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0280	61 a8 03 00 00 52 65 74 75 72 6e 73 20 65 69 67 65 6e 76 61 6c 75 65 73 20 6f 66 20 74 68 65 20	a....Returns.eigenvalues.of.the.
02a0	4c 61 70 6c 61 63 69 61 6e 20 6f 66 20 47 0a 0a 20 20 20 20 50 61 72 61 6d 65 74 65 72 73 0a 20	Laplacian.of.G......Parameters..
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02e0	20 20 20 41 20 4e 65 74 77 6f 72 6b 58 20 67 72 61 70 68 0a 0a 20 20 20 20 77 65 69 67 68 74 20	...A.NetworkX.graph......weight.
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0320	75 6c 74 3d 27 77 65 69 67 68 74 27 29 0a 20 20 20 20 20 20 20 54 68 65 20 65 64 67 65 20 64 61	ult='weight')........The.edge.da
0340	74 61 20 6b 65 79 20 75 73 65 64 20 74 6f 20 63 6f 6d 70 75 74 65 20 65 61 63 68 20 76 61 6c 75	ta.key.used.to.compute.each.valu
0360	65 20 69 6e 20 74 68 65 20 6d 61 74 72 69 78 2e 0a 20 20 20 20 20 20 20 49 66 20 4e 6f 6e 65 2c	e.in.the.matrix.........If.None,
0380	20 74 68 65 6e 20 65 61 63 68 20 65 64 67 65 20 68 61 73 20 77 65 69 67 68 74 20 31 2e 0a 0a 20	.then.each.edge.has.weight.1....
03a0	20 20 20 52 65 74 75 72 6e 73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 65 76 61 6c 73	...Returns.....-------.....evals
03c0	20 3a 20 4e 75 6d 50 79 20 61 72 72 61 79 0a 20 20 20 20 20 20 45 69 67 65 6e 76 61 6c 75 65 73	.:.NumPy.array.......Eigenvalues
03e0	0a 0a 20 20 20 20 4e 6f 74 65 73 0a 20 20 20 20 2d 2d 2d 2d 2d 0a 20 20 20 20 46 6f 72 20 4d 75	......Notes.....-----.....For.Mu
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0460	6e 75 6d 70 79 5f 61 72 72 61 79 60 20 66 6f 72 20 6f 74 68 65 72 20 6f 70 74 69 6f 6e 73 2e 0a	numpy_array`.for.other.options..
0480	0a 20 20 20 20 53 65 65 20 41 6c 73 6f 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 6c	.....See.Also.....--------.....l
04a0	61 70 6c 61 63 69 61 6e 5f 6d 61 74 72 69 78 0a 0a 20 20 20 20 45 78 61 6d 70 6c 65 73 0a 20 20	aplacian_matrix......Examples...
04c0	20 20 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 54 68 65 20 6d 75 6c 74 69 70 6c 69 63 69 74 79 20	..--------.....The.multiplicity.
04e0	6f 66 20 30 20 61 73 20 61 6e 20 65 69 67 65 6e 76 61 6c 75 65 20 6f 66 20 74 68 65 20 6c 61 70	of.0.as.an.eigenvalue.of.the.lap
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0520	65 20 6e 75 6d 62 65 72 20 6f 66 20 63 6f 6e 6e 65 63 74 65 64 20 63 6f 6d 70 6f 6e 65 6e 74 73	e.number.of.connected.components
0540	20 6f 66 20 47 2e 0a 0a 20 20 20 20 3e 3e 3e 20 47 20 3d 20 6e 78 2e 47 72 61 70 68 28 29 20 20	.of.G.......>>>.G.=.nx.Graph()..
0560	23 20 43 72 65 61 74 65 20 61 20 67 72 61 70 68 20 77 69 74 68 20 35 20 6e 6f 64 65 73 20 61 6e	#.Create.a.graph.with.5.nodes.an
0580	64 20 33 20 63 6f 6e 6e 65 63 74 65 64 20 63 6f 6d 70 6f 6e 65 6e 74 73 0a 20 20 20 20 3e 3e 3e	d.3.connected.components.....>>>
05a0	20 47 2e 61 64 64 5f 6e 6f 64 65 73 5f 66 72 6f 6d 28 72 61 6e 67 65 28 35 29 29 0a 20 20 20 20	.G.add_nodes_from(range(5)).....
