triangular

问题 The objective is to copy the lower triangle to upper triangle. Based on the suggestion produced in the OP, the following code was drafted. import numpy as np lw_up_pair = np.tril_indices(4, -1) arr=np.zeros((4,4,1,1)) arr[1,:1,:,0]=1 arr[2,:2,0,0]=2 arr[3,:3,0,0]=3 arr = arr + arr.T - np.diag(np.diag(arr)) However, it given an error ValueError: Input must be 1- or 2-d. May I know how handle this issue? The expected output is as below [[[0.]],, [[1.]],, [[2.]],, [[3.]]] [[[1.]],, [[0.]],, [[2.

问题 The objective is to copy the lower triangle to upper triangle. Based on the suggestion produced in the OP, the following code was drafted. import numpy as np lw_up_pair = np.tril_indices(4, -1) arr=np.zeros((4,4,1,1)) arr[1,:1,:,0]=1 arr[2,:2,0,0]=2 arr[3,:3,0,0]=3 arr = arr + arr.T - np.diag(np.diag(arr)) However, it given an error ValueError: Input must be 1- or 2-d. May I know how handle this issue? The expected output is as below [[[0.]],, [[1.]],, [[2.]],, [[3.]]] [[[1.]],, [[0.]],, [[2.

问题 The objective is to copy the lower triangle to upper triangle. Based on the suggestion produced in the OP, the following code was drafted. import numpy as np lw_up_pair = np.tril_indices(4, -1) arr=np.zeros((4,4,1,1)) arr[1,:1,:,0]=1 arr[2,:2,0,0]=2 arr[3,:3,0,0]=3 arr = arr + arr.T - np.diag(np.diag(arr)) However, it given an error ValueError: Input must be 1- or 2-d. May I know how handle this issue? The expected output is as below [[[0.]],, [[1.]],, [[2.]],, [[3.]]] [[[1.]],, [[0.]],, [[2.

问题 I want to generate x and y having a uniform distribution and limited by [xmin,xmax] and [ymin,ymax] The points (x,y) should be inside a triangle. How can I solve such a problem? 回答1: Here's some code that generates points uniformly on an arbitrary triangle in the plane. import random def point_on_triangle(pt1, pt2, pt3): """ Random point on the triangle with vertices pt1, pt2 and pt3. """ s, t = sorted([random.random(), random.random()]) return (s * pt1[0] + (t-s)*pt2[0] + (1-t)*pt3[0], s *

问题 I want to generate x and y having a uniform distribution and limited by [xmin,xmax] and [ymin,ymax] The points (x,y) should be inside a triangle. How can I solve such a problem? 回答1: Here's some code that generates points uniformly on an arbitrary triangle in the plane. import random def point_on_triangle(pt1, pt2, pt3): """ Random point on the triangle with vertices pt1, pt2 and pt3. """ s, t = sorted([random.random(), random.random()]) return (s * pt1[0] + (t-s)*pt2[0] + (1-t)*pt3[0], s *

问题 I want to generate x and y having a uniform distribution and limited by [xmin,xmax] and [ymin,ymax] The points (x,y) should be inside a triangle. How can I solve such a problem? 回答1: Here's some code that generates points uniformly on an arbitrary triangle in the plane. import random def point_on_triangle(pt1, pt2, pt3): """ Random point on the triangle with vertices pt1, pt2 and pt3. """ s, t = sorted([random.random(), random.random()]) return (s * pt1[0] + (t-s)*pt2[0] + (1-t)*pt3[0], s *

问题 I have 4 parts, every part 10000 times, which should fit into case, and the dimensions of the parts are given by uniform, normal and triangular distribution by randomly generating numbers in added dimensions of each distribution. For each 4 parts there is decision if they fit or not. But that shouldn't be a problem. I've managed somehow to do uniform and normal distribution: public double uniformDistrubution(double min, double max) { Random rand = new Random(); return Math.random() * max +

问题 I have 4 parts, every part 10000 times, which should fit into case, and the dimensions of the parts are given by uniform, normal and triangular distribution by randomly generating numbers in added dimensions of each distribution. For each 4 parts there is decision if they fit or not. But that shouldn't be a problem. I've managed somehow to do uniform and normal distribution: public double uniformDistrubution(double min, double max) { Random rand = new Random(); return Math.random() * max +

问题 I have a vector where the order of the elements are important, say x <- c(1,2,3,4) I would like to arrange my vector into a lower triangular matrix with a specific order where each row contains the preceding element of the vector. My goal is to obtain the following matrix lower_diag_matrix [,1] [,2] [,3] [,4] [1,] 4 0 0 0 [2,] 3 4 0 0 [3,] 2 3 4 0 [4,] 1 2 3 4 I know I can fill the lower triangular area using lower_diag_matrix[lower.tri(lower_diag_matrix,diag = T)]<-some_vector but I can't

问题 I have these indexes: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,etc... Which are indexes of nodes in a matrix (including diagonal elements): 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 etc... and I need to get i,j coordinates from these indexes: 1,1 2,1 2,2 3,1 3,2 3,3 4,1 4,2 4,3 4,4 5,1 5,2 5,3 5,4 5,5 6,1 6,2 6,3 6,4 6,5 6,6 etc... When I need to calculate coordinates I have only one index and cannot access others. 回答1: Not optimized at all : int j = idx; int i = 1; while(j > i) { j -=