truncated normal distribution with scipy in python

Question

I am trying to use a truncated normal distribution with scipy in Python3. I want to do something simple: plot the pdf of a truncated normal centered at 0.5 and ranging from 0 to 1. I have the following code line

from scipy import truncnorm
import matplotlib.pyplot as plt
plt.plot([truncnorm.pdf(p,0,1, loc=0.5) for p in np.arange(0,1.1,0.1)])

However, this does not give the nice bell-shaped probability distribution function I would expect. Rather, it equals 0 before 0.5, and I cannot figure out why. Any advice on this?

Answer 1

Here's the procedure to follow according to the documentation of truncnorm.

# user input
myclip_a = 0
myclip_b = 1
my_mean = 0.5
my_std = 0.3

a, b = (myclip_a - my_mean) / my_std, (myclip_b - my_mean) / my_std
x_range = np.linspace(-1,2,1000)
plt.plot(x_range, truncnorm.pdf(x_range, a, b, loc = my_mean, scale = my_std))