remsky/triplex-knowledge-graph-visualizer

1import plotly.graph_objects as go2import networkx as nx3import numpy as np4from bokeh.models import (BoxSelectTool, HoverTool, MultiLine, NodesAndLinkedEdges, 5                          Plot, Range1d, Scatter, TapTool, LabelSet, ColumnDataSource)6from bokeh.palettes import Spectral47from bokeh.plotting import from_networkx8 9def create_graph(entities, relationships):10    G = nx.Graph()11    for entity_id, entity_data in entities.items():12        G.add_node(entity_id, label=f"{entity_data.get('value', 'Unknown')} ({entity_data.get('type', 'Unknown')})")13    14    for source, relation, target in relationships:15        G.add_edge(source, target, label=relation)16    17    return G18 19def improved_spectral_layout(G, scale=1):20    pos = nx.spectral_layout(G)21    # Add some random noise to prevent overlapping22    pos = {node: (x + np.random.normal(0, 0.1), y + np.random.normal(0, 0.1)) for node, (x, y) in pos.items()}23    # Scale the layout24    pos = {node: (x * scale, y * scale) for node, (x, y) in pos.items()}25    return pos26 27def create_bokeh_plot(G, layout_type='spring'):28    plot = Plot(width=600, height=600,29                x_range=Range1d(-1.2, 1.2), y_range=Range1d(-1.2, 1.2))30    plot.title.text = "Knowledge Graph Interaction"31 32    node_hover = HoverTool(tooltips=[("Entity", "@label")])33    edge_hover = HoverTool(tooltips=[("Relation", "@label")])34    plot.add_tools(node_hover, edge_hover, TapTool(), BoxSelectTool())35 36    # Create layout based on layout_type37    if layout_type == 'spring':38        pos = nx.spring_layout(G, k=0.5, iterations=50)39    elif layout_type == 'fruchterman_reingold':40        pos = nx.fruchterman_reingold_layout(G, k=0.5, iterations=50)41    elif layout_type == 'circular':42        pos = nx.circular_layout(G)43    elif layout_type == 'random':44        pos = nx.random_layout(G)45    elif layout_type == 'spectral':46        pos = improved_spectral_layout(G)47    elif layout_type == 'shell':48        pos = nx.shell_layout(G)49    else:50        pos = nx.spring_layout(G, k=0.5, iterations=50)51 52    graph_renderer = from_networkx(G, pos, scale=1, center=(0, 0))53 54    graph_renderer.node_renderer.glyph = Scatter(size=15, fill_color=Spectral4[0])55    graph_renderer.node_renderer.selection_glyph = Scatter(size=15, fill_color=Spectral4[2])56    graph_renderer.node_renderer.hover_glyph = Scatter(size=15, fill_color=Spectral4[1])57 58    graph_renderer.edge_renderer.glyph = MultiLine(line_color="#000", line_alpha=0.9, line_width=3)59    graph_renderer.edge_renderer.selection_glyph = MultiLine(line_color=Spectral4[2], line_width=4)60    graph_renderer.edge_renderer.hover_glyph = MultiLine(line_color=Spectral4[1], line_width=3)61 62    graph_renderer.selection_policy = NodesAndLinkedEdges()63    graph_renderer.inspection_policy = NodesAndLinkedEdges()64 65    plot.renderers.append(graph_renderer)66 67    # Add node labels68    x, y = zip(*graph_renderer.layout_provider.graph_layout.values())69    node_labels = nx.get_node_attributes(G, 'label')70    source = ColumnDataSource({'x': x, 'y': y, 'label': [node_labels[node] for node in G.nodes()]})71    labels = LabelSet(x='x', y='y', text='label', source=source, background_fill_color='white',72                      text_font_size='8pt', background_fill_alpha=0.7)73    plot.renderers.append(labels)74 75    # Add edge labels76    edge_x, edge_y, edge_labels = [], [], []77    for (start_node, end_node, label) in G.edges(data='label'):78        start_x, start_y = graph_renderer.layout_provider.graph_layout[start_node]79        end_x, end_y = graph_renderer.layout_provider.graph_layout[end_node]80        edge_x.append((start_x + end_x) / 2)81        edge_y.append((start_y + end_y) / 2)82        edge_labels.append(label)83 84    edge_label_source = ColumnDataSource({'x': edge_x, 'y': edge_y, 'label': edge_labels})85    edge_labels = LabelSet(x='x', y='y', text='label', source=edge_label_source,86                           background_fill_color='white', text_font_size='8pt',87                           background_fill_alpha=0.7)88    plot.renderers.append(edge_labels)89 90    return plot91 92def create_plotly_plot(G, layout_type='spring'):93    # Create layout based on layout_type94    if layout_type == 'spring':95        pos = nx.spring_layout(G, k=0.5, iterations=50)96    elif layout_type == 'fruchterman_reingold':97        pos = nx.fruchterman_reingold_layout(G, k=0.5, iterations=50)98    elif layout_type == 'circular':99        pos = nx.circular_layout(G)100    elif layout_type == 'random':101        pos = nx.random_layout(G)102    elif layout_type == 'spectral':103        pos = improved_spectral_layout(G)104    elif layout_type == 'shell':105        pos = nx.shell_layout(G)106    else:107        pos = nx.spring_layout(G, k=0.5, iterations=50)108 109    edge_trace = go.Scatter(x=[], y=[], line=dict(width=1, color="#888"), hoverinfo="text", mode="lines", text=[])110    node_trace = go.Scatter(x=[], y=[], mode="markers+text", hoverinfo="text",111                            marker=dict(showscale=True, colorscale="Viridis", reversescale=True, color=[], size=15,112                                        colorbar=dict(thickness=15, title="Node Connections", xanchor="left", titleside="right"),113                                        line_width=2),114                            text=[], textposition="top center")115 116    edge_labels = []117 118    for edge in G.edges():119        x0, y0 = pos[edge[0]]120        x1, y1 = pos[edge[1]]121        edge_trace["x"] += (x0, x1, None)122        edge_trace["y"] += (y0, y1, None)123        124        mid_x, mid_y = (x0 + x1) / 2, (y0 + y1) / 2125        edge_labels.append(go.Scatter(x=[mid_x], y=[mid_y], mode="text", text=[G.edges[edge]["label"]],126                                      textposition="middle center", hoverinfo="none", showlegend=False, textfont=dict(size=8)))127 128    for node in G.nodes():129        x, y = pos[node]130        node_trace["x"] += (x,)131        node_trace["y"] += (y,)132        node_trace["text"] += (G.nodes[node]["label"],)133        node_trace["marker"]["color"] += (len(list(G.neighbors(node))),)134 135    fig = go.Figure(data=[edge_trace, node_trace] + edge_labels,136                    layout=go.Layout(title="Knowledge Graph", titlefont_size=16, showlegend=False, hovermode="closest",137                                     margin=dict(b=20, l=5, r=5, t=40), annotations=[],138                                     xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),139                                     yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),140                                     width=800, height=600))141 142    fig.update_layout(newshape=dict(line_color="#009900"),143                      xaxis=dict(scaleanchor="y", scaleratio=1),144                      yaxis=dict(scaleanchor="x", scaleratio=1))145 146    return fig