Skip to main content
Ctrl+K

AIXD 0.12.1 documentation

  • 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.check_dataset_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
        • Dataset.write_data_dp_pa
      • 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.plot_distrib
        • 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
        • DataReal.plot_distrib
        • DataReal.append_transformation
        • DataReal.check_data_consistency
        • DataReal.copy
        • DataReal.grid_samples
        • DataReal.has_name
        • DataReal.inverse_transform
        • DataReal.prepend_transformation
        • DataReal.print_transf_norm
        • DataReal.random_samples
        • DataReal.sample_around
        • DataReal.transform
        • DataReal.transform_is_fitted
        • DataReal.update_dobj_types
        • DataReal.update_obj
      • DataDiscrete
        • DataDiscrete.is_data_transformed
        • DataDiscrete.plot_distrib
        • DataDiscrete.append_transformation
        • DataDiscrete.check_data_consistency
        • DataDiscrete.copy
        • DataDiscrete.get_activation_outhead
        • DataDiscrete.get_loss_evaluation
        • DataDiscrete.get_ml_heads
        • DataDiscrete.get_objective
        • DataDiscrete.grid_samples
        • DataDiscrete.has_name
        • DataDiscrete.inverse_transform
        • DataDiscrete.prepend_transformation
        • DataDiscrete.print_transf_norm
        • DataDiscrete.random_samples
        • DataDiscrete.sample_around
        • DataDiscrete.transform
        • DataDiscrete.transform_is_fitted
        • DataDiscrete.update_dobj_types
        • DataDiscrete.update_obj
      • DataInt
        • DataInt.from_range
        • DataInt.get_activation_outhead
        • DataInt.get_loss_evaluation
        • DataInt.get_ml_heads
        • DataInt.get_objective
        • DataInt.append_transformation
        • DataInt.check_data_consistency
        • DataInt.copy
        • DataInt.grid_samples
        • DataInt.has_name
        • DataInt.inverse_transform
        • DataInt.is_data_transformed
        • DataInt.plot_distrib
        • DataInt.prepend_transformation
        • DataInt.print_transf_norm
        • DataInt.random_samples
        • DataInt.sample_around
        • DataInt.transform
        • DataInt.transform_is_fitted
        • DataInt.update_dobj_types
        • DataInt.update_obj
      • DataCategorical
        • DataCategorical.copy
        • DataCategorical.from_options
        • DataCategorical.get_activation_outhead
        • DataCategorical.get_loss_evaluation
        • DataCategorical.get_ml_heads
        • DataCategorical.get_objective
        • DataCategorical.append_transformation
        • DataCategorical.check_data_consistency
        • DataCategorical.grid_samples
        • DataCategorical.has_name
        • DataCategorical.inverse_transform
        • DataCategorical.is_data_transformed
        • DataCategorical.plot_distrib
        • DataCategorical.prepend_transformation
        • DataCategorical.print_transf_norm
        • DataCategorical.random_samples
        • DataCategorical.sample_around
        • DataCategorical.transform
        • DataCategorical.transform_is_fitted
        • DataCategorical.update_dobj_types
        • DataCategorical.update_obj
      • DataBool
        • DataBool.append_transformation
        • DataBool.check_data_consistency
        • DataBool.copy
        • DataBool.from_options
        • DataBool.get_activation_outhead
        • DataBool.get_loss_evaluation
        • DataBool.get_ml_heads
        • DataBool.get_objective
        • DataBool.grid_samples
        • DataBool.has_name
        • DataBool.inverse_transform
        • DataBool.is_data_transformed
        • DataBool.plot_distrib
        • DataBool.prepend_transformation
        • DataBool.print_transf_norm
        • DataBool.random_samples
        • DataBool.sample_around
        • DataBool.transform
        • DataBool.transform_is_fitted
        • DataBool.update_dobj_types
        • DataBool.update_obj
      • 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
        • IntervalMasked.check_domain_consistency
        • IntervalMasked.domain_to_normalised
        • IntervalMasked.grid_samples
        • IntervalMasked.normalised_to_domain
        • IntervalMasked.random_samples
        • IntervalMasked.sample_around
        • IntervalMasked.update_domain
      • DataBlock
