I would go with scikits.audiolab to get you wav data into numpy arrays,
as David mentioned. I use it all the time for bioacoustic research and
it is great (unfortunately still in beta, but works well in practice).
Reading sound data of 5 seconds @ 32000 Hz and finding/measuring your
tones fast sho
gt;> f.close()
With most real data file size can be smaller because you have the
option of enabling compression.
But I must admit that I haven't tried reading HDF5 in Matlab or C (and
never will); I know it is possible, but I don't know how difficult it
is.
Cheers, Gabriel
On T
PyTables is an efficient way of doing it (http://www.pytables.org). You
essentially write data to a HDF5 file, which is portable and can be read
in Matlab or in a C program (using the HDF5 library).
Gabriel
On Tue, 2008-05-20 at 09:32 -0400, Gary Pajer wrote:
> I want to store data in a way that
Does numpy have something like Matlab's accumarray?
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/accumarray.html
Best, Gabriel
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-d
Doesn't work here:
In [1]: import numpy as npy
In [2]: npy.fromstring('23:09:01', dtype=int, sep=':')
Out[2]: array([23, 0])
In [3]: npy.__version__
Out[3]: '1.0.5.dev4722'
In [4]: npy.fromstring('23:09:01', dtype=int, sep=':', count=3)
Out[4]: array([ 23, 0, 151904160])
...
Pe
I found a matlab script that I want to translate into numpy, but have
difficulties with understanding indexing in matlab. I haven't used
matlab very much and I was hoping that someone could help with the
following:
It says:
Uns = ones(1,m);
... and then later
Xijm(:,Uns)
