Minumum Least Squares Through Trial and Error

leastSquaresTrials.py

data = [(0, 0), (1, 2), (2, 4), (3, 6), (4, 8)]
m = 0
b = 0

def testFunc(x):
    return m * x + b

def leastSquares(func, data):
    results = 0
    for datum in data:
        x = datum[0]
        y = datum[1]
        results = results + (y - func(x))**2
    return results

def adjustFunc():
    global data, m, b
    best = leastSquares(testFunc, data)
    mod = 1
    while(True):
        m = m + mod
        curr = leastSquares(testFunc, data)
        if(best > curr):
            best = curr
        elif(best < curr):
            m = m - mod
            mod = -(1/10) * mod
        else:
            return m