        • DataBlock.check_data_consistency
        • DataBlock.get_cols_dobjs
        • DataBlock.get_data_mat
        • DataBlock.get_data_mat_dtypes
        • DataBlock.get_data_mats
        • DataBlock.get_dobjs
        • DataBlock.info_dobj
        • DataBlock.print_objects
        • DataBlock.print_transf
        • DataBlock.read
        • DataBlock.update_obj
        • DataBlock.update_position_indices
        • DataBlock.write
      • DesignParameters
        • DesignParameters.check_data_consistency
        • DesignParameters.get_cols_dobjs
        • DesignParameters.get_data_mat
        • DesignParameters.get_data_mat_dtypes
        • DesignParameters.get_data_mats
        • DesignParameters.get_dobjs
        • DesignParameters.info_dobj
        • DesignParameters.print_objects
        • DesignParameters.print_transf
        • DesignParameters.read
        • DesignParameters.update_obj
        • DesignParameters.update_position_indices
        • DesignParameters.write
      • PerformanceAttributes
        • PerformanceAttributes.check_data_consistency
        • PerformanceAttributes.get_cols_dobjs
        • PerformanceAttributes.get_data_mat
        • PerformanceAttributes.get_data_mat_dtypes
        • PerformanceAttributes.get_data_mats
        • PerformanceAttributes.get_dobjs
        • PerformanceAttributes.info_dobj
        • PerformanceAttributes.print_objects
        • PerformanceAttributes.print_transf
        • PerformanceAttributes.read
        • PerformanceAttributes.update_obj
        • PerformanceAttributes.update_position_indices
        • PerformanceAttributes.write
      • DesignRepresentation
        • DesignRepresentation.read
        • DesignRepresentation.write
        • DesignRepresentation.check_data_consistency
        • DesignRepresentation.get_cols_dobjs
        • DesignRepresentation.get_data_mat
        • DesignRepresentation.get_data_mat_dtypes
        • DesignRepresentation.get_data_mats
        • DesignRepresentation.get_dobjs
        • DesignRepresentation.info_dobj
        • DesignRepresentation.print_objects
        • DesignRepresentation.print_transf
        • DesignRepresentation.update_obj
        • DesignRepresentation.update_position_indices
      • TransformableDataBlock
        • TransformableDataBlock.get_dobj_dimensions
        • TransformableDataBlock.inverse_transform
        • TransformableDataBlock.to_data_block
        • TransformableDataBlock.transform
        • TransformableDataBlock.transformation_is_fitted
        • TransformableDataBlock.check_data_consistency
        • TransformableDataBlock.get_cols_dobjs
        • TransformableDataBlock.get_data_mat
        • TransformableDataBlock.get_data_mat_dtypes
        • TransformableDataBlock.get_data_mats
        • TransformableDataBlock.get_dobjs
        • TransformableDataBlock.info_dobj
        • TransformableDataBlock.print_objects
        • TransformableDataBlock.print_transf
        • TransformableDataBlock.read
        • TransformableDataBlock.update_obj
        • TransformableDataBlock.update_position_indices
        • TransformableDataBlock.write
      • InputML
        • InputML.check_data_consistency
        • InputML.get_cols_dobjs
        • InputML.get_data_mat
        • InputML.get_data_mat_dtypes
        • InputML.get_data_mats
        • InputML.get_dobj_dimensions
        • InputML.get_dobjs
        • InputML.info_dobj
        • InputML.inverse_transform
        • InputML.print_objects
        • InputML.print_transf
        • InputML.read
        • InputML.to_data_block
        • InputML.transform
        • InputML.transformation_is_fitted
        • InputML.update_obj
        • InputML.update_position_indices
        • InputML.write
      • OutputML
        • OutputML.check_data_consistency
        • OutputML.get_cols_dobjs
        • OutputML.get_data_mat
        • OutputML.get_data_mat_dtypes
        • OutputML.get_data_mats
        • OutputML.get_dobj_dimensions
        • OutputML.get_dobjs
        • OutputML.info_dobj
        • OutputML.inverse_transform
        • OutputML.print_objects
        • OutputML.print_transf
        • OutputML.read
        • OutputML.to_data_block
        • OutputML.transform
        • OutputML.transformation_is_fitted
        • OutputML.update_obj
        • OutputML.update_position_indices
        • OutputML.write
      • CustomCallback
        • CustomCallback.run
        • CustomCallback.to_numpy
      • AnalysisCallback
        • AnalysisCallback.analyze
