is this correct ?
to be honnest, it's my first docstring ...


On 10 nov, 16:50, Philippe <[email protected]> wrote:
> from sympy import *
>
> t = Symbol('t')
>
> def partial_derivative(equa, param):
>     """param is a variable, must not be named 'param_sub'
>     >>> from sympy import *
>     >>> t = Symbol('t')
>     >>> k = Symbol('k')
>     >>> x = Function('x')(t)
>     >>> partial_derivative(k*diff(x, t)**2 + k * x, x)
>     k
>     >>> partial_derivative(k*diff(x, t)**2 + k * x, diff(x, t))
>     2*k*D(x(t), t)"""
>
>     param_sub = Symbol('param_sub')
>     equa_subs1 = equa.subs(param, param_sub)
>     dequa_param_sub = diff(equa_subs1, param_sub)
>     dequa_param = dequa_param_sub.subs(param_sub, param)
>     return dequa_param
>
> def lagrange(equa, param):
>     """param is a list of Function of time
>     must not use the name 'param_sub' in the equation
>     >>> from sympy import *
>     >>> t = Symbol('t')
>     >>> k = Symbol('k')
>     >>> x = Function('x')(t)
>     >>> y = Function('y')(t)
>     >>> equa = diff(x, t)**2+diff(y, t)**2 + 5 * x
>     >>> dT_dqvt, dT_dq = lagrange(equa, [x, y])
>     >>> print dT_dqvt
>     [2*D(x(t), t, t), 2*D(y(t), t, t)]
>     >>> print dT_dq
>     [5, 0]
>     >>> equa = k*diff(x, t)**2 + k * x
>     >>> dT_dqvt, dT_dq = lagrange(equa, [x])
>     >>> print dT_dqvt
>     [2*k*D(x(t), t, t)]
>     >>> print dT_dq
>     [k]"""
>
>     vel_var = [diff(e, t) for e in param]
>     dT_dqv = [partial_derivative(equa, p) for p in vel_var]
>     dT_dq = [partial_derivative(equa, p) for p in param]
>
>     dT_dqvt = [diff(e, t) for e in dT_dqv]
>
>     return dT_dqvt, dT_dq
>
> if __name__ == "__main__":
>     import doctest
>     doctest.testmod()
>
> On 10 nov, 15:15, Andy Ray Terrel <[email protected]> wrote:
>
> > I think this would be a great contribution to the SymPy physics
> > module.  Can you put some usage doc strings? Then, we can put it in
> > the appropriate places.
>
> > -- Andy
>
> > On Wed, Nov 10, 2010 at 3:10 AM, Philippe <[email protected]> wrote:
> > > some usage if needed..
> > > this is my unittest file.
> > > the lagrange and partial_derivative functions are in meca.py
>
> > > -  -  -  -  -  -  -  -  -  -  -  -
>
> > > import unittest
> > > from sympy import *
> > > import meca
>
> > > class MyTest(unittest.TestCase):
>
> > >    def test_lagrange_1(self):
> > >        t = Symbol('t')
> > >        x = Function('x')(t)
> > >        y = Function('y')(t)
> > >        dT_dqvt, dT_dq = meca.lagrange(diff(x, t)**2+diff(y, t)**2 + 5
> > > * x, [x, y])
>
> > >        dT_dqvt_0 = 2*diff(x, t, t)
> > >        dT_dqvt_1 = 2*diff(y, t, t)
>
> > >        self.assertEquals(dT_dqvt, [dT_dqvt_0, dT_dqvt_1])
> > >        self.assertEquals(dT_dq, [5, 0])
>
> > >    def test_lagrange_2(self):
> > >        t = Symbol('t')
> > >        k = Symbol('k')
> > >        x = Function('x')(t)
> > >        dT_dqvt, dT_dq = meca.lagrange(k*diff(x, t)**2 + k * x, [x])
>
> > >        dT_dqvt_0 = 2*k*diff(x, t, t)
>
> > >        self.assertEquals(dT_dqvt, [dT_dqvt_0])
> > >        self.assertEquals(dT_dq, [k])
>
> > >    def test_partial_derivative_1(self):
> > >        t = Symbol('t')
> > >        k = Symbol('k')
> > >        x = Function('x')(t)
> > >        dE_q = meca.partial_derivative(k*diff(x, t)**2 + k * x, x)
