[Numpy-discussion] bug in ma.masked_all()?

Eric Firing efiring@hawaii....
Tue Dec 2 03:26:35 CST 2008

Pierre GM wrote:
> Eric,
> That's quite a handful you have with this dtype...

Here is a simplified example of how I made it:

dt = np.dtype({'names': ['a','b'], 'formats': ['f', 'f'], 'titles': 
['aaa', 'bbb']})

 From page 132 in the numpy book:

  The fields dictionary is indexed by keys that are the names of the 
fields. Each entry in the dictionary is a tuple fully describing the 
field: (dtype, offset[,title]). If present, the optional title can 
actually be any object (if it is string or unicode then it will also be 
a key in the fields dictionary, otherwise it’s meta-data).


I put the titles in as a sort of additional documentation, and thinking 
that they might be useful for labeling plots; but it is rather hard to 
get the titles back out, since they are not directly accessible as an 
attribute, like names.  Probably I should just omit them.


> So yes, the fix I gave works with nested dtypes and flexible dtypes  
> with a simple name (string, not tuple). I'm a bit surprised with  
> numpy, here.
> Consider:
>  >>> dt.names
>   ('P', 'D', 'T', 'w', 'S', 'sigtheta', 'theta')
> So we lose the tuple and get a single string instead, corresponding to  
> the right-hand element of the name..
> But this single string is one of the keys of dt.fields, whereas the  
> tuple is not. Puzzling. I'm sure there must be some reference in the  
> numpy book, but I can't look for it now.
> Anyway:
> Prior to version 6127, make_mask_descr was substituting the 2nd  
> element of each tuple of a dtype.descr by a bool. Which failed for  
> nested dtypes. Now, we check the field corresponding to a name, which  
> fails in our particular case.
> I'll be working on it...
> On Dec 2, 2008, at 1:59 AM, Eric Firing wrote:
>> dt = np.dtype([((' Pressure, Digiquartz [db]', 'P'), '<f4'), (('  
>> Depth [salt water, m]', 'D'), '<f4'), ((' Temperature [ITS-90, deg  
>> C]', 'T'), '<f4'), ((' Descent Rate [m/s]', 'w'), '<f4'), (('  
>> Salinity [PSU]', 'S'), '<f4'), ((' Density [sigma-theta, Kg/m^3]',  
>> 'sigtheta'), '<f4'), ((' Potential Temperature [ITS-90, deg C]',  
>> 'theta'), '<f4')])
>> np.ma.zeros((2,2), dt)
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