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0660	63 69 61 6e 5f 6d 61 74 72 69 78 da 07 74 6f 64 65 6e 73 65 a9 03 da 01 47 72 08 00 00 00 da 02	cian_matrix..todense....Gr......
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07e0	75 72 6e 20 65 69 67 65 6e 76 61 6c 75 65 73 20 6f 66 20 74 68 65 20 6e 6f 72 6d 61 6c 69 7a 65	urn.eigenvalues.of.the.normalize
0800	64 20 4c 61 70 6c 61 63 69 61 6e 20 6f 66 20 47 0a 0a 20 20 20 20 50 61 72 61 6d 65 74 65 72 73	d.Laplacian.of.G......Parameters
0820	0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 47 20 3a 20 67 72 61 70 68 0a 20 20	.....----------.....G.:.graph...
0840	20 20 20 20 20 41 20 4e 65 74 77 6f 72 6b 58 20 67 72 61 70 68 0a 0a 20 20 20 20 77 65 69 67 68	.....A.NetworkX.graph......weigh
0860	74 20 3a 20 73 74 72 69 6e 67 20 6f 72 20 4e 6f 6e 65 2c 20 6f 70 74 69 6f 6e 61 6c 20 28 64 65	t.:.string.or.None,.optional.(de
0880	66 61 75 6c 74 3d 27 77 65 69 67 68 74 27 29 0a 20 20 20 20 20 20 20 54 68 65 20 65 64 67 65 20	fault='weight')........The.edge.
08a0	64 61 74 61 20 6b 65 79 20 75 73 65 64 20 74 6f 20 63 6f 6d 70 75 74 65 20 65 61 63 68 20 76 61	data.key.used.to.compute.each.va
08c0	6c 75 65 20 69 6e 20 74 68 65 20 6d 61 74 72 69 78 2e 0a 20 20 20 20 20 20 20 49 66 20 4e 6f 6e	lue.in.the.matrix.........If.Non
08e0	65 2c 20 74 68 65 6e 20 65 61 63 68 20 65 64 67 65 20 68 61 73 20 77 65 69 67 68 74 20 31 2e 0a	e,.then.each.edge.has.weight.1..
0900	0a 20 20 20 20 52 65 74 75 72 6e 73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 65 76 61	.....Returns.....-------.....eva
0920	6c 73 20 3a 20 4e 75 6d 50 79 20 61 72 72 61 79 0a 20 20 20 20 20 20 45 69 67 65 6e 76 61 6c 75	ls.:.NumPy.array.......Eigenvalu
0940	65 73 0a 0a 20 20 20 20 4e 6f 74 65 73 0a 20 20 20 20 2d 2d 2d 2d 2d 0a 20 20 20 20 46 6f 72 20	es......Notes.....-----.....For.
0960	4d 75 6c 74 69 47 72 61 70 68 2f 4d 75 6c 74 69 44 69 47 72 61 70 68 2c 20 74 68 65 20 65 64 67	MultiGraph/MultiDiGraph,.the.edg
0980	65 73 20 77 65 69 67 68 74 73 20 61 72 65 20 73 75 6d 6d 65 64 2e 0a 20 20 20 20 53 65 65 20 74	es.weights.are.summed......See.t
09a0	6f 5f 6e 75 6d 70 79 5f 61 72 72 61 79 20 66 6f 72 20 6f 74 68 65 72 20 6f 70 74 69 6f 6e 73 2e	o_numpy_array.for.other.options.
09c0	0a 0a 20 20 20 20 53 65 65 20 41 6c 73 6f 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20	......See.Also.....--------.....
09e0	6e 6f 72 6d 61 6c 69 7a 65 64 5f 6c 61 70 6c 61 63 69 61 6e 5f 6d 61 74 72 69 78 0a 20 20 20 20	normalized_laplacian_matrix.....
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0a20	00 da 1b 6e 6f 72 6d 61 6c 69 7a 65 64 5f 6c 61 70 6c 61 63 69 61 6e 5f 6d 61 74 72 69 78 72 11	...normalized_laplacian_matrixr.
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0b00	00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 7c 00 7c 01 ac 03 ab 02 00 00 00 00 00 00 6a 0b	................|.|...........j.
0b20	00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ab 00 00 00 00 00 00 00 ab 01 00 00 00 00	................................
0b40	00 00 53 00 29 04 61 16 02 00 00 52 65 74 75 72 6e 73 20 65 69 67 65 6e 76 61 6c 75 65 73 20 6f	..S.).a....Returns.eigenvalues.o
0b60	66 20 74 68 65 20 61 64 6a 61 63 65 6e 63 79 20 6d 61 74 72 69 78 20 6f 66 20 47 2e 0a 0a 20 20	f.the.adjacency.matrix.of.G.....
