Description Usage Arguments Value Examples

View source: R/SETSe_expanded.R

This is a special case function which keeps the history of the network dynamics. It is useful for demonstrations. or parametrising difficult networks

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
SETSe_expanded(
g,
force = "force",
distance = "distance",
edge_name = "edge_name",
k = "k",
tstep = 0.02,
mass = 1,
max_iter = 20000,
coef_drag = 1,
tol = 1e-06,
sparse = FALSE,
verbose = TRUE,
two_node_solution = TRUE
)
``` |

`g` |
An igraph object. The network |

`force` |
A character string |

`distance` |
A character string. The name of the graph attribute that contains the graph distance |

`edge_name` |
A character string. This is the edge attribute that contains the edge_name of the edges. |

`k` |
A character string. This is k for the moment don't change it. |

`tstep` |
A numeric. The time in seconds that elapses between each iteration |

`mass` |
A numeric. The mass in kg of the nodes, this is arbitrary and commonly 1 is used. |

`max_iter` |
An integer. The maximum number of iterations before terminating the simulation |

`coef_drag` |
A numeric. A multiplier used to tune the damping. Generally no need to twiddle |

`tol` |
A numeric. Early termination. If the dynamics of the nodes fall below this value the algorithm will be classed as "converged" and the simulation terminates. |

`sparse` |
Logical. Whether or not the function should be run using sparse matrices. must match the actual matrix, this could prob be automated |

`verbose` |
Logical value. Whether the function should output messages or run quietly. |

`two_node_solution` |
Logical. The Newton-Raphson algo is used to find the correct angle |

A list of four elements. A dat frame with the height embedding of the network, a data frame of the edge embeddings, the convergence dynamics dataframe for the network as well as the search history for convergence criteria of the network

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
g_prep <- biconnected_network %>%
prepare_SETSe_continuous(., node_names = "name", force_var = "force", k = NULL)
#the base configuration does not work
divergent_result <- SETSe_expanded(g_prep, k = "weight", tstep = 0.1)
#with a smaller timestep the algorithm converges
convergent_result <- SETSe_expanded(g_prep, k = "weight", tstep = 0.01)
## Not run:
library(ggplot2)
#plot the results for a given node
convergent_result %>%
ggplot(aes(x = t, y = net_force, colour = node)) + geom_line()
#replot with divergent_result to see what it looks like
## End(Not run)
``` |

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