distance

I'm trying to program the behaviour of birds in flight with boids in Python. I haven't found much yet but currently i'm stuck on the function defining the distance between two boids. It has to be calculated with the formula (a,b) = sqrt( (a_x - b_x)^2 + (a_y - b_y)^2) ) where a and b are the two vectors between which i have to calcualte the distance, a_x and b_x are the x-components of the vectors and a_y and b_y are the y-components. I get an error about the indices in the formula. I've tried solving in in a number of ways but i just can't figure out how to do it... Here is what i've got so

How to allocate a huge distance matrix in an appropriate way to avoid " allocation is unable " error. Imagine you have a 100.000 points randomly spreaded over some space. How can one cleverly create a matrix or "dist"-object, which represents the the half of DistMatrix. Maybe it should be another object, which will be able efficiently allocate the large number of distances. You can get the polygonial object from the following link: https://www.dropbox.com/sh/65c3rke0gi4d8pb/LAKJWhwm-l # Load required packages library(sp) library(maptools) library(maps) # Load the polygonal object x <-

I have 2 sets of points, set1 and set2 . Both sets of points have a data associated with the point. Points in set1 are "ephemeral", and only exist on the given date. Points in set2 are "permanent", are constructed at a given date, and then exist forever after that date. set.seed(1) dates <- seq(as.Date('2011-01-01'),as.Date('2011-12-31'),by='days') set1 <- data.frame(lat=40+runif(10000), lon=-70+runif(10000),date=sample(dates,10000,replace=TRUE)) set2 <- data.frame(lat=40+runif(100), lon=-70+runif(100),date=sample(dates,100,replace=TRUE)) Here's my problem: For each point in set1 (ephemeral)

I need to get the cell numbers within a distance (e.g., 10 km) of one point using R, but I didn't figure out how to handle it for the raster data. library(raster) r <- raster(ncols=10, nrows=10) cellFromXY(r, c(2,2)) # get the cell number of one point How to get the cell numbers within a distance of one point? Use extract with the buffer option and cellnumbers=TRUE r <- raster(ncols=100, nrows=100) r[]<-runif(ncell(r)) xy <- cbind(-50, seq(-80, 80, by=20)) extract(r, xy[1:3,], buffer=1000000,cellnumbers=TRUE) 来源： https://stackoverflow.com/questions/13996256/get-cell-number-within-a-distance-of

Let's say I have color 'FOO', and it is stored in RGB format. I need to recolor 'FOO' so it matches the closest color in a list of colors. Doing this on the fly, couldn't I view the RGB values from each color as points on a 3D grid (r=x, g=y, b=z) and compute the distance between point 'FOO' vs the points from each color in the list? The closest point to 'FOO' would be the replacement color? In theory, yes. In reality, computing the closest color is non-trivial if you want to do it well. Just for example, people's eyes are much more sensitive to changes in brightness than color shifts,

How can I find the distance between two rectangles? Intersects should return 0 in distance. Here's a quick function for calculating distance between two CGRects represented by a CGSize: CGSize CGSizeDistanceBetweenRects(CGRect rect1, CGRect rect2) { if (CGRectIntersectsRect(rect1, rect2)) { return CGSizeMake(0, 0); } CGRect mostLeft = rect1.origin.x < rect2.origin.x ? rect1 : rect2; CGRect mostRight = rect2.origin.x < rect1.origin.x ? rect1 : rect2; CGFloat xDifference = mostLeft.origin.x == mostRight.origin.x ? 0 : mostRight.origin.x - (mostLeft.origin.x + mostLeft.size.width); xDifference =