        • AnalysisCallback.run
        • AnalysisCallback.to_numpy
      • DataloaderCallback
        • DataloaderCallback.run
        • DataloaderCallback.to_numpy
      • ImportCallback
        • ImportCallback.run
        • ImportCallback.to_numpy
      • PostGenerationCallback
        • PostGenerationCallback.run
        • PostGenerationCallback.to_numpy
      • SamplingCallback
        • SamplingCallback.run
        • SamplingCallback.to_numpy
      • aixd.data.transform.register_transformation
      • aixd.data.transform.resolve_transformation
      • DataObjectTransform
        • DataObjectTransform.copy
        • DataObjectTransform.fit
        • DataObjectTransform.fit_transform
        • DataObjectTransform.inverse_transform
        • DataObjectTransform.is_fitted
        • DataObjectTransform.reset
        • DataObjectTransform.transform
      • Log10Transform
        • Log10Transform.inverse_transform
        • Log10Transform.transform
        • Log10Transform.copy
        • Log10Transform.fit
        • Log10Transform.fit_transform
        • Log10Transform.is_fitted
        • Log10Transform.reset
      • SigmoidTransform
        • SigmoidTransform.inverse_transform
        • SigmoidTransform.is_fitted
        • SigmoidTransform.reset
        • SigmoidTransform.transform
        • SigmoidTransform.copy
        • SigmoidTransform.fit
        • SigmoidTransform.fit_transform
      • Standardization
        • Standardization.inverse_transform
        • Standardization.is_fitted
        • Standardization.reset
        • Standardization.transform
        • Standardization.copy
        • Standardization.fit
        • Standardization.fit_transform
      • MinMaxScaler
        • MinMaxScaler.inverse_transform
        • MinMaxScaler.is_fitted
        • MinMaxScaler.reset
        • MinMaxScaler.transform
        • MinMaxScaler.copy
        • MinMaxScaler.fit
        • MinMaxScaler.fit_transform
      • ZeroToOne
        • ZeroToOne.copy
        • ZeroToOne.fit
        • ZeroToOne.fit_transform
        • ZeroToOne.inverse_transform
        • ZeroToOne.is_fitted
        • ZeroToOne.reset
        • ZeroToOne.transform
      • MinusOneToOne
        • MinusOneToOne.copy
        • MinusOneToOne.fit
        • MinusOneToOne.fit_transform
        • MinusOneToOne.inverse_transform
        • MinusOneToOne.is_fitted
        • MinusOneToOne.reset
        • MinusOneToOne.transform
      • MaskedMinMaxScaler
        • MaskedMinMaxScaler.inverse_transform
        • MaskedMinMaxScaler.transform
        • MaskedMinMaxScaler.copy
        • MaskedMinMaxScaler.fit
        • MaskedMinMaxScaler.fit_transform
        • MaskedMinMaxScaler.is_fitted
        • MaskedMinMaxScaler.reset
      • MaskedZeroToOne
        • MaskedZeroToOne.copy
        • MaskedZeroToOne.fit
        • MaskedZeroToOne.fit_transform
        • MaskedZeroToOne.inverse_transform
        • MaskedZeroToOne.is_fitted
        • MaskedZeroToOne.reset
        • MaskedZeroToOne.transform
      • MaskedMinusOneToOne
        • MaskedMinusOneToOne.copy
        • MaskedMinusOneToOne.fit
        • MaskedMinusOneToOne.fit_transform
        • MaskedMinusOneToOne.inverse_transform
        • MaskedMinusOneToOne.is_fitted
        • MaskedMinusOneToOne.reset
        • MaskedMinusOneToOne.transform
      • LabelEncoder
        • LabelEncoder.fit
        • LabelEncoder.inverse_transform
        • LabelEncoder.is_fitted
        • LabelEncoder.reset
        • LabelEncoder.transform
        • LabelEncoder.copy
        • LabelEncoder.fit_transform
      • ToFloat
        • ToFloat.inverse_transform
        • ToFloat.is_fitted
        • ToFloat.transform
        • ToFloat.copy
        • ToFloat.fit
        • ToFloat.fit_transform
        • ToFloat.reset
      • 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_dataset
        • DataModule.from_parameters
        • DataModule.get_checksum
        • DataModule.get_parameters
        • DataModule.inverse_transform
        • DataModule.inverse_transform_x
        • DataModule.inverse_transform_y
        • DataModule.predict_dataloader
        • DataModule.summary_input_output_dimensions
        • DataModule.test_dataloader
        • 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
        • CondVAEModel.calc_x_losses_calculation
        • CondVAEModel.calc_y_losses_calculation
        • CondVAEModel.configure_optimizers
        • CondVAEModel.decode
        • CondVAEModel.encode
