grad evaluation

[dutitello]

It will be determined by finite difference method. Forward, central and backward methods at first.

• All scalar parameters should be evaluated for each declarated parameter:

  If the parameters from the APDL are b, h, l, stress and it's passed to grad just the value of b we could determine db/db (why would we do that?), dh/db, dl/db and dstress/db. If b,h,l are input parameters the derivatives of that will be 0, but all could be calculated and the user will define what it's useful for it (dstress/db).

• It's possible to determine it for arrays/tables??

[dutitello]

It's partially done!

• No support for arrays parameters in paransys yet;
• The three methods works;
• It's possible to choose in relation to what grad is evaluated with (notfor=[] and onlyfor=[])
• It returns a diactionary in the form grad('y','x') = y'(x) = dy/dx.

[dutitello]

Arrays and tables are for now out.
grad looks ok!

[dutitello]

the name of the function is now derivatives!
Since grad(f(X)) are the derivatives of f(X) for all X variables the output should be an dictionary for each output parameter (f) and each dictionary should have it's derivatives.

[dutitello]

I used for central diference method h/2 steps... but it's a good ideia for numerical evaluations... It need to be always h...