Generators - Classic
====================

Unit tests for various classic graph generators in generators/classic.py
------------------------------------------------------------------------

>>> from networkx import *
>>> from networkx.isomorph import graph_could_be_isomorphic
>>> is_isomorphic=graph_could_be_isomorphic



balanced_tree
-------------

balanced_tree(r,h) is a tree with (r**(h+1)-1)/(r-1) edges

>>> r=2; h=2
>>> t=balanced_tree(r,h)
>>> order=t.order()
>>> order==(r**(h+1)-1)/(r-1)
True
>>> is_connected(t)
True
>>> t.size()==order-1
True

>>> r=3; h=3
>>> t=balanced_tree(r,h)
>>> order=t.order()
>>> order==(r**(h+1)-1)/(r-1)
True
>>> is_connected(t)
True
>>> t.size()==order-1
True

>>> r=6; h=2
>>> t=balanced_tree(r,h)
>>> order=t.order()
>>> order==(r**(h+1)-1)/(r-1)
True
>>> is_connected(t)
True
>>> t.size()==order-1
True

balanced_tree(r,1) is the r-star

>>> r=2; h=1
>>> t=balanced_tree(r,h)
>>> is_isomorphic(t,star_graph(r))
True

>>> r=5; h=1
>>> t=balanced_tree(r,h)
>>> is_isomorphic(t,star_graph(r))
True

>>> r=10; h=1
>>> t=balanced_tree(r,h)
>>> is_isomorphic(t,star_graph(r))
True

Raise NetworkXError if r<2

>>> r=1; h=10
>>> t=balanced_tree(r,h)
Traceback (most recent call last):
...
NetworkXError: Invalid graph description, r should be >=2

>>> r=0; h=10
>>> t=balanced_tree(r,h)
Traceback (most recent call last):
...
NetworkXError: Invalid graph description, r should be >=2

Raise NetworkXError if h<1

>>> r=10; h=0
>>> t=balanced_tree(r,h)
Traceback (most recent call last):
...
NetworkXError: Invalid graph description, h should be >=1

Raise NetworkXError if h<1

>>> r=4; h=0
>>> t=balanced_tree(r,h)
Traceback (most recent call last):
...
NetworkXError: Invalid graph description, h should be >=1

barbell_graph
-------------

number of nodes = 2*m1 + m2 (2 m1-complete graphs + m2-path + 2 edges)
number of edges = 2*(number_of_edges(m1-complete graph) + m2 + 1

>>> m1=3; m2=5 
>>> b=barbell_graph(m1,m2) 
>>> number_of_nodes(b)==2*m1+m2
True
>>> number_of_edges(b)==m1*(m1-1) + m2 + 1
True
>>> b.name
'barbell_graph(3,5)'

>>> m1=4; m2=10 
>>> b=barbell_graph(m1,m2) 
>>> number_of_nodes(b)==2*m1+m2
True
>>> number_of_edges(b)==m1*(m1-1) + m2 + 1
True
>>> b.name
'barbell_graph(4,10)'

>>> m1=3; m2=20 
>>> b=barbell_graph(m1,m2) 
>>> number_of_nodes(b)==2*m1+m2
True
>>> number_of_edges(b)==m1*(m1-1) + m2 + 1
True
>>> b.name
'barbell_graph(3,20)'

Raise NetworkXError if m1<2

>>> m1=1; m2=20 
>>> b=barbell_graph(m1,m2)
Traceback (most recent call last): 
...  
NetworkXError: Invalid graph description, m1 should be >=2

Raise NetworkXError if m2<0

>>> m1=5; m2=-2 
>>> b=barbell_graph(m1,m2)
Traceback (most recent call last): 
...  
NetworkXError: Invalid graph description, m2 should be >=0

barbell_graph(2,m) = path_graph(m+4)

>>> m1=2; m2=5 
>>> b=barbell_graph(m1,m2) 
>>> is_isomorphic(b, path_graph(m2+4))
True