        • CondVAEModel.evaluate
        • CondVAEModel.fit
        • CondVAEModel.forward
        • CondVAEModel.forward_evaluation
        • CondVAEModel.from_datamodule
        • CondVAEModel.generate
        • CondVAEModel.get_evaluation_losses
        • CondVAEModel.load_model_from_checkpoint
        • CondVAEModel.on_load_checkpoint
        • CondVAEModel.on_save_checkpoint
        • CondVAEModel.predict
        • CondVAEModel.predict_step
        • CondVAEModel.predict_y
        • CondVAEModel.save_extra_parameters
        • CondVAEModel.split_x_head_in
        • CondVAEModel.split_x_head_out
        • CondVAEModel.split_xy_in
        • CondVAEModel.split_xy_out
        • CondVAEModel.split_y_head_in
        • CondVAEModel.split_y_head_out
        • CondVAEModel.summary
        • CondVAEModel.test
        • CondVAEModel.test_step
        • CondVAEModel.to_untransformed_pred
        • CondVAEModel.training_step
        • CondVAEModel.validate
        • CondVAEModel.validation_step
      • InverseModel
        • InverseModel.fit
        • InverseModel.forward
      • FreezeEncoder
        • FreezeEncoder.finetune_function
        • FreezeEncoder.freeze_before_training
      • ResBlockFC
        • ResBlockFC.forward
      • ResBlockConv
        • ResBlockConv.forward
      • ResBlock1D
        • ResBlock1D.forward
      • ResBlock2D
        • ResBlock2D.forward
      • ResBlock3D
        • ResBlock3D.forward
      • SelfAttn
        • SelfAttn.forward
      • SelfAttn1D
        • SelfAttn1D.forward
      • SelfAttn2D
        • SelfAttn2D.forward
      • SelfAttn3D
        • SelfAttn3D.forward
      • Activation
        • Activation.forward
      • Decoder
        • Decoder.forward
        • Decoder.summary
      • Encoder
        • Encoder.forward
        • Encoder.summary
      • VEncoder
        • VEncoder.forward
        • VEncoder.summary
      • InHeadFC
        • InHeadFC.forward
      • OutHeadFC
        • OutHeadFC.forward
        • OutHeadFC.get_postprocessors
        • OutHeadFC.postprocess
      • InHeadConv
        • InHeadConv.forward
      • OutHeadConv
        • OutHeadConv.forward
        • OutHeadConv.get_postprocessors
        • OutHeadConv.postprocess
      • InHeadConv1D
        • InHeadConv1D.forward
      • OutHeadConv1D
        • OutHeadConv1D.forward
        • OutHeadConv1D.get_postprocessors
        • OutHeadConv1D.postprocess
      • InHeadConv2D
        • InHeadConv2D.forward
      • OutHeadConv2D
        • OutHeadConv2D.forward
        • OutHeadConv2D.get_postprocessors
        • OutHeadConv2D.postprocess
      • InHeadConv3D
        • InHeadConv3D.forward
      • OutHeadConv3D
        • OutHeadConv3D.forward
        • OutHeadConv3D.get_postprocessors
        • OutHeadConv3D.postprocess
      • 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
    • aixd.sampler
      • GeneratorCallback
      • SamplingEngine
        • SamplingEngine.deserialise
        • SamplingEngine.reset_states
        • SamplingEngine.sample
        • SamplingEngine.update
      • AgnosticSamplingEngine
        • AgnosticSamplingEngine.update
        • AgnosticSamplingEngine.deserialise
        • AgnosticSamplingEngine.reset_states
        • AgnosticSamplingEngine.sample
      • AdaptiveSamplingEngine
        • AdaptiveSamplingEngine.update
        • AdaptiveSamplingEngine.deserialise
        • AdaptiveSamplingEngine.reset_states
        • AdaptiveSamplingEngine.sample
      • RandomSamplingEngine
        • RandomSamplingEngine.sample
        • RandomSamplingEngine.deserialise
        • RandomSamplingEngine.reset_states
        • RandomSamplingEngine.update
      • GridamplingEngine
        • GridamplingEngine.sample
        • GridamplingEngine.deserialise
        • GridamplingEngine.reset_states
        • GridamplingEngine.update
      • SobolSamplingEngine
        • SobolSamplingEngine.reset_states
        • SobolSamplingEngine.sample
        • SobolSamplingEngine.deserialise
        • SobolSamplingEngine.update
      • LHCSamplingEngine
        • LHCSamplingEngine.reset_states
        • LHCSamplingEngine.sample
        • LHCSamplingEngine.deserialise
        • LHCSamplingEngine.update
      • BayesOptSamplingEngine
        • BayesOptSamplingEngine.reset_states
        • BayesOptSamplingEngine.sample
        • BayesOptSamplingEngine.update
        • BayesOptSamplingEngine.deserialise
      • Operator
        • Operator.evaluate
        • Operator.is_differentiable
