Skip to main content
Ctrl+K

AIXD

  • Introduction
  • Installation
  • API Reference
  • User Guide
  • Examples
    • License
    • Authors
    • Citing
    • References
  • Introduction
  • Installation
  • API Reference
  • User Guide
  • Examples
  • License
  • Authors
  • Citing
  • References

Section Navigation

  • AI-eXtended Design
    • aixd.data
      • Dataset
        • Dataset.analysis
        • Dataset.check_data_consistency
        • Dataset.data_mat_with_dobjs
        • Dataset.from_dataset_folder
        • Dataset.get_data_objects_by_name
        • Dataset.get_samples
        • Dataset.import_data
        • Dataset.import_data_from_csv
        • Dataset.import_data_from_df
        • Dataset.load
        • Dataset.sampling
        • Dataset.save_dataset_obj
        • Dataset.summary_data
        • Dataset.summary_datablocks
        • Dataset.summary_dataobjects
        • Dataset.update_obj_domains
      • DataObject
        • DataObject.append_transformation
        • DataObject.check_data_consistency
        • DataObject.copy
        • DataObject.get_activation_outhead
        • DataObject.get_loss_evaluation
        • DataObject.get_ml_heads
        • DataObject.get_objective
        • DataObject.grid_samples
        • DataObject.has_name
        • DataObject.inverse_transform
        • DataObject.prepend_transformation
        • DataObject.print_transf_norm
        • DataObject.random_samples
        • DataObject.sample_around
        • DataObject.transform
        • DataObject.transform_is_fitted
        • DataObject.update_dobj_types
        • DataObject.update_obj
      • DataReal
        • DataReal.from_range
        • DataReal.get_activation_outhead
        • DataReal.get_loss_evaluation
        • DataReal.get_ml_heads
        • DataReal.get_objective
      • DataDiscrete
        • DataDiscrete.is_data_transformed
      • DataInt
        • DataInt.from_range
        • DataInt.get_activation_outhead
        • DataInt.get_loss_evaluation
        • DataInt.get_ml_heads
        • DataInt.get_objective
      • DataCategorical
        • DataCategorical.copy
        • DataCategorical.from_options
        • DataCategorical.get_activation_outhead
        • DataCategorical.get_loss_evaluation
        • DataCategorical.get_ml_heads
        • DataCategorical.get_objective
      • DataBool
      • Domain
        • Domain.check_domain_consistency
        • Domain.copy
        • Domain.domain_to_normalised
        • Domain.grid_samples
        • Domain.normalised_to_domain
        • Domain.random_samples
        • Domain.sample_around
        • Domain.update_domain
      • Options
        • Options.check_domain_consistency
        • Options.copy
        • Options.domain_to_normalised
        • Options.grid_samples
        • Options.normalised_to_domain
        • Options.random_samples
        • Options.sample_around
        • Options.update_domain
      • Interval
        • Interval.check_domain_consistency
        • Interval.copy
        • Interval.domain_to_normalised
        • Interval.grid_samples
        • Interval.normalised_to_domain
        • Interval.random_samples
        • Interval.sample_around
        • Interval.update_domain
      • IntervalMasked
        • IntervalMasked.copy
      • DataBlock
        • DataBlock.check_data_consistency
        • DataBlock.get_cols_dobjs
        • DataBlock.get_data_mat
        • DataBlock.get_data_mat_dtypes
        • DataBlock.get_data_mats
        • DataBlock.get_dobj_dimensions
        • DataBlock.get_dobjs
        • DataBlock.info_dobj
        • DataBlock.print_objects
        • DataBlock.print_transf
        • DataBlock.read
        • DataBlock.update_obj
        • DataBlock.update_position_indices
        • DataBlock.write
      • DesignParameters
      • PerformanceAttributes
      • DesignRepresentation
        • DesignRepresentation.read
        • DesignRepresentation.write
      • TransformableDataBlock
        • TransformableDataBlock.get_dobj_dimensions
        • TransformableDataBlock.inverse_transform
        • TransformableDataBlock.to_data_block
        • TransformableDataBlock.transform
        • TransformableDataBlock.transformation_is_fitted
      • InputML
      • OutputML
      • CustomCallback
        • CustomCallback.run
      • AnalysisCallback
        • AnalysisCallback.analyze
        • AnalysisCallback.run
      • ImportCallback
        • ImportCallback.run
      • SamplingCallback
        • SamplingCallback.run
      • DataObjectTransform
        • DataObjectTransform.copy
        • DataObjectTransform.fit
        • DataObjectTransform.fit_transform
        • DataObjectTransform.inverse_transform
        • DataObjectTransform.is_fitted
        • DataObjectTransform.reset
        • DataObjectTransform.transform
      • Log10Transform
        • Log10Transform.inverse_transform
