# Graph Import main classes ```python from hari_plotter import Graph, Dynamics ``` Create Graph ```python H = Graph.strongly_connected_components([10, 10], 10, 3) ``` Get Graph Info ```python print(f"{H = }") print(f"{H.mean_opinion = }") ``` H = H.mean_opinion = 3.039989236795545 Get the information about parameters available for gathering ```python H.gatherer.node_parameters ``` ['Opinion', 'Opinion density', 'Cluster size', 'Importance', 'Neighbor mean opinion', 'Inner opinions', 'Max opinion', 'Min opinion', 'Opinion Standard Deviation', 'Label', 'Type'] Get the node parameters ```python H.gatherer.gather(["Cluster size", "Opinion"]) ``` {'Nodes': [(0,), (1,), (2,), (3,), (4,), (5,), (6,), (7,), (8,), (9,), (10,), (11,), (12,), (13,), (14,), (15,), (16,), (17,), (18,), (19,)], 'Cluster size': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 'Opinion': [1.874213762484462, 1.9797692699253586, 1.9864728476689875, 2.0039220965041564, 2.0122373057404292, 2.0393409858053184, 2.0595745641582326, 2.101099281488391, 2.1243752247086394, 2.2051583723503527, 3.8754472569677465, 3.8934247681969056, 3.9037741673809077, 4.029159827368202, 4.050855128109916, 4.063263981030825, 4.080563322149777, 4.125622363739476, 4.1870486600547645, 4.204461550078053]} Read the graph from Network ```python H = Graph.read_network("../tests/network.txt", "../tests/opinions_0.txt") print(f"{H = }") ``` H = Read Dynamics from Network ```python HD = Dynamics.read_network( "../tests/5_ring/network.txt", [f"../tests/5_ring/opinions_{i}.txt" for i in range(3)], ) print(f"{HD = }") ``` HD =