face2face.imports.create_network.sliding_time_networks¶

face2face.imports.create_network.sliding_time_networks(Data, slide=1, interval=1000)¶

Create multiple Networkx Graphs and DataFrames

Creating multiple Networkx Graphs and DataFrames based on the given interval and the sliding time interval.

Parameters

Data (Data) – Data Object that contains Tij- and Metadata for a data set.
slide (int) – The time steps in which the intervals should be created.
interval (int) – The interval time in which the networkx Graphs should be splitted.

Returns

network_list (list) – A list of all networkx Graphs for a given interval.
df_list (list) – A list of all dataframes for a given interval.

Examples

>>> attr_list = ["ID", "Age", "Sex"]
>>> test_df = Data(path_tij="face2face/data/Test/tij_test.dat", separator_tij="\t",
>>>                path_meta="face2face/data/Test/meta_test.dat", separator_meta = "\t",
>>>                meta_attr_list=attr_list)
>>> test_network_list, test_df_list = sliding_time_networks(test_df, slide=1/3, interval=2/3)
>>> print(test_df_list[0])
   Time  i  j  TimeGroup
0    20  0  1     0-40.0
1    40  1  2     0-40.0
3    40  1  3     0-40.0
5    40  2  3     0-40.0
>>> print(test_network_list[0].nodes)
[0, 1, 2, 3]
>>> print(test_network_list[0].edges)
[(0, 1), (1, 2), (1, 3), (2, 3)]
>>> print(test_df_list[1])
    Time  i  j  TimeGroup
2     40  1  2  20.0-60.0
4     40  1  3  20.0-60.0
6     40  2  3  20.0-60.0
7     60  4  6  20.0-60.0
9     60  4  7  20.0-60.0
11    60  6  7  20.0-60.0
>>> print(test_network_list[1].nodes)
[1, 2, 3, 4, 6, 7]
>>> print(test_network_list[1].edges)
[(1, 2), (1, 3), (2, 3), (4, 6), (4, 7), (6, 7)]