Drawing

Clusters

Useful functions to draw clusters

plot_average_silhouettes(cluster_sets, ax=None)

Plot the average silhouettes across this range of cluster sets

Parameters

• cluster_sets (ClusterSets)

• ax (matplotlib.Axes, optional) – Axes on which to plot

Returns

Return type

None

plot_cluster_set(cluster_set, ax=None, y_height=0, cmap=<matplotlib.colors.ListedColormap object>, number_of_colors=10, colors=None)

Plots this cluster set as a scatter graph

Parameters

• cluster_set

• ax (matplotlib.Axes, optional) – Axes on which to plot

• y_height (int or float, optional) – Height at which to plot (default 0)

• cmap (matplotlib.cm, optional) – Desired colour map (default ‘tab10’)

• number_of_colors (int, optional) – Desired number of colours to use for the colormap (default 10)

Returns

Return type

None

plot_cluster_sets(cluster_sets, axs=None, coloring='consistent', with_silhouettes=False, with_n_clusters=False)

Plot these cluster sets as a scatter graph

Parameters

• cluster_sets (tempnetx ClusterSets)

• axs (matplotlib.Axes, optional) – Matplotlib axes on which to plot

• coloring (str, optional)

• with_silhouettes (bool, optional)

• with_n_clusters (bool, optional)

Returns

Return type

None

plot_ns_clusters(cluster_sets, ax=None)

Plot the average cluster set sizes across this range of cluster sets

Parameters

• cluster_sets (ClusterSets)

• ax (matplotlib.Axes, optional) – Axes on which to plot

Returns

Return type

None

plot_randindex_bars_over_methods_and_sizes(valid_cluster_sets, reference_method='ward', ax=None, plot_ref=False)

Plot Rand Index as bars, to compare any method to a reference method, for all combinations of methods and number of clusters

relabel_clusters_sorted(clusters, final_labels=None)

Returns array of cluster labels sorted in order of appearance, with clusters unchanged

Parameters

• clusters (array of int) – Cluster labels

• final_labels (array of int) – Sorted cluster labels

Example

>>> clusters = np.array([2, 2, 2, 3, 3, 1, 1, 1])
>>> relabel_clusters_sorted(clusters)
[ 1 1 1 2 2 3 3 3 ]

relabel_clustersets(cluster_sets, method='consistent')

Relabels clusters in each cluster set, so that clusters are labeled consistently at different numbers of clusters.

This is especially useful when plotting cluster sets, to have consistent colouring.

Parameters

• cluster_sets (ClusterSets)

• method ({‘consistent’, ‘ascending’})

relabel_next_clusterset_sorted(cluster_sets, cluster_sets_sorted, i)

Relabels the clusters in i+1th cluster set so that it is consistent with ith cluster set

This is especially useful when plotting cluster sets, to have consistent colouring.

Parameters

• cluster_sets (ClusterSets) – Original cluster sets

• cluster_sets_sorted (ClusterSets) – Cluster sets being sorted, already sorted up to i-1

• i (int)

Returns

cluster_sets_sorted

Return type

ClusterSets

Networks

Functions to visualise networks and temporal networks

animate_temporal_network(temporal_network, color_temporal='red', color_constant='silver', width_scale=1.5, with_labels=True, layout=None, ax=None, interval=20, frames=None)

Return animation of the temporal network evolving over time

Parameters

• temporal_network (phasik.TemporalNetwork) – Temporal network to visualise

• color_temporal (str) – Color of the time-varying edges, defaults to ‘red’

• color_constant (str) – Color of the constant edges (defaults to ‘silver’), i.e. for which we have no temporal information

• width_scale (float) – Scale factor for width of the temporal edges compared to the constant ones

• layout (dict) – Dictionary of node positions

• ax (matplotlib.axis) – Axes to plot the animation on

• interval (int) – Interval of time between frames, in ms.

• frames (int) – Number of frames of the animation (should be at most the number of timepoints (default))

Returns

Return type

matplotlib.animation

draw_graph(graph, ax=None, label_nodes=True, color='mediumseagreen', layout=None)

Basic graph drawing function

Parameters

• graph (networkx.Graph) – Graph to visualise

• ax (matplotlib.Axes, optional) – Axes on which to draw the graph

• label_nodes (bool, optional) – Whether to label the nodes or just leave them as small circles (default True)

• color (str, optional) – Color to use for the graph nodes and edges (default ‘mediumseagreen’)

Returns

Return type

None

highlight_subgraphs(graphs, colors, ax=None, layout=None, label_nodes=True)

Draw multiple nested subgraphs on the same axes

Parameters

• graphs (list of networkx.Graph)

• colors (list of str) – List of colors, one for each of the graphs in ‘graphs’

