simulate_vis | R Documentation |
simulate_vis provides visualisation of the graph in addition to simulate function.
simulate_vis( input_graph, cycle = 1, threshold = 0, save = FALSE, Competing_color = "green", mirna_color = "orange", Upregulation = "red", Downregulation = "blue", title = "GRAPH", layout = "kk" )
input_graph |
The graph object that processed in previous steps. |
cycle |
Optimal iteration number for gaining steady-state. |
threshold |
absolute minimum amount of change required to be considered as up/down regulated element |
save |
provides to save graph output |
Competing_color |
The color of competing elements on the graph with "green" default. |
mirna_color |
The color of miRNAs on the graph with "orange" default. |
Upregulation |
The color of Upregulated elements on the graph with "red" default. |
Downregulation |
The color of Downregulated elements on the graph with "blue" default. |
title |
Title of the given graph. |
layout |
The layout that will be used for visualisation of the graph. |
simulate_vis gives the last graph object and each iterations' image.
It gives a graph and the images of states in each iteration until the end of the simulation.
# When does the system gain steady-state conditions again? ## new_counts, the dataset that includes the current counts of nodes. data("minsamp") data("new_counts") priming_graph(minsamp, Competing_expression, miRNA_expression)%>% update_variables(new_counts)%>% simulate_vis() priming_graph(minsamp, Competing_expression, miRNA_expression, aff_factor = c(seed_type,energy), deg_factor = c(region))%>% update_variables(new_counts)%>% simulate_vis(cycle = 12)
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