def compute_normal(vertices, faces):
norm = np.zeros(vertices.shape, dtype=vertices.dtype)
tris = vertices[faces]
## skip the rest of the code ##
where vertices is an np.ndarray of shape (A,3), faces is an np.ndarray of shape (B,3), andtris turns to be of shape (B,3,3). (by the way, B>A)
What is tris = vertices[faces] actually doing?
Maybe this example help you:
import numpy as np
np.random.seed(123)
vertices = np.random.rand(3, 3) # shape -> (3, 3)
faces = np.random.randint(3, size=(4, 3)) # shape -> (4, 3)
print(vertices)
# [[0.69646919 0.28613933 0.22685145]
# [0.55131477 0.71946897 0.42310646]
# [0.9807642 0.68482974 0.4809319 ]]
print(faces)
# [[1 0 2]
# [0 1 2]
# [1 0 0]
# [0 0 1]]
print(vertices[faces]) # shape -> (4, 3, 3)
# [[[0.55131477 0.71946897 0.42310646] # faces==1 -> take second row of vertices
# [0.69646919 0.28613933 0.22685145] # faces==0 -> take first row of vertices
# [0.9807642 0.68482974 0.4809319 ]] # faces==2 -> take third row of vertices
# [[0.69646919 0.28613933 0.22685145] # faces==0 -> take first row of vertices
# [0.55131477 0.71946897 0.42310646] # faces==1 -> take second row of vertices
# [0.9807642 0.68482974 0.4809319 ]] # faces==2 -> take third row of vertices
# [[0.55131477 0.71946897 0.42310646] # faces==1 -> take second row of vertices
# [0.69646919 0.28613933 0.22685145] # faces==0 -> take first row of vertices
# [0.69646919 0.28613933 0.22685145]] # faces==0 -> take first row of vertices
# [[0.69646919 0.28613933 0.22685145] # faces==0 -> take first row of vertices
# [0.69646919 0.28613933 0.22685145] # faces==0 -> take first row of vertices
# [0.55131477 0.71946897 0.42310646]]] # faces==1 -> take second row of vertices