Hello, I am having a problem with the LinearNDInterpolator in SciPy, where it looks like there is a memory leak. I have a simple example here, all I do is setup a very small LinearNDInterpolator object and call the interpolator many times in a loop: https://gist.github.com/aronnem/707dfeec07b74888fb7390d828684184 Note that if the "pts_list" and "vals" are swapped with the integer versions, there is no leak. Using the floats seems to produce the leak. I have tried both conda and Canopy installed environments, they all seem to have the same behavior. For example, here is the output I get with a scipy 1.1.0 compiled with Cython 0.28.5, numpy 1.13.3 on Mac OS X: rss_used= 4 KB vms_used= 0 KB rss_used= 2516 KB vms_used= 2560 KB rss_used= 4836 KB vms_used= 5188 KB rss_used= 6880 KB vms_used= 6664 KB rss_used= 9408 KB vms_used= 10248 KB rss_used= 11680 KB vms_used= 12076 KB rss_used= 14356 KB vms_used= 15872 KB rss_used= 16736 KB vms_used= 17792 KB rss_used= 19416 KB vms_used= 20496 KB rss_used= 22100 KB vms_used= 23472 KB The only workaround I have found so far is to downgrade my numpy version to 1.11.3. So that seems to suggest it is a numpy problem; however this function is implemented in cython, so I am not sure how to tell whether this is a numpy, scipy, or cython problem. Regards, Aronne