gym_ignition.randomizers.model¶

gym_ignition.randomizers.model.sdf¶

class gym_ignition.randomizers.model.sdf.Distribution(value)¶

Bases: enum.Enum

An enumeration.

Gaussian = 2¶

Uniform = 1¶

class gym_ignition.randomizers.model.sdf.GaussianParams(variance, mean)¶

Bases: NamedTuple

mean: float¶: Alias for field number 1

variance: float¶: Alias for field number 0

class gym_ignition.randomizers.model.sdf.Method(value)¶

Bases: enum.Enum

An enumeration.

Absolute = 1¶

Additive = 2¶

Coefficient = 3¶

class gym_ignition.randomizers.model.sdf.RandomizationData(xpath, distribution, parameters, method, ignore_zeros, force_positive, element)¶

Bases: NamedTuple

distribution: str¶: Alias for field number 1

element: lxml.etree.Element¶: Alias for field number 6

force_positive: bool¶: Alias for field number 5

ignore_zeros: bool¶: Alias for field number 4

method: gym_ignition.randomizers.model.sdf.Method¶: Alias for field number 3

parameters: Union[gym_ignition.randomizers.model.sdf.UniformParams, gym_ignition.randomizers.model.sdf.GaussianParams]¶: Alias for field number 2

xpath: str¶: Alias for field number 0

class gym_ignition.randomizers.model.sdf.RandomizationDataBuilder(randomizer)¶

Bases: object

Builder class of a RandomizationData object.

Parameters: randomizer (SDFRandomizer) – The SDFRandomizer object to which the created randomization will be inserted.

add()¶

Close the chaining of methods and return to the SDF randomizer the configuration.

Raises: RuntimeError – If the XPath pattern does not find any match in the SDF.
Return type: None

at_xpath(xpath)¶

Set the XPath pattern associated to the randomization.

Parameters: xpath (str) – The XPath pattern.
Return type: RandomizationDataBuilder
Returns: The randomization builder to allow chaining methods.

force_positive(force_positive=True)¶

Force the randomized value to be greater than zero.

This option is helpful to enforce that values e.g. the mass will stay positive regardless of the applied distribution parameters.

Parameters: force_positive (bool) – True to force positive parameters, false otherwise.
Return type: RandomizationDataBuilder
Returns: The randomization builder to allow chaining methods.

ignore_zeros(ignore_zeros)¶

Ignore the randomization of values that are zero.

If the value to randomize has a default value of 0 in the SDF, when this method is chained the randomization is skipped. In the case of a multi-match XPath pattern, the values that are not zero are not skipped.

Parameters: ignore_zeros (bool) – True if zeros should be ignored, false otherwise.
Return type: RandomizationDataBuilder
Returns: The randomization builder to allow chaining methods.

method(method)¶

Set the randomization method.

Parameters: method (Method) – The desired randomization method.
Return type: RandomizationDataBuilder
Returns: The randomization builder to allow chaining methods.

sampled_from(distribution, parameters)¶

Set the distribution associated to the randomization.

Parameters

distribution (Distribution) – The desired distribution.
parameters (Union[UniformParams, GaussianParams]) – The namedtuple with the parameters of the distribution.

Return type

RandomizationDataBuilder

Returns

The randomization builder to allow chaining methods.

class gym_ignition.randomizers.model.sdf.SDFRandomizer(sdf_model)¶

Bases: object

Randomized SDF files generator.

Parameters: sdf_model (str) – The absolute path to the SDF file.
Raises: ValueError – If the SDF file does not exist.

clean()¶

Clean the SDF randomizer.

Return type: None

find_xpath(xpath)¶

Find the elements that match an XPath pattern.

This method could be helpful to test the matches of a XPath pattern before using it in at_xpath().

Parameters: xpath (str) – The XPath pattern.
Return type: List[Element]
Returns: A list of elements matching the XPath pattern.

get_active_randomizations()¶

Return the active randomizations.

This method could be helpful also in the case of multi-match XPath patterns to validate that the inserted randomizations have been processed correctly.

Return type: List[RandomizationData]
Returns: The list of the active randomizations.

insert(randomization_data)¶

Insert a randomization.

Parameters: randomization_data – A new randomization.
Return type: None

new_randomization()¶

Start the chaining to build a new randomization.

Return type: RandomizationDataBuilder
Returns: A randomization builder.

process_data()¶

Process all the inserted randomizations.

Raises: RuntimeError – If the XPath of a randomization has no matches.
Return type: None

sample(pretty_print=False)¶

Sample a randomized SDF string.

Parameters

pretty_print – True to pretty print the output.

Raises

ValueError – If the distribution of a randomization is not recognized.
ValueError – If the method of a randomization is not recognized.

Return type

str

Returns

The randomized model as SDF string.

seed(seed)¶

Seed the SDF randomizer.

Parameters: seed (int) – The seed number.
Return type: None

class gym_ignition.randomizers.model.sdf.UniformParams(low, high)¶

Bases: NamedTuple

high: float¶: Alias for field number 1

low: float¶: Alias for field number 0