        • Log10Transform.transform
      • SigmoidTransform
        • SigmoidTransform.inverse_transform
        • SigmoidTransform.is_fitted
        • SigmoidTransform.reset
        • SigmoidTransform.transform
      • Standardization
        • Standardization.inverse_transform
        • Standardization.is_fitted
        • Standardization.reset
        • Standardization.transform
      • MinMaxScaler
        • MinMaxScaler.inverse_transform
        • MinMaxScaler.is_fitted
        • MinMaxScaler.reset
        • MinMaxScaler.transform
      • ZeroToOne
      • MinusOneToOne
      • MaskedMinMaxScaler
        • MaskedMinMaxScaler.inverse_transform
        • MaskedMinMaxScaler.transform
      • MaskedZeroToOne
      • MaskedMinusOneToOne
      • LabelEncoder
        • LabelEncoder.fit
        • LabelEncoder.inverse_transform
        • LabelEncoder.is_fitted
        • LabelEncoder.reset
        • LabelEncoder.transform
      • ToFloat
        • ToFloat.inverse_transform
        • ToFloat.is_fitted
        • ToFloat.transform
      • aixd.data.utils_data.convert_to
      • aixd.data.utils_data.combine_formats
      • aixd.data.utils_data.reformat_dict_to_dataframe
      • aixd.data.utils_data.reformat_dataframe_to_dict
      • aixd.data.utils_data.reformat_dataframe_to_dictlist
      • aixd.data.utils_data.reformat_dataframeflat_to_dict
      • aixd.data.utils_data.reformat_dataframe_to_dataframeflat
      • aixd.data.utils_data.reformat_dataframeflat_to_dataframe
      • aixd.data.utils_data.reformat_list_to_array
      • aixd.data.utils_data.reformat_array_to_list
      • aixd.data.utils_data.reformat_list_to_dataframe
      • aixd.data.utils_data.reformat_dataframe_to_list
      • aixd.data.utils_data.reformat_list_to_dict
      • aixd.data.utils_data.reformat_list_to_dictlist
      • aixd.data.utils_data.reformat_dictlist_to_dict
      • aixd.data.utils_data.reformat_dict_to_dictlist
      • aixd.data.utils_data.reformat_array_to_torch
      • aixd.data.utils_data.reformat_torch_to_array
    • aixd.mlmodel
      • DataModule
        • DataModule.convert_to_dataloader
        • DataModule.from_config_dict
        • DataModule.from_dataset
        • DataModule.from_json
        • DataModule.from_parameters
        • DataModule.get_checksum
        • DataModule.get_data_objects_by_name
        • DataModule.get_parameters
        • DataModule.get_x_test
        • DataModule.get_x_train
        • DataModule.get_x_val
        • DataModule.get_y_test
        • DataModule.get_y_train
        • DataModule.get_y_val
        • DataModule.inverse_transform
        • DataModule.inverse_transform_x
        • DataModule.inverse_transform_y
        • DataModule.load
        • DataModule.predict_dataloader
        • DataModule.save
        • DataModule.summary_input_output_dimensions
        • DataModule.test_dataloader
        • DataModule.to_config_dict
        • DataModule.train_dataloader
        • DataModule.transform
        • DataModule.transform_x
        • DataModule.transform_y
        • DataModule.val_dataloader
      • CondAEModel
        • CondAEModel.calc_x_losses_calculation
        • CondAEModel.calc_y_losses_calculation
        • CondAEModel.configure_optimizers
        • CondAEModel.decode
        • CondAEModel.encode
        • CondAEModel.evaluate
        • CondAEModel.fit
        • CondAEModel.forward
        • CondAEModel.forward_evaluation
        • CondAEModel.from_datamodule
        • CondAEModel.generate
        • CondAEModel.get_evaluation_losses
        • CondAEModel.load_model_from_checkpoint
        • CondAEModel.on_load_checkpoint
        • CondAEModel.on_save_checkpoint
        • CondAEModel.predict
        • CondAEModel.predict_step
        • CondAEModel.predict_y
        • CondAEModel.save_extra_parameters
        • CondAEModel.split_x_head_in
        • CondAEModel.split_x_head_out
        • CondAEModel.split_xy_in
        • CondAEModel.split_xy_out
        • CondAEModel.split_y_head_in
        • CondAEModel.split_y_head_out
        • CondAEModel.summary
        • CondAEModel.test
        • CondAEModel.test_step
        • CondAEModel.to_untransformed_pred
        • CondAEModel.training_step
        • CondAEModel.validate
        • CondAEModel.validation_step
      • CondVAEModel
      • InverseModel
        • InverseModel.fit
        • InverseModel.forward
      • FreezeEncoder
        • FreezeEncoder.finetune_function
        • FreezeEncoder.freeze_before_training
      • ResBlockFC
        • ResBlockFC.forward
      • ResBlockConv
        • ResBlockConv.forward
      • ResBlock1D
      • ResBlock2D
      • ResBlock3D
      • SelfAttn
        • SelfAttn.forward
      • SelfAttn1D
      • SelfAttn2D
      • SelfAttn3D
      • Activation
        • Activation.forward
      • Decoder
        • Decoder.forward
