Average_simulations.f: Average of the dynamic trajectory of the network.
In SPIDDOR/SPIDDOR: SPIDDOR

Description Usage Arguments Details Value Examples

Function to compute the simulation algorithm repeated times and obtain the average of the dynamic trajectory of the network.

Average_simulations.f(BN, 
                      time.steps, 
                      Knockouts="",  
                      Over_expr="", 
                      Over_expr_AA="",
                      KO_times=NULL,
                      OE_times=NULL, 
                      asynchronous=TRUE,
                      repetitions)

`BN`	A list containing the most relevant information of the loaded network.It has the following components: nodes.names: A vector of the node names of the network Initial_conditions: A vector with the name of the nodes that will start in ON state in the first iteration of the simulation algorithm. Modulator: The duration of the modulation interactions that take place in the network dynamics. It could have specific arguments for each Boolean expression where a modulation occurs, or it can have a general argument "modulation_dur" where the user can specify a general time duration for all the modulation of the network. Arguments: A list with other arguments needed for a correct simulation of the network. Here, we included the duration of the threshold operators (THR). Polymorphism: A vector specifying the activity level of each node in the network. Default values are 1 for each node, meaning a 100% activity for all the components of the network.
`time.steps`	A number specifying the iterations for the simulation algorithm.
`Knockouts`	A character vector with the name of the nodes to knockout (fixed to 0) over all the simulation (empty by default).
`Over_expr`	A character vector with the name of the nodes to overexpress (fixed to 1) over all the simulation (empty by default).
`Over_expr_AA`	A character vector with the name of the nodes to overexpress (fixed to 1) after their first activation (empty by default).
`KO_times`	A numeric vector specifying the iterations where the nodes in Knockouts argument will be fixed to 0. If empty the knockout is applied to the nodes for the entire simulation (empty by default).
`OE_times`	A numeric vector specifying the iterations where the nodes in Over_expr argument will be fixed to 1. If empty the overexpression is applied to the nodes for the entire simulation (empty by default).
`asynchronous`	logical; if FALSE the synchronous mode is selected; if TRUE the asynchronous scheme is chosen (by default).
`repetitions`	Number of repetitions to compute the average of the dynamic trajectory of the network.

This functions is mainly used when the asynchronous updating method is choosen. However, it can also be applied with the synchronous updating scheme when polymorphisms are added to the network.

A matrix with the average of the dynamics of the network nodes (rows) over each iteration of the algorithm (columns).

  data("cellcycle")
  BN<-read.Boolean.functions(Lines=BN_cellcycle$BooleanFunctions)
  
  #Normal average of the dynamic trajectory of the network with asynchronous updating method:
  AVG<-Average_simulations.f(BN,time.steps=49,repetitions=2500)
  
  #Plot the results with ggplot2:
   AVG2<-toggplot(AVG)
   
   library(ggplot2)
   ggplot(data=AVG2,aes(x=time,y=value)) +
   geom_line( colour="#336600",size = 1.5) + ylab(" % of activation") + xlab("Time steps") +
   facet_wrap(~variable)