user2751556 - 6 months ago 4x

Python Question

First my code:

`import numpy as np`

def square(list):

return [i ** 2 for i in list]

def multLists(x, y):

return x * y

def main():

x = np.array([1.02, 0.95, 0.87, 0.77, 0.67, 0.55, 0.44, 0.30, 0.16, 0.01])

y = np.array([0.39, 0.32, 0.27, 0.22, 0.18, 0.15, 0.13, 0.12, 0.13, 0.15])

a = square(y)

b = multLists(x,y)

c = x

d = y

e = np.ones(len(x))

x2 = square(x)

Matrix = np.matrix([a,b,c,d,e])

Output = np.linalg.lstsq(Matrix,x2)[0]

print Output

main()

And my error code:

`Traceback (most recent call last):`

File "problem6.py", line 26, in <module>

main()

File "problem6.py", line 22, in main

Output = np.linalg.lstsq(Matrix,x2)[0]

File "/usr/lib/python2.7/dist-packages/numpy/linalg/linalg.py", line 1828, in lstsq

raise LinAlgError('Incompatible dimensions')

numpy.linalg.linalg.LinAlgError: Incompatible dimensions

Essentially, I'm trying to solve Ax=b, with A equaling "Matrix", and b="x2". I'm then trying to use least-squares to solve for X, but it isn't working. If, however, I change Matrix to equal:

`Matrix = [[0 for x in range(5)] for x in range(10)]`

The code then compiles and runs properly (although obviously with wrong values, since Matrix isn't supposed to equal ^ that. Any thoughts? Thanks.

Answer

You need to transpose your matrix:

```
Output = np.linalg.lstsq(Matrix.T, x2)[0]
```

Your broken code produces a matrix with 5 rows of 10 elements. Your working code produces a matrix with 10 rows of 5 elements.

You should probably also use `np.array`

instead of `np.matrix`

, and return an `np.array`

rather than a list from `square`

Source (Stackoverflow)

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