Function in a class requires inputs from another function in the class - python-3.x

Question

I am pretty new to Python and are trying to make a option pricing class with three functions: call, put and graph. The call and put function work fine, but I can't figure out the graph function. I want the p.append to get the values from the call function, hold all the variables constant except for S0 which is equal to i.
import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt
class Option():
def __init__(self, S0, K, T, r, sigma, start, stop, N):
self.S0 = S0
self.K = K
self.T = T
self.r = r
self.sigma = sigma
self.start = start
self.stop = stop
self.N = N
def call(self):
d1 = (np.log(self.S0/self.K) + \
(self.r + 0.5*self.sigma**2)*self.T)/(self.sigma*np.sqrt(self.T))
d2 = d1 - self.sigma*np.sqrt(self.T)
price = (self.S0 * norm.cdf(d1, 0.0, 1.0) - \
self.K * np.exp(-self.r * self.T) * norm.cdf(d2, 0.0, 1.0))
return price
def put(self):
d1 = (np.log(self.S0/self.K) + \
(self.r + 0.5*self.sigma**2)*self.T)/(self.sigma*np.sqrt(self.T))
d2 = d1 - self.sigma*np.sqrt(self.T)
price = (self.K * np.exp(-self.r * self.T) * norm.cdf(-d2, 0.0, 1.0) - \
self.S0 * norm.cdf(-d1, 0.0, 1.0))
return price
def graphCall(self):
S = np.linspace(self.start, self.stop, self.N)
p = []
for i in S:
p.append()
plt.plot(S, p)
x = Option(100, 50, 3, 0.05, 0.40, 100, 200, 500)
print(x.call())
x.graphCall()

Answer 1

You could decide to use self.S0 as the default value for calls to call and put, but allow for a other arguments as well.
import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt
class Option():
def __init__(self, S0, K, T, r, sigma, start, stop, N):
self.S0 = S0
self.K = K
self.T = T
self.r = r
self.sigma = sigma
self.start = start
self.stop = stop
self.N = N
def call(self, s=None):
if s is None:
s=self.S0
d1 = (np.log(s/self.K) + \
(self.r + 0.5*self.sigma**2)*self.T)/(self.sigma*np.sqrt(self.T))
d2 = d1 - self.sigma*np.sqrt(self.T)
price = (s * norm.cdf(d1, 0.0, 1.0) - \
self.K * np.exp(-self.r * self.T) * norm.cdf(d2, 0.0, 1.0))
return price
def put(self, s=None):
if s is None:
s=self.S0
d1 = (np.log(s/self.K) + \
(self.r + 0.5*self.sigma**2)*self.T)/(self.sigma*np.sqrt(self.T))
d2 = d1 - self.sigma*np.sqrt(self.T)
price = (self.K * np.exp(-self.r * self.T) * norm.cdf(-d2, 0.0, 1.0) - \
s * norm.cdf(-d1, 0.0, 1.0))
return price
def graphCall(self):
S = np.linspace(self.start, self.stop, self.N)
plt.plot(S, self.call(S))
plt.show()
x = Option(100, 50, 3, 0.05, 0.40, 100, 200, 500)
print(x.call())
x.graphCall()