Curve creation

import numpy as np
import bezier
def bezierCurve(start=(0,0), end=(1,1), skew=0):
# skew: (-0.5,0.5) otherwise this shit will look ugly.
assert skew >=-0.5
assert skew <=0.5
x_start, y_start = start
x_end, y_end = end
x_diff = x_end - x_start
y_diff = y_end - y_start
nodes1 = np.asfortranarray(
[
[x_start, x_diff * (0.5 + skew), x_end],
[y_start, y_diff * (0.5 - skew), y_end],
]
)
curve1 = bezier.Curve(nodes1, degree=2)
curve_params = {'x_start':x_start, 'x_diff':x_diff,'x_end':x_end}
return curve1, curve_params
def evaluateBezierCurve(input_value:float,curve, curve_params:dict)
x_start = curve_params['x_start']
x_end = curve_params['x_end']
assert x_start <= input_value
assert x_end >= input_value
x_diff = curve_params['x_diff']
s = (input_value - x_start)/x_diff
points = curve.evaluate(s)
# we only get the single point.
point = points.T[0]
x,y = point
result = y
return result

def multiParameterExponentialNetwork(*args, input_bias=0.05, curve_function=bezierCurve, curve_function_kwargs = {'start':(0,0),'end':(1,1)'skew':0}, evaluate_function=evaluateBezierCurve):
curve, curve_params = curve_function(**curve_function_kwargs)
value = evaluate_function(input_bias, curve, curve_params)
for index, input_value in enumerate(args):
apply_list = [input_value]*(index+1)
for apply_item in apply_list:
value += (1-value)*function(apply_item, **function_kwargs)
return value