0b80	20 20 50 61 72 61 6d 65 74 65 72 73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20	..Parameters.....----------.....
0ba0	47 20 3a 20 67 72 61 70 68 0a 20 20 20 20 20 20 20 41 20 4e 65 74 77 6f 72 6b 58 20 67 72 61 70	G.:.graph........A.NetworkX.grap
0bc0	68 0a 0a 20 20 20 20 77 65 69 67 68 74 20 3a 20 73 74 72 69 6e 67 20 6f 72 20 4e 6f 6e 65 2c 20	h......weight.:.string.or.None,.
0be0	6f 70 74 69 6f 6e 61 6c 20 28 64 65 66 61 75 6c 74 3d 27 77 65 69 67 68 74 27 29 0a 20 20 20 20	optional.(default='weight').....
0c00	20 20 20 54 68 65 20 65 64 67 65 20 64 61 74 61 20 6b 65 79 20 75 73 65 64 20 74 6f 20 63 6f 6d	...The.edge.data.key.used.to.com
0c20	70 75 74 65 20 65 61 63 68 20 76 61 6c 75 65 20 69 6e 20 74 68 65 20 6d 61 74 72 69 78 2e 0a 20	pute.each.value.in.the.matrix...
0c40	20 20 20 20 20 20 49 66 20 4e 6f 6e 65 2c 20 74 68 65 6e 20 65 61 63 68 20 65 64 67 65 20 68 61	......If.None,.then.each.edge.ha
0c60	73 20 77 65 69 67 68 74 20 31 2e 0a 0a 20 20 20 20 52 65 74 75 72 6e 73 0a 20 20 20 20 2d 2d 2d	s.weight.1.......Returns.....---
0c80	2d 2d 2d 2d 0a 20 20 20 20 65 76 61 6c 73 20 3a 20 4e 75 6d 50 79 20 61 72 72 61 79 0a 20 20 20	----.....evals.:.NumPy.array....
0ca0	20 20 20 45 69 67 65 6e 76 61 6c 75 65 73 0a 0a 20 20 20 20 4e 6f 74 65 73 0a 20 20 20 20 2d 2d	...Eigenvalues......Notes.....--
0cc0	2d 2d 2d 0a 20 20 20 20 46 6f 72 20 4d 75 6c 74 69 47 72 61 70 68 2f 4d 75 6c 74 69 44 69 47 72	---.....For.MultiGraph/MultiDiGr
0ce0	61 70 68 2c 20 74 68 65 20 65 64 67 65 73 20 77 65 69 67 68 74 73 20 61 72 65 20 73 75 6d 6d 65	aph,.the.edges.weights.are.summe
0d00	64 2e 0a 20 20 20 20 53 65 65 20 74 6f 5f 6e 75 6d 70 79 5f 61 72 72 61 79 20 66 6f 72 20 6f 74	d......See.to_numpy_array.for.ot
0d20	68 65 72 20 6f 70 74 69 6f 6e 73 2e 0a 0a 20 20 20 20 53 65 65 20 41 6c 73 6f 0a 20 20 20 20 2d	her.options.......See.Also.....-
0d40	2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 61 64 6a 61 63 65 6e 63 79 5f 6d 61 74 72 69 78 0a 20 20 20	-------.....adjacency_matrix....
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0d80	73 72 0f 00 00 00 da 10 61 64 6a 61 63 65 6e 63 79 5f 6d 61 74 72 69 78 72 11 00 00 00 72 12 00	sr......adjacency_matrixr....r..
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0e80	00 00 00 00 00 7c 00 ab 01 00 00 00 00 00 00 ab 01 00 00 00 00 00 00 53 00 7c 01 6a 04 00 00 00	.....|.................S.|.j....
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0ee0	00 7c 00 ab 01 00 00 00 00 00 00 ab 01 00 00 00 00 00 00 53 00 29 03 61 aa 01 00 00 52 65 74 75	.|.................S.).a....Retu
0f00	72 6e 73 20 65 69 67 65 6e 76 61 6c 75 65 73 20 6f 66 20 74 68 65 20 6d 6f 64 75 6c 61 72 69 74	rns.eigenvalues.of.the.modularit
0f20	79 20 6d 61 74 72 69 78 20 6f 66 20 47 2e 0a 0a 20 20 20 20 50 61 72 61 6d 65 74 65 72 73 0a 20	y.matrix.of.G.......Parameters..
