numpy.mean(): accumulator default type should not be single precision (Trac #435)

[numpy-gitbot]

Original ticket http://projects.scipy.org/numpy/ticket/435 on 2007-01-24 by @chanley, assigned to unknown.

The accumulator used in the mean algorithm should not be single precision by default. This default can cause unexpected results. Please see the following example:

In [5]: a.dtype
Out[5]: dtype('>f4')

In [6]: print a
[[ 132.  132.  132. ...,  132.  132.  132.]
 [ 132.  132.  132. ...,  132.  132.  132.]
 [ 132.  132.  132. ...,  132.  132.  132.]
 ..., 
 [ 132.  132.  132. ...,  132.  132.  132.]
 [ 132.  132.  132. ...,  132.  132.  132.]
 [ 132.  132.  132. ...,  132.  132.  132.]]

In [7]: a.min()
Out[7]: 132.0

In [8]: a.max()
Out[8]: 389.0

In [9]: a.mean()
Out[9]: 129.742439153

However, if you recast the array as float64 you get the correct result:

In [11]: a.astype(numpy.float64).mean()
Out[11]: 132.062805059

I believe that double precision would be a more appropriate default type for the accumulator.

[numpy-gitbot]

@chanley wrote on 2007-03-23

Closing this ticket since it is a duplicate of #1063