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vector field visualisation R

I have a big text file with a lot of rows. Every row corresponds to one vector. This is the example of each row:

        x           y               dx              dy
99.421875   52.078125   0.653356799108  0.782479314511

First two columns are coordinates of the beggining of the vector. And two second columnes are coordinate increments (the end minus the start). I need to make the picture of this vector field (all the vectors on one picture). How could I do this? Thank you

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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)

Van der Pol attractor

You may want to apply some image processing to the result to make it more readable.

image(res > quantile(res,.6), col=0:1)

After thresholding

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).


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