I've been using sympy in jupyter notebooks as a simple free symbolic
algebra system while helping my kids review calculus and physics in
anticipation of starting as freshman at an engineering school in the fall.
We made it through all of single variable calculus without too much
trouble, but no
Look at the following link. Galgebra is built on top of sympy -
https://galgebra.readthedocs.io/en/latest/
You can define a set of basis vectors say e1, e2, and e3, and
coefficients a1, a2, and a3, then a general vector a1*e1+a2*e2+a3*e3.
The coefficients can be functions of the coordinates.
On Thu, 13 May 2021 at 10:02, Davide Sandona'
wrote:
> Hello Ryan,
>
> # HERE - Is there a less awkward way to evaluate the scalar field at a
>> # given vector?
>>
>
> Not that I'm aware of. I would have done the same intricate loop that you
> did.
> Note that you were "lucky": if your gp vector
Oscar makes a good point here:
> Conceptually this is a bit muddled though as it conflates vectors with
> points. Formally what is wanted here is to evaluate a scalar field at a point
> represented by a particular position vector wrt some reference frame. I don't
> know if the vector module has
Here is galgebra/sympy code for vector derivatives in rectangular and
spherical coordinate with output annotated using latex -
def derivatives_in_rectangular_coordinates():
#Print_Function()
X = (x,y,z) = symbols('x y z') #coordinates
o3d = Ga('e_x e_y e_z',g=[1,1,1],coords=X) #Recta
Hi, Alan.
> Here is galgebra/sympy code for vector derivatives in rectangular and
> spherical coordinate with output annotated using latex -
I did have a look at the galgebra package, and I was able to define my scalar
field and vectors and compute the gradient or directional derivative, just