>>> m1=2; m2=10 
>>> b=barbell_graph(m1,m2) 
>>> is_isomorphic(b, path_graph(m2+4))
True

>>> m1=2; m2=20 
>>> b=barbell_graph(m1,m2) 
>>> is_isomorphic(b, path_graph(m2+4))
True



complete_graph
--------------

complete_graph(m) is a connected graph with 
m nodes and  m*(m+1)/2 edges

>>> m=0
>>> g=complete_graph(m)
>>> number_of_nodes(g)==0
True
>>> number_of_edges(g)==0
True

>>> m=1
>>> g=complete_graph(m)
>>> number_of_nodes(g)==m
True
>>> number_of_edges(g)==0
True

>>> m=3
>>> g=complete_graph(m)
>>> number_of_nodes(g)==m
True
>>> number_of_edges(g)==m*(m-1)/2
True

>>> m=5
>>> g=complete_graph(m)
>>> number_of_nodes(g)==m
True
>>> number_of_edges(g)==m*(m-1)/2
True

complete_bipartite_graph
------------------------

>>> G=complete_bipartite_graph(0,0)
>>> is_isomorphic( G, null_graph() )
True

>>> G=complete_bipartite_graph(1,0)
>>> is_isomorphic( G, empty_graph(1) )
True
>>> G=complete_bipartite_graph(0,1)
>>> is_isomorphic( G, empty_graph(1) )
True

>>> G=complete_bipartite_graph(5,0)
>>> is_isomorphic( G, empty_graph(5) )
True
>>> G=complete_bipartite_graph(0,5)
>>> is_isomorphic( G, empty_graph(5) )
True

>>> G=complete_bipartite_graph(2,2)
>>> is_isomorphic( G, cycle_graph(4) )
True

>>> G=complete_bipartite_graph(1,5)
>>> is_isomorphic( G, star_graph(5) )
True
>>> G=complete_bipartite_graph(5,1)
>>> is_isomorphic( G, star_graph(5) )
True

complete_bipartite_graph(m1,m2) is a connected graph with 
m1+m2 nodes and  m1*m2 edges

>>> G=complete_bipartite_graph(5,11)
>>> number_of_nodes(G)
16
>>> number_of_edges(G)
55


>>> G=complete_bipartite_graph(7,3)
>>> number_of_nodes(G)
10
>>> number_of_edges(G)
21


circular_ladder_graph
---------------------

>>> G=circular_ladder_graph(5) 

cycle_graph
-----------

>>> G=cycle_graph(4)
>>> sorted(G.edges())
[(0, 1), (0, 3), (1, 2), (2, 3)]

>>> G=cycle_graph(4, create_using=DiGraph())
>>> G.has_edge(2,1)
False
>>> G.has_edge(1,2)
True

dorogovtsev_goltsev_mendes_graph 
--------------------------------
 
>>> G=dorogovtsev_goltsev_mendes_graph(0) 
>>> G.edges()
[(0, 1)]
>>> G.nodes()         
[0, 1]
>>> G=dorogovtsev_goltsev_mendes_graph(1) 
>>> G.edges()                                                
[(0, 1), (0, 2), (1, 2)]
>>> average_clustering(G) 
1.0
>>> triangles(G) 
[1, 1, 1]
>>> G=dorogovtsev_goltsev_mendes_graph(10) 
>>> number_of_nodes(G) 
29526
>>> number_of_edges(G) 
59049
>>> G.degree(0) 
1024
>>> G.degree(1) 
1024
>>> G.degree(2) 
1024

empty_graph
-----------

>>> G=empty_graph()
>>> number_of_nodes(G)
0

>>> G=empty_graph(42)
>>> number_of_nodes(G)
42
>>> number_of_edges(G)
0
>>> print G.name
empty_graph(42)


create empty digraph

>>> G=empty_graph(42,create_using=DiGraph(name="duh")) 
>>> number_of_nodes(G)
42
>>> number_of_edges(G)
0
>>> G.name # name was cleared, so nothing
'empty_graph(42)'
>>> isinstance(G,DiGraph)
True


