K3dMesh#

class discretisedfield.plotting.K3dMesh(mesh)#

Methods

__call__

k3d plot.

__dir__

Default dir() implementation.

__eq__

Return self==value.

__repr__

Return repr(self).

subregions

k3d subregions plot.
__call__(*, plot=None, color=[5010096, 14517330], multiplier=None, **kwargs)#

k3d plot.

If plot is not passed, k3d.Plot object is created automatically. The color of the region and the discretisation cell can be specified using color length-2 tuple, where the first element is the colour of the region and the second element is the colour of the discretisation cell.

It is often the case that the object size is either small (e.g. on a nanoscale) or very large (e.g. in units of kilometers). Accordingly, multiplier can be passed as \(10^{n}\), where \(n\) is a multiple of 3 (…, -6, -3, 0, 3, 6,…). According to that value, the axes will be scaled and appropriate units shown. For instance, if multiplier=1e-9 is passed, all axes will be divided by \(1\,\text{nm}\) and \(\text{nm}\) units will be used as axis labels. If multiplier is not passed, the best one is calculated internally.

This method is based on k3d.voxels, so any keyword arguments accepted by it can be passed (e.g. wireframe).

Parameters:

  • plot (k3d.Plot, optional) – Plot to which the plot is added. Defaults to None - plot is created internally.

  • color ((2,) array_like) – Colour of the region and the discretisation cell. Defaults to the default color palette.

  • multiplier (numbers.Real, optional) – Axes multiplier. Defaults to None.

Examples

  1. Visualising the mesh using k3d.

>>> import discretisedfield as df
>>> p1 = (0, 0, 0)
>>> p2 = (100, 100, 100)
>>> n = (10, 10, 10)
>>> mesh = df.Mesh(p1=p1, p2=p2, n=n)
...
>>> mesh.k3d()
Plot(...)
subregions(*, plot=None, color=[5010096, 14517330, 5613672, 12865106, 8483507, 9664608, 14322627, 9211020, 13416820, 6600141], multiplier=None, **kwargs)#

k3d subregions plot.

If plot is not passed, k3d.Plot object is created automatically. The color of the subregions can be specified using color.

It is often the case that the object size is either small (e.g. on a nanoscale) or very large (e.g. in units of kilometers). Accordingly, multiplier can be passed as \(10^{n}\), where \(n\) is a multiple of 3 (…, -6, -3, 0, 3, 6,…). According to that value, the axes will be scaled and appropriate units shown. For instance, if multiplier=1e-9 is passed, all axes will be divided by \(1\,\text{nm}\) and \(\text{nm}\) units will be used as axis labels. If multiplier is not passed, the best one is calculated internally.

This method is based on k3d.voxels, so any keyword arguments accepted by it can be passed (e.g. wireframe).

Parameters:

  • plot (k3d.Plot, optional) – Plot to which the plot is added. Defaults to None - plot is created internally.

  • color (array_like) – Colour of the subregions. Defaults to the default color palette.

  • multiplier (numbers.Real, optional) – Axes multiplier. Defaults to None.

Examples

  1. Visualising subregions using k3d.

>>> import discretisedfield as df
>>> p1 = (0, 0, 0)
>>> p2 = (100, 100, 100)
>>> n = (10, 10, 10)
>>> subregions = {'r1': df.Region(p1=(0, 0, 0), p2=(50, 100, 100)),
...               'r2': df.Region(p1=(50, 0, 0), p2=(100, 100, 100))}
>>> mesh = df.Mesh(p1=p1, p2=p2, n=n, subregions=subregions)
...
>>> mesh.k3d.subregions()
Plot(...)