Example of numpy cov() not correct?
Hi, all, I am trying out the example here (http://www.scipy.org/Numpy_Example_List_With_Doc#cov)
from numpy import * ... T = array([1.3, 4.5, 2.8, 3.9]) P = array([2.7, 8.7, 4.7, 8.2]) cov(T,P)
The answer is supposed to be 3.9541666666666657 The result I got is instead a cov matrix array([[ 1.97583333, 3.95416667], [ 3.95416667, 8.22916667]]) So, I just wanna confirm this particular example may be no longer correct. I am using python 2.4.3 with numpy 1.1.0 on MS win Cheers, Anthony NOTICE This e-mail and any attachments are confidential and may contain copyright material of Macquarie Group Limited or third parties. If you are not the intended recipient of this email you should not read, print, re-transmit, store or act in reliance on this e-mail or any attachments, and should destroy all copies of them. Macquarie Group Limited does not guarantee the integrity of any emails or any attached files. The views or opinions expressed are the author's own and may not reflect the views or opinions of Macquarie Group Limited.
On Tue, Jul 29, 2008 at 9:10 PM, Anthony Kong
I am trying out the example here (http://www.scipy.org/Numpy_Example_List_With_Doc#cov)
from numpy import * ... T = array([1.3, 4.5, 2.8, 3.9]) P = array([2.7, 8.7, 4.7, 8.2]) cov(T,P)
The answer is supposed to be 3.9541666666666657
The result I got is instead a cov matrix array([[ 1.97583333, 3.95416667], [ 3.95416667, 8.22916667]]) So, I just wanna confirm this particular example may be no longer correct.
I am using python 2.4.3 with numpy 1.1.0 on MS win
It works for me (1.1 on GNU/Linux):
import numpy as np T = np.array([1.3, 4.5, 2.8, 3.9]) P = np.array([2.7, 8.7, 4.7, 8.2]) np.cov(T,P)
array([[ 1.97583333, 3.95416667], [ 3.95416667, 8.22916667]])'
If you read the cov function documentation you'll see that if a second vector is given, it joins the 2 into one matrix and calculate the covariance of it. In your case, you are looking for the off-diagonal elements.
Nadav.
-----הודעה מקורית-----
מאת: numpy-discussion-bounces@scipy.org בשם Keith Goodman
נשלח: ד 30-יולי-08 17:04
אל: Discussion of Numerical Python
נושא: Re: [Numpy-discussion] Example of numpy cov() not correct?
On Tue, Jul 29, 2008 at 9:10 PM, Anthony Kong
I am trying out the example here (http://www.scipy.org/Numpy_Example_List_With_Doc#cov)
from numpy import * ... T = array([1.3, 4.5, 2.8, 3.9]) P = array([2.7, 8.7, 4.7, 8.2]) cov(T,P)
The answer is supposed to be 3.9541666666666657
The result I got is instead a cov matrix array([[ 1.97583333, 3.95416667], [ 3.95416667, 8.22916667]]) So, I just wanna confirm this particular example may be no longer correct.
I am using python 2.4.3 with numpy 1.1.0 on MS win
It works for me (1.1 on GNU/Linux):
import numpy as np T = np.array([1.3, 4.5, 2.8, 3.9]) P = np.array([2.7, 8.7, 4.7, 8.2]) np.cov(T,P)
array([[ 1.97583333, 3.95416667], [ 3.95416667, 8.22916667]])' _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Wed, 30 Jul 2008 18:49:10 +0300, Nadav Horesh wrote:
If you read the cov function documentation you'll see that if a second vector is given, it joins the 2 into one matrix and calculate the covariance of it. In your case, you are looking for the off-diagonal elements.
So the final answer to the OP's question is: Yes, the example on http://www.scipy.org/Numpy_Example_List_With_Doc#cov is wrong; cov(T,P) indeed returns a matrix. And it would be nice if someone fixed this, you can simply register a wiki account and fix the problem. -- Pauli Virtanen
On Thu, Jul 31, 2008 at 1:14 AM, Pauli Virtanen
Yes, the example on
http://www.scipy.org/Numpy_Example_List_With_Doc#cov
is wrong; cov(T,P) indeed returns a matrix. And it would be nice if someone fixed this, you can simply register a wiki account and fix the problem.
Done.
participants (4)
-
Anthony Kong -
Keith Goodman -
Nadav Horesh -
Pauli Virtanen