I am creating a problem which requires me to find the cube root of certain numbers, some of them have whole number roots, but a lot of them don't.
I have numbers like 125, that should return a cube root of 5 but instead Python returns 4.99999 Example:
>>> 125 ** (1.0/3.0)
4.999999999999999
This is my code:
processing = True
n = 12000
while processing:
if (n ** (1.0/3.0)).is_integer() == True:
print((n ** (1.0/3.0)), "is the cube root of ", n)
processing = False
else:
n -= 1
The standard way to check for equality with floating point is to check for quality within a certain tolerance:
def floateq(a, b, tolerance=0.00000001):
return abs(a-b) < tolerance
Now you can check if the rounded, converted-to-an-integer version of the cube root is equal to the cube root itself within a certain tolerance:
def has_integer_cube_root(n):
floatroot = (n ** (1.0 / 3.0))
introot = int(round(floatroot))
return floateq(floatroot, introot)
Usage:
>>> has_integer_cube_root(125)
True
>>> has_integer_cube_root(126)
False
However, this is quite imprecise for your use case:
>>> has_integer_cube_root(40000**3)
True
>>> has_integer_cube_root(40000**3 + 1)
True
You can mess with the tolerance, but at some point, floating point numbers just won't be enough to have the accuracy you need.
EDIT: Yes, as the comment said, in this case you can check the result with integer arithmetic:
def has_integer_cube_root(n):
floatroot = (n ** (1.0 / 3.0))
introot = int(round(floatroot))
return introot*introot*introot == n
>>> has_integer_cube_root(40000**3)
True
>>> has_integer_cube_root(40000**3 + 1)
False
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