torchphysics.problem.domains.domain0D package

Submodules

torchphysics.problem.domains.domain0D.point module

class torchphysics.problem.domains.domain0D.point.Point(space, point)

Bases: Domain

Creates a single point at the given coordinates.

Parameters:

• space (Space) – The space in which this object lays.

• coord (Number, List or callable) – The coordinate of the point.

__call__(**data)

Evaluates the domain at the given data.

bounding_box(params=Points: {}, device='cpu')

Computes the bounds of the domain.

Returns:

A torch.Tensor with the length of 2*self.dim. It has the form [axis_1_min, axis_1_max, axis_2_min, axis_2_max, …], where min and max are the minimum and maximum value that the domain reaches in each dimension-axis.

Return type:

tensor

sample_grid(n=None, d=None, params=Points: {}, device='cpu')

Creates an equdistant grid in the domain.

Parameters:

• n (int, optional) – The number of points that should be created.

• d (float, optional) – The density of points that should be created, if n is not defined.

• params (torchphysics.problem.Points, optional) – Additional paramters that are maybe needed to evaluate the domain.

• device (str) – The device on which the points should be created. Default is ‘cpu’.

Returns:

A Points object containing the sampled points.

Return type:

Points

sample_random_uniform(n=None, d=None, params=Points: {}, device='cpu')

Creates random uniformly distributed points in the domain.

Parameters:

• n (int, optional) – The number of points that should be created.

• d (float, optional) – The density of points that should be created, if n is not defined.

• params (torchphysics.problem.Points, optional) – Additional paramters that are maybe needed to evaluate the domain.

• device (str) – The device on which the points should be created. Default is ‘cpu’.

Returns:

A Points object containing the sampled points.

Return type:

Points