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| Date | Mon, 18 Feb 2013 19:10:55 -0500 |
| From | Dave Angel <davea@davea.name> |
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| Subject | Re: memory management |
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On 02/18/2013 10:29 AM, Sudheer Joseph wrote: > HI, > I have been trying to compute cross correlation between a time series at a location f(1) and the timeseries of spatial data f(XYT) and saving the resulting correlation coefficients and lags in a 3 dimensional array which is of fairly big size. Though the code I made for this purpose works up to few iterations then it hangs due to apparent memory crunch. Can anybody suggest a better way to handle this situation so that the computation and data storing can be done with out hangups. Finally I intend to save the data as netcdf file which is not implemented as of now. Below is the piece of code I wrote for this purpose. > Python version and OS please. And is the Python 32bit or 64bit? How much RAM does the computer have, and how big are the swapfiles ? "Fairly big" is fairly vague. To some people, a list with 100k members is huge, but not to a modern computer. How have you checked whether it's running out of memory? Have you run 'top' on it? Or is that just a guess? I haven't used numpy, scipy, nor matplotlib, and it's been a long time since I did correlations. But are you sure you're not just implementing an O(n**3) algorithm or something, and it's just extremely slow? > from mpl_toolkits.basemap import Basemap as bm, shiftgrid, cm > import numpy as np > import matplotlib.pyplot as plt > from netCDF4 import Dataset > from math import pow, sqrt > import sys > from scipy.stats import t <snip> -- DaveA
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memory management Sudheer Joseph <sjo.india@gmail.com> - 2013-02-18 07:29 -0800
Re: memory management Dave Angel <davea@davea.name> - 2013-02-18 19:10 -0500
Re: memory management Sudheer Joseph <sjo.india@gmail.com> - 2013-02-18 17:13 -0800
Re: memory management Sudheer Joseph <sjo.india@gmail.com> - 2013-02-18 17:13 -0800
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