Hi there,
I've been trying to take the numpy docstring and apply the same
methodology to a different project I work on, but there are a couple
details that I think I'm unclear on, and I was hoping for some
pointers or at least reassurances that it's working as intended,
despite Sphinx's protests.
Hi Robert,
> It's not quite an overflow.
>
> In [1]: from numpy import *
>
> In [2]: x = float32(16777216.0)
>
> In [3]: x + float32(0.9)
> Out[3]: 16777216.0
>
> You are accumulating your result in a float32. With the a.sum()
> approach, you eventually hit a level where the next number to add is
Hi all,
I have a possibly naive question. I don't really understand this
particular set of output:
In [1]: import numpy
In [2]: a1 = numpy.random.random((512,512,512)).astype("float32")
In [3]: a1.sum(axis=0).sum(axis=0).sum(axis=0)
Out[3]: 67110312.0
In [4]: a1.sum()
Out[4]: 16777216.0
I re
Hi Everyone,
Thanks for your suggestions and replies. I initially tried what Anne
suggested, modifying the strides in the third dimension to account for
the 8-byte delimiters between slabs, but I couldn't control the
performance as much as I'd like, and I wasn't entirely sure when and
where "real
Hi there,
I've quite a bit of unformatted fortran data that I'd like to use as
input to a memmap, as sort of a staging area for selection of
subregions to be loaded into RAM. Unfortunately, what I'm running
into is that the data was output as a set of "slices" through a 3D
cube, instead of a sing
