dgf.plot

dgf.plot.plot_graph

Plots an in-memory graph.

Usage example:

import graphviz

schema = dgf.io.read_schema("path")
graph = dgf.io.tfgnn_graph_to_graph(...)
# Or use the in-memory sampler to generate in_memory_graphb5s.

dot = dgf.plot.plot_graph(graph, schema)
# Display in a colab
dot
# Save to file.
dot.render('in_memory_graph', format='png')

Parameters:

Name	Type	Description	Default
`graph`	`InMemoryGraph`	The `InMemoryGraph` object to plot.	required
`schema`	`GraphSchema`	The `GraphSchema` object describing the graph.	required
`features`	`bool`	If true, display the node and edges features.	`True`

Returns:

Type	Description
`Digraph`	A `graphviz.Digraph` object representing the graph schema.

dgf.plot.plot_nx_graph

Helper function to draw an nx graph.

Parameters:

Name	Type	Description	Default
`g`	`Graph`	The nx graph to draw.	required
`label_name`	`Optional[str]`	The name of the nx node data attribute to use as the name of the node in the visualization. If provided, nodes will be colored according to this label.	`None`
`ax`	`Optional[Axes]`	The matplotlib axes to draw on. If not provided, a new figure and axes will be created.	`None`

dgf.plot.plot_schema

Plots the graphschema's meta-graph (i.e., its nodesets and edgesets).

Usage example:

import graphviz

schema = dgf.io.read_schema("path")
# Or use "dgf.io.tfgnn_schema_to_schema" if you have a TF-GNN schema.

dot = dgf.plot.plot_schema(schema)
# Display in a colab
dot
# Save to file.
dot.render('in_memory_graph', format='png')

Parameters:

Name	Type	Description	Default
`schema`	`GraphSchema`	The `GraphSchema` object to plot.	required
`features`	`bool`	If true, display the node and edges features.	`True`

Returns:

Type	Description
`Digraph`	A `graphviz.Digraph` object representing the graph schema.