"""This module contains functions to generate networks and save them to files."""
from bindings import seldoncore
import logging
import bindings
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
[docs]
def generate_n_connections(model_string, n_agents:int, n_connections:int, self_interaction:bool= False, rng_seed:int=None):
"""
Generate n_connections Network for n_agents.
Parameters
-----------
model_string : str
The model string. Allowed values are "DeGroot", "Deffuant", "DeffuantVector", "ActivityDriven", "Inertial", "Float".
n_agents : int
The number of agents.
n_connections : int
The number of connections.
self_interaction : bool, default=False
If True, self iteraction is allowed.
rng_seed : int, default=None
The seed for the random number generator. If not provided, a random seed is picked.
Returns
-----------
Network: The network.
"""
if model_string == "DeGroot" or model_string == "Deffuant":
if rng_seed is not None:
return seldoncore.generate_n_connections_simple_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction,seed = rng_seed)
else:
return seldoncore.generate_n_connections_simple_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction)
elif model_string == "DeffuantVector":
if rng_seed is not None:
return seldoncore.generate_n_connections_discrete_vector_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction,seed = rng_seed)
else:
return seldoncore.generate_n_connections_discrete_vector_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction)
elif model_string == "ActivityDriven":
if rng_seed is not None:
return seldoncore.generate_n_connections_activity_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction,seed = rng_seed)
else:
return seldoncore.generate_n_connections_activity_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction)
elif model_string == "Inertial":
if rng_seed is not None:
return seldoncore.generate_n_connections_inertial_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction,seed = rng_seed)
else:
return seldoncore.generate_n_connections_inertial_agent(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction)
elif model_string == "Float":
if rng_seed is not None:
return seldoncore.generate_n_connections_(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction,seed = rng_seed)
else:
return seldoncore.generate_n_connections_(n_agents= n_agents,n_connections = n_connections,self_interaction = self_interaction)
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def generate_fully_connected(model_string, n_agents:int, weight:float= None, rng_seed:int=None):
"""
Generate a fully connected Network for n_agents.
Parameters
-----------
model_string : str
The model string. Allowed values are "DeGroot", "Deffuant", "DeffuantVector", "ActivityDriven", "Inertial", "Float".
n_agents : int
The number of agents.
weight : float
The weight of the agent.
rng_seed : int, default=None
The seed for the random number generator. If not provided, a random seed is picked.
Returns
-----------
Network: The fully connected network.
"""
if model_string == "DeGroot" or model_string == "Deffuant":
return seldoncore.generate_fully_connected_simple_agent(n_agents= n_agents,weight = weight,seed = rng_seed)
elif model_string == "DeffuantVector":
return seldoncore.generate_fully_connected_discrete_vector_agent(n_agents= n_agents,weight = weight,seed = rng_seed)
elif model_string == "ActivityDriven":
return seldoncore.generate_fully_connected_activity_agent(n_agents= n_agents,weight = weight,seed = rng_seed)
elif model_string == "Inertial":
return seldoncore.generate_fully_connected_inertial_agent(n_agents= n_agents,weight = weight,seed = rng_seed)
elif model_string == "Float":
return seldoncore.generate_fully_connected_(n_agents= n_agents,weight = weight,seed = rng_seed)
[docs]
def generate_square_lattice(model_string, n_edge: int, weight: float):
"""
Generate a square lattice Network.
Parameters
-----------
model_string : str
The model string. Allowed values are "DeGroot", "Deffuant", "DeffuantVector", "ActivityDriven", "Inertial", "Float".
n_edge : int
The number of edges.
weight : float
The weight of the agent.
Returns
-----------
Network: The square lattice network.
