On 03/07/13 19:17, Andre' Walker-Loud wrote:
Your terminology is all kixed up and therefore does not make sense.
WE definitely need to know more about the my_class module and do_stuff....
################################################
# generic code skeleton
# import a class I wrote to utilize the 3rd party software
import my_class
This import a module which may contain some code that you wrote
but...
# instantiate the function do_stuff
my_func = my_class.do_stuff()
You don;t instantiate functions you call them. You are setting my_func
to be the return value of do_stuff(). What is that return value? What
does my_func actually refer to?
my_array = numpy.zeros([20,10,10])
# loop over parameters and fill array with desired output
for i in range(loop_1):
for j in range(loop_2):
for k in range(loop_3):
# create tmp_data that has a shape which is the same as data
except the first dimension can range from 1 - 1024 instead of being fixed at 300
''' Is the next line where I am causing memory problems? '''
tmp_data = my_class.chop_data(data,i,j,k)
Again we must guess what the chop_data function is returning. Some
sample data would be useful here.
my_func(tmp_data)
Here you call a function but do not store any return values. Or are you
using global variables somewhere?
my_func.third_party_function()
But now you are accessing an attribute of my_func. What is my_func? Is
it a function or an object? We cannot begin to guess what is going on
without knowing that.
my_array([i,j,k]) = my_func.results() # this is just a floating
point number
''' should I do something to flush tmp_data? '''
No idea, you haven't begun to give us enough information.
--
Alan G
Author of the Learn to Program web site
http://www.alan-g.me.uk/
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