If there is a lot of data (the question says "big file"),
plotting the individual vectors may not give a very readable plot.
Here is another approach: the vector field describes a way of deforming something drawn on the plane;
apply it to a white noise image.
vector_field <- function(
f, # Function describing the vector field
xmin=0, xmax=1, ymin=0, ymax=1,
width=600, height=600,
iterations=50,
epsilon=.01,
trace=TRUE
) {
z <- matrix(runif(width*height),nr=height)
i_to_x <- function(i) xmin + i / width * (xmax - xmin)
j_to_y <- function(j) ymin + j / height * (ymax - ymin)
x_to_i <- function(x) pmin( width, pmax( 1, floor( (x-xmin)/(xmax-xmin) * width ) ) )
y_to_j <- function(y) pmin( height, pmax( 1, floor( (y-ymin)/(ymax-ymin) * height ) ) )
i <- col(z)
j <- row(z)
x <- i_to_x(i)
y <- j_to_y(j)
res <- z
for(k in 1:iterations) {
v <- matrix( f(x, y), nc=2 )
x <- x+.01*v[,1]
y <- y+.01*v[,2]
i <- x_to_i(x)
j <- y_to_j(y)
res <- res + z[cbind(i,j)]
if(trace) {
cat(k, "/", iterations, "
", sep="")
dev.hold()
image(res)
dev.flush()
}
}
if(trace) {
dev.hold()
image(res>quantile(res,.6), col=0:1)
dev.flush()
}
res
}
# Sample data
van_der_Pol <- function(x,y, mu=1) c(y, mu * ( 1 - x^2 ) * y - x )
res <- vector_field(
van_der_Pol,
xmin=-3, xmax=3, ymin=-3, ymax=3,
width=800, height=800,
iterations=50,
epsilon=.01
)
image(-res)
You may want to apply some image processing to the result to make it more readable.
image(res > quantile(res,.6), col=0:1)
In your case, the vector field is not described by a function:
you can use the value of the nearest neighbour or some 2-dimensional interpolation
(e.g., from the akima
package).