I want to select a specific row/column of a matrix i have, the twist however is that i want an added noise in the selection of the chosen row. Example I have a matrix m of size 100×100. I now want to select row 40 i.e. m[40,:]. What is actually wanted however is not an array with all values of
Tag: matrix
How to get this result when multiplying 1d-array by 2d-array?
I am struggling to figure out, how the output is calculated can you please explain? I have this multiplied by this array : c = np.array([3267. , 3375.9, 3484.8, 3630., 3740.]) the output is: array([1050885., 1068309., 1085733., 1103157., 1120581.]) Answer Grasping at straws because it feels like there’s not enough information to solve this. But, here is one way to
python iterate over arrays matrices
I am trying to create a new matrix(array) where I have been scouring the documentation in numpy but can’t find a function to satisfy this. Answer You’re looking for numpy.matmul. You’ll need to make the vectors have two dimensions (with a size of one in one of the dimensions). For example:
Compute row distance matrix using only for loops
I am stuck in trying to calculate a distance matrix from different binary arrays and I can only use for loops to resolve this… The problem consists of the following; Imagine I have a binary matrix built with different rows as follows, with dimension n=3,m=3 in this case: And I would like to achieve the following symmetric matrix, by adding
Reading Matrix from file
I have a txt file consisting some numbers with space and I want to make it as three 4*4 matrixes in python. Each matrix is also divided with two symbols in the text file. The format of the txt file is like this: My code is now like this but it is not showing the output I want. Can you
how to randomize a matrix keeping the rows fixed in python
I’m trying to randomize all the rows of my DataFrame but with no success. What I want to do is from this matrix to this I’ve tried with np. random.shuffle but it doesn’t work. I’m working in Google Colaboratory environment. Answer If you want to make this work with np.random.shuffle, then one way would be to extract the rows into
Multiply two matrices with different dimensions python
Error: ValueError: shapes (3,1) and (3,2) not aligned: 1 (dim 1) != 3 (dim 0) The error occurs because the matrices are different sizes, but how can I multiply two matrices with different size and where the resulting output should be: [-0.78 0.85]? Any help is appreciated! Mathematical question, for better understanding: A principal component analysis is carried out on
Distance Matrix Haversine
I am working on a data frame that looks like this : I’m trying to make a Haverisne distance matrix. Basically for each zone, I would like to calculate the distance between it and all the others in the dataframe. So there should be only 0s on the diagonal. Here is the Haversine function that I use but I can’t
Divide matrix into submatrix python
The program must accept an integer matrix of size R*C and four integers X, Y, P, Q as the input. The program must divide the matrix into nine submatrices based on the following condition. The program must divide the matrix horizontally after the Xth row and Yth row. Then the program must divide the matrix vertically after the Pth column
Smallest Submatrix in python
It contains an R*C matrix with unique digits. I have to print the submatrix having minimum and maximum integer This is my code: I need a solution without a NumPy array. I found the max and min values and also their index. After that, I don’t know what to do. Answer You can iterate over matrix again and get only