abs min Algorithm
The abs min algorithm, also known as the absolute minimum algorithm, is a mathematical procedure used for finding the smallest absolute value in a given set of numbers. The algorithm essentially involves iterating through the elements of the input set, comparing the absolute values of each element, and determining the element with the least absolute value. The purpose of this algorithm is to identify the number that is closest to zero, regardless of its sign, which can be useful in various applications such as optimization problems, data analysis, and error minimization.
To implement the abs min algorithm, one typically starts by initializing a variable to store the current minimum absolute value, often by assigning the absolute value of the first element in the dataset. Then, the algorithm proceeds by iterating through the remaining elements, calculating the absolute value of each element, and comparing it to the current minimum absolute value. If the algorithm finds an element with an absolute value smaller than the current minimum, it updates the minimum absolute value with the newfound smaller value. Once the iteration is complete, the algorithm returns the element with the smallest absolute value (i.e., the one closest to zero). This simple yet effective method allows for efficient identification of the least absolute value in a set of numbers, making it a valuable tool in various computational and mathematical contexts.
from .abs import abs_val
def absMin(x):
"""
>>> absMin([0,5,1,11])
0
>>> absMin([3,-10,-2])
-2
"""
j = x[0]
for i in x:
if abs_val(i) < abs_val(j):
j = i
return j
def main():
a = [-3, -1, 2, -11]
print(absMin(a)) # = -1
if __name__ == "__main__":
main()
