import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
w = np.array([-0.03314521 - 0.99945055])
z = np.linspace(-3, 2, 500)
points = np.column_stack([z, z])
projection_points = points * w
normal_point_1 = norm.pdf(z, 0, 1)
normal_point_2 = norm.pdf(z, 1, 1)
normal_vector_1 = np.column_stack([normal_point_1, normal_point_1]
    ) * np.transpose(w)
normal_vector_2 = np.column_stack([normal_point_2, normal_point_2]
    ) * np.transpose(w)
normal_1 = projection_points + normal_vector_1
normal_2 = projection_points + normal_vector_2
plt.plot(normal_1[::1, 0], normal_1[::1, 1], '-', color='b', alpha=0.5)
plt.plot(normal_2[::1, 0], normal_2[::1, 1], '-', color='b', alpha=0.5)
plt.show()

2959229d17ee622bfddbd0a2be4de689f500c0ce
<mask token>

<mask token>
plt.plot(normal_1[::1, 0], normal_1[::1, 1], '-', color='b', alpha=0.5)
plt.plot(normal_2[::1, 0], normal_2[::1, 1], '-', color='b', alpha=0.5)
plt.show()

<mask token>
w = np.array([-0.03314521 - 0.99945055])
z = np.linspace(-3, 2, 500)
points = np.column_stack([z, z])
projection_points = points * w
normal_point_1 = norm.pdf(z, 0, 1)
normal_point_2 = norm.pdf(z, 1, 1)
normal_vector_1 = np.column_stack([normal_point_1, normal_point_1]
    ) * np.transpose(w)
normal_vector_2 = np.column_stack([normal_point_2, normal_point_2]
    ) * np.transpose(w)
normal_1 = projection_points + normal_vector_1
normal_2 = projection_points + normal_vector_2
plt.plot(normal_1[::1, 0], normal_1[::1, 1], '-', color='b', alpha=0.5)
plt.plot(normal_2[::1, 0], normal_2[::1, 1], '-', color='b', alpha=0.5)
plt.show()

import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
w = np.array([-0.03314521 - 0.99945055])
z = np.linspace(-3, 2, 500)
points = np.column_stack([z, z])
projection_points = points * w
normal_point_1 = norm.pdf(z, 0, 1)
normal_point_2 = norm.pdf(z, 1, 1)
normal_vector_1 = np.column_stack([normal_point_1, normal_point_1]
    ) * np.transpose(w)
normal_vector_2 = np.column_stack([normal_point_2, normal_point_2]
    ) * np.transpose(w)
normal_1 = projection_points + normal_vector_1
normal_2 = projection_points + normal_vector_2
plt.plot(normal_1[::1, 0], normal_1[::1, 1], '-', color='b', alpha=0.5)
plt.plot(normal_2[::1, 0], normal_2[::1, 1], '-', color='b', alpha=0.5)
plt.show()
