Eric's probably right and it's indexing with a masked array that's causing
you trouble.
Since you seem to say your NaN values correspond to your mask, you should
be able to simply do:
modelData[modeData.mask] = dataMin
Note that in further processing it may then make more sense to remove the
mask
On Fri, Jan 27, 2012 at 4:37 PM, Howard wrote:
> I have found, in using tricontourf, that in the mapping from data values
> to color values, the range of the data seems to include even the data from
> the masked triangles. This causes the data to be either monochromatic or
> bi-chromatic (the hi
On 1/27/12 5:21 PM, Eric Firing wrote:
On 01/27/2012 11:18 AM, Howard wrote:
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
times
On 01/27/2012 11:18 AM, Howard wrote:
> 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
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
modelD
Hi Olivier
I added this to the code:
print "modelData:", type(modelData), modelData.shape, modelData.size
print "dataMin:", type(dataMin)
and got
modelData: (1767734,) 1767734
dataMin:
What's funny is I tried the example from
http://docs.scipy.org/doc/numpy-1.6.0/numpy-user.pdf
and it wor
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
> Hi all
>
> I am a fairly recent convert to python and I have got a question that's
> got me stumped. I hope
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 t
