normalizing score

app.py

import numpy as np
import matplotlib.pyplot as plt

from math import exp, log


def getGaussDecayValue(value,origin,scale,decay,offset=0):
    # does this work?
    z = -1*(scale**2)/(2*log(decay))
    a = (-1* (max(0, abs(value - origin) - offset)**2))
    value = exp(a/2*z)
    return value

def getExpDecayValue(value, origin, scale, decay, offset=0):
    z = log(decay) / scale
    value = exp(z * max(0, abs(value - origin) - offset))
    return value


def getDecayValue(type, value, origin, scale, decay, offset=0):
    if type == 'exp':
        return getExpDecayValue(value, origin, scale, decay, offset)
    else:
        return getGaussDecayValue(value, origin, scale, decay, offset)


def getApproachValue(type, value, bar, scale, decay, offset=0):
    v = getDecayValue(type, value, 0, scale, decay, offset)
    return (bar - (bar * v)) / bar


plt.axis([0, 500, 0, 1])
x = []
y = []
for score in range(1, 200, 10):
    # what does bar do?
    val = getApproachValue('exp', score, 10, 70, 0.40, 0)
    print(score, '\t', val)
    x.append(score)
    y.append(val)

plt.plot(x, y)
plt.show()