3d

问题 To make clear what I'm asking I've created an easy example. Step one is to create some data: gender <- factor(rep(c(1, 2), c(43, 41)), levels = c(1, 2),labels = c("male", "female")) numberofdrugs <- rpois(84, 50) + 1 geneticvalue <- rpois(84,75) death <- rpois(42,50) + 15 y <- data.frame(death, numberofdrugs, geneticvalue, gender) So these are some random dates merged to one data.frame . So from these dates I'd like to plot a cloud where I can differ between the males and females and where I

问题 I have a 3D matrix of data in matlab, but I want to extract an arbitrarily rotated slice of data from that matrix and store it as a 2D matrix, which I can access. Similar to how the slice() function displays data sliced at any angle, except I would also like to be able to view and modify the data as if it were an array. I have the coordinates of the pivot-point of the plane as well as the angles of rotation (in x, y and z axis), I have also calculated the equation of the plane in the form: Ax

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . I have two 3D matrices. Each pixel is a gray scale value. The first 3D matrix is a reference shape. e.g. imagine a 3D model of a mouth. The second 3D matrix is an approximate subsection of the reference shape. e.g. imagine a tooth. The subsection is approximate as it is from a different mouth. Note the

问题 I've seen many posts (here, here, here, and here) on how to add color gradient on the Z axis (but none on "z" values that range from 0 to 1). The only thing is that when I do this, I end up with only two colors if my data on the Z axis is between 0 and 1. Here is an example: I would like to have a figure where the Z axis is show a red color when it's near 0 and yellow when it's near 1. The other problem is that I have a bunch of NA's in the Z axis because I'm defining the surface for only the

问题 How do I extend theanos downsample.max_pool_2d_same_size in order to pool not only within a feature map, but also between those - in a efficient manner? Lets say i got 3 feature maps, each of size 10x10, that would be a 4D Tensor (1,3,10,10). First lets max pool ((2,2), no overlapping) each of the (10,10) feature map. The results are 3 sparse feature maps, still (10,10) but most values equal to zero: within a (2,2) window is at most one value greater than zero. This is what downsample.max

问题 I'm struggling to get a cube to render in opengl. When I pass in the MVP already calculated to the vertex shader it works fine, but when I pass in the model, view and projection then do the calculation in the vertex shader it doesn't show the cube. I'm also getting error 1282 when I change the vertex shader's uniform types to mat4 instead of vec4. Main.cpp #include <iostream> #include <GL/glew.h> #include <GLFW/glfw3.h> #include <glm/glm.hpp> #include <glm/gtc/type_ptr.hpp> #include <glm/gtc

问题 I have a triangle with points A, B, C and Point in space (P). How can I get distance from point to plane? I need to calc distance from P to plane, even when my triangle lie far away(or not above to the point, like on picture). Point and triangle: 回答1: If the point is P(x1,y1,z1) and the plane is ax+by+cz+d = 0 Distance dist = Abs(a*x1+b*y1+c*z1+d) / Sqrt(a^2+b^2+c^2) 回答2: I assume you want to compute perpendicular distance between point and plane given 3 points on it forming a triangle. Here

问题 I have a triangle with points A, B, C and Point in space (P). How can I get distance from point to plane? I need to calc distance from P to plane, even when my triangle lie far away(or not above to the point, like on picture). Point and triangle: 回答1: If the point is P(x1,y1,z1) and the plane is ax+by+cz+d = 0 Distance dist = Abs(a*x1+b*y1+c*z1+d) / Sqrt(a^2+b^2+c^2) 回答2: I assume you want to compute perpendicular distance between point and plane given 3 points on it forming a triangle. Here

问题 I am trying to 3D plot the magnification factor in vibrations for multiple types of damping. To simplify it for those who have no idea what it is, basically, you have 3 variables: beta, which varies between 0 and infinite, but I would like to visualize it from 0 to 3, in 0.2 intervals. damping ratio, d, which varies between 0 and infinite, but I would like to plot it from 0 to 1, in 0.1 intervals. finally, nu, which is a function that varies according to the two variables before. My intuition

问题 I am working on a tool that requires a 3D "voxel-based" engine. By that I mean it will involve adding and removing cubes from a grid. In order to manage these cubes I need a data structure that allows for quick insertions and deletes. The problem I've seen with k-d trees and octrees is that it seems like they would frequently need to be recreated (or at least rebalanced) because of these operations. Before I jumped in I wanted to get opinions on what the best way to go about this would be.