Oh, one other thing I should mention:
I did the install of numpy yesterday and I also have 1.6.1
Howard
On 1/27/12 4:54 PM, Howard wrote:
Hi Olivier
I added this to the code:
print "modelData:", type(modelData), modelData.shape, modelData.size
print "dataMin:", type(dataMin)
and got
modelData: <class 'numpy.ma.core.MaskedArray'> (1767734,) 1767734
dataMin: <type 'float'>
What's funny is I tried the example from
http://docs.scipy.org/doc/numpy-1.6.0/numpy-user.pdf
and it works fine for me. Maybe 1.7 million is over some threshhold?
Thanks
Howard
>>> myarr = np.ma.core.MaskedArray([1., 0., np.nan, 3.])
>>> myarr[np.isnan(myarr)] = 30
>>> myarr
masked_array(data = [ 1. 0. 30. 3.],
mask = False,
fill_value = 1e+20)
On 1/27/12 4:42 PM, Olivier Delalleau wrote:
What are the types and shapes of modelData and dataMin? (it works for
me with modelData a (3, 4) numpy array and dataMin a Python float,
with numpy 1.6.1)
-=- Olivier
2012/1/27 Howard <how...@renci.org <mailto:how...@renci.org>>
Hi all
I am a fairly recent convert to python and I have got a question
that's got me stumped. I hope this is the right mailing list:
here goes :)
I am reading some time series data out of a netcdf file a single
timestep at a time. If the data is NaN, I want to reset it to
the minimum of the dataset over all timesteps (which I already
know). The data is in a variable of type
numpy.ma.core.MaskedArray called modelData.
If I do this:
for i in range(len(modelData)):
if math.isnan(modelData[i]):
modelData[i] = dataMin
I get the effect I want, If I do this:
modelData[np.isnan(modelData)] = dataMin
it doesn't seem to be working. Of course I could just do the
first one, but len(modelData) is about 3.5 million, and it's
taking about 20 seconds to run. This is happening inside of a
rendering loop, so I'd like it to be as fast as possible, and I
thought the second one might be faster, and maybe it is, but it
doesn't seem to be working! :)
Any ideas would be much appreciated.
Thanks
Howard
--
Howard Lander <mailto:how...@renci.org>
Senior Research Software Developer
Renaissance Computing Institute (RENCI) <http://www.renci.org>
The University of North Carolina at Chapel Hill
Duke University
North Carolina State University
100 Europa Drive
Suite 540
Chapel Hill, NC 27517
919-445-9651
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--
Howard Lander <mailto:how...@renci.org>
Senior Research Software Developer
Renaissance Computing Institute (RENCI) <http://www.renci.org>
The University of North Carolina at Chapel Hill
Duke University
North Carolina State University
100 Europa Drive
Suite 540
Chapel Hill, NC 27517
919-445-9651
--
Howard Lander <mailto:how...@renci.org>
Senior Research Software Developer
Renaissance Computing Institute (RENCI) <http://www.renci.org>
The University of North Carolina at Chapel Hill
Duke University
North Carolina State University
100 Europa Drive
Suite 540
Chapel Hill, NC 27517
919-445-9651
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion