With the help of python and SymPy module one can do pretty neat computations.
For example when I took a course about Robotic Preception on Coursera I had to find a cross product of
v1 x v2 represented in a generic form:
v1 = (a, b, c) v2 = (d, e, 0)
Normally I would write it down on a piece of paper and do the computations myself. Luckily python can help with that. Unfortunately it takes a bit of work to explain to SymPy what you want. But it is worth the trouble.
First we install Sympy:
pip install sympy
Now we can switch to python/ipython/jupyter. Import the module
from sympy import *
For vector representation we have to define a coordinate system:
from sympy.vector import CoordSys3D C = CoordSys3D('C')
also we need a could of generic symbols:
a, b, c, d, e = symbols('a b c d e ')
Now we can define our vectors in that coordinate system using the symbols:
v1 = a*C.i + b*C.j + c*C.k v2 = d*C.i + e*C.j + 0*C.k
And finally we can compute the cross product:
>>> v1.cross(v2) (-c*e)*C.i + c*d*C.j + (a*e - b*d)*C.k
So the answer is
(-ce, cd, ae-bd).
Alternative operator for the cross product:
>>> v1 ^ v2 (-c*e)*C.i + c*d*C.j + (a*e - b*d)*C.k
More info about vector operations: SymPy documentation