Dot Product using Python, NumPy, Matplotlib

Dot product / Inner product / Scalar product

Algebraic Definition    



Geometric Definition


Python Code







from matplotlib.pyplot import plot

point1 = [0, 0]
point2 = [3, 0]

x_values = [point1[0], point2[0]]
y_values = [point1[1], point2[1]]
plot(x_values, y_values, 'b-') # format: Blue dashes

point1 = [0, 0]
point2 = [3, 3]

x_values = [point1[0], point2[0]]
y_values = [point1[1], point2[1]]

plot(x_values, y_values, color='red', marker='o') 



import numpy as np

a = np.array([3, 0])
b = np.array([3, 3])
c = np.array([1, 1])

print("a, b, c:", a, b, c, end = "\n\n")
print("a.dot(b):", a.dot(b))
print("b.dot(a):", b.dot(a), end = "\n\n")

print("np.dot(a, b):", np.dot(a, b))
print("sum(a*b):", sum(a*b), end = "\n\n")

print("np.dot(b, c):", np.dot(b, c))
print("sum(b*c):", sum(b*c), end = "\n\n")

theta = np.pi / 4
print("theta = np.pi / 4")
print("np.linalg.norm(a) * np.linalg.norm(b) * np.cos(theta):", 
     np.linalg.norm(a) * np.linalg.norm(b) * np.cos(theta)) 

a, b, c: [3 0] [3 3] [1 1]

a.dot(b): 9
b.dot(a): 9

np.dot(a, b): 9
sum(a*b): 9

np.dot(b, c): 6
sum(b*c): 6

theta = np.pi / 4
np.linalg.norm(a) * np.linalg.norm(b) * np.cos(theta): 9.0 
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