CODEWITHSUNDEEP
python
James
James

Reputation: 1

Python rounding numpy array entries down to the nearest whole number. How can I fix this?

Bear with me as I'm not very experienced with coding, but an example of my problem is as follows:

I define a matrix V as below and then attempt to scale the first row by a factor equal to the first entry in V:

V=np.array([[3,1],[1,3]])
V[0]=V[0]/V[0,0]
print(V)

Output:
[[1 0]
 [1 3]]

For some reason, Python has rounded the scaled entries down to the nearest whole number. Another example:

V=np.array([[3,1],[1,3]])
print(V[0]*1.8)

Output:
[5.4 1.8]

There seems to be no issue, but when I assign the first row of V equal to the scaled version the same problem arises.

V=np.array([[3,1],[1,3]])
V[0]=V[0]*1.8

Output:
 [[5 1] 
 [1 3]]

Expected output:

[[5.4 1.8],
[1 3]]

Clearly, the output should have [5.4 1.8] as the first row, but Python has rounded each entry down to the nearest whole number.

Why is Python doing this? What am I doing wrong?

Problem outlined completely above, not much to say here.

Thanks,

James

Upvotes: 0

Views: 37

Answers (1)

Rodrigo Guzman
Rodrigo Guzman

Reputation: 487

This is because your numpy array is int. ALL elements in the numpy array must be the same type. So when you multiply by a float your array, the array remains as an int (no decimals)

You need to convert your array to float first in order to get the output you expect.

V=np.array([[3,1],[1,3]]).astype('float')
V[0]=V[0]*1.8

Upvotes: 2

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