"""
if model_string == "DeGroot" or model_string == "Deffuant":
return seldoncore.generate_square_lattice_simple_agent(n_edge= n_edge,weight = weight)
elif model_string == "DeffuantVector":
return seldoncore.generate_square_lattice_discrete_vector_agent(n_edge= n_edge,weight = weight)
elif model_string == "ActivityDriven":
return seldoncore.generate_square_lattice_activity_agent(n_edge= n_edge,weight = weight)
elif model_string == "Inertial":
return seldoncore.generate_square_lattice_inertial_agent(n_edge= n_edge,weight = weight)
elif model_string == "Float":
return seldoncore.generate_square_lattice_(n_edge= n_edge,weight = weight)
[docs]
def generate_network_from_file(model_string,file_path):
"""
Generate a Network from a file.
Parameters
-----------
model_string : str
The model string. Allowed values are "DeGroot", "Deffuant", "DeffuantVector", "ActivityDriven", "Inertial", "Float".
file_path : str
The file path.
Returns
-----------
Network: The network.
"""
if model_string == "DeGroot" or model_string == "Deffuant":
return seldoncore.generate_network_from_file_simple_agent(file_path)
elif model_string == "DeffuantVector":
return seldoncore.generate_network_from_file_discrete_vector_agent(file_path)
elif model_string == "ActivityDriven":
return seldoncore.generate_network_from_file_activity_agent(file_path)
elif model_string == "Inertial":
return seldoncore.generate_network_from_file_inertial_agent(file_path)
elif model_string == "Float":
return seldoncore.generate_network_from_file_(file_path)
[docs]
def network_to_file(network, file_path):
"""
Save the network to a file along with weights.
Parameters
-----------
network : Network
The network.
file_path : str
The file path.
"""
if isinstance(network, bindings.seldoncore.SimpleAgentNetwork):
return network.network_to_file_simple_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.DiscreteVectorAgentNetwork):
return network.network_to_file_discrete_vector_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.ActivityDrivenAgentNetwork):
return network.network_to_file_activity_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.InertialAgentNetwork):
return network.network_to_file_inertial_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.Network):
return network.network_to_file(network, file_path)
else:
raise TypeError("Invalid network type")
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def network_to_dot_file(network, file_path):
"""
Save the network to a dot file. This is a graph description language file.
Parameters
-----------
network : Network
The network.
file_path : str
The file path.
"""
if isinstance(network, bindings.seldoncore.SimpleAgentNetwork):
return network.network_to_dot_file_simple_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.DiscreteVectorAgentNetwork):
return network.network_to_dot_file_discrete_vector_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.ActivityDrivenAgentNetwork):
return network.network_to_dot_file_activity_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.InertialAgentNetwork):
return network.network_to_dot_file_inertial_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.Network):
return network.network_to_dot_file(network, file_path)
else:
raise TypeError("Invalid network type")
[docs]
def agents_from_file(model_string, file_path):
"""
Load agents from a file.
Parameters
-----------
model_string : str
The model string. Allowed values are "DeGroot", "Deffuant", "DeffuantVector", "ActivityDriven", "Inertial", "Float".
file_path : str
The file path.
Returns
-----------
list: The list of agents.
"""
if model_string == "DeGroot" or model_string == "Deffuant":
return seldoncore.agents_from_file_simple_agent(file_path)
elif model_string == "DeffuantVector":
return seldoncore.agents_from_file_discrete_vector_agent(file_path)
elif model_string == "ActivityDriven":
return seldoncore.agents_from_file_activity_agent(file_path)
elif model_string == "Inertial":
return seldoncore.agents_from_file_inertial_agent(file_path)
elif model_string == "Float":
return seldoncore.agents_from_file(file_path)
else:
raise TypeError("Invalid model string")
[docs]
def agents_to_file(network, file_path):
"""
Save agents to a file.
Parameters
-----------
network : Network
The network.
file_path : str
The file path.
"""
if isinstance(network, bindings.seldoncore.SimpleAgentNetwork):
return network.agents_to_file_simple_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.DiscreteVectorAgentNetwork):
return network.agents_to_file_discrete_vector_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.ActivityDrivenAgentNetwork):
return network.agents_to_file_activity_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.InertialAgentNetwork):
return network.agents_to_file_inertial_agent(network, file_path)
elif isinstance(network, bindings.seldoncore.Network):
return network.agents_to_file(network, file_path)
else:
raise TypeError("Invalid network type")
