ó
 ,µ[c           @   sô   d  Z  d d l Z d d l j Z d d l m Z d Z d Z e j	 e e ƒ Z
 d GHxA e j e
 ƒ D]0 Z d e e j e
 e ƒ e j e
 e ƒ f GHqd Wy e j e
 e j ƒ Wn' e k
 rØ e j e
 e j j ƒ n Xe j e
 ƒ e j ƒ  d S(   s  
===========
Erdos Renyi
===========

Create an G{n,m} random graph with n nodes and m edges
and report some properties.

This graph is sometimes called the ErdÅ‘s-RÃ©nyi graph
but is different from G{n,p} or binomial_graph which is also
sometimes called the ErdÅ‘s-RÃ©nyi graph.
iÿÿÿÿN(   t   nxi
   i   s   node degree clusterings   %s %d %f(   t   __doc__t   syst   matplotlib.pyplott   pyplott   pltt   networkxR    t   nt   mt   gnm_random_grapht   Gt   nodest   vt   degreet
   clusteringt   write_adjlistt   stdoutt	   TypeErrort   buffert   drawt   show(    (    (    s9   share/doc/networkx-2.2/examples/graph/plot_erdos_renyi.pyt   <module>   s   
.