scimba_torch.integration.monte_carlo_parameters¶

Parameter samplers for Monte Carlo simulations.

Classes

`UniformParametricSampler`(bounds)	Sample uniformly from given bounds for each dimension.
`UniformVelocitySampler`(velocity_domain)	Sample uniformly the velocities in a circle of radius r.
`UniformVelocitySamplerOnCuboid`(velocity_domain)	Sample uniformly the velocities in a cuboid.

class UniformParametricSampler(bounds)[source]¶

Bases: object

Sample uniformly from given bounds for each dimension.

Parameters:

bounds (list[tuple[float, float]]) – A list of tuples where each tuple contains the lower and upper bounds for each dimension.

Raises:

TypeError – If parameters domain is not a list of tuples of two floats.
ValueError – If any bound has lower value greater than upper value.

bounds¶: A list of tuples where each tuple contains the lower and upper bounds for each dimension.

dim¶: The number of dimensions, inferred from the length of bounds.

sample(n)[source]¶

Generates samples uniformly within the specified bounds for each dimension.

Parameters:

n (int) – The number of samples to generate.

Return type:

LabelTensor

Returns:

A tensor containing the generated samples and corresponding labels.

Raises:

TypeError – If argument is not an integer.
ValueError – If argument is negative.

class UniformVelocitySampler(velocity_domain)[source]¶

Bases: object

Sample uniformly the velocities in a circle of radius r.

Parameters:: velocity_domain (Circle2D) – Velocity domain in which the velocity will be drawn.
Raises:: TypeError – If velocity domain is not an object of class Circle2D.

dim¶: The number of dimensions, here equal to 2.

sample(n)[source]¶

Generates samples uniformly within the specified bounds for each dimension.

Parameters:

n (int) – The number of samples to generate.

Return type:

LabelTensor

Returns:

A tensor containing the generated samples and corresponding labels.

Raises:

TypeError – If argument is not an integer.
ValueError – If argument is negative.

class UniformVelocitySamplerOnCuboid(velocity_domain)[source]¶

Bases: object

Sample uniformly the velocities in a cuboid.

Parameters:: velocity_domain (Segment1D | Square2D | Cube3D) – Velocity domain in which the velocity will be drawn.
Raises:: TypeError – If velocity domain is not an object of class Segment1D, Square2D or Cube3D.

dim¶: The number of dimensions.

domain_size¶: The size of the domain in each dimension.

lower_bound¶: The lower bound of the domain.

sample(n)[source]¶

Generates samples uniformly within the specified bounds for each dimension.

Parameters:

n (int) – The number of samples to generate.

Return type:

LabelTensor

Returns:

A tensor containing the generated samples and corresponding labels.

Raises:

TypeError – If argument is not an integer.
ValueError – If argument is negative.