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README
Hamilton
Simulate physics on arbitrary coordinate systems using automatic differentiation and Hamiltonian mechanics. State only an arbitrary parameterization of your system and a potential energy function!
For example, a simulating a double pendulum system by simulating the progression of the angles of each bob:
You only need:
Your generalized coordinates (in this case,
θ1
andθ2
), and equations to convert them to cartesian coordinates of your objects:x1 = sin θ1 y1 = cos θ1 x2 = sin θ1 + sin θ2 / 2  second pendulum is halflength y2 = cos θ1  cos θ2 / 2
The masses/inertias of each of those cartesian coordinates (
m1
forx1
andy1
,m2
forx2
andy2
)A potential energy function for your objects:
U = (m1 y1 + m2 y2) * g
And that's it! Hamiltonian mechanics steps your generalized coordinates (θ1
and θ2
) through time, without needing to do any simulation involving
x1
/y1
/x2
/y2
! And you don't need to worry about tension or any other
stuff like that. All you need is a description of your coordinate system
itself, and the potential energy!
doublePendulum :: System 4 2
doublePendulum =
mkSystem' (vec4 m1 m1 m2 m2)  masses
(\(V2 θ1 θ2) > V4 (sin θ1) (cos θ1)
(sin θ1 + sin θ2/2) (cos θ1  cos θ2/2)
)  coordinates
(\(V4 _ y1 _ y2) > (m1 * y1 + m2 * y2) * g)
 potential
Thanks to Alexander William Rowan Hamilton, we can express our
system parameterized by arbitrary coordinates and get back equations of motions
as firstorder differential equations. This library solves those firstorder
differential equations for you using automatic differentiation and some matrix
manipulation.
See a blog post I wrote on this, and also the hackage documentation and the example runner user guide (and its source).
Full Example
Let's turn our double pendulum (with the second pendulum half as long) into an
actual running program. Let's say that g = 5
, m1 = 1
, and m2 = 2
.
First, the system:
import Numeric.LinearAlgebra.Static
import qualified Data.Vector.Sized as V
doublePendulum :: System 4 2
doublePendulum = mkSystem' masses coordinates potential
where
masses :: R 4
masses = vec4 1 1 2 2
coordinates
:: Floating a
=> V.Vector 2 a
> V.Vector 4 a
coordinates (V2 θ1 θ2) = V4 (sin θ1) (cos θ1)
(sin θ1 + sin θ2/2) (cos θ1  cos θ2/2)
potential
:: Num a
=> V.Vector 4 a
> a
potential (V4 _ y1 _ y2) = (y1 + 2 * y2) * 5
 some helper patterns to pattern match on sized vectors
pattern V2 :: a > a > V.Vector 2 a
pattern V2 x y < (V.toList>[x,y])
where
V2 x y = fromJust (V.fromList [x,y])
pattern V4 :: a > a > a > a > V.Vector 4 a
pattern V4 x y z a < (V.toList>[x,y,z,a])
where
V4 x y z a = fromJust (V.fromList [x,y,z,a])
Neat! Easy, right?
Okay, now let's run it. Let's pick a starting configuration (state of the
system) of θ1
and θ2
:
config0 :: Config 2
config0 = Cfg (vec2 1 0 )  initial positions
(vec2 0 0.5)  initial velocities
Configurations are nice, but Hamiltonian dynamics is all about motion through phase space, so let's convert this configurationspace representation of the state into a phasespace representation of the state:
phase0 :: Phase 2
phase0 = toPhase doublePendulum config0
And now we can ask for the state of our system at any amount of points in time!
ghci> evolveHam doublePendulum phase0 [0,0.1 .. 1]
 result: state of the system at times 0, 0.1, 0.2, 0.3 ... etc.
Or, if you want to run the system stepbystep:
evolution :: [Phase 2]
evolution = iterate (stepHam 0.1 doublePendulum) phase0
And you can get the position of the coordinates as:
positions :: [R 2]
positions = phsPositions <$> evolution
And the position in the underlying cartesian space as:
positions' :: [R 4]
positions' = underlyingPos doublePendulum <$> positions
Example App runner
(Source)
Installation:
$ git clone https://github.com/mstksg/hamilton
$ cd hamilton
$ stack install
Usage:
$ hamiltonexamples [EXAMPLE] (options)
$ hamiltonexamples help
$ hamiltonexamples [EXAMPLE] help
The example runner is a command line application that plots the progression of several example system through time.
Example  Description  Coordinates  Options 

doublepend 
Double pendulum, described above  θ1 , θ2 (angles of bobs) 
Masses of each bob 
pend 
Single pendulum  θ (angle of bob) 
Initial angle and velocity of bob 
room 
Object bounding around walled room  x , y 
Initial launch angle of object 
twobody 
Two gravitationally attracted bodies, described below  r , θ (distance between bodies, angle of rotation) 
Masses of bodies and initial angular veocity 
spring 
Spring hanging from a block on a rail, holding up a weight  r , x , θ (position of block, spring compression, spring angle) 
Masses of block, weight, spring constant, initial compression 
bezier 
Bead sliding at constant velocity along bezier curve  t (Bezier time parameter) 
Control points for arbitrary bezier curve 
Call with help
(or [EXAMPLE] help
) for more information.
More examples
Twobody system under gravity
 The generalized coordinates are just:
* `r`, the distance between the two bodies
* `θ`, the current angle of rotation
~~~haskell
x1 = m2/(m1+m2) * r * sin θ  assuming (0,0) is the center of mass
y1 = m2/(m1+m2) * r * cos θ
x2 = m1/(m1+m2) * r * sin θ
y2 = m1/(m1+m2) * r * cos θ
~~~
The masses/inertias are again
m1
forx1
andy1
, andm2
forx2
andy2
The potential energy function is the classic gravitational potential:
U =  m1 * m2 / r
And...that's all you need!
Here is the actual code for the twobody system, assuming m1
is 100
and
m2
is 1
:
twoBody :: System 4 2
twoBody = mkSystem masses coordinates potential
where
masses :: R 4
masses = vec4 100 100 1 1
coordinates
:: Floating a
=> V.Vector 2 a
> V.Vector 4 a
coordinates (V2 r θ) = V4 (r1 * cos θ) (r1 * sin θ)
(r2 * cos θ) (r2 * sin θ)
where
r1 = r * 1 / 101
r2 =  r * 100 / 101
potential
:: Num a
=> V.Vector 4 a
> a
potential (V2 r _) =  100 / r
Potential improvements
Timedependent systems: Shouldn't be an problem in theory/math; just add a time parameter before all of the functions. This opens a lot of doors, like deriving inertial forces for free (like the famous Coriolis force and centrifugal force).
The only thing is that it makes the API pretty inconvenient, because it'd require all of the functions to also take a time parameter. Of course, the easy way out/ugly solution would be to just offer two versions of the same function (one for timeindependent systems and one for timedependent systems. But this is unideal.
Velocitydependent potentials: Would give us the ability to model systems with velocitydependent Lagrangians like a charged particle in an electromagnetic field, and also dissipative systems, like systems with friction (dependent on
signum v
) and linear & quadratic wind resistance.This issue is much harder, theoretically. It involves inverting arbitrary functions
forall a. RealFloat a => V.Vector n a > V.Vector m a
. It might be possible with the help of some bidirectionalization techniques, but I can't get the bff package to compile, and I'm not sure how to get bffmono to work with numeric functions.If anyone is familiar with bidirectionalization techniques and is willing to help out, please send me a message or open an issue! :)