Interactive plots¶

This notebook show how to use Holoviews based plotting methods to create interactive plots of the magnetisation or derived quantities. The interface is the same as in discretisedfield.Field.hv. For details on the different plotting methods refer to the documentation of Holoviews based plotting in discretisedfield.

We have a set of example simulations stored in the test directory of micromagneticdata that we use to demonstrate its functionality.

Data¶

First, we creata a Data object. We need to pass the name of the micromagneticmodel.System that we used to run the simulation and optionally an additional path to the base directory.

The Data object contains all simulation runs of the System. These are called drives.

Time evolution of the magnetisation¶

We first create a plot for the averaged magnetisation components to better understand the behaviour of the system. We can see a precession of all three components of the averaged magnetisation.

We can use the .hv convenience method to create a plot similar to the plotting functionality in discretisedfield. We get an additional slider for the time variable.

We see that the magnetisation direction per time-step is uniform throughout the sample.

Resampling can be done like in discretisedfield using a tuple (to only affect kdims) or a dictionary to affect arbitrary dimensions. Here we reduce the number of points of the scalar part only in t direction and the number of arrows/the vector part in x, y, and t direction. We have to make sure that the same number of points are used for the scalar and vector part of the plot.

Computing derived quantities¶

If we want to first compute something for each field and then plot the result we have to use the following code snippet. Here, we plot the normalised magnetisation instead of the full magnetisation.

First we compute the desired quantity for each field and save xarray.DataArrays of the resulting Field objects.

Then we can use xarray to concatenate the results along the time dimension t. This dimension (the independent variable of the drive) can be accessed as time_drive.x. To get coordinates of that dimension we can use the table object of the drive.

We can then use the Holoviews based plotting methods. These are part of discretisedfield. Here, we plot the resulting data over t and x. We create a scalar plot and get a drop-dow selection for the individual components. We can see that the magnetisation per time step is uniform througout spatial x (and y and z) and changes over time.

We have to change the aspect of the plot data_aspect to get a proper plot. We use the ratio of the plot x direction (time) and the plot y direction (spatial x coordinate).

To give a second example, we compute the topological charge density on xy planes. This operation is implemented in discretisedfield.tools. However, discretisedfield.tools.topological_charge_density can only work on a single plane. Therefore, we compute the emergent_magnetic_field and take the x component (which gives the topolical charge on xy planes). As the magnetisation is uniform throughout the sample the topological charge density is zero everywhere (rendering this example somewhat boring). To still see the resulting data we have to use norm_filter=False when creating the plot.