I would like to do simple division and average using jit function where nopython = True. my jit function goes however this throws me an error, what would be the workaround for this? I am trying to do this without the loop, any lights would be appreiciate. Answer numba doesn’t support some arguments for some of numpy modules (e.g. np.mean()
Tag: jit
Why does this code fail to compile with Numba?
I have a sample code that illustrates my issue. If you run: It will fail with: argsort is supposed to argsort on the last axis. Essentially it should give me: I thought copying the arr2 array (with copy()) could solve as it would make the array contiguous in memory (instead of a view), but it fails with the same message
(JIT) Compilation of Python code with FFI library calls
I’m using Python with a library that uses cppyy to get access to a ton of C++ functions natively in Python. However, the calls to cppyy methods take a lot of time, and looping in Python with a library call means that overhead becomes a serious issue. Here’s an example of what I mean: This code would be really fast
Find minimum difference between two vectors with numba
I’ve tried to optimize searching for minimum value between two numpy vectors with numba. There is speed up and result is correct until I use prange and parallel=True option. I understand that the issue is in sharing variables min_val, tmp, min_val_idx_a, min_val_idx_b during parallel execution (maybe with parallel threads). Is there way to overcome the problem and use numba in
Using typed dictionaries in ahead of time compilation in numba
I’m trying to use ahead of time compilation in numba on a function that takes a numba typed dictionary as its input. The file compiles without errors, but when I load the resulting module I get an error: An example function that produces the same error is: This function will be called by another function in the compiled code. Answer