class ScalarField:
"""A scalar field defined by a regular grid and values"""
def __init__(self,
values,
step_vector,
nsteps,
origin=np.zeros(3),
name="scalar field"):
"""[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
"""
self.values = values
self.grid = StructuredGrid(origin, nsteps, step_vector)
self.name = name
@property
def nodes(self):
return self.grid.nodes
def evaluate_value(self, xyz):
"""Evaluate the scalar field at locations
Parameters
----------
xyz : numpy array
locations in real coordinates
Returns
-------
numpy array
interpolated values
"""
v = self.grid.evaluate_value(xyz, self.values)
return v
def min(self):
return np.min(self.values)
def max(self):
return np.max(self.values) # 14
def test_evaluate_value():
grid = StructuredGrid()
grid.update_property('X', grid.nodes[:, 0])
assert np.sum(grid.barycentre()[:, 0] -
grid.evaluate_value(grid.barycentre(), 'X')) == 0
def test_evaluate_value():
grid = StructuredGrid()
assert (
np.sum(grid.barycentre[:, 0] -
grid.evaluate_value(grid.barycentre, grid.nodes[:, 0])) == 0)