Improve NumPy code in equalizing differences lecture

[jstac]

The NumPy code does not adhere to PEP8 and the class could easily be removed, so that compute_gap is just a function of the different parameters.

Then we could get rid of all the separate functions in the code block that starts with

# ϕ_R
def ϕ_R(mc, R_new):
    mc_new = equalizing_diff(R_new, mc.T, mc.γ_h, mc.γ_c, mc.w_h0, mc.D, mc.π)
    return mc_new.compute_gap()

ϕ_R = np.vectorize(ϕ_R)

@thomassargent30 Would you be willing to let @HumphreyYang and I simplify the NumPy part of the code without changing what it does?

[jstac]

The benchmark parameters

# set benchmark parameters
R = 1.05
T = 40
γ_h, γ_c = 1.01, 1.01
w_h0 = 1
D = 10

could be included at default values for the compute_gap function.

[HumphreyYang]

Hi @jstac,

I think this issue has been addressed in #388. Would you like me to close it?

[jstac]

Thanks @HumphreyYang, closing.