0f40	20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 47 20 3a 20 47 72 61 70 68 0a 20 20 20 20	...----------.....G.:.Graph.....
0f60	20 20 20 41 20 4e 65 74 77 6f 72 6b 58 20 47 72 61 70 68 20 6f 72 20 44 69 47 72 61 70 68 0a 0a	...A.NetworkX.Graph.or.DiGraph..
0f80	20 20 20 20 52 65 74 75 72 6e 73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 65 76 61 6c	....Returns.....-------.....eval
0fa0	73 20 3a 20 4e 75 6d 50 79 20 61 72 72 61 79 0a 20 20 20 20 20 20 45 69 67 65 6e 76 61 6c 75 65	s.:.NumPy.array.......Eigenvalue
0fc0	73 0a 0a 20 20 20 20 53 65 65 20 41 6c 73 6f 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20	s......See.Also.....--------....
0fe0	20 6d 6f 64 75 6c 61 72 69 74 79 5f 6d 61 74 72 69 78 0a 0a 20 20 20 20 52 65 66 65 72 65 6e 63	.modularity_matrix......Referenc
1000	65 73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 2e 2e 20 5b 31 5d 20 4d 2e 20	es.....----------........[1].M..
1020	45 2e 20 4a 2e 20 4e 65 77 6d 61 6e 2c 20 22 4d 6f 64 75 6c 61 72 69 74 79 20 61 6e 64 20 63 6f	E..J..Newman,."Modularity.and.co
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1120	7e 00 00 00 73 50 00 00 00 80 00 f3 2e 00 05 17 e0 07 08 87 7d 81 7d 84 7f d8 0f 11 8f 79 89 79	~...sP..............}.}......y.y
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11c0	00 00 00 00 00 00 00 00 00 00 00 00 74 07 00 00 00 00 00 00 00 00 6a 08 00 00 00 00 00 00 00 00	............t.........j.........
11e0	00 00 00 00 00 00 00 00 00 00 7c 00 7c 01 ab 02 00 00 00 00 00 00 6a 0b 00 00 00 00 00 00 00 00	..........|.|.........j.........
1200	00 00 00 00 00 00 00 00 00 00 ab 00 00 00 00 00 00 00 ab 01 00 00 00 00 00 00 53 00 29 03 75 fe	..........................S.).u.
1220	01 00 00 52 65 74 75 72 6e 73 20 65 69 67 65 6e 76 61 6c 75 65 73 20 6f 66 20 74 68 65 20 42 65	...Returns.eigenvalues.of.the.Be
1240	74 68 65 20 48 65 73 73 69 61 6e 20 6d 61 74 72 69 78 20 6f 66 20 47 2e 0a 0a 20 20 20 20 50 61	the.Hessian.matrix.of.G.......Pa
1260	72 61 6d 65 74 65 72 73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 47 20 3a 20	rameters.....----------.....G.:.
1280	47 72 61 70 68 0a 20 20 20 20 20 20 20 41 20 4e 65 74 77 6f 72 6b 58 20 47 72 61 70 68 20 6f 72	Graph........A.NetworkX.Graph.or
12a0	20 44 69 47 72 61 70 68 0a 0a 20 20 20 20 72 20 3a 20 66 6c 6f 61 74 0a 20 20 20 20 20 20 20 52	.DiGraph......r.:.float........R
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12e0	73 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 65 76 61 6c 73 20 3a 20 4e 75 6d 50 79 20	s.....-------.....evals.:.NumPy.
1300	61 72 72 61 79 0a 20 20 20 20 20 20 45 69 67 65 6e 76 61 6c 75 65 73 0a 0a 20 20 20 20 53 65 65	array.......Eigenvalues......See
1320	20 41 6c 73 6f 0a 20 20 20 20 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 62 65 74 68 65 5f 68 65 73	.Also.....--------.....bethe_hes
1340	73 69 61 6e 5f 6d 61 74 72 69 78 0a 0a 20 20 20 20 52 65 66 65 72 65 6e 63 65 73 0a 20 20 20 20	sian_matrix......References.....
1360	2d 2d 2d 2d 2d 2d 2d 2d 2d 2d 0a 20 20 20 20 2e 2e 20 5b 31 5d 20 41 2e 20 53 61 61 64 65 2c 20	----------........[1].A..Saade,.
