Black Scholes "Option Payoff" versus "time" in Python

import math
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams['font.family'] = 'serif'
from scipy.integrate import quad

def dN(x):
    ''' Probability density function of standard normal random variable x.'''
    return math.exp(-0.5 * x ** 2) / math.sqrt(2 * math.pi)
def N(d):
    ''' Cumulative density function of standard normal random variable x. '''
    return quad(lambda x: dN(x), -20, d, limit=50)[0]
def d1f(St, K, t, T, r, sigma):
    ''' Black-Scholes-Merton d1 function.
        Parameters see e.g. BSM_call_value function. '''
    d1 = (math.log(St / K) + (r + 0.5 * sigma ** 2)
        * (T - t)) / (sigma * math.sqrt(T - t))
    return d1
#
# Valuation Functions
#
def BSM_call_value(St, K, t, T, r, sigma): 
    ''' Calculates Black-Scholes-Merton European call option value.86 DERIVATIVES ANALYTICS WITH PYTHON
    Parameters
    ==========
    St: float
    stock/index level at time t
    K: float
    strike price
    t: float
    valuation date
    T: float
    date of maturity/time-to-maturity if t = 0; T > t
    r: float
    constant, risk-less short rate
    sigma: float
    volatility
    Returns
    =======
call_value: float
European call present value at t
    '''
    d1 = d1f(St, K, t, T, r, sigma)
    d2 = d1 - sigma * math.sqrt(T - t)
    call_value = St * N(d1) - math.exp(-r * (T - t)) * K * N(d2)
    return call_value
def BSM_put_value(St, K, t, T, r, sigma):
    ''' Calculates Black-Scholes-Merton European put option value.
    Parameters
    ==========
    St: float
    stock/index level at time t
    K: float
    strike price
    t: float
    valuation date
    T: float
    date of maturity/time-to-maturity if t = 0; T > t
    r: float
    constant, risk-less short rate
    sigma: float
    volatility
    Returns
    =======
    put_value: float
        European put present value at t
    '''
    put_value = BSM_call_value(St, K, t, T, r, sigma) \
        - St + math.exp(-r * (T - t)) * K
    return put_value
#
# Plotting European Option Values
#
def plot_values(function):
    ''' Plots European option values for different parameters c.p. '''
    plt.figure(figsize=(10, 8.3))
    points = 100
#
# Model Parameters
#
    St = 100.0 # index level
    K = 100.0 # option strike
    t = 0.0 # valuation date
    T = 1.0 # maturity date
    r = 0.05 # risk-less short rate
    sigma = 0.2 # volatility
# C(T) plot
    plt.subplot(222)
    tlist = np.linspace(0.0001, 1, points)
    vlist = [function(St, K, t, T, r, sigma) for T in tlist]
    plt.plot(tlist, vlist)
    plt.grid(True)
    plt.xlabel('maturity $T$')