Unfortunately, today is a crazy day for me so I can't test until late  
tonight at the earliest.  But Charlie, I do think we should hold the  
release until we resolve this.  We should be able to fix and test this  
by tomorrow afternoon so perhaps Monday night for the release if  
everything is in order by then and you still have time.

Sent from my iPhone

On Dec 7, 2008, at 1:55 PM, "Jae-Joon Lee" <[EMAIL PROTECTED]> wrote:

> John,
>
> I can't reproduce the error on my intel macbook.
> Anyhow, it seems to me a bug in the code and bugs in numpy.
> (I'm using numpy version 1.1.1, and I'm not sure these bugs are fixed
> in newer numpy. )
> Can you try the patch below and see if this fix your problem?
>
> -JJ
>
>
>
> Index: lib/matplotlib/scale.py
> ===================================================================
> --- lib/matplotlib/scale.py     (revision 6487)
> +++ lib/matplotlib/scale.py     (working copy)
> @@ -301,7 +301,8 @@
>             self._linadjust = (np.log(linthresh) / self._log_base) /  
> linthre
>
>         def transform(self, a):
> -            sign = np.sign(np.asarray(a))
> +            a = np.asarray(a)
> +            sign = np.sign(a)
>             masked = ma.masked_inside(a, -self.linthresh,
> self.linthresh, co   False)
>             log = sign * ma.log(np.abs(masked)) / self._log_base
>             if masked.mask.any():
> @@ -328,6 +329,7 @@
>             self._linadjust = linthresh / (np.log(linthresh) /  
> self._log_bas
>
>         def transform(self, a):
> +            a = np.asarray(a)
>             return np.where(a <= self._log_linthresh,
>                              np.where(a >= -self._log_linthresh,
>
>
>
>
>
>
> On Sat, Dec 6, 2008 at 5:09 PM, John Hunter <[EMAIL PROTECTED]> wrote:
>> There appears to be a bug in the 3rd subplot of symlog_demo.py  
>> because
>> the ticker is generating an OverflowError on my powerbook.
>>
>> The problem is in SymmetricalLogLocator.__call__ when the vmin,  
>> vmax =
>> self._transform.transform((vmin, vmax)) call transforms
>> vmin,vmax=[-1,1] to [-3.30039237078e+17,1.0] numdec is set to
>> 3.30039237078e+17.  Then the while loop runs until I kill the job::
>>
>>       stride = 1
>>       while numdec/stride+1 > self.numticks:
>>           stride += 1
>>
>> This may have something to do with a platform specific floating point
>> computations, because I am seeing different results on a linux box I
>> am also testing on, but even there the results don't look right.  For
>> example, on that box, a 64 bit linux machine, I see [-1,1]  
>> transformed
>> to [2.18190930577e-316, 6.90437063896e-310] and numdec=-1 but the
>> example does run w/o crashing.
>>
>> In any case, it looks like there is some non-robust computation going
>> on, and I'm hoping Michael has a quick insight :-)
>>
>> JDH
>>
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