Reducing numpy memory footprint in long-running application

Question

In my application one hundred numpy arrays (1000 complex elements each) are generated and filled with data. Then over many iterations, the array elements are modified over and o

Answer 1

Via using the system monitor and code inspection/commenting, I found the memory leak. It was caused by comparing a numpy array with an empty list in a different file. I will dig into the leak in a different place and vote to delete this question as I find it too specific to assist anyone else.

[Update 1]: New question describing the source of the problem: Why does comparison of a numpy array with a list consume so much memory?