• ax (matplotlib.Axes, optional) – Axes to plot on

• label_nodes (bool, optional) – Whether or not to label the graph nodes or leave them as circles

Returns

Return type

None

standard_edge_params(color)

Returns a dictionary containing standard values of edge plotting parameters

standard_label_params(color)

Returns a dictionary containing standard values of label plotting parameters

standard_node_params(color)

Returns a dictionary containing standard values of node plotting parameters

standard_params(color)

Returns a dictionary containing standard values of plotting parameters

Drawing

Useful drawing functions

plot_events(events, ax=None, text_y_pos=None, text_x_offset=0, period=None, n_periods=1, add_labels=True, orientation='vertical', zorder=- 1, alpha=1, va='bottom')

Plot events as vertical lines on axes

Parameters

• events (list of tuples (time, name, line_style)) – time - time at which the event occurred name - the name of the event line_style - any string accepted by matplotlib.lines.Line2D.set_linestyle

• ax (matplotlib.Axes, optional) – Axes on which to plot the events

• text_y_pos (float, optional) – Height at which to place the name of the event (default None)

• text_x_offset (float, optional) – Distance along x-axis by which to offset the placement of the event name (default 0)

• period (float or None, optional) – Length of time of one period, if events repeat periodically.

• n_periods (int, optional) – Number of periods to draw, if events repeat periodically.

• add_labels (bool, optional) – Wether to display the label of each vertical line, True by default.

Returns

Return type

None

plot_interval(binary_series, times, y=0, peak=None, color='k', ax=None, zorder=0)

Plot a binary series as a sequence of coloured intervals

Specifically, when a binary series has value 1, plot it as a continuous rectangular interval. When it has value 0 do nothing.

Parameters

• binary_series (ndarray) – 2D array of binary data to plot

• times (ndarray) – 1D array consisting of the corresponding time points

• y (float, optional) – Height (y-axis value) at which to plot the interval (default 0)

• color (str, optional) – Color to use for the intervals (default ‘k’)

• ax (matplotlib.Axes, optional) – Axes to plot on

• zorder (int, optional) – Height on the z-axis which to plot the interval (default 0)

Returns

Return type

None

plot_phases(phases, ax=None, y_pos=None, ymin=0, ymax=1, t_offset=0)

Plot phases as shaded regions on axes

Parameters

• phases (list of tuples (start_time, end_time, name))

• ax (matplotlib.Axes) – Axes on which to plot the phases

• y_pos (float or None, optional) – Height at which to place the name of the phase

• ymin (float, optional) – Height at which to start shaded region (default 0)

• ymax (float, optional) – Height at which to stop shaded region (default 1)

• t_offset (float, optional) – Offset of phase on the time axis

Returns

Return type

None

threshold_plot(x, y, threshold, color_below_threshold, color_above_threshold, ax=None)

Plot values above a certain threshold in a particular colour

Parameters

• x (array) – 1D array of alues to plot along x-axis

• y (array) – 1D array of values to plot along y-axis

• threshold (float) – Only plot in colour the points (x,y) with y >= threshold

• colour_below_threshold (str) – Colour to use for points below threshold

• colour_above_threshold (list of str) – Colour to use for points above threshold

• ax (matplotlib.Axes, optional) – Axes to use

Returns

Return type

None

Utils

General utility functions for plots

adjust_margin(ax=None, top=0, bottom=0, left=0, right=0)

Extend the margin of a plot by a percentage of its original width/height

Parameters

• ax (matplotlib.Axes, optional) – Axes whose margins to adjust

• top (float, optional) – Percentage (as decimal) by which to increase top margin

• bottom (float, optional) – Percentage (as decimal) by which to increase bottom margin

• left (float, optional) – Percentage (as decimal) by which to increase left margin

• right (float, optional) – Percentage (as decimal) by which to increase right margin

Returns

Return type

None

configure_sch_color_map(cmap)

Set SciPy’s colour palette to use a particular colour map

display_name(key)

Get more user-friendly name for certain keywords

label_subplot_grid_with_shared_axes(rows, columns, total_subplots, xlabel, ylabel, fig, axes)

Method to tidy up cases where we have a grid of plots with shared axes, by deleting unused subplots (if number of of subplots is not rectangular) and adding axes ticks

Parameters

• rows (int) – Number of rows in the grid of subplots

• columns (int) – Number of columns in the grid of subplots

• total_subplots (int) – Number of subplots in the grid; need not be a ‘rectangular’ number

• xlabel (str) – Label of the x-axis

• ylabel (str) – Label of the y-axis

• fig (matplotlib.Figure) – Figure that the subplots are a part of

• axes (list of matplotlib.Axes) – Axes containing the subplots

Returns

Return type

None