Oops - except the m \ddot{x} formats properly in the notebook.
On Thursday, August 14, 2014 11:09:08 AM UTC-7, Rathmann wrote:
>
> Thanks a lot! It turned out that init_vprinting() gives the behavior I
> wanted.
>
> In case others want to go down this path, I am appending a minimal
> notebook entry which shows the syntax. I am really impressed that diff(L,
> xdot) just works, and that I can use solve to get algebraic expressions for
> velocities and accelerations.
>
> One additional question - is there a better way to get the time variable
> than dynamicsymbols._t ? I look at that leading underscore as an
> indication that I shouldn't be touching it from user code.
>
> ------------------
>
> In [1]:
>
> from sympy.physics.vector import dynamicsymbols
> from sympy import diff, symbols, S
> from sympy.physics.vector import init_vprinting
>
> init_vprinting()
>
> # Simplest test case .. particle of mass m in uniform gravitational field g
> x = dynamicsymbols('x')
> t = dynamicsymbols._t
> xdot = diff(x,t)
> m, g = symbols('m g')
>
> T = (m * xdot**2)/S(2) #kinetic energy
> V = m*g*x # potential energy is just mgh
> L = T - V
>
> #Euler-Lagrange equation
> diff(L, xdot,t) - diff(L,x)
>
>
> Out[1]:
> gm+mx¨
>
>
>
>
>
> On Wednesday, August 13, 2014 10:24:47 PM UTC-7, Jason Moore wrote:
>>
>> Oh, you should use
>>
>> sympy.physics.vector.init_printing()
>>
>> If you want the dot notation in latex in your notebooks.
>>
>>
>> Jason
>> moorepants.info
>> +01 530-601-9791
>>
>>
>> On Wed, Aug 13, 2014 at 10:23 PM, Jason Moore <moore...@gmail.com> wrote:
>>
>>> You can subclass a printer and have it do what you want. You can see
>>> here:
>>>
>>>
>>> https://github.com/sympy/sympy/blob/master/sympy/physics/vector/printing.py#L145
>>>
>>> where we subclass the latex printer and get the \dot{} notation for
>>> derivatives, for example. There is also an example here:
>>>
>>> http://docs.sympy.org/dev/modules/printing.html
>>>
>>> of subclassing to do custom derivative printing. Maybe exactly what you
>>> want.
>>>
>>> The LagrangesMethod in sympy.physics.mechanics works with the classes
>>> available in that package (RigidBody, ReferemceFrame, etc). The other one
>>> is more basic math. So if you want to write all the math yourself then
>>> maybe the later is preferable, but if you want to use the objects in
>>> sympy.physics.mechanics to build up a rigid body system and find the
>>> equations of motion, the use the former.
>>>
>>>
>>> Jason
>>> moorepants.info
>>> +01 530-601-9791
>>>
>>>
>>> On Wed, Aug 13, 2014 at 10:13 PM, Rathmann <rathm...@gmail.com> wrote:
>>>
>>>> Hello,
>>>>
>>>> I have been watching the lectures of Susskind's "Theoretical Minimum"
>>>> course, and using Sympy with IPython notebook to take notes, and work
>>>> through some of the examples.
>>>>
>>>> Sympy is serious overkill for this purpose, but overall it has been
>>>> working well.
>>>>
>>>> A couple of questions:
>>>>
>>>> - What is the best way to deal with dynamics variables and the dot
>>>> convention for printing? (In physics, the first time derivative of x is
>>>> often written as \dot{x} instead of dx/dt.) Is there an easy way
>>>> to get IPython notebook to print dynamics variables using the dot
>>>> convention, and still give the nice LaTeX-rendered equations? If I use
>>>> vprint (from physics.vector), I get the variables with primes, but
>>>> just a
>>>> text rendering of the equations.
>>>> - I notice sympy.physics.mechanics.LagrangesMethod and
>>>> sympy.calculus.euler.euler_equations both implement Lagrangian
>>>> mechanics.
>>>> Is one of these more "official" than the other? Both seem to work for
>>>> the
>>>> very simple examples I have tried.
>>>>
>>>> Thanks
>>>>
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>>>
>>>
>>
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