> > >        dE_q_sol = k
> > >        self.assertEquals(dE_q, dE_q_sol)
>
> > >    def test_partial_derivative_2(self):
> > >        t = Symbol('t')
> > >        k = Symbol('k')
> > >        x = Function('x')(t)
> > >        dE_q = meca.partial_derivative(k*diff(x, t)**2 + k * x,
> > > diff(x, t))
> > >        dE_q_sol = 2*k*diff(x, t)
> > >        self.assertEquals(dE_q, dE_q_sol)
>
> > > if __name__ == '__main__':
> > >    unittest.main()
>
> > > -  -  -  -  -  -  -  -  -  -  -  -
>
> > > On 9 nov, 17:18, Philippe <[email protected]> wrote:
> > >> from sympy import *
>
> > >> t = Symbol('t')
> > >> x = Function('x')(t)
> > >> y = Function('y')(t)
>
> > >> def partial_derivative(equa, param):
> > >>     param_sub = Symbol('param_sub')
> > >>     equa_subs1 = equa.subs(param, param_sub)
> > >>     dequa_param_sub = diff(equa_subs1, param_sub)
> > >>     dequa_param = dequa_param_sub.subs(param_sub, param)
> > >>     return dequa_param
>
> > >> def lagrange(equa, param):
> > >>     """
> > >>     param is a list of Function of time
> > >>     must not use 'q1', 'q2', .... 'qv1', ... in the equation
> > >>     """
> > >>     vel_var = [diff(e, t) for e in param]
> > >>     dT_dqv = [partial_derivative(equa, p) for p in vel_var]
> > >>     dT_dq = [partial_derivative(equa, p) for p in param]
>
> > >>     dT_dqvt = [diff(e, t) for e in dT_dqv]
>
> > >>     return dT_dqvt, dT_dq
>
> > >> On 31 oct, 20:51, Tim Lahey <[email protected]> wrote:
>
> > >> > On Sun, Oct 31, 2010 at 3:41 PM, Aaron S. Meurer <[email protected]> 
> > >> > wrote:
>
> > >> > > I am still trying to fully understand the code below, but if one of 
> > >> > > the subs is trying to do something like diff(f(x), x).subs(x, g(x)), 
> > >> > > then you will get an error in SymPy for the above reason.
>
> > >> > > Aaron Meurer
>
> > >> > The basic approach is to substitute a symbol for f(x) say f1 and then
> > >> > take the derivative
> > >> > with respect to that. You know the substitution, so you can reverse
> > >> > it. Once the derivative
> > >> > is done, you reverse the substitution. Then, you can take the
> > >> > derivative with respect to
> > >> > x.
>
> > >> > So, the steps become.
>
> > >> > 1. Build list of symbols for functions.
> > >> > 2. Build a list of substitutions for the functions and the reverse.
> > >> > 3. Substitute for the functions.
> > >> > 4. Run derivatives with respect to the symbols.
> > >> > 5. Substitute functions for the symbols.
> > >> > 6. Take any derivatives with respect to the function variables.
>
> > >> > Hope that helps the explanation. A lot of what's done in the code is 
> > >> > using
> > >> > zip and map to make the code fast, but I originally wrote it as above. 
> > >> > Python
> > >> > has appropriate functions that this should still be fast.
>
> > >> > Cheers,
>
> > >> > Tim.
>
> > >> > --
> > >> > Tim Lahey
> > >> > PhD Candidate, Systems Design Engineering
> > >> > University of Waterloohttp://www.linkedin.com/in/timlahey
>
> > > --
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> > > "sympy" group.
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> > > [email protected].
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> > > athttp://groups.google.com/group/sympy?hl=en.
>
>

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