def field2topological_density(field, slice_axis, slice_coord):
"""
field2topological_density(field, slice_axis, slice_coord)
This function constructs a Holoviews object
which shows the topological density.
Inputs
======
field:
Path to an OMF file or object of type disc.Field
slice_axis:
The axis along which the vector field will be sliced given as a string.
Must be one of ['x', 'y', 'z']
slice_coord:
The coordinate along the slice_axis where the field is sliced
"""
# Construct a field object if not a field object
if isinstance(field, str):
field = discretisedfield.read_oommf_file(field, normalisedto=1)
field.normalise()
if slice_axis == 'z':
axis = (0, 1, 2)
elif slice_axis == 'y':
axis = (0, 2, 1)
elif slice_axis == 'x':
axis = (1, 2, 0)
else:
raise ValueError("Slice Axis must be one of 'x', 'y' ,'z'")
dims = ['x', 'y', 'z']
bounds = [field.mesh.p1[axis[0]],
field.mesh.p1[axis[1]],
field.mesh.p2[axis[0]],
field.mesh.p2[axis[1]]]
x, y, vec, coords = field.slice_field(slice_axis, slice_coord)
shape = np.shape(vec)[0], np.shape(vec)[1]
mbig = np.zeros((shape[0] + 2, shape[1] + 2, 3))
mbig[1:-1, 1:-1] = vec
Q = np.zeros((shape[0] + 2, shape[1] + 2))
print(shape)
for i in range(1, shape[0]+1):
for j in range(1, shape[1]+1):
Q[i, j] = (mbig[i, j].dot(np.cross(mbig[i+1, j], mbig[i, j+1])) +
mbig[i, j].dot(np.cross(mbig[i-1, j], mbig[i, j-1])) -
mbig[i, j].dot(np.cross(mbig[i-1, j], mbig[i, j+1])) -
mbig[i, j].dot(np.cross(mbig[i+1, j], mbig[i, j-1]))
)
return hv.Image(Q[1:-1, 1:-1],
label='Topological Density',
bounds=bounds,
kdims=[dims[axis[0]], dims[axis[1]]],
vdims=[hv.Dimension('Q_{}'.format(slice_axis))])
def _update_m(self, system):
# Find last omf file.
dirname = self._filenames(system)["dirname"]
last_omf_file = max(glob.iglob("{}*.omf".format(dirname)),
key=os.path.getctime)
# Update system's magnetisaton.
m_field = df.read_oommf_file(last_omf_file)
m_field.normalisedto = system.m.normalisedto
m_field.normalise()
system.m = m_field
def field2topological_density(field, slice_axis, slice_coord):
"""
field2topological_density(field, slice_axis, slice_coord)
This function constructs a Holoviews object
which shows the topological density.
Inputs
======
field:
Path to an OMF file or object of type disc.Field
slice_axis:
The axis along which the vector field will be sliced given as a string.
Must be one of ['x', 'y', 'z']
slice_coord:
The coordinate along the slice_axis where the field is sliced
"""
# Construct a field object if not a field object
if isinstance(field, str):
field = discretisedfield.read_oommf_file(field, normalisedto=1)
field.normalise()
if slice_axis == 'z':
axis = (0, 1, 2)
elif slice_axis == 'y':
axis = (0, 2, 1)
elif slice_axis == 'x':
axis = (1, 2, 0)
else:
raise ValueError("Slice Axis must be one of 'x', 'y' ,'z'")
dims = ['x', 'y', 'z']
bounds = [
field.mesh.p1[axis[0]], field.mesh.p1[axis[1]], field.mesh.p2[axis[0]],
field.mesh.p2[axis[1]]
]
x, y, vec, coords = field.slice_field(slice_axis, slice_coord)
shape = np.shape(vec)[0], np.shape(vec)[1]
mbig = np.zeros((shape[0] + 2, shape[1] + 2, 3))
mbig[1:-1, 1:-1] = vec
Q = np.zeros((shape[0] + 2, shape[1] + 2))
print(shape)
for i in range(1, shape[0] + 1):
for j in range(1, shape[1] + 1):
Q[i,
j] = (mbig[i, j].dot(np.cross(mbig[i + 1, j], mbig[i, j + 1])) +
mbig[i, j].dot(np.cross(mbig[i - 1, j], mbig[i, j - 1])) -
mbig[i, j].dot(np.cross(mbig[i - 1, j], mbig[i, j + 1])) -
mbig[i, j].dot(np.cross(mbig[i + 1, j], mbig[i, j - 1])))
return hv.Image(Q[1:-1, 1:-1],
label='Topological Density',
bounds=bounds,
kdims=[dims[axis[0]], dims[axis[1]]],
vdims=[hv.Dimension('Q_{}'.format(slice_axis))])
def update_plot(self, value):
self.out.clear_output(wait=True)
omffile = self.find_omf_file()
field = df.read_oommf_file(omffile)
slice_index = {"x": 0, "y": 1, "z": 2}[self.select.value]
point = field.mesh.pmin[
slice_index] + self.slice_slider.value * field.mesh.l[slice_index]
field.plot_slice(self.select.value, point, xsize=10)
with self.out:
display(plt.gcf())
plt.close()
def __init__(self, name):
