RcppNested/grow_test.R at master · zamanlh/RcppNested · GitHub

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require(Rcpp)
setwd('~/RcppNested')
sourceCpp("nestedness.cpp")

d <- read.csv('~/Desktop/200up_events.csv')
d <- subset(d, rep==2 & update < 100000)
summary(d)

original_mat <- as.matrix(read.csv('interaction_matrix.csv', head=F))
calculateNODF(sortMatrix(original_mat))

t <- getRandomMatrix_GrowEvents(d$host_event, d$parasite_event, d$edge_event)

t_time_event <- replicate(20, getEventTimeseries(d$host_event, d$parasite_event, d$edge_event, 5, T))
matplot(t_time_event, type="l")


t_time_rand <- replicate(20, getMonotonicTimeseries(t, 500, 5, T))
rand_min <- min(sapply(t_time_rand, FUN=function(d) {length(d)}))
matplot(sapply(t_time_rand, FUN=function(d) {d[1:rand_min]}), type="l")


calculateNODF(sortMatrix(getRandomMatrix_GrowEvents(d$host_event, d$parasite_event, d$edge_event)))$NODF
calculateNODF(sortMatrix(getRandomMatrix_GrowMonotonic(original_mat, length(d$host_event))))$NODF


image(sortMatrix(t))


#different null model generators
nodf_null_col <- replicate(1000, calculateNODF(getRandomMatrix_ColShuffle(t))$NODF)
nodf_null_row <- replicate(1000, calculateNODF(getRandomMatrix_RowShuffle(t))$NODF)
nodf_null_fill <- replicate(1000, calculateNODF(getRandomMatrix_Fill(t))$NODF)
par(mfcol=c(3,1))
hist(nodf_null_col)
hist(nodf_null_row)
hist(nodf_null_fill)