问题
I have a plane, plane A
, defined by its orthogonal vector, say (a, b, c)
.
(i.e. the vector (a, b, c)
is orthogonal to plane A
)
I wish to project a vector (d, e, f)
onto plane A
.
How can I do it in Python? I think there must be some easy ways.
回答1:
Take (d, e, f)
and subtract off the projection of it onto the normalized normal to the plane (in your case (a, b, c)
). So:
v = (d, e, f)
- sum((d, e, f) *. (a, b, c)) * (a, b, c) / sum((a, b, c) *. (a, b, c))
Here, by *.
I mean the component-wise product. So this would mean:
sum([x * y for x, y in zip([d, e, f], [a, b, c])])
or
d * a + e * b + f * c
if you just want to be clear but pedantic
and similarly for (a, b, c) *. (a, b, c)
. Thus, in Python:
from math import sqrt
def dot_product(x, y):
return sum([x[i] * y[i] for i in range(len(x))])
def norm(x):
return sqrt(dot_product(x, x))
def normalize(x):
return [x[i] / norm(x) for i in range(len(x))]
def project_onto_plane(x, n):
d = dot_product(x, n) / norm(n)
p = [d * normalize(n)[i] for i in range(len(n))]
return [x[i] - p[i] for i in range(len(x))]
Then you can say:
p = project_onto_plane([3, 4, 5], [1, 2, 3])
来源:https://stackoverflow.com/questions/17915475/how-may-i-project-vectors-onto-a-plane-defined-by-its-orthogonal-vector-in-pytho