#### Category : matrix

Basically I have to write a program that creates a matrix of N by N and fills it with random numbers and calculates the sum of all the elements below the main diagonal of the matrix. I already did everything except the sum of elements and this is what I have import random def llenar_matriz(n): ..

I used svd of a matrix A of size 64*64 in Python as follows. U,D,V=svd(A) Now, D is an array of all eigenvalues of A. How to rewrite all values in D as a diagonal matrix? For example, if D=[d1,d2,d3,d4], how to have D_new=[[d1,0,0,0],[0,d2,0,0],[0,0,0,d3],[0,0,0,d4]]? Source: Python..

I have two NxM arrays in numpy, a and b. I would like to perform a vectorized operation that does the following: c = np.zeros(N) for i in range(N): for j in range(M): c[i] += a[i, j]*b[i, j] Stated in a more mathematical way, I have two matrices A and B, and want to compute ..

Given an NxN matrix W, I’m looking to calculate an NxN matrix C given by the equation in this link: https://i.stack.imgur.com/dY7rY.png, or in LaTeX \$\$C_{ij} = max_k bigg{ sum_l bigg( W_{ik}W_{kl}W_{lj} – W_{ik}W_{kj} bigg) bigg}.\$\$ I have tried to implement this in PyTorch but I’ve either encountered memory problems by constructing an intermediate NxNxN 3D ..

I have a dataset with data in which at each time a value from a given user is achieved. I would like to create a dataframe for each user ID or a matrix of vectors where I can add a value independently. For instance: t0 t1 t2 t3 t4 t5 … tM User1 2 3 ..

Im newbbie in code. I would like to ask something about numpy matrix. Right now, I need to save a matrix values which I import with fileinput() from a .tqc doc. ”’ with fi.input(files=[r’D:RANDOMJUSTEXAMPLEMEfile.tqc’]) as f: for line in f: dados = line.split() #dividir os dados do txt x = dados[2:3] y = dados[4:5] z ..

I am looking for a faster alternative for the following code. rows = 30 cols = 10**3 v_mat = np.random.rand(rows,cols) a_mat = np.random.rand(cols,cols) b_vec = (v_mat @ a_mat @ v_mat.T).diagonal() Source: Python..