Hmm
I'm trying to duplicate the behavior with a simple program
---------
import numpy
datasize=5529000
numrows=121
fd=open("biggie","w")
fd.close()
big=numpy.memmap("biggie",mode="readwrite",
shape=(numrows,datasize),dtype=numpy.float32)
c=numpy.ones(shape=(datasize,),dtype=numpy.float32)
for r in range(0,numrows):
print r
big[r,:] = c
c[r] = 2.0
---------------------
but it is fast. Hmmm. Any ideas about where to go from here?
Mathew
Robert Kern wrote:
> Mathew Yeates wrote:
>
>> Hi
>>
>> I have a line in my program that looks like
>> outarr[1,:] = computed_array
>> where outarr is a memory mapped file. This takes forever.
>>
>> I checked and copying the data using "cp" at the command line takes 1
>> or 2 seconds. So the problem can't be attributed simply to disk i/o. Is
>> it because the elements are being written one at a time? Any ideas on
>> how to speed this up?
>>
>
> Memory-mapping is highly platform dependent. What platform are you on? What
> are
> the sizes of the arrays? Can you write up a small, self-contained script that
> demonstrates the issue so we can experiment and try things out on different
> machines?
>
>
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