        • Operator.print_all
      • Arithmetic
        • Arithmetic.is_differentiable
        • Arithmetic.evaluate
        • Arithmetic.print_all
      • Boolean
        • Boolean.is_differentiable
        • Boolean.evaluate
        • Boolean.print_all
      • Constant
        • Constant.evaluate
        • Constant.is_differentiable
        • Constant.print_all
      • Add
        • Add.evaluate
        • Add.is_differentiable
        • Add.print_all
      • Multiply
        • Multiply.evaluate
        • Multiply.is_differentiable
        • Multiply.print_all
      • Subtract
        • Subtract.evaluate
        • Subtract.is_differentiable
        • Subtract.print_all
      • Divide
        • Divide.evaluate
        • Divide.is_differentiable
        • Divide.print_all
      • LessThan
        • LessThan.evaluate
        • LessThan.is_differentiable
        • LessThan.print_all
      • LessOrEqual
        • LessOrEqual.evaluate
        • LessOrEqual.is_differentiable
        • LessOrEqual.print_all
      • GreaterThan
        • GreaterThan.evaluate
        • GreaterThan.is_differentiable
        • GreaterThan.print_all
      • GreaterOrEqual
        • GreaterOrEqual.evaluate
        • GreaterOrEqual.is_differentiable
        • GreaterOrEqual.print_all
      • Log
        • Log.evaluate
        • Log.is_differentiable
        • Log.print_all
      • Exp
        • Exp.evaluate
        • Exp.is_differentiable
        • Exp.print_all
      • Pow
        • Pow.evaluate
        • Pow.is_differentiable
        • Pow.print_all
      • Not
        • Not.evaluate
        • Not.is_differentiable
        • Not.print_all
      • And
        • And.evaluate
        • And.is_differentiable
        • And.print_all
      • Or
        • Or.evaluate
        • Or.is_differentiable
        • Or.print_all
      • XOr
        • XOr.evaluate
        • XOr.is_differentiable
        • XOr.print_all
      • Equal
        • Equal.evaluate
        • Equal.is_differentiable
        • Equal.print_all
      • Negative
        • Negative.evaluate
        • Negative.is_differentiable
        • Negative.print_all
      • CastBooleanToConstant
        • CastBooleanToConstant.evaluate
        • CastBooleanToConstant.is_differentiable
        • CastBooleanToConstant.print_all
      • Reducer
        • Reducer.evaluate
        • Reducer.is_differentiable
      • Sum
        • Sum.evaluate
        • Sum.is_differentiable
      • Mean
        • Mean.evaluate
        • Mean.is_differentiable
      • Std
        • Std.evaluate
        • Std.is_differentiable
      • Var
        • Var.evaluate
        • Var.is_differentiable
      • All
        • All.evaluate
        • All.is_differentiable
      • Any
        • Any.evaluate
        • Any.is_differentiable
      • aixd.sampler.sampler_definitions.sampler_uniform
      • aixd.sampler.sampler_definitions.sampler_kde
      • aixd.sampler.sampler_definitions.sampler_quantile
      • aixd.sampler.sampler_definitions.sampler_custom
      • aixd.sampler.sampler_definitions.sampler_conditional_kde
      • aixd.sampler.sampler_definitions.sampler_bayesian_kde
      • SamplesGenerator
        • SamplesGenerator.fit
        • SamplesGenerator.generate
        • SamplesGenerator.reset_states
      • Strategy
        • Strategy.fit
        • Strategy.reset_states
        • Strategy.sample
        • Strategy.update
      • UniformStrategy
        • UniformStrategy.sample
        • UniformStrategy.fit
        • UniformStrategy.reset_states
        • UniformStrategy.update
      • QuantileStrategy
        • QuantileStrategy.fit
        • QuantileStrategy.reset_states
        • QuantileStrategy.sample
        • QuantileStrategy.update
      • 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.evaluate_generation
        • Plotter.evaluate_training
        • Plotter.generation_scatter
        • Plotter.kde_distribution_attributes
        • Plotter.performance_summary
  • API Reference
  • AI-eXtended Design
  • aixd.data
  • DataDiscrete
  • DataDiscrete.prepend_transformation

DataDiscrete.prepend_transformation

DataDiscrete.prepend_transformation(t: str | DataObjectTransform)[source]

Adds the transformation at the start.

previous

DataDiscrete.inverse_transform

next

DataDiscrete.print_transf_norm
On this page
  • DataDiscrete.prepend_transformation()

© Copyright 2020-2024 ETH Zurich & Swiss Data Science Center.

Created using Sphinx 7.4.7.

Built with the PyData Sphinx Theme 0.16.0.