viz.poincare – Visualize Poincare embeddings

Utilities for creating 2-D visualizations of Poincare models and Poincare distance heatmaps.

gensim.viz.poincare.poincare_2d_visualization(model, tree, figure_title, num_nodes=50, show_node_labels=())

Create a 2-d plot of the nodes and edges of a 2-d poincare embedding.

  • model (PoincareModel) – The model to visualize, model size must be 2.

  • tree (set) – Set of tuples containing the direct edges present in the original dataset.

  • figure_title (str) – Title of the plotted figure.

  • num_nodes (int or None) – Number of nodes for which edges are to be plotted. If None, all edges are plotted. Helpful to limit this in case the data is too large to avoid a messy plot.

  • show_node_labels (iterable) – Iterable of nodes for which to show labels by default.


Plotly figure that contains plot.

Return type


gensim.viz.poincare.poincare_distance_heatmap(origin_point, x_range=(-1.0, 1.0), y_range=(-1.0, 1.0), num_points=100)

Create a heatmap of Poincare distances from origin_point for each point (x, y), where x and y lie in x_range and y_range respectively, with num_points points chosen uniformly in both ranges.

  • origin_point (tuple (int, int)) – (x, y) from which distances are to be measured and plotted.

  • x_range (tuple (int, int)) – Range for x-axis from which to choose num_points points.

  • y_range (tuple (int, int)) – Range for y-axis from which to choose num_points points.

  • num_points (int) – Number of points to choose from x_range and y_range.


Points outside the unit circle are ignored, since the Poincare distance is defined only for points inside the circle boundaries (exclusive of the boundary).


Plotly figure that contains plot

Return type