1380	46 2e 20 4b 72 7a 61 6b 61 6c 61 20 61 6e 64 20 4c 2e 20 5a 64 65 62 6f 72 6f 76 c3 a1 0a 20 20	F..Krzakala.and.L..Zdeborov.....
13a0	20 20 20 20 20 22 53 70 65 63 74 72 61 6c 20 63 6c 75 73 74 65 72 69 6e 67 20 6f 66 20 67 72 61	....."Spectral.clustering.of.gra
13c0	70 68 73 20 77 69 74 68 20 74 68 65 20 62 65 74 68 65 20 68 65 73 73 69 61 6e 22 2c 0a 20 20 20	phs.with.the.bethe.hessian",....
13e0	20 20 20 20 41 64 76 61 6e 63 65 73 20 69 6e 20 4e 65 75 72 61 6c 20 49 6e 66 6f 72 6d 61 74 69	....Advances.in.Neural.Informati
1400	6f 6e 20 50 72 6f 63 65 73 73 69 6e 67 20 53 79 73 74 65 6d 73 2e 20 32 30 31 34 2e 0a 20 20 20	on.Processing.Systems..2014.....
1420	20 72 02 00 00 00 4e 29 06 72 0c 00 00 00 72 0d 00 00 00 72 0e 00 00 00 72 0f 00 00 00 da 14 62	.r....N).r....r....r....r......b
1440	65 74 68 65 5f 68 65 73 73 69 61 6e 5f 6d 61 74 72 69 78 72 11 00 00 00 29 03 72 13 00 00 00 da	ethe_hessian_matrixr....).r.....
1460	01 72 72 14 00 00 00 73 03 00 00 00 20 20 20 72 15 00 00 00 72 07 00 00 00 72 07 00 00 00 9d 00	.rr....s.......r....r....r......
1480	00 00 73 32 00 00 00 80 00 f3 36 00 05 17 e0 0b 0d 8f 39 89 39 d7 0b 1d d1 0b 1d 9c 62 d7 1e 35	..s2......6.......9.9.......b..5
14a0	d1 1e 35 b0 61 b8 11 d3 1e 3b d7 1e 43 d1 1e 43 d3 1e 45 d3 0b 46 d0 04 46 72 16 00 00 00 72 0b	..5.a....;..C..C..E..F..Fr....r.
14c0	00 00 00 29 01 4e 29 0a da 07 5f 5f 64 6f 63 5f 5f da 08 6e 65 74 77 6f 72 6b 78 72 0f 00 00 00	...).N)...__doc__..networkxr....
14e0	da 07 5f 5f 61 6c 6c 5f 5f da 0d 5f 64 69 73 70 61 74 63 68 61 62 6c 65 72 03 00 00 00 72 06 00	..__all__.._dispatchabler....r..
1500	00 00 72 04 00 00 00 72 05 00 00 00 72 07 00 00 00 a9 00 72 16 00 00 00 72 15 00 00 00 fa 08 3c	..r....r....r......r....r......<
1520	6d 6f 64 75 6c 65 3e 72 28 00 00 00 01 00 00 00 73 b5 00 00 00 f0 03 01 01 01 f1 02 02 01 04 f3	module>r(.......s...............
1540	08 00 01 16 f2 04 06 0b 02 80 07 f0 12 00 02 12 80 12 d7 01 11 d1 01 11 98 58 d4 01 26 f2 02 28	.........................X..&..(
1560	01 4f 01 f3 03 00 02 27 f0 02 28 01 4f 01 f0 56 01 00 02 12 80 12 d7 01 11 d1 01 11 98 58 d4 01	.O.....'..(.O..V.............X..
1580	26 f2 02 1e 01 06 f3 03 00 02 27 f0 02 1e 01 06 f0 42 01 00 02 12 80 12 d7 01 11 d1 01 11 98 58	&.........'......B.............X
15a0	d4 01 26 f2 02 1c 01 4e 01 f3 03 00 02 27 f0 02 1c 01 4e 01 f0 3e 00 02 04 d7 01 11 d1 01 11 f1	..&....N.....'....N..>..........
15c0	02 1b 01 3a f3 03 00 02 12 f0 02 1b 01 3a f0 3c 00 02 04 d7 01 11 d1 01 11 f2 02 1c 01 47 01 f3	...:.........:.<.............G..
15e0	03 00 02 12 f1 02 1c 01 47 01 72 16 00 00 00	........G.r....