On 15/06/2006 8:27 AM, sonjaa wrote: > Serge Orlov wrote: >> sonjaa wrote: >>> Hi >>> >>> I'm new to programming in python and I hope that this is the problem. >>> >>> I've created a cellular automata program in python with the numpy array >>> extensions. After each cycle/iteration the memory used to examine and >>> change the array as determined by the transition rules is never freed. >>> I've tried using "del" on every variable possible, but that hasn't >>> worked. >> Python keeps track of number of references to every object if the >> object has more that one reference by the time you use "del" the object >> is not freed, only number of references is decremented. >> >> Print the number of references for all the objects you think should be >> freed after each cycle/iteration, if is not equal 2 that means you are >> holding extra references to those objects. You can get the number of >> references to any object by calling sys.getrefcount(obj) > > thanks for the info. I used this several variables/objects and > discovered that little counters i.e. k = k +1 have many references to > them, up tp 10000+. > Is there a way to free them?
If (for example) k refers to the integer object 10, all that means is that you have 10000+ objects whose value is 10. The references to them will be scattered throughout your data structures somewhere. Caveat: I'm not a numpy user. Now read on: I would have thought [by extrapolation from the built-in "array" module] that numpy would allow you to "declare" a homogeneous array of integers which would be internal integers, not python object integers, in which case you would not be getting 10000+ references to whatever "k" refers to. Suggested approaches: read numpy manual, publish relevant parts of your code, wait for a numpy guru to appear. HTH, John -- http://mail.python.org/mailman/listinfo/python-list
