API Reference¶

`ariane.lib`¶

`Server`	Base class for server communication.
`Client`	Base class for client communication.

`GaussianProcessRegressorBase`	Base class (interface) for Gaussian process regressors.
`GaussianProcessRegressor`	Class for wrapping an implementation of a Gaussian process regressor.
`LogGaussianProcessRegressor`	Class for log-transforming and wrapping an implementation of a Gaussian process regressor.
`GaussianProcessRegressorImplementation`	Base class (interface) for implementations of Gaussian process regressors.
`implementations.sklearn.ScikitLearnGaussianProcessRegressor`	Wrapper class for scikit-learn's implementation of a Gaussian process regressor.
`learning.acquisitions.standard_deviation`	Return standard deviation function of a Gaussian Process regressor gpr.

`config.ConfigMixin`	Mixin class for adding a configuration instance.
`logging.LoggerMixin`	Mixin class for adding a logger instance.
`math.map_intervals`	Return function mapping between two intervals.
`math.normalizer`	Return function mapping an interval to (0, 1).
`math.denormalizer`	Return function mapping (0, 1) to an interval.
`math.cartesian_product`	Return the cartesian product of a set of sets.
`math.cholesky_update`	Update a Cholesky decomposition for new entries.
`math.compute_corner_pairs`	Return all pairs of corner points of a hypercube.
`math.make_grid`	Return a grid in a hyperrectangle with given number(s) of points per dimension.
`math.rotation_matrix_2d`	Return a 2D matrix rotating a coordinate system by a given angle.
`math.normalized_linear_interpolator`	Return a linear interpolator interpolating on a normalized (unit) hypercube.

`TASServer`	Base class for servers in TAS application.
`_server_gpr.server.GPRTASServer`	Class implementing template methods from TASServer based on log-Gaussian processes.
`_server_gpr.server.compute_heuris_experi_param`	Compute heuristic for experimental parameters like the background level and intensity threshold with intensities in intens.
`_server_gpr.server.maximize_obj_fct`
`_server_gpr.server.difference_hyperparameters`	Compute the difference of two arrays of kernel hyperparameters.
`_server_gpr.server.criterion_kernel_optims_stop`	Boolean criterion for stopping optimization of kernel hyperparameters.
`_server_gpr.server.normalize_det_cts`	Normalize detector counts to reference value mon_cts0.
`_server_gpr.server.process_det_cts_to_training_data`	Process detector counts before using it for training.
`_server_gpr.server.run`
`_server_gpr.gpr.TASGaussianProcessRegressorBase`	Base class for TAS-related Gaussian process regressors.
`_server_gpr.gpr.TASLogGaussianProcessRegressor`	Class for TAS-related log-Gaussian process regressors.
`_server_gpr.gpr.PotentialRotationDecorator`	Decorator class for TAS-related Gaussian process regressors.

`TASClient`	Base class for a client in a TAS application.
`_client_gpr.GPRTASClient`	Class implementing template methods from TASClient w.r.t.
`stubs.GPRTASClientStub`	Class imitating a GPRTASClient.

`x2qe`	Transform coordinates from 2D plane to 4D Q-E space.
`qe2x`	Transform coordinates from 4D Q-E space to 2D plane.
`Sample`	Class representing a sample.
`Orientation`	Class representing an orientation of a sample.
`InstrumentConfiguration`	Class representing an instrument configuration.
`Instrument`	Class representing an instrument.
`AngleMap`	Class for mapping Q-E points to corresponding angles of instrument axes.
`AngleMapInducedMetric`	Class representing a metric on 2D plane induced by an angle map.
`Scenario`	Class representing an experimental scenario.