4i|]^}}t||Sr)r))rrds rr1z-draw_networkx_edge_labels.. s$QQQ(4uT{{AQQQr r<cHg|]}|d|dfSrrrs rrz-draw_networkx_edge_labels.. rr c*tjdSrrrr rrz+draw_networkx_edge_labels.. sIOA4F4Fr c dg|],}tt|dd-Srrrs rrz-draw_networkx_edge_labels.. s4HHH!YuQrrU||455HHHr rrrct|trKt|tkrt|d||<dSdS)Nz' must have the same length as edgelist.)rrrriter)rrrrs rrz:draw_networkx_edge_labels..check_individual_params sf gt $ $ 77||s8}},, F!S!S!STTT(/  f % % % 7 7r c:|vrt|S|Sr%)r)rrrs rr!z2draw_networkx_edge_labels..get_param_value s( & & &)&122 2r r"r#r$rXrFrGrnrrr%) rTrUrVrWrXrFrGrrr[rr&)rTrUrVrWrXrFrGrr[rr&rrrr{Fr|r)$r6rTrUrVrYrZrrrrr=rrr7r4r^rr.rrSrrrrrrr9rr_rrrrrrrX)2r0rm edge_labelsrr"r#r%r$rXr[rFrGrrnr&rLrrrzr6rr}rrrr rrrrr!r(rArrEn1n2rrxrrryr'rrrrrDrrs2 ` @@@@@@rr r shb######g#g#g#g#g#g#g#g#g##(-g#g#g#T |#?/RR/3'' *+ _ % % // ,    z WWYY!"!2!2:~~QQgag6P6P46P46P6PQQQ  K--//0Hf ??zzDDDD8DDDEEH++,F,FGG HHHHxHHH sS]]* AwwrxxAAAq 12233wwrxxAAAq 12233 4K66aaurxx /B/B/F/F/H/H'HO+    777777 I{333J 555K777E7+++/1FGGG-/BCCCFH---I{333J%c(F&;&;<<77=D%%%% JJEbqbB##A&& 88"'";";"="= <))#b'22D++D$77I --//>>yIII%a(DAq!ww$_Y <<%oj,??&{MBB&{MBB%oeW55$3O')>%%#2/%':##,' '  Jt  , /$_Y <<%oj,??&{MBB&{MBB%oeW55$3O')>%%#2/%':##,)/)[AA&5ofh&G&G"G)   Jt  .       r c Ht|fdtj|i|dS)aEDraw the graph `G` with a bipartite layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.bipartite_layout(G), **kwargs) Parameters ---------- G : graph A networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Raises ------ NetworkXError : If `G` is not bipartite. Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.bipartite_layout` directly and reuse the result:: >>> G = nx.complete_bipartite_graph(3, 3) >>> pos = nx.bipartite_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.complete_bipartite_graph(2, 5) >>> nx.draw_bipartite(G) See Also -------- :func:`~networkx.drawing.layout.bipartite_layout` rmN)rr=bipartite_layoutr0rs rr r  s1R 11#A&&1&11111r c Ht|fdtj|i|dS)aDraw the graph `G` with a circular layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.circular_layout(G), **kwargs) Parameters ---------- G : graph A networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.circular_layout` directly and reuse the result:: >>> G = nx.complete_graph(5) >>> pos = nx.circular_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.path_graph(5) >>> nx.draw_circular(G) See Also -------- :func:`~networkx.drawing.layout.circular_layout` rmN)rr=circular_layoutrCs rr r K s1H 00"1%%000000r c Ht|fdtj|i|dS)aDraw the graph `G` with a Kamada-Kawai force-directed layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.kamada_kawai_layout(G), **kwargs) Parameters ---------- G : graph A networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.kamada_kawai_layout` directly and reuse the result:: >>> G = nx.complete_graph(5) >>> pos = nx.kamada_kawai_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.path_graph(5) >>> nx.draw_kamada_kawai(G) See Also -------- :func:`~networkx.drawing.layout.kamada_kawai_layout` rmN)rr=kamada_kawai_layoutrCs rrrr s1J 44&q))4V44444r c Ht|fdtj|i|dS)aDraw the graph `G` with a random layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.random_layout(G), **kwargs) Parameters ---------- G : graph A networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.random_layout` directly and reuse the result:: >>> G = nx.complete_graph(5) >>> pos = nx.random_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.lollipop_graph(4, 3) >>> nx.draw_random(G) See Also -------- :func:`~networkx.drawing.layout.random_layout` rmN)rr= random_layoutrCs rrr s1H .. ##.v.....r c Ht|fdtj|i|dS)aODraw the graph `G` with a spectral 2D layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.spectral_layout(G), **kwargs) For more information about how node positions are determined, see `~networkx.drawing.layout.spectral_layout`. Parameters ---------- G : graph A networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.spectral_layout` directly and reuse the result:: >>> G = nx.complete_graph(5) >>> pos = nx.spectral_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.path_graph(5) >>> nx.draw_spectral(G) See Also -------- :func:`~networkx.drawing.layout.spectral_layout` rmN)rr=spectral_layoutrCs rrr s1N 00"1%%000000r c Ht|fdtj|i|dS)aVDraw the graph `G` with a spring layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.spring_layout(G), **kwargs) Parameters ---------- G : graph A networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Notes ----- `~networkx.drawing.layout.spring_layout` is also the default layout for `draw`, so this function is equivalent to `draw`. The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.spring_layout` directly and reuse the result:: >>> G = nx.complete_graph(5) >>> pos = nx.spring_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.path_graph(20) >>> nx.draw_spring(G) See Also -------- draw :func:`~networkx.drawing.layout.spring_layout` rmN)rr=r]rCs rrr s1P .. ##.v.....r c Lt|fdtj||i|dS)aDraw networkx graph `G` with shell layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.shell_layout(G, nlist=nlist), **kwargs) Parameters ---------- G : graph A networkx graph nlist : list of list of nodes, optional A list containing lists of nodes representing the shells. Default is `None`, meaning all nodes are in a single shell. See `~networkx.drawing.layout.shell_layout` for details. kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.shell_layout` directly and reuse the result:: >>> G = nx.complete_graph(5) >>> pos = nx.shell_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.path_graph(4) >>> shells = [[0], [1, 2, 3]] >>> nx.draw_shell(G, nlist=shells) See Also -------- :func:`~networkx.drawing.layout.shell_layout` rm)nlistN)rr= shell_layout)r0rNrs rrr s5T ::///:6:::::r c Ht|fdtj|i|dS)a$Draw a planar networkx graph `G` with planar layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.planar_layout(G), **kwargs) Parameters ---------- G : graph A planar networkx graph kwargs : optional keywords See `draw_networkx` for a description of optional keywords. Raises ------ NetworkXException When `G` is not planar Notes ----- The layout is computed each time this function is called. For repeated drawing it is much more efficient to call `~networkx.drawing.layout.planar_layout` directly and reuse the result:: >>> G = nx.path_graph(5) >>> pos = nx.planar_layout(G) >>> nx.draw(G, pos=pos) # Draw the original graph >>> # Draw a subgraph, reusing the same node positions >>> nx.draw(G.subgraph([0, 1, 2]), pos=pos, node_color="red") Examples -------- >>> G = nx.path_graph(4) >>> nx.draw_planar(G) See Also -------- :func:`~networkx.drawing.layout.planar_layout` rmN)rr= planar_layoutrCs rrrC s1R .. ##.v.....r c Ht|fdtj|i|dS)aDraw a networkx graph with forceatlas2 layout. This is a convenience function equivalent to:: nx.draw(G, pos=nx.forceatlas2_layout(G), **kwargs) Parameters ---------- G : graph A networkx graph kwargs : optional keywords See networkx.draw_networkx() for a description of optional keywords, with the exception of the pos parameter which is not used by this function. rmN)rr=forceatlas2_layoutrCs rrro s0" 33%a((3F33333r c ddlm}m}ddl ddl}ddl}ddl} t|t|krbt|dtrG j |} | ||| |} nf |  jj |g} n1#t"$r$|  fd|D} YnwxYw t|t| ks| jt|krR| | t|df} | d| dddf<| d | dddf<| d | ddd f<t)|||t| | ddd f<n#t*$r || ddd f<YnwxYw| S)aApply an alpha (or list of alphas) to the colors provided. Parameters ---------- colors : color string or array of floats (default='r') Color of element. Can be a single color format string, or a sequence of colors with the same length as nodelist. If numeric values are specified they will be mapped to colors using the cmap and vmin,vmax parameters. See matplotlib.scatter for more details. alpha : float or array of floats Alpha values for elements. This can be a single alpha value, in which case it will be applied to all the elements of color. Otherwise, if it is an array, the elements of alpha will be applied to the colors in order (cycling through alpha multiple times if necessary). elem_list : array of networkx objects The list of elements which are being colored. These could be nodes, edges or labels. cmap : matplotlib colormap Color map for use if colors is a list of floats corresponding to points on a color mapping. vmin, vmax : float Minimum and maximum values for normalizing colors if a colormap is used Returns ------- rgba_colors : numpy ndarray Array containing RGBA format values for each of the node colours. r)cycleisliceNr!cNg|]!}jj|"Sr)rrr*)rrUrDs rrzapply_alpha.. s,NNNe*22599NNNr r)rrrr)rrrr)rrUrVr6 matplotlib.cmrrVrrrr:r;r<r*rrrrrTresizerr) rrX elem_listr"rBrCrUrVr6rr+ rgba_colorsrDs @rrr s8J(''''''' 6{{c)nn$$F1Iv)F)F$&&D&11d###nnV,,  ((CJ$=$E$Ef$M$M#NOOKK   ((NNNNvNNNKKK  # u::K(( ( (K,<I,N,N))K#i..!1DEEK!,T!2KA !,T!2KA !,T!2KA  e c+6F6F!G!GHH AAAqD ###" AAArE# s%3C+C?>C?CGGG)NNTr%)NN)NrMrKr]NNNNNNNNNT)NrRrrNNruNNNNNNrMNr]rvrrT) NrOrrPrQNNrSrSNTT)NrlrurrPrQNNrSrSNTTrMNrvT)NNN)rrSrnumbersrnetworkxr=__all__rrrrrrr r r r r rrrrrrrrrr rr`s&   ,>B@ @ @ @ J U U U U pL L L L ^zzzz@     !ggggTX1X1X1X1X1X1X1X1|      -rrrrp     VVVVx      'ssssl )2)2)2X$1$1$1N%5%5%5P$/$/$/N'1'1'1T(/(/(/V*;*;*;*;Z)/)/)/X444(JJJJJJr