geometry-surface

问题 Using Three.js, (although I believe this is more math related) I have a set of 2D points that can create a 2D geometry. such as square, rectangle, pentagon, or custom 2D shape. Based of the original 2D shape, I would like to create a method to offset the points inward or outward uniformly in such a way like the attached image. I don't know if there is a simple way to offset/grow/shrink all the points (vector3) uniformly on the 2D shape inward or outward. And if so, it'll be cool if I can

问题 I need to find the 2 points of the visual horizon , of a curved face. I have: XYZ of the 4 corner points XYZ of the 2 curved edge bezier points And I need to calculate either: XY of the 2 horizon points XYZ of the 2 horizon points Note: I got a solution the last time I asked this question, but it only found the extrema of the curves, not the horizon points , which changes based on the position and rotation of both curves in respect to each other. 回答1: You don't say how your surface is defined

问题 How do I animate a surface if it's coordinates change in time (e.g. ellipsoid) using MATLAB? 回答1: Here are a couple of examples of ways you can animate plots in MATLAB... Modify a plot in a for loop: You can create a loop in which you change the surface coordinates, update the plot object using the set command, and use the pause command to pause each loop iteration for a short period of time. Here's an example: [x, y, z] = ellipsoid(0, 0, 0, 4, 1, 1); % Make an ellipsoid shape hMesh = mesh(x,

问题 I am currently working with astronomical data among which I have comet images. I would like to remove the background sky gradient in these images due to the time of capture (twilight). The first program I developed to do so took user selected points from Matplotlib's "ginput" (x,y) pulled the data for each coordinate (z) and then gridded the data in a new array with SciPy's "griddata." Since the background is assumed to vary only slightly, I would like to fit a 3d low order polynomial to this

问题 I have a large data set which I would like to make a 3D surface from. I would like the x-axis to be the date, the y-axis to be the time (24h) and the z-axis (height) to be a value I have ($). I am a beginner with R, so the simpler the better! http://www.quantmod.com/examples/chartSeries3d/ has a nice example, but the code is way to complicated for my skill level! Any help would be much appreciated - anything I have researched so far needs to have the data sorted, which is not suitable I think

问题 I have an image with 6 colors each indicating a value. I had obtained an image as shown below. I need to smoothen the edges and then find out the area as well as the surface area of that region. The second image shows a black line drawn in the edges which indicates that I need to smoothen the edges in such a way. I had used segmentation to create a mask as shown in the third image, and then obtain a segmented image using the code following the image. I have used the following code for

问题 I have a set of points on an OPEN surface in 3D space. I have identified a subset of points which lay on the boundary. I mean to generate a triangulation of those points, which gives me an open surface and keeps my selected points on the boundary. All references I found deal with (sometimes?) closed surfaces, e.g., CGAL. See examples below. In addition, some CGAL algorithms require oriented normals at each point, which I do not have. Is there an available algorithm and code for this? (either

问题 I'm trying to obtain a surface plot from data frame AAA : j a m p o f 13929 0.86739583 19 165.83 0.1588727 13.24444 13930 0.63166667 19 178.19 0.6105804 12.68333 13932 0.90212963 17 157.77 0.3345627 12.52222 13933 0.80152778 68 146.19 0.1219885 12.35000 13934 0.75784722 62 134.88 0.1531627 12.36667 13935 0.57763889 66 123.80 0.4093869 12.47500 13936 0.56201389 88 112.87 0.9095722 12.45833 13937 0.51680556 26 102.03 0.8494420 12.37500 13938 0.46093333 28 91.20 0.9153419 12.21111 13939 0

问题 I am plotting a surface from a data file. I want to remove the mesh line parallel to x axis. Here is my code: set xlabel 'x'; set ylabel 'y'; splot "-" using 1:2:3 notitle w l; 1 1.0 0.998 1 2.0 0.998 1 3.0 0.998 1 4.0 0.998 1 5.0 0.997 1 6.0 0.997 1 7.0 0.997 1 8.0 0.997 1 9.0 0.997 1 10.0 0.997 2 1.0 0.998 2 2.0 0.997 2 3.0 0.996 2 4.0 0.995 2 5.0 0.995 2 6.0 0.995 2 7.0 0.995 2 8.0 0.994 2 9.0 0.989 2 10.0 0.987 3 1.0 0.997 3 2.0 0.997 3 3.0 0.997 3 4.0 0.997 3 5.0 0.997 3 6.0 0.997 3 7.0

问题 I'm using Simulated Annealing for Rectangular Nesting problem. I'm able to get good results, but the solution i got is DISCRETE. Even global optimum is not always obtained. Problem Description: Objective - To minimize the length of the infinite sheet (Width is constant) by changing the order in which parts are placed. Problem i Face: The output Results i get are DISCRETE(only 15 possible utilization %) instead of ANALOG (as there is 11!*2^11 possible solution -> We expect the results to be