Tuto test

>>> import networkx as nx
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> import pandas as pd
>>>
>>> from phasik.classes import TemporalNetwork

Title

Test text

>>> # generate static network
>>> N = 4
>>> p = 0.7
>>> static_network = nx.erdos_renyi_graph(N, p)
>>>
>>> N_edges = static_network.number_of_edges()
>>>
>>> # relabel nodes with strings
>>> node_labels = ['a', 'b', 'c', 'd']
>>> mapping = {i : x for i,x in enumerate(node_labels)}
>>> static_network = nx.relabel_nodes(static_network, mapping)
>>>
>>> nx.draw_networkx(static_network)
>>> plt.show()

(png, hires.png, pdf)

>>> # def str_name(name) :
>>> #     return '-'.join(name)
>>>
>>> # edges_labels = [str_name(edge) for edge in static_network.edges()]

>>> T = 10
>>> node_series = np.random.random((T, N))

>>> node_table = pd.DataFrame(node_series, columns=node_labels)
>>> node_table

	a	b	c	d
0	0.541966	0.823289	0.234176	0.146126
1	0.127284	0.304599	0.541704	0.603139
2	0.793611	0.923618	0.211838	0.523801
3	0.817821	0.346724	0.574949	0.921824
4	0.917800	0.182292	0.633973	0.991735
5	0.593825	0.246298	0.425232	0.668774
6	0.238783	0.191160	0.221105	0.287929
7	0.900313	0.945168	0.070468	0.284179
8	0.161511	0.577583	0.410588	0.288009
9	0.672275	0.104990	0.357841	0.538351

>>> node_table.plot()
>>> plt.xlabel("Time")
>>> plt.ylabel("Edge time series")
>>>
>>> plt.show()

(png, hires.png, pdf)

>>> temporal_network = TemporalNetwork.from_static_network_and_node_table_dataframe(
...     static_network=static_network,
...     node_table=node_table,
...     combine_node_weights=lambda x, y: x*y)
The following edges were not found in the static network (20 edges):
[('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd'), ('a', 'b'), ('c', 'd')]

>>> temporal_network.info()
'4 nodes, 4 edges (of which 4 temporal), over 10 time points.'

>>> # %matplotlib

>>> anim = temporal_network.animate_highlight_temporal(filepath="video.mp4", fps=1)

Using matplotlib backend: Qt5Agg