dynamic-pricing-c01.py

def linear(a, b, x):
    return b + a*x

# a linear demand function is generated for every 
# pair of coefficients in vectors a_vec and b_vec 
def demand_hypotheses(a_vec, b_vec):
    for a, b in itertools.product(a_vec, b_vec):
        yield {
            'd': functools.partial(linear, a, b),
            'p_opt': -b/(2*a)
        }

https://gist.github.com/ikatsov/559dda69b7a8f86c5e0d6fb394eeb702#file-dynamic-pricing-c01-py

def linear(a, b, x):
return b + a*x

a linear demand function is generated for every

pair of coefficients in vectors a_vec and b_vec

def demand_hypotheses(a_vec, b_vec):
for a, b in itertools.product(a_vec, b_vec):
yield {
'd': functools.partial(linear, a, b),
'p_opt': -b/(2*a)
}