[SciPy-dev] MCMC, Kalman Filtering, AI for SciPy?

[Travis Oliphant]

Fernando Perez wrote:

> Travis Oliphant schrieb:
>
>>> 2. The matrixmultiply != bug I recently reported is _very_ serious 
>>> for people working with large matrices.  I also reported it in the 
>>> numpy list, but nobody replied.  Since scipy can trivially work 
>>> around it with the one-liner I showed, I think this really should be 
>>> done.
>>
>>
>>
>> I think you will see that I released a new version of Numeric that 
>> fixed this problem.   See 23.5
>
>
> Great!  But since you didn't mention anything on the list, and my 
> telepathy link has been acting up lately, I missed it ;)


Sorry, I assumed you were monitoring releases of Numeric.  I should have 
said something, or I should let you have my new telepathy upgrade...

>
>
> I also had this old patch lying around, which I sent to the list about 
> a year ago.  It's far from critical, so feel free to drop it if you 
> don't like it/disagree.  I'll just paste my old email and reattach the 
> patch (I hope it still applies).
>
> here's a simple patch for pilutil which adds a simple 'flatten' option 
> to the
> image reading functions imread.  Here are the resulting definition and 
> docstrings:
>
> In [2]: scipy.fromimage?
> Definition:     scipy.fromimage(im, flatten=0)
> Docstring:
>      Takes a PIL image and returns a copy of the image in a Numeric 
> container.
>      If the image is RGB returns a 3-dimensional array:  arr[:,:,n] is 
> each
> channel
>
>      Optional arguments:
>
>       - flatten (0): if true, the image is flattened by calling 
> convert('F') on
>       the image object before extracting the numerical data.  This 
> flattens the
>       color layers into a single grayscale layer.  Note that the 
> supplied image
>       object is NOT modified.
>
>
> In [3]: scipy.imread?
> Definition:     scipy.imread(name, flatten=0)
> Docstring:
>      Read an image file from a filename.
>
>      Optional arguments:
>
>       - flatten (0): if true, the image is flattened by calling 
> convert('F') on
>       the resulting image object.  This flattens the color layers into 
> a single
>       grayscale layer.
>
>
> This is useful in case you want to load straight from an image file 
> (jpeg,
> tiff, ...) but you want a single grayscale array to do numerics on.  The
> change is fully backwards compatible.  I did it because we needed here to
> easily read images for testing some numerical transformations without 
> dealing
> with the color channels.  It was easier to patch scipy than to tell my
> coworkers to remember to convert every image first :)
>
> Regards,
>
> Fernando.


Seems reasonable.  If there are no complaints.  I'll add it.