What you want is to find the root(s) or zero(s) of an array. This question's answer shows how to do that: How to get values from a graph?
Applying the solution to this case here would look as follows:
import matplotlib.pyplot as plt
import numpy as np
# given values
y = np.array([0, 38.39, 71.41, 99.66, 123.67, 143.88, 160.61, 174.03, 184.16, 190.8, 193.52])
x = np.array([0, 0.37, 0.74, 1.11, 1.48, 1.85, 2.22, 2.59, 2.96, 3.33, 3.7])
x_val = np.linspace(0,7)
plt.plot(x, y, '-')
def find_roots(x,y):
s = np.abs(np.diff(np.sign(y))).astype(bool)
return x[:-1][s] + np.diff(x)[s]/(np.abs(y[1:][s]/y[:-1][s])+1)
a = 0.8
b = 150
y_val = np.multiply(a, b)
roots = find_roots(x, y-y_val)
plt.plot(roots[0],y_val, marker="o")
plt.plot([roots[0],roots[0],0],[0,y_val,y_val], "--")
plt.xlim(0,None)
plt.ylim(0,None)
plt.show()
If the arrays are monotonically increasing, you may of course also simply interpolate:
import matplotlib.pyplot as plt
import numpy as np
# given values
y = np.array([0, 38.39, 71.41, 99.66, 123.67, 143.88, 160.61, 174.03, 184.16, 190.8, 193.52])
x = np.array([0, 0.37, 0.74, 1.11, 1.48, 1.85, 2.22, 2.59, 2.96, 3.33, 3.7])
x_val = np.linspace(0,7)
plt.plot(x, y, '-')
a = 0.8
b = 150
y_val = np.multiply(a, b)
root = np.interp(y_val,y,x)
plt.plot(root,y_val, marker="o")
plt.plot([root,root,0],[0,y_val,y_val], "--")
plt.xlim(0,None)
plt.ylim(0,None)
plt.show()