The question is very straight forward. Content here is information collected during the run of an interconnected system. I simplified functions to emphasise the bottlenecks from line_profiler into three dependend functions objectively similar to real code.
As of now it seems all lines are mandatory, but I refuse to believe this. I did try simplifying logical parts with .all() and .any() but either I am not proficient in Python, or I keep running into a bizarre limitation; just keep giving me a different result than expected.
If you are unable to gather full use case of the 3 functions, try to comprehend on a purely syntactic manner (while at least preserving same number of variables) and provide a usable solution to achieve the same functionality.
Total time: 419.632 s
File: switch_array_logic.py
Function: func_A at line 336
Line # Hits Time Per Hit % Time Line Contents
==============================================================
336 @profile
337 def func_A(_switch,_loc,_prev_state=None,_cur_state=None,bulb_on=True):
338 43048749 27529633.0 0.6 6.6 if bulb_on:
339 43048651 43186202.0 1.0 10.3 _p_cur_state = _switch[_loc][2]
340 43048651 42282929.0 1.0 10.1 _p_prev_state = _switch[_loc-1][2]
341 else:
342 98 80.0 0.8 0.0 _p_prev_state = _prev_state
343 98 54.0 0.6 0.0 _p_cur_state = _cur_state
348 43048749 38735332.0 0.9 9.2 cond_11 = (_p_cur_state >= 0)
349 43048749 35887392.0 0.8 8.6 cond_10 = (_p_cur_state < 0)
350 43048749 34747819.0 0.8 8.3 cond_00 = (_p_prev_state < 0)
351 43048749 34685101.0 0.8 8.3 cond_01 = (_p_prev_state > 0)
352
353 43048749 24860540.0 0.6 5.9 cond_x = cond_00 and cond_11
354 43048749 24083554.0 0.6 5.7 cond_y = cond_10 and cond_01
355 43048749 24902602.0 0.6 5.9 condition = cond_x or cond_y
356
357 43048749 23279349.0 0.5 5.5 _brighness = 0
358 43048749 23704315.0 0.6 5.6 if condition:
359 21573867 18852346.0 0.9 4.5 _brighness = _p_prev_state/2
360 43048749 22894531.0 0.5 5.5 return _brighness
Total time: 66.9593 s
File: switch_array_logic.py
Function: func_B at line 362
Line # Hits Time Per Hit % Time Line Contents
==============================================================
362 @profile
363 def func_B(_switch,_pos,_loc,_brighness):
364 43638012 66959275.0 1.5 100.0 return _switch[_pos][3] - _switch[_loc][3] - _brighness
Total time: 9.59384 s
File: switch_array_logic.py
Function: func_C at line 378
Line # Hits Time Per Hit % Time Line Contents
==============================================================
378 @profile
379 def func_C(_switchs_slice,_valid,_PH_LEVEL):
380 114012 82093.0 0.7 0.9 _idx = 0
381 114012 2403035.0 21.1 25.0 _brighness = func_A(_switchs_slice,_idx+1)
382 809223 583712.0 0.7 6.1 for _pos in range(1, _switchs_slice.shape[0]):
383 808216 831149.0 1.0 8.7 if _valid and _switchs_slice[_idx][0] < _switchs_slice[_pos][0]:
385 57307 44704.0 0.8 0.5 return False,_pos
386 750909 1686519.0 2.2 17.6 elif ~_valid and _switchs_slice[_idx][1] > _switchs_slice[_pos][1]:
388 47536 41899.0 0.9 0.4 return False,_pos
389 703373 3320805.0 4.7 34.6 _ph_out = func_B(_switchs_slice,_pos,_idx,_brighness)
391 703373 592597.0 0.8 6.2 if abs(_ph_out) > _PH_LEVEL[1] :
393 8162 6334.0 0.8 0.1 return True, _pos #Successful Case
395 1007 990.0 1.0 0.0 return False,_switchs_slice.shape[0]
Additionally, as I am not familiar with Cython, but can someone try to provide an optimised version of this in Cython in answers really appreciate it. Not sure we will use it in the code. But I would very much like to see performance disparity.
Thanks in advance!
