"
]
},
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"source": [
"fig4 = go.Figure(data=[trace7, trace8], layout=layout)\n",
"fig4['layout'].update(width=900, height=900)\n",
"fig4['layout']['annotations'][0]['text'] = annot4\n",
"iplot(fig4)"
]
},
{
"cell_type": "markdown",
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"source": [
"**Conclusion**\n",
"\n",
"The networks defined as instances of the graph classes provided by the three Python packages, and displayed with the same KK layout, are quite different. To avoid any doubt, we instantiated the class `pygraphvix.AGraph`, and the `networkx.Graph` from the same lists of nodes, V, and edges, E, extracted from the `igraph.Graph`.\n",
" \n",
"- Zooming the igraph graph we notice that singleton nodes are located almost circular on an arc of circle\n",
"surrounding most of the complementary nodes.\n",
"\n",
"- The `pygraphviz` `neato` layout seems to display the multi-node connected components in the similar way, but here the singleton nodes are placed around a square, bounding the graph.\n",
"\n",
"- At the first sight the `networkx` with KK layout displays a connected graph. We cannot see any singleton in the graph plot.\n",
"The multi-node connected components are indistinguishable, although the total number of reported connected components is the same as the number found via `igraph`. \n",
"\n",
"- Networkx spring layout generates a disconnected coautorship graph, but the relative position of nodes in connected components is far from looking acceptable, compared with the igraph, respectively the pygraphviz graph."
]
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