Source code for raphtory.export

  1"""
  2Generate a visualisation using matplotlib or pyvis from Raphtory graphs.
  3"""
  4from pyvis.network import Network
  5import networkx as nx
  6import pandas as pd
  7
  8
[docs] 9def to_pyvis( 10 graph, 11 explode_edges=False, 12 edge_color="#000000", 13 shape=None, 14 node_image=None, 15 edge_weight=None, 16 edge_label=None, 17 colour_nodes_by_type=False, 18 type_property="type", 19 notebook=True, 20 **kwargs, 21): 22 r"""Draw a graph with Pyvis. 23 24 .. note:: 25 26 Pyvis is a required dependency. 27 If you intend to use this function make sure that 28 you install Pyvis with ``pip install pyvis`` 29 30 :param graph: A Raphtory graph. 31 :param explode_edges: A boolean that is set to True if you want to explode the edges in the graph. By default this is set to False. 32 :param str edge_color: A string defining the colour of the edges in the graph. By default ``#000000`` (black) is set. 33 :param str shape: An optional string defining what the node looks like. 34 There are two types of nodes. One type has the label inside of it and the other type has the label underneath it. 35 The types with the label inside of it are: ellipse, circle, database, box, text. 36 The ones with the label outside of it are: image, circularImage, diamond, dot, star, triangle, triangleDown, square and icon. 37 By default ``"dot"`` is set. 38 :param str node_image: An optional string defining the url of a custom node image. By default an image of a circle is set. 39 :param str edge_weight: An optional string defining the name of the property where edge weight is set on your Raphtory graph. By default ``1`` is set. 40 :param str edge_label: An optional string defining the name of the property where edge label is set on your Raphtory graph. By default, an empty string as the label is set. 41 :param bool notebook: A boolean that is set to True if using jupyter notebook. By default this is set to True. 42 :param kwargs: Additional keyword arguments that are passed to the pyvis Network class. 43 44 :returns: A pyvis network 45 46 For Example: 47 48 .. code-block:: python 49 50 from raphtory import Graph 51 from raphtory import export 52 53 g = Graph() 54 g.add_vertex(1, src, properties={"image": "image.png"}) 55 g.add_edge(1, 1, 2, {"title": "edge", "weight": 1}) 56 g.add_edge(1, 2, 1, {"title": "edge", "weight": 3}) 57 58 export.to_pyvis(graph=g, edge_color="#FF0000", edge_weight= "weight", shape="image", node_image="image", edge_label="title") 59 60 """ 61 visGraph = Network(notebook=notebook, **kwargs) 62 if colour_nodes_by_type: 63 groups = { 64 value: index + 1 65 for index, value in enumerate( 66 set(graph.vertices.properties.get(type_property)) 67 ) 68 } 69 70 for v in graph.vertices: 71 image = ( 72 v.properties.get(node_image) 73 if node_image != None 74 else "https://cdn-icons-png.flaticon.com/512/7584/7584620.png" 75 ) 76 shape = shape if shape is not None else "dot" 77 if colour_nodes_by_type: 78 visGraph.add_node( 79 v.id, 80 label=v.name, 81 shape=shape, 82 image=image, 83 group=groups[v.properties.get(type_property)], 84 ) 85 else: 86 visGraph.add_node(v.id, label=v.name, shape=shape, image=image) 87 88 edges = graph.edges.explode() if explode_edges else graph.edges.explode_layers() 89 for e in edges: 90 weight = e.properties.get(edge_weight) if edge_weight is not None else 1 91 if weight is None: 92 weight = 1 93 label = e.properties.get(edge_label) if edge_label is not None else "" 94 if label is None: 95 label = "" 96 visGraph.add_edge( 97 e.src.id, 98 e.dst.id, 99 value=weight, 100 color=edge_color, 101 title=label, 102 arrowStrikethrough=False, 103 ) 104 105 return visGraph
106 107
[docs] 108def to_networkx( 109 graph, 110 explode_edges=False, 111 include_vertex_properties=True, 112 include_edge_properties=True, 113 include_update_history=True, 114 include_property_histories=True, 115): 116 r"""Returns a graph with NetworkX. 117 118 .. note:: 119 120 Network X is a required dependency. 121 If you intend to use this function make sure that 122 you install Network X with ``pip install networkx`` 123 124 :param Graph graph: A Raphtory graph. 125 :param bool explode_edges: A boolean that is set to True if you want to explode the edges in the graph. By default this is set to False. 126 :param bool include_vertex_properties: A boolean that is set to True if you want to include the vertex properties in the graph. By default this is set to True. 127 :param bool include_edge_properties: A boolean that is set to True if you want to include the edge properties in the graph. By default this is set to True. 128 :param bool include_update_history: A boolean that is set to True if you want to include the update histories in the graph. By default this is set to True. 129 :param bool include_property_histories: A boolean that is set to True if you want to include the histories in the graph. By default this is set to True. 130 131 :returns: A Networkx MultiDiGraph. 