How NumPy speeds array math in Python. A big part of NumPy’s speed comes from using machine-native datatypes, instead of Python’s object types.

When you call the Cython function in your Python code, send the entire NumPy array object as an argument for that function call. Perform all the iteration over the object in Cython.

Gommers added, "Really long-term I expect the NumPy 'execution engine' (i.e., the C and Python code that does the heavy lifting for fast array operations) to become less and less relevant, and the ...

This NumPy version performs admirably, clocking in at around 28.77 ns per element -- almost two times faster than the pure Python rendition. Comparison established -- we have a clear winner. However, ...

We really recommend that fans of Python and NumPy give this one a look over! Posted in Arduino Hacks , Microcontrollers Tagged fft , matrix , microcontroller , micropython , numpy , python , ulab ...