Solving linear equation system using Numpy

Question

I have 3 equations

-950 X = B1
-550 X = B2
-250 X = B3

B1, B2, B3 are known values 3D arrays

X should be also a 3D array

My code is

A = np.array([-950],[-550],[-250])
B = np.array([np.log(b1000_data/b50_data), np.log(b600_data/b50_data),     np.log(b300_data/b50_data)])
X = np.linalg.solve(A,B) 

However, it fails

A = np.array([-950],[-550],[-250]) ValueError: only 2 non-keyword arguments accepted 

Answer 1

First you should be doing like:

a = np.array([[-950], [-550],[-250]])

Given your equation Ax=B . In this case you have more equations than required. This results in many possible x values. In this case 3 . It will result into error.
Read here: https://andreask.cs.illinois.edu/cs357-s15/public/demos/06-qr-applications/Solving%20Least-Squares%20Problems.html