I have two points in 3D: (xa,ya,za) (xb,yb,zb) And I want to calculate the distance: dist = sqrt((xa-xb)^2 + (ya-yb)^2 + (za-zb)^2) What's the best way to do this with Numpy, or with Python in general? I have: a = numpy.array((xa,ya,za)) b = numpy.array((xb,yb,zb)) ...
It is described as -||xi-xy||^2. So for 2 two dimensional points do I code it like this? - ((x1-x2) + (y1-y2))^2 or -( (x1-x2)^2 + (y1-y2)^2 ) or -(sqrt( (x1-x2)^2 + (y1-y2)^2 )) or some other way? ...
I am playing with the following code from programming collective intelligence, this is a function from the book that calculated eclidian distance between two movie critics. This function sums the difference of the rankings in the dictionary, but euclidean distance in n dimensions also includes the square root of that sum. AFAIK since w...
I have two arrays of x-y coordinates, and I would like to find the minimum Euclidean distance between each point in one array with all the points in the other array. The arrays are not necessarily the same size. For example: xy1=numpy.array( [[ 243, 3173], [ 525, 2997]]) xy2=numpy.array( [[ 682, 2644], [ 277, 2651], [ 396, 2640]]) ...
I am playing with the euclidian distance example from programming collective intelligence book, # Returns a distance-based similarity score for person1 and person2 def sim_distance(prefs,person1,person2): # Get the list of shared_items si={} for item in prefs[person1]: if item in prefs[person2]: si[item]=1 # ...
I need to calculate the overlap (amount or yes/no) that two rectangles make on a special x/y grid. The grid is 500x500 but the sides and corners connect (are continuous). So the next point after 499 becomes 0 again. In a previous question I asked for a way to calculate the distance between two points in this grid. This turned out to be ...
I have an array of points in unknown dimensional space, such as: data=numpy.array( [[ 115, 241, 314], [ 153, 413, 144], [ 535, 2986, 41445]]) and I would like to find the average euclidean distance between all points. Please note that I have over 20,000 points, so I would like to do this as efficiently as possible. Thanks. ...
I have an array of points in numpy: points = rand(dim, n_points) And I want to: Calculate all the l2 norm (euclidian distance) between a certain point and all other points Calculate all pairwise distances. and preferably all numpy and no for's. How can one do it? ...
Hi everyone. Given : An array A[1..n] of real numbers. Goal : An array D[1..n] such that D[i] = min{ distance(i,j) : A[j] > A[i] } or some default value (like 0) when there is no higher-valued element. I would really like to use Euclidean distance here. Example : A = [-1.35, 3.03, 0.73, -0.06, 0.71, -0.21, -0.12, 1.49, 1.41, 1...
Hi Guys, I have read through the source code for mplsh, but I still unsure on how to use the indexes generated by lshkit to speed up the process in comparing feature vector in Euclidean Distance. Do you guys have any experience regarding this? ...
Hi All, I was in need of a little math help that I can't seem to find the answer to, any links to documentation would be greatly appreciated. Heres my situation, I have no idea where I am in this maze, but I need to move around and find my way back to the start. I was thinking of implementing a waypoint list of places i've been offset ...
List1 contains a high number (~7^10) of N-dimensional points (N <=10), List2 contains the same or fewer number of N-dimensional points (N <=10). My task is this: I want to check which point in List2 is closest (euclidean distance) to a point in List1 for every point in List1 and subsequently perform some operation on it. I have been do...
Hi, I'm attempting to find the euclidean distance in meters between two points on an MKMapView using iPhone OS 3.2. The problem is that I have these coordinates in terms of latitude and longitude, which, mathematically provides me enough data to find the distance, but it's going to take some tricky trigonometry. Is there any simpler sol...
Hi please any one help me to solve my proplem: I compute the color histogram for both image database (THisto) and Query image (QHisto)then I used Euclidean distance to compute the distance between them in order to retrieve the similar one. when I run the program I get the following error: THisto and QHisto) must be 2 Dimension Pl...
i am going to develop an application for image comparison on java. For this i have choosen euclidean algorithm. This application involves with 2 images. 1. Actual image 2. Part of the actual image. Algorithm should compare the part of the image with actual image. If the part is existed in actual image, it should return one value as matc...