Time my code

Time my code

I timed my update_fractal() function for different scenarios in the final code using the time module from python.

What? I only changed the max_levels, nothing else has changed yet.
Amount times executed? 3 times
This is the average time per level that the update_fractal() takes to execute:

max_level	average (in seconds)
0	0.0055 sec
1	0.0154 sec
2	0.1101 sec

What? I change the rotation for the 3 axes, then I change the max_level:
Amount times executed? 3 times
Results - time it takes update_fractal() to execute:

max_level	first time	second time	third time
0	0.0080 sec	0.0085 sec	0.0099 sec
1	0.0177 sec	0.0198 sec	0.0232 sec
2	0.1376 sec	0.1372 sec	0.1461 sec

What? I empty the canvas and I change my desired level and then change all properties.

max_level	amount times update_fractal executed	min. value	max. value	average
0	54	0.0010 sec	0.0108 sec	0.0018 sec
1	69	0.0065 sec	0.0319 sec	0.0096 sec
2	42	0.0816 sec	0.5206 sec	0.3599 sec

Conclusion: I find that with max_level = 2, things are a lot harder when I want to change things quickly. It’s just about right. So you have to be a bit careful to adjust things, a bit more patient to adjust things.

What? I also timed the time to calculate everything in my refactored matplotlib project (without interactions).
Amount times executed? 6 times
Result:

project	average
without NumPy	0.1591 sec
with NumPy	0.0914 sec

Conclusion: when refactored with NumPy, the code is faster than without NumPy. NumPy then also makes for faster calculations because it uses N-dimensional arrays and no python list to go over.