[Numpy-discussion] R: R: R: fast numpy.fromfile skipping data chunks

2013-03-13 Thread Andrea Cimatoribus
On top of that, there is another issue: it can be that the data available 
itself is not a multiple of dtype, since there can be write errors at the end 
of the file, and I don't know how to deal with that.

Da: numpy-discussion-boun...@scipy.org [numpy-discussion-boun...@scipy.org] per 
conto di Andrea Cimatoribus
Inviato: mercoledì 13 marzo 2013 15.37
A: Discussion of Numerical Python
Oggetto: [Numpy-discussion] R: R: fast numpy.fromfile skipping data chunks

Indeed, but that offset it should be a multiple of the byte-size of dtype as 
the help says.
Indeed, this is silly.


Da: numpy-discussion-boun...@scipy.org [numpy-discussion-boun...@scipy.org] per 
conto di Nathaniel Smith [n...@pobox.com]
Inviato: mercoledì 13 marzo 2013 15.32
A: Discussion of Numerical Python
Oggetto: Re: [Numpy-discussion] R: fast numpy.fromfile skipping data chunks

On Wed, Mar 13, 2013 at 2:18 PM, Andrea Cimatoribus
andrea.cimatori...@nioz.nl wrote:
 This solution does not work for me since I have an offset before the data 
 that is not a multiple of the datatype (it's a header containing various 
 stuff).

np.memmap takes an offset= argument.

-n
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[Numpy-discussion] R: R: R: fast numpy.fromfile skipping data chunks

2013-03-13 Thread Andrea Cimatoribus
Indeed, but that offset it should be a multiple of the byte-size of dtype as 
the help says.

My mistake, sorry, even if the help says so, it seems that this is not the case 
in the actual code. Still, the problem with the size of the available data 
(which is not necessarily a multiple of dtype byte-size) remains.
ac
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Re: [Numpy-discussion] R: R: R: fast numpy.fromfile skipping data chunks

2013-03-13 Thread Nathaniel Smith
On Wed, Mar 13, 2013 at 2:46 PM, Andrea Cimatoribus
andrea.cimatori...@nioz.nl wrote:
Indeed, but that offset it should be a multiple of the byte-size of dtype 
as the help says.

 My mistake, sorry, even if the help says so, it seems that this is not the 
 case in the actual code. Still, the problem with the size of the available 
 data (which is not necessarily a multiple of dtype byte-size) remains.

Worst case you can always work around such issues with an extra layer
of view manipulation:

# create a raw view onto the contents of the file
file_bytes = np.memmap(path, dtype=np.uint8, ...)
# cut out any arbitrary number of bytes from the beginning and end
data_bytes = file_bytes[...some slice expression...]
# switch to viewing the bytes as the proper data type
data = data_bytes.view(dtype=np.uint32)
# proceed as before

-n
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