Node properties

There are various possabilities to customize the network using the node properties function d3graph.d3graph.d3graph.set_node_properties(). Intially, all default node properties are created which can than be customized. The underneath properties can be changed for each node. I will use the karate network to demonstrate the working.

Note

• 1. Node label

• 1. Node tooltip

• 3. Node color

• 4. Node size

• 5. Node opacity

• 6. Node edge color

• 7. Node fontcolor

• 8. Node fontsize

• 9. Node edge size

Node label

Lets change the node labels from the karate example into something more meaningfull.

# Import library
from d3graph import d3graph
# Initialization
d3 = d3graph()
# Load karate example
adjmat, df = d3.import_example('karate')
# Process the adjacency matrix
d3.graph(adjmat)

# Set node properties
d3.set_node_properties(label=df['label'].values)

# Plot
d3.show()

Tooltips

Getting more information when hovering over a node can be easily done using the tooltip parameter.

# Import library
from d3graph import d3graph
# Initialization
d3 = d3graph()
# Load karate example
adjmat, df = d3.import_example('karate')
# Process the adjacency matrix
d3.graph(adjmat)

# Set node properties
tooltip = '\nId: ' + adjmat.columns.astype(str) +'\nDegree: ' + df['degree'].astype(str) + '\nLabel: ' + df['label'].values
tooltip = tooltip.values
label = df['label'].values

# Set node properties
d3.set_node_properties(label=label, tooltip=tooltip, color=label, size='degree')
d3.show()

# If you want thinner lines
d3.set_node_properties(label=label, tooltip=tooltip, color=label, size='degree', minmax=[0.1, 15])
d3.show()

Node color

Lets change the node colors from the karate example using the label information. We do not need to re-initialize the whole graph but we can simply update the node properties.

# Set node properties
d3.set_node_properties(label=df['label'].values, color=df['label'].values)

# Plot
d3.show()

Node color on clustering

We can also change the node color on the clustering.

# Set node properties
d3.set_node_properties(label=df['label'].values, color='cluster')

# Plot
d3.show()

Node fontcolor

Lets change the node font colors and ajust it according to the node color.

# Set node properties
d3.set_node_properties(label=df['label'].values, color='cluster', fontcolor='node_color')

# Plot
d3.show()

Node fontsize

Change the node fontsize and ajust it according to the node color.

d3 = d3graph()
adjmat = d3.import_example('bigbang')

fontsize=np.random.randint(low=6, high=40, size=adjmat.shape[0])
d3.set_node_properties(color='cluster', scaler='minmax', fontcolor='node_color', fontsize=fontsize)

# Plot
d3.show()

Node edge color on clustering

We can also change the node color on the clustering.

# Set node properties
d3.set_node_properties(label=df['label'].values, edge_color='cluster')

# Plot
d3.show()

Node size

Lets change the node size from the karate example using the degree of the network. We do not need to re-initialize the whole graph but we can simply update the node properties.

# Set node properties
d3.set_node_properties(label=df['label'].values, color=df['label'].values, size=df['degree'].values)
# Plot
d3.show()

# Set node properties
d3.set_node_properties(label=df['label'].values, color=df['label'].values, size='degree')
# Plot
d3.show()

Node opacity

We can change the node opacity using the degree of the network. We do not need to re-initialize the whole graph but we can simply update the node properties.

# Set node properties
d3.set_node_properties(opacity='degree', size='degree', color='cluster')

# Plot
d3.show()

Node edge size

Lets change the node edge size from the karate example using the degree of the network. We do not need to re-initialize the whole graph but we can simply update the node properties.

# Set node properties
d3.set_node_properties(label=df['label'].values, color=df['label'].values, size=df['degree'].values, edge_size=df['degree'].values)

# Plot
d3.show()

Node edge color

Lets change the node edge color from the karate example using a specified color. We do not need to re-initialize the whole graph but we can simply update the node properties.

# Set node properties
d3.set_node_properties(label=df['label'].values, color=df['label'].values, size=df['degree'].values, edge_size=df['degree'].values, edge_color='#FFF000')

# Plot
d3.show()

Customize the properties of one specific node

# Import library
from d3graph import d3graph
# Initialization
d3 = d3graph()
# Load karate example
adjmat = d3.import_example('bigbang')
# Process the adjacency matrix
d3.graph(adjmat)

# Examine the node properties
print(d3.node_properties)
# {'Amy': {'label': 'Amy', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'},
# 'Bernadette': {'label': 'Bernadette', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'},
# 'Howard': {'label': 'Howard', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'},
# 'Leonard': {'label': 'Leonard', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'},
# 'Penny': {'label': 'Penny', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'},
# 'Rajesh': {'label': 'Rajesh', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'},
# 'Sheldon': {'label': 'Sheldon', 'color': '#000080', 'size': 10, 'edge_size': 0.1, 'edge_color': '#000000'}}

# Customize the properties of one specific node
d3.node_properties['Penny']['label']='Penny Hofstadter'
d3.node_properties['Penny']['color']='#ffc0cb' # Pink
d3.node_properties['Penny']['size']=20
d3.node_properties['Penny']['edge_size']=5
d3.node_properties['Penny']['edge_color']='#0000ff' # Blue

# Customize a specific edge property
d3.edge_properties['Leonard', 'Penny']['color']='#FF0000' # red

# Print
print(d3.node_properties['Penny'])
# {'label': 'Penny Hofstadter', 'color': '#ffc0cb', 'size': 20, 'edge_size': 5, 'edge_color': '#000000'}

# Plot
d3.show()

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