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  • Committer: Bazaar Package Importer
  • Author(s): Cyril Brulebois
  • Date: 2009-11-23 15:44:34 UTC
  • mfrom: (1.2.3 upstream)
  • Revision ID: james.westby@ubuntu.com-20091123154434-ellm2ut3a4edf9wh
Tags: 1.0~rc1~svn1492-1
http://bugs.debian.org/549996
http://bugs.debian.org/539942
* New upstream snapshot, past 1.0~rc1, as requested by Yaroslav
  Halchenko (Closes: #549996).
* Refresh patch accordingly:
   + debian/patches/10_doc_relocation.
* Get rid of extra LICENSE.txt file in /usr/share/doc.
* Use dh_compress -Xexamples/ to avoid compressing examples, thanks to
  Sandro Tosi (Closes: #539942).
* Bump Standards-Version from 3.8.0 to 3.8.3 (no changes needed).

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Lines of Context:
networkx/tests/convert_scipy.txt
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Convert
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=======
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>>> import os,tempfile
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>>> from networkx import *
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>>> from networkx.convert import *
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>>> from networkx.operators import *
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>>> from networkx.generators.classic import barbell_graph,cycle_graph
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>>> import scipy
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>>> import scipy.sparse
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Bad shape
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---------
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>>> A=scipy.sparse.lil_matrix([[1,2,3],[4,5,6]])
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>>> from_scipy_sparse_matrix(A)
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Traceback (most recent call last):
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...
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NetworkXError: Adjacency matrix is not square. nx,ny=(2, 3)
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Simple Graphs
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--------------
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>>> G=barbell_graph(10,3)
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Scipy sparse matrix
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~~~~~~~~~~~~~~~~~~~
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>>> A=to_scipy_sparse_matrix(G)
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>>> GG=from_scipy_sparse_matrix(A)
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>>> sorted(G.nodes())==sorted(GG.nodes())
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True
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>>> sorted(G.edges())==sorted(GG.edges())
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True
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>>> GW=from_whatever(A)
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>>> sorted(G.nodes())==sorted(GW.nodes())
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True
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>>> sorted(G.edges())==sorted(GW.edges())
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True
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>>> GI=Graph(A)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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>>> ACSR=A.tocsr()
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>>> GI=Graph(ACSR)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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>>> ACOO=A.tocoo()
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>>> GI=Graph(ACOO)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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>>> ACSC=A.tocsc()
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>>> GI=Graph(ACSC)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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>>> AD=A.todense()
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>>> GI=Graph(AD)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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>>> AA=A.toarray()
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>>> GI=Graph(AA)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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DiGraphs
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--------
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>>> G=cycle_graph(10,create_using=DiGraph())
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Scipy sparse matrix
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~~~~~~~~~~~~~~~~~~~
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>>> A=to_scipy_sparse_matrix(G)
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>>> GG=from_scipy_sparse_matrix(A,create_using=DiGraph())
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>>> sorted(G.nodes())==sorted(GG.nodes())
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True
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>>> sorted(G.edges())==sorted(GG.edges())
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True
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>>> GW=from_whatever(A,create_using=DiGraph())
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>>> sorted(G.nodes())==sorted(GW.nodes())
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True
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>>> sorted(G.edges())==sorted(GW.edges())
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True
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>>> GI=DiGraph(A)
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>>> sorted(G.nodes())==sorted(GI.nodes())
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True
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>>> sorted(G.edges())==sorted(GI.edges())
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True
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Graph
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------
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>>> G=cycle_graph(4)
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>>> e=G.edges()
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>>> source=[u for u,v in e]
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>>> dest=[v for u,v in e]
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>>> weight=[s+10 for s in source]
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>>> ex=zip(source,dest,weight)
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>>> XG=Graph()
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>>> XG.add_edges_from(ex)
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Numpy matrix
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~~~~~~~~~~~~
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>>> A=to_scipy_sparse_matrix(XG)
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>>> GG=from_scipy_sparse_matrix(A,create_using=Graph())
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>>> sorted(XG.nodes())==sorted(GG.nodes())
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True
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>>> sorted(XG.edges())==sorted(GG.edges())
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True
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>>> GW=from_whatever(A,create_using=Graph())
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>>> sorted(XG.nodes())==sorted(GW.nodes())
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True
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>>> sorted(XG.edges())==sorted(GW.edges())
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True
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>>> GI=Graph(A)
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>>> sorted(XG.nodes())==sorted(GI.nodes())
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True
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>>> sorted(XG.edges())==sorted(GI.edges())
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True
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DiGraph
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------
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>>> G=cycle_graph(4)
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>>> e=G.edges()
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>>> source=[u for u,v in e]
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>>> dest=[v for u,v in e]
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>>> weight=[s+10 for s in source]
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>>> ex=zip(source,dest,weight)
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>>> XG=DiGraph()
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>>> XG.add_edges_from(ex)
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Scipy sparse matrix
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~~~~~~~~~~~~~~~~~~~
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>>> A=to_scipy_sparse_matrix(XG)
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>>> GG=from_scipy_sparse_matrix(A,create_using=DiGraph())
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>>> sorted(XG.nodes())==sorted(GG.nodes())
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True
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>>> sorted(XG.edges())==sorted(GG.edges())
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True
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>>> GW=from_whatever(A,create_using=DiGraph())
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>>> sorted(XG.nodes())==sorted(GW.nodes())
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True
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>>> sorted(XG.edges())==sorted(GW.edges())
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True
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>>> GI=DiGraph(A)
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>>> sorted(XG.nodes())==sorted(GI.nodes())
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True
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>>> sorted(XG.edges())==sorted(GI.edges())
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True
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170
 
With nodelist keyword
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---------------------
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>>> P4=path_graph(4)
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>>> P3=path_graph(3)
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>>> A=to_scipy_sparse_matrix(P4,nodelist=[0,1,2])
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>>> GA=Graph(A)
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>>> sorted(GA.nodes())==sorted(P3.nodes())
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True
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>>> sorted(GA.edges())==sorted(P3.edges())
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True