import networkx as nx
import igviz as ig

G = nx.random_geometric_graph(200, 0.125)
nx.set_node_attributes(G, 3, "prop")
nx.set_edge_attributes(G, 5, "edge_prop")

ig.plot(G)

ig.plot(
    G, # Your graph
    title="My Graph",
    size_method="static", # Makes node sizes the same
    color_method="#ffcccb", # Makes all the node colours black,
    node_text=["prop"], # Adds the 'prop' property to the hover text of the node
    annotation_text="Visualization made by <a href='https://github.com/Ashton-Sidhu/plotly-graph'>igviz</a> & plotly.", # Adds a text annotation to the graph
)

ig.plot(
    G,
    title="My Graph",
    size_method="prop", # Makes node sizes the size of the "prop" property
    color_method="prop", # Colors the nodes based off the "prop" property and a color scale,
    node_text=["prop"], # Adds the 'prop' property to the hover text of the node
)

ig.plot(
    G,
    node_label="prop", # Display the "prop" attribute as a label on the node
    node_label_position="top center", # Display the node label directly above the node
    edge_text=["edge_prop"], # Display the "edge_prop" attribute on hover over the edge
    edge_label="edge_prop", # Display the "edge_prop" attribute on the edge
    edge_label_position="bottom center", # Display the edge label below the edge
)

color_list = []
sizing_list = []

for node in G.nodes():
    size_and_color = G.degree(node) * 3

    color_list.append(size_and_color)
    sizing_list.append(size_and_color)

ig.plot(
    G,
    title="My Graph",
    size_method=sizing_list, # Makes node sizes the size of the "prop" property
    color_method=color_list, # Colors the nodes based off the "prop" property and a color scale,
    node_text=["prop"], # Adds the 'prop' property to the hover text of the node
)

ig.plot(
    G,
    title="My Graph",
    layout="kamada",
)

pos_dict = {
    0: [1, 2], # X, Y coordinates for Node 0
    1: [1.5, 3], # X, Y coordinates for Node 1
    ...
}

nx.set_node_attributes(G, pos_dict, "pos")

ig.plot(
    G
)

def createDiGraph():
    # Create a directed graph (digraph) object; i.e., a graph in which the edges
    # have a direction associated with them.
    G = nx.DiGraph()

    # Add nodes:
    nodes = ['A', 'B', 'C', 'D', 'E']
    G.add_nodes_from(nodes)

    # Add edges or links between the nodes:
    edges = [('A','B'), ('B','C'), ('B', 'D'), ('D', 'E')]
    G.add_edges_from(edges)
    return G

DG = createDiGraph()

ig.plot(DG, size_method="static")

MG = nx.MultiGraph()
MG.add_weighted_edges_from([(1, 2, 0.5), (1, 2, 0.75), (2, 3, 0.5)])

ig.plot(
    MG,
    layout="spring",
    size_method="static",
    edge_text=["weight"],
    colorscale="Rainbow"
)