Content¶
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nngt.plot.
Animation2d
¶
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nngt.plot.
AnimationNetwork
¶
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nngt.plot.
draw_network
(network, nsize='total-degree', ncolor='group', nshape='o', nborder_color='k', nborder_width=0.5, esize=1.0, ecolor='k', max_nsize=5.0, max_esize=2.0, spatial=True, size=(600, 600), dpi=75)[source]¶ Draw a given graph/network.
Parameters: - network (
Graph
or subclass) – The graph/network to plot. - nsize (float, array of float or string, optional (default: “total-degree”)) – Size of the nodes as a percentage of the canvas length. Otherwise, it can be a string that correlates the size to a node attribute among “in/out/total-degree”, or “betweenness”.
- ncolor (float, array of floats or string, optional (default: 0.5)) – Color of the nodes; if a float in [0, 1], position of the color in the current palette, otherwise a string that correlates the color to a node attribute among “in/out/total-degree”, “betweenness” or “group”.
- nshape (char or array of chars, optional (default: “o”)) – Shape of the nodes (see Matplotlib markers).
- nborder_color (char, float or array, optional (default: “k”)) – Color of the node’s border using predefined Matplotlib colors). or floats in [0, 1] defining the position in the palette.
- nborder_width (float or array of floats, optional (default: 0.5)) – Width of the border in percent of canvas size.
- esize (float, str, or array of floats, optional (default: 0.5)) – Width of the edges in percent of canvas length. Available string values are “betweenness” and “weight”.
- ecolor (char, float or array, optional (default: “k”)) – Edge color.
- max_esize (float, optional (default: 5.)) – If a custom property is entered as esize, this normalizes the edge width between 0. and max_esize.
- spatial (bool, optional (default: True)) – If True, use the neurons’ positions to draw them.
- size (tuple of ints, optional (default: (600,600))) – (width, height) tuple for the canvas size (in px).
- dpi (int, optional (default: 75)) – Resolution (dot per inch).
- network (
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nngt.plot.
degree_distribution
(network, deg_type='total', nodes=None, num_bins=50, use_weights=False, logx=False, logy=False, fignum=None, axis_num=None, colors=None, norm=False, show=True)[source]¶ Plotting the degree distribution of a graph.
Parameters: - graph (
Graph
or subclass) – the graph to analyze. - deg_type (string or tuple, optional (default: “total”)) – type of degree to consider (“in”, “out”, or “total”)
- nodes (list or numpy.array of ints, optional (default: all nodes)) – Restrict the distribution to a set of nodes.
- num_bins (int, optional (default: 50):) – Number of bins used to sample the distribution.
- use_weights (bool, optional (default: False)) – use weighted degrees (do not take the sign into account : only the magnitude of the weights is considered).
- logx (bool, optional (default: False)) – use log-spaced bins.
- logy (bool, optional (default: False)) – use logscale for the degree count.
- fignum (int, optional (default:
None
)) – Index of the figure on which the plot should be drawn (default creates a new figure). - show (bool, optional (default: True)) – Show the Figure right away if True, else keep it warm for later use.
- graph (
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nngt.plot.
betweenness_distribution
(network, btype='both', use_weights=True, nodes=None, logx=False, logy=False, num_nbins=None, num_ebins=None, fignum=None, axis_num=None, colors=None, norm=False, show=True)[source]¶ Plotting the betweenness distribution of a graph.
Parameters: - graph (
Graph
or subclass) – the graph to analyze. - btype (string, optional (default: “both”)) – type of betweenness to display (“node”, “edge” or “both”)
- use_weights (bool, optional (default: True)) – use weighted degrees (do not take the sign into account : all weights are positive).
- nodes (list or numpy.array of ints, optional (default: all nodes)) – Restrict the distribution to a set of nodes (taken into account only for the node attribute).
- logx (bool, optional (default: False)) – use log-spaced bins.
- logy (bool, optional (default: False)) – use logscale for the degree count.
- fignum (int, optional (default: None)) – Number of the Figure on which the plot should appear
- show (bool, optional (default: True)) – Show the Figure right away if True, else keep it warm for later use.
- graph (
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nngt.plot.
node_attributes_distribution
(network, attributes, nodes=None, num_bins=50, show=True)[source]¶ Return node attributes for a set of nodes.
Parameters: - network (
Graph
) – The graph where the nodes belong. - attributes (str or list) – Attributes which should be returned, among: * “betweenness” * “clustering” * “in-degree”, “out-degree”, “total-degree” * “subgraph_centrality” * “b2” (requires NEST) * “firing_rate” (requires NEST)
- nodes (list, optional (default: all nodes)) – Nodes for which the attributes should be returned.
- num_bins (int or list, optional (default: 50)) – Number of bins to plot the distributions. If only one int is provided, it is used for all attributes, otherwize a list containing one int per attribute in attributes is required.
- network (
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nngt.plot.
compare_population_attributes
(network, attributes, nodes=None, reference_nodes=None, num_bins=50, reference_color='gray', title=None, show=True)[source]¶ Compare node attributes between two sets of nodes. Since number of nodes can vary, normalized distributions are used.
Parameters: - network (
Graph
) – The graph where the nodes belong. - attributes (str or list) – Attributes which should be returned, among: * “betweenness” * “clustering” * “in-degree”, “out-degree”, “total-degree” * “subgraph_centrality” * “b2” (requires NEST) * “firing_rate” (requires NEST)
- nodes (list, optional (default: all nodes)) – Nodes for which the attributes should be returned.
- reference_nodes (list, optional (default: all nodes)) – Reference nodes for which the attributes should be returned in order to compare with nodes.
- num_bins (int or list, optional (default: 50)) – Number of bins to plot the distributions. If only one int is provided, it is used for all attributes, otherwize a list containing one int per attribute in attributes is required.
- network (
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nngt.plot.
correlation_to_attribute
(network, reference_attribute, other_attributes, nodes=None, title=None, show=True)[source]¶ For each node plot the value of reference_attributes against each of the other_attributes to check for correlations.
Parameters: - network (
Graph
) – The graph where the nodes belong. - reference_attribute (str or array-like) – Attribute which should serve as reference, among:
- “betweenness”
- “clustering”
- “in-degree”, “out-degree”, “total-degree”
- “subgraph_centrality”
- “b2” (requires NEST)
- “firing_rate” (requires NEST)
- a custom array of values, in which case one entry per node in nodes is required.
- other_attributes (str or list)
- nodes (list, optional (default: all nodes)) – Nodes for which the attributes should be returned.
- network (