Re: [Matplotlib-users] filled contours, and missing data

[John H. <jdh...@ac...>]

>>>>> "Perry" == Perry Greenfield <pe...@st...> writes:

    Perry> As far as keyword args go, it seems to me that they would
    Perry> be more convenient in many cases, but as Stephen mentions,
    Perry> may be a fair amount of work (and in essence, they are an
    Perry> attribute of the data, so that may be where they belong).

In the context of plotting, it isn't clear that NaNess is an attribute
of the data.  If the data are y = sin(2*pi*t), then NaNess enters only
under certain transformations (eg log) of the data.  From my
perspective, or the perspective of a matplotlib Line, the data are
intact, it is just that under certain transformations the data are
invalid.  Thus the mask is only needed under certain views
(transformations) which the Line class is mostly unaware of.  I think
there are two cases to be distinguished: the case Eric mentioned where
some data points are NaN or None because the measurements are missing
or invalid, and the case where the data are valid but are nan under
certain transformations.

For the latter, it would be maximally useful to be able to do

  #x,y,xt,yt are numerix arrays; transform puts in NaN on domain error
  xt, yt = transform(x, y)  
  
and the drawing routine drops NaN points and handles the connecting
segments properly.  That it only works for float arrays is not a
problem since that is what we are using, eg in the line class

        self._x = asarray(x, Float)
        self._y = asarray(y, Float)

but it is my current understanding that this ain't gonna happen in a
consistent way for Numeric, Numeric3, and numarray across platforms,
because my brief forays into researching this issue turned up posts by
Tim Peters saying that there was no standard way of dealing with IEEE
754 special values across compilers.  If that's true, and we can't fix
it or work around it, then I think boolean masks passed as a kwarg may
be the easiest way to handle this across various numerix
implementations, assuming that Numeric3 comes to fruition and assuming
that there isn't a consistent MA approach that is accessible at the
API level, which I don't know to be true but I get the feeling that
this is a reasonable guess.

I'd be interested in getting feedback from those of you who have
informed opinions on these matters:

  - Is it possible to handle NaN in Numeric/numarray arrays across the
    big three platforms?  I'm pretty sure the answer here is no.

  - Are Numeric and numarray MAs similar enough to be used at the
    C-API level, which is where agg would be checking the mask?  Does
    anyone know whether MAs will be part of the Numeric3 core?  I
    haven't seen any reference to them in the PEP.

JDH