create empty graph from another

>>> pete=petersen_graph()
>>> G=empty_graph(42,create_using=pete) 
>>> number_of_nodes(G)
42
>>> number_of_edges(G)
0
>>> G.name # name was cleared, so nothing
'empty_graph(42)'
>>> isinstance(G,Graph)
True



grid_2d_graph
-------------

>>> G=grid_2d_graph(5,6)

grid_graph
----------

grid_graph([n,m]) is a connected simple graph with the following properties:
number_of_nodes=n*m
degree_histogram=[0,0,4,2*(n+m)-8,(n-2)*(m-2)

>>> n=3; m=5
>>> g=grid_graph([n,m])
>>> number_of_nodes(g)==n*m
True
>>> degree_histogram(g)==[0,0,4,2*(n+m)-8,(n-2)*(m-2)]
True

>>> n=5; m=3
>>> g=grid_graph([n,m])
>>> number_of_nodes(g)==n*m
True
>>> degree_histogram(g)==[0,0,4,2*(n+m)-8,(n-2)*(m-2)]
True

>>> n=4; m=5
>>> g=grid_graph([n,m])
>>> number_of_nodes(g)==n*m
True
>>> degree_histogram(g)==[0,0,4,2*(n+m)-8,(n-2)*(m-2)]
True

>>> n=5; m=4
>>> g=grid_graph([n,m])
>>> number_of_nodes(g)==n*m
True
>>> degree_histogram(g)==[0,0,4,2*(n+m)-8,(n-2)*(m-2)]
True

>>> n=1; m=5
>>> g=grid_graph([n,m])
>>> number_of_nodes(g)==n*m
True
>>> is_isomorphic(g,path_graph(m))
True

>>> n=5; m=1
>>> g=grid_graph([n,m])
>>> number_of_nodes(g)==n*m
True
>>> is_isomorphic(g,path_graph(n))
True


hypercube_graph
---------------

>>> g=hypercube_graph(0)
>>> is_isomorphic(g, null_graph())
True

>>> g=hypercube_graph(1)
>>> is_isomorphic(g, path_graph(2))
True

>>> g=hypercube_graph(2)
>>> is_isomorphic(g, cycle_graph(4))
True

>>> g=hypercube_graph(3)
>>> is_isomorphic(g, cubical_graph())
True

>>> g=hypercube_graph(4)
>>> degree_histogram(g)
[0, 0, 0, 0, 16]

>>> g=hypercube_graph(5)
>>> degree_histogram(g)
[0, 0, 0, 0, 0, 32]

>>> g=hypercube_graph(6)
>>> degree_histogram(g)
[0, 0, 0, 0, 0, 0, 64]


ladder_graph
------------
 
>>> g=ladder_graph(0)
>>> is_isomorphic(g, empty_graph(0))
True

>>> g=ladder_graph(1)
>>> is_isomorphic(g, path_graph(2))
True

>>> g=ladder_graph(2)
>>> is_isomorphic(g, hypercube_graph(2))
True

>>> is_isomorphic( ladder_graph(10), grid_graph([2,10]))
True

lollipop_graph
--------------

number of nodes = m1 + m2
number of edges = number_of_edges(complete_graph(m1)) + m2

>>> m1=3; m2=5 
>>> b=lollipop_graph(m1,m2) 
>>> number_of_nodes(b)==m1+m2
True
>>> number_of_edges(b)==m1*(m1-1)/2 + m2
True
>>> b.name
'lollipop_graph(3,5)'

>>> m1=4; m2=10 
>>> b=lollipop_graph(m1,m2) 
>>> number_of_nodes(b)==m1+m2
True
>>> number_of_edges(b)==m1*(m1-1)/2 + m2
True
>>> b.name
'lollipop_graph(4,10)'

