Vectormatrix & matrixmatrix multiplication using SSE for any size of input matrix and vector
By : MichaelDroid
Date : March 29 2020, 07:55 AM

can we change the vector into matrix in numpy with the elements in the vector repeats in a matrix with m*n dimensions
By : Adam
Date : March 29 2020, 07:55 AM
help you fix your problem If I understand the question correctly you could simply use np.repeat and reshape: code :
>>> import numpy as np
>>> arr = np.array([1,2,3,4])
>>> n = 3
>>> np.repeat(arr, n).reshape(1, arr.size)
array([[1, 1, 1],
[2, 2, 2],
[3, 3, 3],
[4, 4, 4]])
>>> n = 7
>>> np.broadcast_to(arr, (n, arr.size)).T
array([[1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 2, 2, 2],
[3, 3, 3, 3, 3, 3, 3],
[4, 4, 4, 4, 4, 4, 4]])

Error: requires numeric/complex matrix/vector arguments when using matrix times vector multiplication
By : Greg Gould
Date : March 29 2020, 07:55 AM
I hope this helps . This works fine. You must have some NAs in your cpi_calc table. Try na.omit(cpi_calc) code :
cpi_calc < read.table(text="0.358 0.359 0.06 0.419 0.191 0.296
100 100 100 100 100 100
99.99 100 100.07 100.01 100.8 101.59
99.52 99.58 99.94 100.01 101.03 101.38
99.46 99.44 99.85 100.01 101.03 101.03
99.13 99.37 99.79 99.97 101 101.82",header=FALSE)
as.matrix(cpi_calc[2:6, 1:6]) %*% t(cpi_calc[1, 1:6])
1
2 168.3000
3 168.9282
4 168.5832
5 168.4024
6 168.4669

How do I multiply a matrix by a vector in python without any built in functions where both the vector and matrix are inp
By : user2580804
Date : March 29 2020, 07:55 AM
this one helps. Input validation First, you should introduce some validation checks on the input. code :
ncols = len(matrix1[0])
for row in matrix1[1:]:
if len(row) != ncols:
#stop the program and raise an error to the user.

Nonintuitive perf diff between `matrix * vector`, `matrix’ * vector` and `copy(matrix’) * vector` Usage Performance bla
By : user3232940
Date : March 29 2020, 07:55 AM

