coordinates

I'm having trouble converting my OpenGL scene coordiates to my screen coordinates. I thought I needed to multiply my coordinates with the modelview matrix then with the projection matrix to get the ndc. But i'm getting weird coordinates. Here is my piece of code GLKVector3 coor = GLKVector3Make(point.x, point.y, 0); GLKMatrix4 modelview = GLKMatrix4MakeWithArray(glProjectionMatrix); GLKMatrix4 projetion = GLKMatrix4MakeWithArray(modelViewMatrix.data); GLKVector3 eyeCoor = GLKMatrix4MultiplyVector3(modelview, coor); GLKVector3 ndcCoor = GLKMatrix4MultiplyVector3(projetion,eyeCoor); CGPoint p =

I am trying to plot GIS coordinates, specifically UK national Grid Coordinates which eastings and northings ressemble: 194630000 562220000 I can plot these using clusplot in the Cluster library: clusplot (df2,k.means.fit$cluster,main=i,color=TRUE,shade=FALSE,labels=0,lines=0,bty="7") where df2 is my data frame and k.means.fit is the result of the K means analysis on df2. Note that the coordinates of the centers after the k means analysis have not been normalised: k.means.fit$centers # Grid.Ref.Northing Grid.Ref.Easting #1 206228234 581240726 But when I plot the clusters, all the points are

I am currently working in Python to do color detection on a single image. After loading my image and establishing my RGB (or BGR in CV2), I use the following 2 lines to produce a mask and a output image. mask = cv2.inRange(image, lower, upper) output = cv2.bitwise_and(image, image, mask = mask) Then the code displays the following image. But now, I would like to take the processed image and extract pixel coordinate points for the green line. Thanks. Any help would be appreciated. Soltius So, how about findNonZeros() on a binarised version of your image ? Starting with the image with the green

I need to verify if a coordinate LAT/LNG point is between other two points (a segment line like a road). I followed THIS topic with no success. function inRange(start, point, end) { start_x = start.lat(); start_y = start.lng(); end_x = end.lat(); end_y = end.lng(); point_x = point.lat(); point_y = point.lng(); var dx = end_x - start_x; var dy = end_y - start_y; var innerProduct = (point_x - start_x)*dx + (point_y - start_y)*dy; return 0 <= innerProduct && innerProduct <= dx*dx + dy*dy; } function checkRange(start, point, end){ var x1 = start.lat(); var y1 = start.lng(); var x2 = end.lat(); var

I have a collection of 2D coordinate sets (on the scale of a 100K-500K points in each set) and I am looking for the most efficient way to measure the similarity of 1 set to the other. I know of the usuals: Cosine, Jaccard/Tanimoto, etc. However I am hoping for some suggestions on any fast/efficient ones to measure similarity, especially ones that can cluster by similarity. Edit 1: The image shows what I need to do. I need to cluster all the reds, blues and greens by their shape/orientatoin, etc. alt text http://img402.imageshack.us/img402/8121/curves.png It seems that the first step of any

I am trying to make a python script to extract the nodal coordinates from the ODB file (from abaqus). So far i have come up with the code attached below (don't mind the extra information i put behind the #, sometimes it's just so i can keep track of what i'm doing) The problem is that the coordinates i extract are those from the undeformed test subject. and i need the coordinates of the nodes from the deformed test subject. Can somebody help me with how i reach this information using python code? from abaqus import * from abaqusConstants import * import __main__ import section import