LoopStructural.visualisation.ScalarField

class LoopStructural.visualisation.ScalarField(values, step_vector, nsteps, origin=array([0., 0., 0.]), name='scalar field', mode='node')

Bases: object

A scalar field defined by a regular grid and values

[summary]

Parameters:

• values (numpy array) – nodes values of regular grid

• step_vector (numpy array) – step vector for x,y,z step

• nsteps (numpy array) – number of steps

• name (string, optional) – name of the feature for the visualisation

• mode (string, optional) – property stored on nodes or as cell values, ‘node’ or ‘cell’

__init__(values, step_vector, nsteps, origin=array([0., 0., 0.]), name='scalar field', mode='node')

[summary]

Parameters:

• values (numpy array) – nodes values of regular grid

• step_vector (numpy array) – step vector for x,y,z step

• nsteps (numpy array) – number of steps

• name (string, optional) – name of the feature for the visualisation

• mode (string, optional) – property stored on nodes or as cell values, ‘node’ or ‘cell’

Methods

__init__(values, step_vector, nsteps[, ...])	[summary]
evaluate_value(xyz)	Evaluate the scalar field at locations
max()
min()

Attributes

nodes

evaluate_value(xyz)

Evaluate the scalar field at locations

Parameters:

xyz (numpy array) – locations in real coordinates

Returns:

numpy array – interpolated values, same shape as xyz