[Numpy-discussion] find location of maximum values

Benjamin Root ben.root@ou....
Mon Jan 9 17:22:39 CST 2012

On Monday, January 9, 2012, questions anon <questions.anon@gmail.com> wrote:
> thanks for the responses.
> Unfortunately they are not matching shapes
>>>> print TSFC.shape, TIME.shape, LAT.shape, LON.shape
> (721, 106, 193) (721,) (106,) (193,)
> So I still receive index out of bounds error:
> numpy array of max values for the month
> 2928
>>>>maxtemp=tmax.ravel()[maxindex] #or maxtemp=TSFC.max()
> 35.5 (degrees celcius)
> IndexError: index out of bounds
> lonloc=LON[tmax.argmax()]
> timeloc=TIME[tmax.argmax()]
> Any other ideas for this type of situation?
> thanks

Right, we realize they are not the same shape.  When you use argmax on the
temperature data, take that index number and use unravel_index(index,
TSFC.shape) to get a three-element tuple, each being the index in the TIME,
LAT, LON arrays, respectively.

Ben Root

> On Wed, Jan 4, 2012 at 10:29 PM, Derek Homeier <
derek@astro.physik.uni-goettingen.de> wrote:
>> On 04.01.2012, at 5:10AM, questions anon wrote:
>> > Thanks for your responses but I am still having difficuties with this
problem. Using argmax gives me one very large value and I am not sure what
it is.
>> > There shouldn't be any issues with the shape. The latitude and
longitude are the same shape always (covering a state) and the temperature
(TSFC) data are hourly for a whole month.
>> There will be an issue if not TSFC.shape == TIME.shape == LAT.shape ==
>> One needs more information on the structure of these data to say
anything definite,
>> but if e.g. your TSFC data have a time and a location dimension, argmax
>> per default return the index for the flattened array (see the argmax
>> for details, and how to use the axis keyword to get a different output).
>> This might be the very large value you mention, and if your location
data have fewer
>> dimensions, the index will easily be out of range. As Ben wrote, you'd
need extra work to
>> find the maximum location, depending on what maximum you are actually
looking for.
>> As a speculative example, let's assume you have the temperature data in
>> array(ntime, nloc) and the position data in array(nloc). Then
>> TSFC.argmax(axis=1)
>> would give you the index for the hottest place for each hour of the month
>> (i.e. actually an array of ntime indices, and pointer to so many
different locations).
>> To locate the maximum temperature for the entire month, your best way
would probably
>> be to first extract the array of (monthly) maximum temperatures in each
location as
>> tmax = TSFC.max(axis=0)
>> which would have (in this example) the shape (nloc,), so you could
directly use it to index
>> LAT[tmax.argmax()]   etc.
>> Cheers,
>>                                                Derek
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/numpy-discussion/attachments/20120109/4b1e0db4/attachment.html 

More information about the NumPy-Discussion mailing list