#!/usr/bin/env python
# coding: utf-8

# # Calculating a stray field using an airbox method
# 
# In order to calculate the stray field outside the sample, we have to define an "airbox" which is going to contain our sample. In this example we define a box with 100 nm edgle length as a mesh which then contains a magnetic sample which is a cube with 50 nm dimensions. We achieve this by implementing a Python function for defining the Ms (`norm_fun`). Outside our sample the value of saturation magnetisation is zero.

# In[1]:


import discretisedfield as df
import micromagneticmodel as mm
import oommfc as oc

region = df.Region(p1=(-100e-9, -100e-9, -100e-9), p2=(100e-9, 100e-9, 100e-9))
mesh = df.Mesh(region=region, cell=(5e-9, 5e-9, 5e-9))


def norm_fun(pos):
    x, y, z = pos
    if -50e-9 <= x <= 50e-9 and -50e-9 <= y <= 50e-9 and -50e-9 <= z <= 50e-9:
        return 8e5
    else:
        return 0


system = mm.System(name="airbox_method")
system.energy = mm.Exchange(A=1e-12) + mm.Demag()
system.dynamics = mm.Precession(gamma0=mm.consts.gamma0) + mm.Damping(alpha=1)
system.m = df.Field(mesh, nvdim=3, value=(0, 0, 1), norm=norm_fun, valid="norm")


# We can now plot the norm to confirm our definition.

# In[2]:


system.m.norm.sel("z").mpl()


# In the next step, we can relax the system and show its magnetisation.

# In[3]:


md = oc.MinDriver()
md.drive(system)

system.m.sel("z").mpl(figsize=(10, 10))


# Stray field can now be calculated as an effective field for the demagnetisation energy.

# In[4]:


stray_field = oc.compute(system.energy.demag.effective_field, system)


# `stray_field` is a `df.Field` and all operations characteristic to vector fields can be performed.

# In[5]:


stray_field.sel("z").mpl(figsize=(8, 8), vector_kw={"scale": 1e6})