Hi,
I just noticed this and found it surprising:
In [8]: from numpy import ma
In [9]: a = ma.array([1,2,3,4],mask=[False,False,True,False],fill_value=0)
In [10]: a
Out[10]:
masked_array(data = [1 2 -- 4],
mask = [False False True False],
fill_value=0)
In [11]: a[2]
Out[11]:
Ryan May wrote:
Hi,
I just noticed this and found it surprising:
In [8]: from numpy import ma
In [9]: a = ma.array([1,2,3,4],mask=[False,False,True,False],fill_value=0)
In [10]: a
Out[10]:
masked_array(data = [1 2 -- 4],
mask = [False False True False],
Eric Firing wrote:
Ryan May wrote:
Hi,
I just noticed this and found it surprising:
In [8]: from numpy import ma
In [9]: a = ma.array([1,2,3,4],mask=[False,False,True,False],fill_value=0)
In [10]: a
Out[10]:
masked_array(data = [1 2 -- 4],
mask = [False False True False],
On Saturday 19 July 2008 18:41:22 Ryan May wrote:
There was a thread about this a couple months ago, and Pierre GM
explained it. I think the point was that indexing is giving you a new
masked scalar, which is therefore taking the default mask value of the
type. I don't see it as a
