from teneto import TenetoWorkflow
twf = TenetoWorkflow()
nodename = 'create_temporalnetwork'
func = 'TemporalNetwork'
twf.add_node(nodename=nodename, func=func)
# Generate network node 1
nodename = 'generatenetwork_lowprob'
func = 'generatenetwork'
params = {
    'networktype': 'rand_binomial',
    'size': (10,5),
    'prob': (0.25,0.25),
    'randomseed': 2019
    }
twf.add_node(nodename, func, params=params)
# Calc temporal degree centrality node
nodename = 'degree_lowprob'
func = 'calc_networkmeasure'
params = {
    'networkmeasure': 'temporal_degree_centrality',
    'calc': 'time'
    }
twf.add_node(nodename, func, params=params)
# Generate network node 2
nodename = 'generatenetwork_highprob'
func = 'generatenetwork'
depends_on = 'create_temporalnetwork'
params = {
    'networktype': 'rand_binomial',
    'size': (10,5),
    'prob': (0.75,0.1),
    'randomseed': 2019
    }
twf.add_node(nodename, func, depends_on, params)
# Calc temporal degree centrality node
nodename = 'degree_highprob'
func = 'calc_networkmeasure'
params = {
    'networkmeasure': 'temporal_degree_centrality',
    'calc': 'time'
    }
twf.add_node(nodename, func, params=params)
fig, ax = twf.make_workflow_figure()
fig.show()