>>> m1=3; m2=20 
>>> b=lollipop_graph(m1,m2) 
>>> number_of_nodes(b)==m1+m2
True
>>> number_of_edges(b)==m1*(m1-1)/2 + m2 
True
>>> b.name
'lollipop_graph(3,20)'

Raise NetworkXError if m<2

>>> m1=1; m2=20 
>>> b=lollipop_graph(m1,m2)
Traceback (most recent call last): 
...  
NetworkXError: Invalid graph description, m should be >=2

Raise NetworkXError if n<0

>>> m1=5; m2=-2 
>>> b=lollipop_graph(m1,m2)
Traceback (most recent call last): 
...  
NetworkXError: Invalid graph description, n should be >=0

lollipop_graph(2,m) = path_graph(m+2)

>>> m1=2; m2=5 
>>> b=lollipop_graph(m1,m2) 
>>> is_isomorphic(b, path_graph(m2+2))
True

>>> m1=2; m2=10 
>>> b=lollipop_graph(m1,m2) 
>>> is_isomorphic(b, path_graph(m2+2))
True

>>> m1=2; m2=20 
>>> b=lollipop_graph(m1,m2) 
>>> is_isomorphic(b, path_graph(m2+2))
True




null_graph
----------

>>> number_of_nodes(null_graph())
0
 
path_graph
----------

>>> p=path_graph(0)
>>> is_isomorphic(p, null_graph())
True
>>> p.name
'path_graph(0)'

>>> p=path_graph(1)
>>> is_isomorphic( p, empty_graph(1))
True
>>> p.name
'path_graph(1)'

>>> p=path_graph(10)
>>> is_connected(p)
True
>>> p.degree()
[1, 2, 2, 2, 2, 2, 2, 2, 2, 1]
>>> p.order()-1==p.size()
True

>>> p=path_graph(3, create_using=DiGraph())
>>> p.has_edge(0,1)
True
>>> p.has_edge(1,0)
False

periodic_grid_2d_graph
----------------------

>>> g=grid_2d_graph(0,0, periodic=True)
>>> g.degree()==[]
True

>>> g=grid_2d_graph(2,2, periodic=True)
>>> is_isomorphic( g, cycle_graph(4) )
True

>>> g=grid_2d_graph(1,7, periodic=True)
>>> is_isomorphic( g, cycle_graph(7) )
True
>>> g=grid_2d_graph(7,1, periodic=True)
>>> is_isomorphic( g, cycle_graph(7) )
True

>>> g=grid_2d_graph(2,5, periodic=True)
>>> is_isomorphic( g, circular_ladder_graph(5) )
True
>>> g=grid_2d_graph(5,2, periodic=True)
>>> is_isomorphic( g, circular_ladder_graph(5) )
True

>>> g=grid_2d_graph(2,4, periodic=True)
>>> is_isomorphic( g, cubical_graph() )
True
>>> g=grid_2d_graph(4,2, periodic=True)
>>> is_isomorphic( g, cubical_graph() )
True

 
star_graph
----------

>>> is_isomorphic( star_graph(0), empty_graph(1) )
True

>>> is_isomorphic( star_graph(1), path_graph(2) )
True

>>> is_isomorphic( star_graph(2), path_graph(3) )
True

>>> s=star_graph(10)
>>> s.degree()==[10, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
True


trivial_graph
-------------

>>> number_of_nodes(trivial_graph())
1

wheel_graph
-----------

>>> g=wheel_graph(0)
>>> is_isomorphic( g, null_graph())
True

>>> g=wheel_graph(1)
>>> is_isomorphic( g, empty_graph(1))
True

>>> g=wheel_graph(2)
>>> is_isomorphic( g, path_graph(2))
True

>>> g=wheel_graph(3)
>>> is_isomorphic( g, complete_graph(3))
True

>>> g=wheel_graph(4)
>>> is_isomorphic( g, complete_graph(4))
True
>>> g.name
'wheel_graph(4)'

>>> g=wheel_graph(10)
>>> sorted(g.degree())
[3, 3, 3, 3, 3, 3, 3, 3, 3, 9]

