| evolution_games {tidygraph} | R Documentation |
This games create graphs through different types of evolutionary mechanisms (not necessarily in a biological sense). The nature of their algorithm is described in detail at the linked igraph documentation.
play_citation_age(n, growth = 1, bins = n/7100, p_pref = (1:(bins + 1))^-3, directed = TRUE) play_forestfire(n, p_forward, p_backward = p_forward, growth = 1, directed = TRUE) play_growing(n, growth = 1, directed = TRUE, citation = FALSE) play_barabasi_albert(n, power, growth = 1, growth_dist = NULL, use_out = FALSE, appeal_zero = 1, directed = TRUE, method = "psumtree") play_barabasi_albert_aging(n, power, power_age, growth = 1, growth_dist = NULL, bins = 300, use_out = FALSE, appeal_zero = 1, appeal_zero_age = 0, directed = TRUE, coefficient = 1, coefficient_age = 1, window = NULL)
n |
The number of nodes in the graph. |
growth |
The number of edges added at each iteration |
bins |
The number of aging bins |
p_pref |
The probability that an edge will be made to an age bin. |
directed |
Should the resulting graph be directed |
p_forward, p_backward |
Forward and backward burning probability |
citation |
Should a citation graph be created |
power |
The power of the preferential attachment |
growth_dist |
The distribution of the number of added edges at each iteration |
use_out |
Should outbound edges be used for calculating citation probability |
appeal_zero |
The appeal value for unconnected nodes |
method |
The algorithm to use for graph creation. Either |
power_age |
The aging exponent |
appeal_zero_age |
The appeal value of nodes without age |
coefficient |
The coefficient of the degree dependent part of attrictiveness |
coefficient_age |
The coefficient of the age dependent part of attrictiveness |
window |
The aging window to take into account when calculating the preferential attraction |
A tbl_graph object
play_citation_age: Create citation graphs based on a specific age
link probability. See igraph::sample_last_cit()
play_forestfire: Create graphs by simulating the spead of fire in
a forest. See igraph::sample_forestfire()
play_growing: Create graphs by adding a fixed number of edges
at each iteration. See igraph::sample_growing()
play_barabasi_albert: Create graphs based on the Barabasi-Alberts
preferential attachment model. See igraph::sample_pa()
play_barabasi_albert_aging: Create graphs based on the Barabasi-Alberts
preferential attachment model, incoorporating node age preferrence. See
igraph::sample_pa_age().
play_traits() and play_citation_type() for an evolutionary
algorithm based on different node types
Other graph games: component_games,
sampling_games, type_games
plot(play_forestfire(50, 0.5))