Calculating distance more quickly #2
Description
Rather than using math functions (such as math.sqrt and math.pow) to calculate euclidean distance, use the builtin operators: x**2 and x**0.5
The code object disassembly shows fewer instructions in the latter:
>>> def foper(x1, y1, x2, y2): #Using builtins
... return ((x2-x1)**2 + (y2-y1)**2)**0.5
...
>>> import math
>>> def ffunc(x1, y1, x2, y2): #Using functions from math module
... return math.sqrt(math.pow(x2-x1,2) + math.pow(y2-y1,2))
...
>>> dis.dis(foper)
2 0 LOAD_FAST 2 (x2)
3 LOAD_FAST 0 (x1)
6 BINARY_SUBTRACT
7 LOAD_CONST 1 (2)
10 BINARY_POWER
11 LOAD_FAST 3 (y2)
14 LOAD_FAST 1 (y1)
17 BINARY_SUBTRACT
18 LOAD_CONST 1 (2)
21 BINARY_POWER
22 BINARY_ADD
23 LOAD_CONST 2 (0.5)
26 BINARY_POWER
27 RETURN_VALUE
>>> dis.dis(ffunc)
2 0 LOAD_GLOBAL 0 (math)
3 LOAD_ATTR 1 (sqrt)
6 LOAD_GLOBAL 0 (math)
9 LOAD_ATTR 2 (pow)
12 LOAD_FAST 2 (x2)
15 LOAD_FAST 0 (x1)
18 BINARY_SUBTRACT
19 LOAD_CONST 1 (2)
22 CALL_FUNCTION 2
25 LOAD_GLOBAL 0 (math)
28 LOAD_ATTR 2 (pow)
31 LOAD_FAST 3 (y2)
34 LOAD_FAST 1 (y1)
37 BINARY_SUBTRACT
38 LOAD_CONST 1 (2)
41 CALL_FUNCTION 2
44 BINARY_ADD
45 CALL_FUNCTION 1
48 RETURN_VALUE
>>>
This can also be empirically show by the timeit results:
>>> import timeit
>>> toper = timeit.Timer("((23-76)**2 + (45-43)**2)**0.5")
>>> tfunc = timeit.Timer("math.sqrt(math.pow(23-76,2) + math.pow(45-43,2))", "import math")
>>> toper.timeit()
0.11890888214111328
>>> tfunc.timeit()
0.4799330234527588
Using the operators is about 75% faster.