stock-correlations-node_features.py

def assign_colour(correlation):
    if correlation <= 0:
        return "#ffa09b"  # red
    else:
        return "#9eccb7"  # green


def assign_thickness(correlation, benchmark_thickness=2, scaling_factor=3):
    return benchmark_thickness * abs(correlation)**scaling_factor


def assign_node_size(degree, scaling_factor=50):
    return degree * scaling_factor


# assign colours to edges depending on positive or negative correlation
# assign edge thickness depending on magnitude of correlation
edge_colours = []
edge_width = []
for key, value in nx.get_edge_attributes(Gx, 'correlation').items():
    edge_colours.append(assign_colour(value))
    edge_width.append(assign_thickness(value))

# assign node size depending on number of connections (degree)
node_size = []
for key, value in dict(Gx.degree).items():
    node_size.append(assign_node_size(value))