[Numpy-discussion] python array

[Nicolas Rougier]

Seems to be related to the masked values:

print r2010[:3,:3]
[[-- -- --]
 [-- -- --]
 [-- -- --]]

print abs(r2010)[:3,:3]
[[-- -- --]
 [-- -- --]
 [-- -- --]]


print r2010[ r2010[:3,:3] <0 ]
[-- -- -- -- -- -- -- -- --]

print r2010[ abs(r2010)[:3,:3] < 0]
[]

Nicolas



On 13 Mar 2014, at 16:52, Sudheer Joseph <sudheer.joseph at yahoo.com> wrote:

> Dear experts,
>                      I am encountering a strange behaviour of python data array as below. I have been trying to use the data from a netcdf file(attached herewith) to do certain calculation using below code. If I take absolute value of the same array and look for values <.5  I get a different value than the original array. But the fact is that this particular case do not have any negative values in the array( but there are other files where it can have negative values so the condition is put). I do not see any reason for getting different numbers for values <.5 in case of bt and expected it to be same as that of r2010. If any one has a guess on what is behind this behaviour please help.
> 
> 
> In [14]: from netCDF4 import Dataset as nc
> 
> In [15]: nf=nc('r2010.nc')
> In [16]: r2010=nf.variables['R2010'][:]
> In [17]: bt=abs(r2010)
> In [18]: bt[bt<=.5].shape
> Out[18]: (2872,)
> In [19]: r2010[r2010<.5].shape
> Out[19]: (36738,)
> 
> 
> bt.min()
> Out[20]: 0.0027588337040836768
> 
> In [21]: bt.max()
> Out[21]: 3.5078965479057089
> In [22]: r2010.max()
> Out[22]: 3.5078965479057089
> In [23]: r2010.min()
> Out[23]: 0.0027588337040836768
> 
> 
>  
> ***************************************************************
> Sudheer Joseph 
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