In spite of my best efforts I cannot get lambdify to cope with array/
list inputs. All the lambdify examples have 1D inputs.
Can you pass in x= x1,x2 ?
dof and d_dof are both 4*1 lists
I am also have trouble with lambdify seeing list if length 4 as on
input rather thab as 4 inputs, Iam using veversion .6.3
Cheers
Scott
def F0(dof,d_dof,U,dt):
> > h1=dof[0];theta1=dof[1];v_h1=dof[2];v_theta1=dof[3]
> > delta_h=d_dof[0];delta_theta=d_dof[1];delta_v_h=d_dof
> > [2];delta_v_theta=d_dof[3]
> > res=-delta_v_h/2 - delta_v_theta/20 + dt*(-2*h1/25 - delta_h/25 -
> > 3*U*
> > (v_theta1 + delta_v_theta/2)/50 - U*(v_h1 + delta_v_h/2)/20 - U**2*
> > (theta1 + delta_theta/2)/20)#qs
> > return res
On Dec 4, 7:15 am, "Ondrej Certik" <[EMAIL PROTECTED]> wrote:
> On Thu, Dec 4, 2008 at 1:08 PM, Scott <[EMAIL PROTECTED]> wrote:
>
> > How can I translate a formula output by sympy into one that is scipy
> > friendly?
>
> > Given the following formula how can I automate turning the formula
> > into a fast funtion.
>
> > f0=-delta_v_h/2 - delta_v_theta/20 + dt*(-2*h1/25 - delta_h/25 - 3*U*
> > (v_theta1 + delta_v_theta/2)/50 - U*(v_h1 + delta_v_h/2)/20 - U**2*
> > (theta1 + delta_theta/2)/20)
>
> > This first function is an order fo magnitude slower than the second
> > when I solve it and its 3 sister nonlinear algebraic equations with
> > scipy.optimize.fsolve
>
> > def F0(dof1,ddof,U,dt):return f0.subs(dict(zip(s1(dof),dof1))).subs
> > (dict(zip(del_0(dof),ddof))).subs('dt',dt).subs('U',U)
>
> > def F0(dof,d_dof,U,dt):
> > h1=dof[0];theta1=dof[1];v_h1=dof[2];v_theta1=dof[3]
> > delta_h=d_dof[0];delta_theta=d_dof[1];delta_v_h=d_dof
> > [2];delta_v_theta=d_dof[3]
> > res=-delta_v_h/2 - delta_v_theta/20 + dt*(-2*h1/25 - delta_h/25 -
> > 3*U*
> > (v_theta1 + delta_v_theta/2)/50 - U*(v_h1 + delta_v_h/2)/20 - U**2*
> > (theta1 + delta_theta/2)/20)#qs
> > return res
>
> Try lambdify and read it's docstring, I think it should do exactly
> what you want.
>
> Ondrej- Hide quoted text -
>
> - Show quoted text -
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