        • Decoder.summary
      • Encoder
        • Encoder.forward
        • Encoder.summary
      • VEncoder
        • VEncoder.forward
      • InHeadFC
        • InHeadFC.forward
      • OutHeadFC
        • OutHeadFC.forward
      • InHeadConv
        • InHeadConv.forward
      • OutHeadConv
        • OutHeadConv.forward
      • InHeadConv1D
      • OutHeadConv1D
      • InHeadConv2D
      • OutHeadConv2D
      • InHeadConv3D
      • OutHeadConv3D
      • LossStd
        • LossStd.forward
      • MGEloss
        • MGEloss.forward
      • Generator
        • Generator.generate
        • Generator.info_attributes_req
        • Generator.print_results_gen
      • GeneratorSampler
        • GeneratorSampler.generate
        • GeneratorSampler.generate_z
        • GeneratorSampler.summary_sampling_types
      • LocalSensitivity
        • LocalSensitivity.calculate
        • LocalSensitivity.plot
      • GlobalSensitivity
        • GlobalSensitivity.calculate
        • GlobalSensitivity.plot
    • aixd.sampler
      • GeneratorCallback
      • SamplingEngine
        • SamplingEngine.deserialise
        • SamplingEngine.reset_states
        • SamplingEngine.sample
        • SamplingEngine.update
      • AgnosticSamplingEngine
        • AgnosticSamplingEngine.update
      • AdaptiveSamplingEngine
        • AdaptiveSamplingEngine.update
      • RandomSamplingEngine
        • RandomSamplingEngine.sample
      • GridSamplingEngine
        • GridSamplingEngine.sample
      • SobolSamplingEngine
        • SobolSamplingEngine.reset_states
        • SobolSamplingEngine.sample
      • LHCSamplingEngine
        • LHCSamplingEngine.reset_states
        • LHCSamplingEngine.sample
      • BayesOptSamplingEngine
        • BayesOptSamplingEngine.reset_states
        • BayesOptSamplingEngine.sample
        • BayesOptSamplingEngine.update
      • Arithmetic
        • Arithmetic.is_differentiable
      • Boolean
        • Boolean.is_differentiable
      • Constant
        • Constant.evaluate
      • Add
        • Add.evaluate
      • Multiply
        • Multiply.evaluate
      • Subtract
        • Subtract.evaluate
      • Divide
        • Divide.evaluate
      • LessThan
        • LessThan.evaluate
      • LessOrEqual
        • LessOrEqual.evaluate
      • GreaterThan
        • GreaterThan.evaluate
      • GreaterOrEqual
        • GreaterOrEqual.evaluate
      • Log
        • Log.evaluate
      • Exp
        • Exp.evaluate
      • Pow
        • Pow.evaluate
      • Not
        • Not.evaluate
      • And
        • And.evaluate
      • Or
        • Or.evaluate
      • XOr
        • XOr.evaluate
      • Equal
        • Equal.evaluate
      • Negative
        • Negative.evaluate
      • CastBooleanToConstant
        • CastBooleanToConstant.evaluate
        • CastBooleanToConstant.is_differentiable
      • Reducer
        • Reducer.evaluate
        • Reducer.is_differentiable
      • Sum
        • Sum.evaluate
      • Mean
        • Mean.evaluate
      • Std
        • Std.evaluate
      • Var
        • Var.evaluate
      • All
        • All.evaluate
        • All.is_differentiable
      • Any
        • Any.evaluate
        • Any.is_differentiable
      • SamplesGenerator
        • SamplesGenerator.fit
        • SamplesGenerator.generate
        • SamplesGenerator.reset_states
      • Strategy
        • Strategy.fit
        • Strategy.reset_states
        • Strategy.sample
        • Strategy.update
      • UniformStrategy
        • UniformStrategy.sample
      • QuantileStrategy
        • QuantileStrategy.fit
        • QuantileStrategy.reset_states
        • QuantileStrategy.sample
      • KernelDensityStrategy
        • KernelDensityStrategy.fit
        • KernelDensityStrategy.reset_states
        • KernelDensityStrategy.sample
        • KernelDensityStrategy.update
    • aixd.visualisation
      • Plotter
        • Plotter.attributes_obs_vs_pred
        • Plotter.available_block_names
        • Plotter.contours2d
        • Plotter.correlation
        • Plotter.distrib_attributes
        • Plotter.distrib_attributes2d
        • Plotter.distrib_attributes_high_dim
        • Plotter.evaluate_generation
        • Plotter.evaluate_training
        • Plotter.generation_scatter
        • Plotter.kde_distribution_attributes
        • Plotter.parallel_coordinates
        • Plotter.performance_summary
    • aixd.utils
      • Logger
        • Logger.from_config
        • Logger.get_child
        • Logger.get_name
        • Logger.set_verbosity
  • API Reference
  • AI-eXtended Design

AI-eXtended Design

data

aixd.data

mlmodel

aixd.mlmodel

sampler

aixd.sampler

visualisation

aixd.visualisation

utils

aixd.utils

previous

API Reference

next

aixd.data

© Copyright 2020-2026 ETH Zurich & Swiss Data Science Center.

Created using Sphinx 7.4.7.

Built with the PyData Sphinx Theme 0.17.1.