<jupyter_start><jupyter_text>![OpenDreamKit logo and EU Flag](header.png)Review meeting 26 April 2017, Brussels Micromagnetic model in Notebook Mesh<jupyter_code>import oommfc as oc
import discretisedfield as df
%matplotlib inline
system = oc.System(name="system")

L = 30e-9   # size of simulation cube
d = 5e-9   # discretisation cell size 
mesh = oc.Mesh(p1=(0, 0, 0), p2=(L, L, L), cell=(d, d, d), name="mesh")
mesh<jupyter_output><empty_output><jupyter_text>LaTeX representation of equations: Hamiltonian and equation of motionPhysical system contains Hamiltonian, dynamics equation and magnetisation vector field:<jupyter_code>exchange = oc.Exchange(A=1e-12)
exchange
system.hamiltonian = exchange + oc.Zeeman(H=(0, 0, 1e6))
system.hamiltonian<jupyter_output><empty_output><jupyter_text>Dynamics<jupyter_code>system.dynamics = oc.Precession(gamma=2.211e5) + oc.Damping(alpha=0.15)
system.dynamics<jupyter_output><empty_output><jupyter_text>Analysing time-dependent data<jupyter_code>td = oc.TimeDriver() 
system.m = df.Field(mesh, value=(1, 0, 0), norm=8.6e5)
td.drive(system, t=2e-10, n=200)    # compute some data
system.dt.head()
system.dt.plot("t", "mx");
system.dt.plot("t", ["mx", "my", "mz"]);<jupyter_output><empty_output>
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