132 """ 133 134 networkXGraph = nx.MultiDiGraph() 135 136 vertex_tuples = [] 137 for v in graph.vertices: 138 properties = {} 139 if include_vertex_properties: 140 if include_property_histories: 141 properties.update(v.properties.constant.as_dict()) 142 properties.update(v.properties.temporal.histories()) 143 else: 144 properties = v.properties.as_dict() 145 if include_update_history: 146 properties.update({"update_history": v.history()}) 147 vertex_tuples.append((v.name, properties)) 148 networkXGraph.add_nodes_from(vertex_tuples) 149 150 edge_tuples = [] 151 edges = graph.edges.explode() if explode_edges else graph.edges.explode_layers() 152 for e in edges: 153 properties = {} 154 src = e.src.name 155 dst = e.dst.name 156 if include_edge_properties: 157 if include_property_histories: 158 properties.update(e.properties.constant.as_dict()) 159 properties.update(e.properties.temporal.histories()) 160 else: 161 properties = e.properties.as_dict() 162 layer = e.layer_name 163 if layer is not None: 164 properties.update({"layer": layer}) 165 if include_update_history: 166 if explode_edges: 167 properties.update({"update_history": e.time}) 168 else: 169 properties.update({"update_history": e.history()}) 170 edge_tuples.append((src, dst, properties)) 171 172 networkXGraph.add_edges_from(edge_tuples) 173 174 return networkXGraph
175 176
[docs] 177def to_edge_df( 178 graph, 179 explode_edges=False, 180 include_edge_properties=True, 181 include_update_history=True, 182 include_property_histories=True, 183): 184 r"""Returns an edge list pandas dataframe for the given graph. 185 186 .. note:: 187 188 Pandas is a required dependency. 189 If you intend to use this function make sure that 190 you install pandas with ``pip install pandas`` 191 192 :param Graph graph: A Raphtory graph. 193 :param bool explode_edges: A boolean that is set to True if you want to explode the edges in the graph. By default this is set to False. 194 :param bool include_edge_properties: A boolean that is set to True if you want to include the edge properties in the graph. By default this is set to True. 195 :param bool include_update_history: A boolean that is set to True if you want to include the update histories in the graph. By default this is set to True. 196 :param bool include_property_histories: A boolean that is set to True if you want to include the histories in the graph. By default this is set to True. 197 198 :returns: A pandas dataframe. 199 """ 200 edge_tuples = [] 201 202 columns = ["src", "dst", "layer"] 203 if include_edge_properties: 204 columns.append("properties") 205 if include_update_history: 206 columns.append("update_history") 207 208 edges = graph.edges.explode() if explode_edges else graph.edges.explode_layers() 209 for e in edges: 210 tuple = [e.src.name, e.dst.name, e.layer_name] 211 if include_edge_properties: 212 properties = {} 213 if include_property_histories: 214 properties.update(e.properties.constant.as_dict()) 215 properties.update(e.properties.temporal.histories()) 216 else: 217 properties = e.properties.as_dict() 218 tuple.append(properties) 219 220 if include_update_history: 221 if explode_edges: 222 tuple.append(e.time) 223 else: 224 tuple.append(e.history()) 225 226 edge_tuples.append(tuple) 227 228 return pd.DataFrame(edge_tuples, columns=columns)
229 230
[docs] 231def to_vertex_df( 232 graph, 233 include_vertex_properties=True, 234 include_update_history=True, 235 include_property_histories=True, 236): 237 r"""Returns an vertex list pandas dataframe for the given graph. 238 239 .. note:: 240 241 Pandas is a required dependency. 242 If you intend to use this function make sure that 243 you install pandas with ``pip install pandas`` 244 245 :param Graph graph: A Raphtory graph. 246 :param bool include_vertex_properties: A boolean that is set to True if you want to include the vertex properties in the graph. By default this is set to True. 247 :param bool include_update_history: A boolean that is set to True if you want to include the update histories in the graph. By default this is set to True. 248 :param bool include_property_histories: A boolean that is set to True if you want to include the histories in the graph. By default this is set to True. 249 250 :returns: A pandas dataframe. 251 252 """ 253 vertex_tuples = [] 254 columns = ["id"] 255 if include_vertex_properties: 256 columns.append("properties") 257 if include_update_history: 258 columns.append("update_history") 259 260 for v in graph.vertices: 261 tuple = [v.name] 262 if include_vertex_properties: 263 properties = {} 264 if include_property_histories: 265 properties.update(v.properties.constant.as_dict()) 266 properties.update(v.properties.temporal.histories()) 267 else: 268 properties = v.properties.as_dict() 269 tuple.append(properties) 270 if include_update_history: 271 tuple.append(v.history()) 272 vertex_tuples.append(tuple) 273 return pd.DataFrame(vertex_tuples, columns=columns)