transform

ENS_VPORT.transform(axis_angle: List[float] | None = None, quaternion: List[float] | None = None, translation: List[float] | None = None, data_translation: List[float] | None = None, scale: List[float] | None = None, link: int = 0) → None

This method applies an incremental transformation to the specified viewport view.

For an pyensight.ens_part_particle_trace.ENS_PART_PARTICLE_TRACE instance, this method will return the data spce coordinates and time of each particle trace point. Optionally, it can return variable values sampled at those coordinates.

Args:

axis_angle:

For a four value input tuple of the form [nx,ny,nz,angle], apply a rotation over the normal specified by [nx,ny,nz] in data space by the angle (in radians).

quaternion:

For a four value input tuple of the form [a,b,c,d], apply the rotation specified by the normalized quaternion represented by the tuple. The rotation is applied in data space. Note: this is equivalent to combining the input with the to the pyensight.ens_vport.ENS_VPORT.ROTATION attribute.

translation:

For a three value input tuple of the form [dx,dy,dz], apply a translation in screen space by the input tuple. Note: this is equivalent to adding the components to the pyensight.ens_vport.ENS_VPORT.TRANSLATION attribute.

data_translation:

For a three value input tuple of the form [dx,dy,dz], apply a translation in data space by the input tuple.

scale:

The value may either be a scalar or a three value tuple. The former specifies isotropic data space scaling and the latter allows for anisotropic scaling. Note: it is strongly recommended that anisotropic scaling not be used if it can at all be avoided as many EnSight operations assume isotropic scaling. This is equivalent to component-wise multiplication with the pyensight.ens_vport.ENS_VPORT.SCALE attribute.

link:

If non-zero and the target viewport is linked to other viewports, the transform will be applied to this and all linked viewports.

Example:

# get the default viewport
v = session.ensight.objs.core.VPORTS[0]
# apply a rotation over the data X axis and increase the scale 20%
v.transform(axis_angle=[1,0,0,0.07], scale=1.2)
# translate in the data space X axis by one unit
v.transform(data_translation=(-1,0,0))