MstrPikachu
176 lines
6.2 KiB
Python
176 lines
6.2 KiB
Python
"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Visualization)
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Module Description
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==================
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This module contains some Python functions that you can use to visualize the graphs
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you're working with on this assignment. You should not modify anything in this file.
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It will not be submitted for grading.
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Disclaimer: we didn't have time to make this file fully PythonTA-compliant!
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Copyright and Usage Information
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===============================
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This file is provided solely for the personal and private use of students
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taking CSC111 at the University of Toronto St. George campus. All forms of
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distribution of this code, whether as given or with any changes, are
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expressly prohibited. For more information on copyright for CSC111 materials,
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please consult our Course Syllabus.
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This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
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"""
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import networkx as nx
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from plotly.graph_objs import Scatter, Figure
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import a3_part1
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# Colours to use when visualizing different clusters.
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COLOUR_SCHEME = [
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'#2E91E5', '#E15F99', '#1CA71C', '#FB0D0D', '#DA16FF', '#222A2A', '#B68100',
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'#750D86', '#EB663B', '#511CFB', '#00A08B', '#FB00D1', '#FC0080', '#B2828D',
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'#6C7C32', '#778AAE', '#862A16', '#A777F1', '#620042', '#1616A7', '#DA60CA',
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'#6C4516', '#0D2A63', '#AF0038'
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]
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LINE_COLOUR = 'rgb(210,210,210)'
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VERTEX_BORDER_COLOUR = 'rgb(50, 50, 50)'
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BOOK_COLOUR = 'rgb(89, 205, 105)'
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USER_COLOUR = 'rgb(105, 89, 205)'
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def visualize_graph(graph: a3_part1.Graph,
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layout: str = 'spring_layout',
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max_vertices: int = 5000,
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output_file: str = '') -> None:
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"""Use plotly and networkx to visualize the given graph.
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Optional arguments:
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- layout: which graph layout algorithm to use
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- max_vertices: the maximum number of vertices that can appear in the graph
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- output_file: a filename to save the plotly image to (rather than displaying
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in your web browser)
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"""
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graph_nx = graph.to_networkx(max_vertices)
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pos = getattr(nx, layout)(graph_nx)
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x_values = [pos[k][0] for k in graph_nx.nodes]
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y_values = [pos[k][1] for k in graph_nx.nodes]
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labels = list(graph_nx.nodes)
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kinds = [graph_nx.nodes[k]['kind'] for k in graph_nx.nodes]
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colours = [BOOK_COLOUR if kind == 'book' else USER_COLOUR for kind in kinds]
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x_edges = []
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y_edges = []
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for edge in graph_nx.edges:
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x_edges += [pos[edge[0]][0], pos[edge[1]][0], None]
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y_edges += [pos[edge[0]][1], pos[edge[1]][1], None]
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trace3 = Scatter(x=x_edges,
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y=y_edges,
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mode='lines',
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name='edges',
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line=dict(color=LINE_COLOUR, width=1),
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hoverinfo='none',
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)
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trace4 = Scatter(x=x_values,
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y=y_values,
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mode='markers',
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name='nodes',
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marker=dict(symbol='circle-dot',
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size=5,
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color=colours,
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line=dict(color=VERTEX_BORDER_COLOUR, width=0.5)
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),
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text=labels,
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hovertemplate='%{text}',
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hoverlabel={'namelength': 0}
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)
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data1 = [trace3, trace4]
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fig = Figure(data=data1)
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fig.update_layout({'showlegend': False})
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fig.update_xaxes(showgrid=False, zeroline=False, visible=False)
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fig.update_yaxes(showgrid=False, zeroline=False, visible=False)
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if output_file == '':
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fig.show()
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else:
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fig.write_image(output_file)
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def visualize_graph_clusters(graph: a3_part1.Graph, clusters: list[set],
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layout: str = 'spring_layout',
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max_vertices: int = 5000,
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output_file: str = '') -> None:
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"""Visualize the given graph, using different colours to illustrate the different clusters.
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Hides all edges that go from one cluster to another. (This helps the graph layout algorithm
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positions vertices in the same cluster close together.)
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Same optional arguments as visualize_graph (see that function for details).
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"""
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graph_nx = graph.to_networkx(max_vertices)
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all_edges = list(graph_nx.edges)
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for edge in all_edges:
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# Check if edge is within the same cluster
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if any((edge[0] in cluster) != (edge[1] in cluster) for cluster in clusters):
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graph_nx.remove_edge(edge[0], edge[1])
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pos = getattr(nx, layout)(graph_nx)
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x_values = [pos[k][0] for k in graph_nx.nodes]
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y_values = [pos[k][1] for k in graph_nx.nodes]
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labels = list(graph_nx.nodes)
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colors = []
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for k in graph_nx.nodes:
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for i, c in enumerate(clusters):
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if k in c:
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colors.append(COLOUR_SCHEME[i % len(COLOUR_SCHEME)])
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break
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else:
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colors.append(BOOK_COLOUR)
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x_edges = []
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y_edges = []
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for edge in graph_nx.edges:
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x_edges += [pos[edge[0]][0], pos[edge[1]][0], None]
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y_edges += [pos[edge[0]][1], pos[edge[1]][1], None]
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trace3 = Scatter(x=x_edges,
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y=y_edges,
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mode='lines',
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name='edges',
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line=dict(color=LINE_COLOUR, width=1),
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hoverinfo='none'
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)
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trace4 = Scatter(x=x_values,
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y=y_values,
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mode='markers',
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name='nodes',
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marker=dict(symbol='circle-dot',
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size=5,
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color=colors,
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line=dict(color=VERTEX_BORDER_COLOUR, width=0.5)
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),
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text=labels,
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hovertemplate='%{text}',
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hoverlabel={'namelength': 0}
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)
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data1 = [trace3, trace4]
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fig = Figure(data=data1)
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fig.update_layout({'showlegend': False})
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fig.update_xaxes(showgrid=False, zeroline=False, visible=False)
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fig.update_yaxes(showgrid=False, zeroline=False, visible=False)
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fig.show()
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if output_file == '':
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fig.show()
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else:
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fig.write_image(output_file)
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