Source code for kmapper.drawing

    Methods for drawing graphs


import numpy as np

__all__ = ["draw_matplotlib"]

[docs]def draw_matplotlib(g, ax=None, fig=None, layout="kk"): """Draw the graph using NetworkX drawing functionality. Parameters ------------ g: graph object returned by ``map`` The Mapper graph as constructed by ```` ax: matplotlib Axes object A matplotlib axes object to plot graph on. If none, then use ``plt.gca()`` fig: matplotlib Figure object A matplotlib Figure object to plot graph on. If none, then use ``plt.figure()`` layout: string Key for which of NetworkX's layout functions. Key options implemented are: :: >>> "kk": nx.kamada_kawai_layout, >>> "spring": nx.spring_layout, >>> "bi": nx.bipartite_layout, >>> "circ": nx.circular_layout, >>> "spect": nx.spectral_layout Returns -------- nodes: nx node set object list List of nodes constructed with Networkx ``draw_networkx_nodes``. This can be used to further customize node attributes. """ import networkx as nx import os # import matplotlib as mpl if os.environ.get("DISPLAY", "") == "": print("no display found. Using non-interactive Agg backend") mpl.use("Agg") import matplotlib.pyplot as plt fig = fig if fig else plt.figure() ax = ax if ax else plt.gca() if not isinstance(g, nx.Graph): from .adapter import to_networkx g = to_networkx(g) # Determine a fine size for nodes bbox = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted()) width, height = bbox.width, bbox.height area = width * height * fig.dpi n_nodes = len(g.nodes) # size of node should be related to area and number of nodes -- heuristic node_size = np.pi * area / n_nodes node_r = np.sqrt(node_size / np.pi) node_edge = node_r / 3 layouts = { "kk": nx.kamada_kawai_layout, "spring": nx.spring_layout, "bi": nx.bipartite_layout, "circ": nx.circular_layout, "spect": nx.spectral_layout, } pos = layouts[layout](g) nodes = nx.draw_networkx_nodes(g, node_size=node_size, pos=pos, ax=ax) edges = nx.draw_networkx_edges(g, pos=pos, ax=ax) nodes.set_edgecolor("w") nodes.set_linewidth(node_edge) ax.axis("square") ax.axis("off") return nodes