r - Conditionally Fill Matrix based on values of another Matrix using For loop

Question

I am trying to fill a matrix with specific values based on a different matrix.

I created an empty matrix with:

n <- 64 #length of matrix
vector_walk<- matrix(0, ncol = 1, nrow = n)

Then I filled that matrix from this Distribution

n <- 100000 #How many observations in the distribution
mu <- 180 #Mean vector for distribution
kappa <- 1.5 #How wide the distribution is
mu <- circular(mu, units = c("degrees"), 
               modulo = c("2pi"),
               template = ("geographics"))
Dist <- rvonmises(n, mu, kappa, control.circular=list(units="degrees"))

Filling the matrix

for (i in 1:n){
  vector[i] = sample(Dist, 1)
}  

Now here is where I am stuck. I want to fill a new matrix "grid_walk" with 2 columns and conditionally fill it with values based on the "vector_walk" matrix. I want to put a 0 in the first column and a 1 in the second whenever the "vector matrix has a value greater than 0 and less than 23 and a few others listed below. I am trying this for loop with if statements

    
for (j in 1:2){
  for(i in 1:n){
    if(vector_walk[i] > 0 & vector_walk[i] < 23) grid_walk[i,j] <- c(0,1)
    if(vector_walk[i] > 23  & vector_walk[i] < 68) grid_walk[i,j] <- c(1,1)
    if(vector_walk[i] > 68 & vector_walk[i] < 113) grid_walk[i,j] <- c(1,0)
    if(vector_walk[i] > 113 & vector_walk[i] < 158) grid_walk[i,j] <- c(1,-1)
    if(vector_walk[i] > 158 & vector_walk[i] < 203) grid_walk[i,j] <- c(0,-1)
    if(vector_walk[i] > 203 & vector_walk[i] < 248) grid_walk[i,j] <- c(-1,-1)
    if(vector_walk[i] > 248 & vector_walk[i] < 293) grid_walk[i,j] <- c(-1,0)
    if(vector_walk[i] > 293 & vector_walk[i] < 338) grid_walk[i,j] <- c(-1,1)
    if(vector_walk[i] > 338 & vector_walk[i] < 361) grid_walk[i,j] <- c(0,1)
  }
}

Any help would be appreciated as I have never used if or for statements in R

question from:https://stackoverflow.com/questions/65893463/conditionally-fill-matrix-based-on-values-of-another-matrix-using-for-loop

Answer 1

I would implement this one column at a time, because for loops are (generally) slow in R. We start by creating a matrix of zeros, and replacing values if they fall within the conditions.

library(Rfast)
library(circular)

n <- 100000 #How many observations in the distribution
mu <- 180 #Mean vector for distribution
kappa <- 1.5 #How wide the distribution is
mu <- circular(mu, units = c("degrees"), 
               modulo = c("2pi"),
               template = ("geographics"))
Dist <- rvonmises(n, mu, kappa, control.circular=list(units="degrees"))

# Equivalent to your current "Filling the matrix" step but avoids the loop
vector_walk <- sample(Dist)

# Start by filling everything with zeros
grid_walk <- matrix(numeric(1), nrow = length(vector_walk), ncol = 2)

# If vector_walk is between 23 and 158, replace the first column's default zero with a 1
grid_walk[vector_walk>23&vector_walk<158, 1] <- 1
# If vector_walk is between 203 and 338, replace the first column's default zero with a -1
grid_walk[vector_walk>203&vector_walk<338, 1] <- -1

# Repeat for the second column
grid_walk[(vector_walk>0&vector_walk<68)|(vector_walk>293&vector_walk<361), 2] <- 1
grid_walk[vector_walk>113&vector_walk<248, 2] <- -1