[+] A3 Starter Files

2022-03-12 18:11:54 -05:00
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+"""CSC111 Winter 2022 Assignment 3: Graphs, Recommender Systems, and Clustering (Visualization)
+
+Module Description
+==================
+
+This module contains some Python functions that you can use to visualize the graphs
+you're working with on this assignment. You should not modify anything in this file.
+It will not be submitted for grading.
+
+Disclaimer: we didn't have time to make this file fully PythonTA-compliant!
+
+Copyright and Usage Information
+===============================
+
+This file is provided solely for the personal and private use of students
+taking CSC111 at the University of Toronto St. George campus. All forms of
+distribution of this code, whether as given or with any changes, are
+expressly prohibited. For more information on copyright for CSC111 materials,
+please consult our Course Syllabus.
+
+This file is Copyright (c) 2022 Mario Badr, David Liu, and Isaac Waller.
+"""
+import networkx as nx
+from plotly.graph_objs import Scatter, Figure
+
+import a3_part1
+
+
+# Colours to use when visualizing different clusters.
+COLOUR_SCHEME = [
+    '#2E91E5', '#E15F99', '#1CA71C', '#FB0D0D', '#DA16FF', '#222A2A', '#B68100',
+    '#750D86', '#EB663B', '#511CFB', '#00A08B', '#FB00D1', '#FC0080', '#B2828D',
+    '#6C7C32', '#778AAE', '#862A16', '#A777F1', '#620042', '#1616A7', '#DA60CA',
+    '#6C4516', '#0D2A63', '#AF0038'
+]
+
+LINE_COLOUR = 'rgb(210,210,210)'
+VERTEX_BORDER_COLOUR = 'rgb(50, 50, 50)'
+BOOK_COLOUR = 'rgb(89, 205, 105)'
+USER_COLOUR = 'rgb(105, 89, 205)'
+
+
+def visualize_graph(graph: a3_part1.Graph,
+                    layout: str = 'spring_layout',
+                    max_vertices: int = 5000,
+                    output_file: str = '') -> None:
+    """Use plotly and networkx to visualize the given graph.
+
+    Optional arguments:
+        - layout: which graph layout algorithm to use
+        - max_vertices: the maximum number of vertices that can appear in the graph
+        - output_file: a filename to save the plotly image to (rather than displaying
+            in your web browser)
+    """
+    graph_nx = graph.to_networkx(max_vertices)
+
+    pos = getattr(nx, layout)(graph_nx)
+
+    x_values = [pos[k][0] for k in graph_nx.nodes]
+    y_values = [pos[k][1] for k in graph_nx.nodes]
+    labels = list(graph_nx.nodes)
+    kinds = [graph_nx.nodes[k]['kind'] for k in graph_nx.nodes]
+
+    colours = [BOOK_COLOUR if kind == 'book' else USER_COLOUR for kind in kinds]
+
+    x_edges = []
+    y_edges = []
+    for edge in graph_nx.edges:
+        x_edges += [pos[edge[0]][0], pos[edge[1]][0], None]
+        y_edges += [pos[edge[0]][1], pos[edge[1]][1], None]
+
+    trace3 = Scatter(x=x_edges,
+                     y=y_edges,
+                     mode='lines',
+                     name='edges',
+                     line=dict(color=LINE_COLOUR, width=1),
+                     hoverinfo='none',
+                     )
+    trace4 = Scatter(x=x_values,
+                     y=y_values,
+                     mode='markers',
+                     name='nodes',
+                     marker=dict(symbol='circle-dot',
+                                 size=5,
+                                 color=colours,
+                                 line=dict(color=VERTEX_BORDER_COLOUR, width=0.5)
+                                 ),
+                     text=labels,
+                     hovertemplate='%{text}',
+                     hoverlabel={'namelength': 0}
+                     )
+
+    data1 = [trace3, trace4]
+    fig = Figure(data=data1)
+    fig.update_layout({'showlegend': False})
+    fig.update_xaxes(showgrid=False, zeroline=False, visible=False)
+    fig.update_yaxes(showgrid=False, zeroline=False, visible=False)
+
+    if output_file == '':
+        fig.show()
+    else:
+        fig.write_image(output_file)
+
+
+def visualize_graph_clusters(graph: a3_part1.Graph, clusters: list[set],
+                             layout: str = 'spring_layout',
+                             max_vertices: int = 5000,
+                             output_file: str = '') -> None:
+    """Visualize the given graph, using different colours to illustrate the different clusters.
+
+    Hides all edges that go from one cluster to another. (This helps the graph layout algorithm
+    positions vertices in the same cluster close together.)
+
+    Same optional arguments as visualize_graph (see that function for details).
+    """
+    graph_nx = graph.to_networkx(max_vertices)
+    all_edges = list(graph_nx.edges)
+    for edge in all_edges:
+        # Check if edge is within the same cluster
+        if any((edge[0] in cluster) != (edge[1] in cluster) for cluster in clusters):
+            graph_nx.remove_edge(edge[0], edge[1])
+
+    pos = getattr(nx, layout)(graph_nx)
+
+    x_values = [pos[k][0] for k in graph_nx.nodes]
+    y_values = [pos[k][1] for k in graph_nx.nodes]
+    labels = list(graph_nx.nodes)
+
+    colors = []
+    for k in graph_nx.nodes:
+        for i, c in enumerate(clusters):
+            if k in c:
+                colors.append(COLOUR_SCHEME[i % len(COLOUR_SCHEME)])
+                break
+        else:
+            colors.append(BOOK_COLOUR)
+
+    x_edges = []
+    y_edges = []
+    for edge in graph_nx.edges:
+        x_edges += [pos[edge[0]][0], pos[edge[1]][0], None]
+        y_edges += [pos[edge[0]][1], pos[edge[1]][1], None]
+
+    trace3 = Scatter(x=x_edges,
+                     y=y_edges,
+                     mode='lines',
+                     name='edges',
+                     line=dict(color=LINE_COLOUR, width=1),
+                     hoverinfo='none'
+                     )
+    trace4 = Scatter(x=x_values,
+                     y=y_values,
+                     mode='markers',
+                     name='nodes',
+                     marker=dict(symbol='circle-dot',
+                                 size=5,
+                                 color=colors,
+                                 line=dict(color=VERTEX_BORDER_COLOUR, width=0.5)
+                                 ),
+                     text=labels,
+                     hovertemplate='%{text}',
+                     hoverlabel={'namelength': 0}
+                     )
+
+    data1 = [trace3, trace4]
+    fig = Figure(data=data1)
+    fig.update_layout({'showlegend': False})
+    fig.update_xaxes(showgrid=False, zeroline=False, visible=False)
+    fig.update_yaxes(showgrid=False, zeroline=False, visible=False)
+    fig.show()
+
+    if output_file == '':
+        fig.show()
+    else:
+        fig.write_image(output_file)