self.dirname = os.path.join(name, "")
odtfile = max(glob.iglob("{}*.odt".format(self.dirname)),
key=os.path.getctime)
self.omffiles = sorted(glob.iglob("{}*.omf".format(self.dirname)),
key=os.path.getctime)
last_omf_file = max(glob.iglob("{}*.omf".format(self.dirname)),
key=os.path.getctime)
self.last_field = df.read_oommf_file(last_omf_file)
self.dt = oommfodt.OOMMFodt(odtfile).df
self.stage = self.dt["stage"].as_matrix()
self.slider = ipywidgets.IntSlider(
value=self.stage[0],
min=self.stage[0],
max=self.stage[-1],
step=self.stage[1] - self.stage[0],
description="Stage:",
readout=True,
layout=ipywidgets.Layout(width="80%"),
continuous_update=False)
self.slice_slider = ipywidgets.FloatSlider(
value=0,
min=0,
max=1,
step=0.01,
description="Point:",
readout=True,
layout=ipywidgets.Layout(width="75.5%"),
continuous_update=False)
self.play = ipywidgets.Play(value=self.stage[0],
min=self.stage[0],
max=self.stage[-1],
step=self.stage[1] - self.stage[0])
self.select = ipywidgets.RadioButtons(options=["x", "y", "z"],
description="Slice:")
ipywidgets.jslink((self.play, "value"), (self.slider, "value"))
self.slider.observe(self.update_plot)
self.slice_slider.observe(self.update_plot)
self.select.observe(self.update_plot)
self.out = ipywidgets.Output(layout=ipywidgets.Layout(width="300%"))
self.update_plot(None)
def field2inplane_angle(field, slice_axis, slice_coord):
"""
field2hv(field, slice_axis, slice_coord)
This function constructs a Holoviews object
which shows the in plane Magnetisation and out of plane Magnetisation
Inputs
======
field:
Path to an OMF file or object of type discretisedfield.Field
slice_axis:
The axis along which the vector field will be sliced given as a string.
Must be one of ['x', 'y', 'z']
slice_coord:
The coordinate along the slice_axis where the field is sliced
"""
# Construct a field object if not a field object
if isinstance(field, str):
field = discretisedfield.read_oommf_file(field, normalisedto=1)
field.normalise()
if slice_axis == 'z':
axis = (0, 1, 2)
elif slice_axis == 'y':
axis = (0, 2, 1)
elif slice_axis == 'x':
axis = (1, 2, 0)
else:
raise ValueError("Slice Axis must be one of 'x', 'y' ,'z'")
dims = ['x', 'y', 'z']
bounds = [
field.mesh.p1[axis[0]], field.mesh.p1[axis[1]], field.mesh.p2[axis[0]],
field.mesh.p2[axis[1]]
]
x, y, vec, coords = field.slice_field(slice_axis, slice_coord)
X, Y = np.meshgrid(x, y)
flat = vec.flatten()
angm = np.pi + np.arctan2(flat[axis[1]::3], flat[axis[0]::3]).reshape(
(len(x), len(y)))
kdims = [dims[axis[0]], dims[axis[1]]]
return hv.Image(angm,
bounds=bounds,
kdims=kdims,
label='In-plane Magnetisation angle',
vdims=[
hv.Dimension('xyfield'.format(slice_axis),
range=(0, 2 * np.pi))
])
def field2inplane_angle(field, slice_axis, slice_coord):
"""
field2hv(field, slice_axis, slice_coord)
This function constructs a Holoviews object
which shows the in plane Magnetisation and out of plane Magnetisation
Inputs
======
field:
Path to an OMF file or object of type discretisedfield.Field
slice_axis:
The axis along which the vector field will be sliced given as a string.
Must be one of ['x', 'y', 'z']
slice_coord:
The coordinate along the slice_axis where the field is sliced
"""
# Construct a field object if not a field object
if isinstance(field, str):
field = discretisedfield.read_oommf_file(field, normalisedto=1)
field.normalise()
if slice_axis == 'z':
axis = (0, 1, 2)
elif slice_axis == 'y':
axis = (0, 2, 1)
elif slice_axis == 'x':
axis = (1, 2, 0)
else:
raise ValueError("Slice Axis must be one of 'x', 'y' ,'z'")
dims = ['x', 'y', 'z']
bounds = [field.mesh.p1[axis[0]],
field.mesh.p1[axis[1]],
field.mesh.p2[axis[0]],
field.mesh.p2[axis[1]]]
x, y, vec, coords = field.slice_field(slice_axis, slice_coord)
X, Y = np.meshgrid(x, y)
flat = vec.flatten()
angm = np.pi + np.arctan2(flat[axis[1]::3],
flat[axis[0]::3]).reshape((len(x), len(y)))
kdims = [dims[axis[0]], dims[axis[1]]]
return hv.Image(angm,
bounds=bounds,
kdims=kdims,
label='In-plane Magnetisation angle',
vdims=[hv.Dimension('xyfield'.format(slice_axis),
range=(0, 2*np.pi))])