Releasing memory of huge numpy array in IPython
UPDATE:- This problem solved itself after a machine reboot. Not yet able to figure out why this error was happening before.
I have a function that loads a huge numpy array (~ 980MB) and returns it.
When I first start Ipython and call this function, it loads the array into the variable without any problem.
But if I run the same command again, it exits raising a "Memory Error".
I tried the following,
del hugeArray
Still the same error was occurring. I even tried the following
del hugeArray
gc.collect()
gc.collect()
Initially, gc.collect()
returned 145 and the second call returned 48.
But even after this when I call the function, it was still raising a Memory error.
The only way I could load again was to restart ipython. Is there something I can do to free all memory in ipython, so that I don't have to restart it?
----------------Update
Following is the output of %whos
Variable Type Data/Info
------------------------------
gc module <module 'gc' (built-in)>
gr module <module 'Generate4mRamp' <...>rom 'Generate4mRamp.pyc'>
np module <module 'numpy' from '/us<...>ages/numpy/__init__.pyc'>
plt module <module 'matplotlib.pyplo<...>s/matplotlib/pyplot.pyc'>
Out of this, gr is my module containing the function which i used to load the data cube.
---------How to Reproduce the error
The following simple function is able to reproduce the error.
import numpy as np
import gc
def functionH():
cube=np.zeros((200,1024,1024))
return cube
testcube=functionH() #Runs without any issue
del testcube
testcube=functionH() # Raises Memory Error
del testcube
gc.collect()
gc.collect()
testcube=functionH() # Still Raises Memory Error
This error is occurring only in Ipython. In simple python (>>>) after giving del testcube
, there is no Memory Error.
Are you looking at the value? IPython caches output variables as e.g. Out[8]
, so if you examine it, it will be kept in memory.
You can do %xdel testcube
to delete the variable and remove it from IPython's cache. Alternatively, %reset out
or %reset array
will clear either all your output history, or only references to numpy arrays.