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R/step_forward.r
In BoolFilter: Optimal Estimation of Partially Observed Boolean Dynamical Systems
Defines functions
step.forward
step.forward <- function(z, p, net) {
a <- t(apply(z, 1, function(x) {BoolNet::stateTransition(net,x)}))
a[a>0] = 1
a[a<0] = 0
b <- xor(a, matrix(Rlab::rbern(length(net$genes)*nrow(z), p), ncol=length(net$genes)))
return (b)
}
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BoolFilter documentation built on May 2, 2019, 1:27 p.m.
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Defines functions step.forward
step.forward <- function(z, p, net) {
a <- t(apply(z, 1, function(x) {BoolNet::stateTransition(net,x)}))
a[a>0] = 1
a[a<0] = 0
b <- xor(a, matrix(Rlab::rbern(length(net$genes)*nrow(z), p), ncol=length(net$genes)))
return (b)
}
Try the BoolFilter package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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