matplotlib

Plotting with 'nans' doesn't work as far as I know.
Read the discussion on using masked arrays posted in the last 2 weeks.
They work well in my experience,
Mark

On Tuesday 12 July 2005 01:03 pm, Mark Bakker wrote:
> Plotting with 'nans' doesn't work as far as I know.
> Read the discussion on using masked arrays posted in the last 2 weeks.

I had asked about plotting with NaNs a while back. John says the problem is 
with the way the Agg backend deals with them. plot([0,nan,2,3],'o') works, 
plot([nan,1,2,3],'o') does not.

-- 

Darren

>>     x=[1,2,nan,4,5] plot(x) plots a single line.  
>>     I expect two segments and a gap. 

On Mon, 11 Jul 2005, Eric Firing apparently wrote: 
> Slightly modifying a reply to a similar question not long ago: 
> At present, you need to use masked arrays instead of NaN. 

So if I use masked arrays, 
I should get two segments and a gap in the above case? 

I'm not familiar with masked arrays. 
Sounds like I'll have to learn about them. 

But I still feel something is missing from this discussion. 
Would it be odd/hard for plot() to have an option that says, 
effectively, mask NaNs so that the expected behavior results? 

Thanks, 
Alan

Alan,

> 
> But I still feel something is missing from this discussion. 
> Would it be odd/hard for plot() to have an option that says, 
> effectively, mask NaNs so that the expected behavior results? 

Again, the problem is that automatic masking of nans would be easy with 
numarray but not at all easy with Numeric.  Given that mpl is designed 
to work the same with numarray and Numeric, it is not easy to build good 
nan support into mpl.  This will change when the successor to Numeric 
becomes common enough that support for old Numeric can be dropped, but 
not soon.  In the meantime, if you want to use nans, you can do 
something like this:

 >>> import numarray as N
 >>> from numarray.ieeespecial import isnan, nan
 >>> import numarray.ma as ma
 >>> a = N.array([1, 2, nan, 3, 4])
 >>> b = ma.masked_where(isnan(a), a)

Now you can plot b and it will have a gap in the middle.

Eric

On Tue, 12 Jul 2005, Eric Firing apparently wrote: 
>>> import numarray as N 
>>> from numarray.ieeespecial import isnan, nan 
>>> import numarray.ma as ma 
>>> a = N.array([1, 2, nan, 3, 4]) 
>>> b = ma.masked_where(isnan(a), a) 

> Now you can plot b and it will have a gap in the middle. 

Thanks.
Alan

Hi Eric,

Eric Firing wrote:
> Again, the problem is that automatic masking of nans would be easy with 
> numarray but not at all easy with Numeric.  Given that mpl is designed 
> to work the same with numarray and Numeric, it is not easy to build good 
> nan support into mpl.  This will change when the successor to Numeric 
> becomes common enough that support for old Numeric can be dropped, but 
> not soon.  In the meantime, if you want to use nans, you can do 
> something like this:
> 
>  >>> import numarray as N
>  >>> from numarray.ieeespecial import isnan, nan
>  >>> import numarray.ma as ma
>  >>> a = N.array([1, 2, nan, 3, 4])
>  >>> b = ma.masked_where(isnan(a), a)
> 
> Now you can plot b and it will have a gap in the middle.
> 

I tried it as described above but plotting with pylab.plot results in an error
message:

MAError: Cannot automatically convert masked array to Numeric because data
                    is masked in one or more locations.

Am I missing something?

Regards, Christian

Christian,

>>
>>  >>> import numarray as N
>>  >>> from numarray.ieeespecial import isnan, nan
>>  >>> import numarray.ma as ma
>>  >>> a = N.array([1, 2, nan, 3, 4])
>>  >>> b = ma.masked_where(isnan(a), a)
>>
>> Now you can plot b and it will have a gap in the middle.
>>
> 
> 
> I tried it as described above but plotting with pylab.plot results in an 
> error message:
> 
> MAError: Cannot automatically convert masked array to Numeric because data
>                    is masked in one or more locations.
> 
> Am I missing something?
> 
> Regards, Christian
> 

The problem is that you need to use numarray, not Numeric, as your 
numerix choice.  In your matplotlibrc file, use

numerix      : numarray # Numeric or numarray

instead of the default, which is Numeric.

Unfortunately, although there is some partial compatibility between 
Numeric and numarray, it does not extend to one being able to read 
masked arrays from the other, so you need to use one or the other 
consistently.  And if you want to work with nans, then numarray is the 
one you need to use.

Eric