Machine learning components
Project description
Vector
from abel.linalg.vector import Vector
a, b = Vector([1, 2]), Vector([3, 4])
c, d = Vector([1, 2, 3]), Vector([4, 5, 6])
assert a.shape == b.shape == (1, 2)
assert c.shape == d.shape == (1, 3)
Addition
assert a + a == Vector([2, 4])
assert a + b == Vector([4, 6])
assert b + b == Vector([6, 8])
Subtraction
assert a - b == Vector([-2, -2])
assert b - a == Vector([2, 2])
Scaling
assert a * 5 == Vector([5, 10])
assert 5 * a == Vector([5, 10])
Dot (inner) product
assert a @ b == 11
assert a @ a == 5
Norm (length)
assert a.norm() - 2.236 < 0.001
assert b.norm() - 5 < 0.001
Angle
assert Vector.angle(a, a) < 0.001
assert Vector.angle(a, b) - 0.1799 < 0.001
assert Vector.angle(a, b) == Vector.angle(b, a)
Vector projection
assert Vector.proj(a, a) == a
assert Vector.proj(a, b) == Vector([1.32, 1.76])
assert Vector.proj(b, a) == Vector([2.2, 4.4])
Scalar projection
assert Vector.scalproj(a, b) - 4.919 < 0.01
assert Vector.scalproj(b, a) - 2.2 < 0.01
assert Vector.scalproj(a, a) - 2.236 < 0.01
assert Vector.scalproj(b, b) - 5 < 0.1
Cross product
assert Vector.cross(c, d) == Vector([-3, 6, -3])
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
abel-0.0.3.tar.gz
(2.4 kB
view hashes)
Built Distribution
abel-0.0.3-py3-none-any.whl
(3.2 kB
view hashes)