On 2012/09/04 9:09 AM, Benjamin Root wrote:
>
>
> On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremb...@gmail.com
> <mailto:paulhtremb...@gmail.com>> wrote:
>
>
>     The following Python code:
>
>      >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
>
>     Produces this error with Python 3.2:
>
>     Traceback (most recent call last):
>        File "scripts/audit_reports_weekly.py", line 150, in <module>
>          ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
>        File
>     
> "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
>     line 6741, in fill_between
>          y1 = ma.masked_invalid(self.convert_yunits(y1))
>        File
>     
> "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
>     line 2241, in masked_invalid
>          condition = ~(np.isfinite(a))
>     TypeError: ufunc 'isfinite' not supported for the input types, and
>     the inputs could not be safely coerced to any supported types
>     according to the casting rule ''safe''
>
>
>     [Decimal('3619.900530366609820157812617'), .....]
>
>     If I change the list from type Decimal to type float, then I don't
>     get the error. Likewise, if I use Python 2.7, I also don't get an error.
>
>     After reading over the error message, I realize that this error
>     really results because of numpy, not matplotlib. But I'll go ahead
>     and post this message, in case you are unaware of the problem.
>
>
> Just a quick note, mpl v1.1.x is not officially supported for py3k.  The
> upcoming release of v1.2.0 will be the first official release with such
> support.
>
> That being said, it probably would be a good idea to make sure where the
> bug lies for this one (numpy or matplotlib).  Which version of numpy are
> you using?

To clarify my previous message: I think we will remain mostly at the 
mercy of numpy, which may change from version to version, to determine 
what we can handle.  Apart from registered unit types, we fall back on 
numpy, typically masked_invalid, to handle inputs.  If we really want to 
handle Decimal reliably, then it probably has to be done within the 
units framework.

Eric


>
> Ben Root


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