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Challenge Accepted 1.0.0a6+4.g54a3c18 documentation
Challenge Accepted 1.0.0a6+4.g54a3c18 documentation
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Getting Started

  • Installation
  • Quickstart

User Guide

  • User’s Guide
    • Create Config File
    • Create a more complex Config File
    • Create Steady-State Problems
    • Write plugins

API

  • API
    • simba_ml
      • error_handler
      • example_problems
        • constant_function
        • salt_and_brine_tanks
        • sir
        • sird
        • trigonometry
      • prediction
        • logging
          • logging_config
          • wandb_logger
        • normalizer
        • plugin_loader
        • preprocessing
        • steady_state
          • config
            • steady_state_data_config
          • data_loader
            • dataset_generator
            • mixed_data_loader
            • splits
        • time_series
          • config
            • mixed_data_pipeline
              • mixed_data_config
              • pipeline_config
            • synthetic_data_pipeline
              • pipeline_config
              • synthetic_data_config
            • time_series_config
            • transfer_learning_pipeline
              • transfer_learning_data_config
              • transfer_learning_pipeline_config
          • data_loader
            • mixed_data_loader
            • splits
            • synthetic_data_loader
            • transfer_learning_data_loader
            • window_generator
          • metrics
            • factory
            • metrics
          • models
            • average_predictor
            • factory
            • keras
              • dense_neural_network
              • keras_model
            • last_value_predictor
            • model
            • model_to_transfer_learning_model
            • pytorch_lightning
              • dense_neural_network
              • pytorch_lightning_model
            • sk_learn
              • decision_tree_regressor
              • linear_regressor
              • nearest_neighbors_regressor
              • random_forest_regressor
              • sk_learn_model
              • support_vector_machine_regressor
            • transfer_learning_factory
            • transfer_learning_model
          • pipelines
            • mixed_data_pipeline
            • synthetic_data_pipeline
            • transfer_learning_pipeline
      • simulation
        • constraints
          • constraint
          • keep_species_sum
          • species_value_in_range
          • species_value_truncator
        • derivative_noiser
          • additive_deriv_noiser
          • derivative_noiser
          • multi_deriv_noiser
          • multiplicative_deriv_noiser
          • no_deriv_noiser
          • sequential_deriv_noiser
        • distributions
          • beta_distribution
          • constant
          • continuous_uniform_distribution
          • distribution
          • helper_functions
          • lognormal_distribution
          • normal_distribution
          • vector_distribution
        • generators
          • pertubation_generator
          • steady_state_generator
          • time_points_generator
          • time_series_generator
        • kinetic_parameters
          • constant_kinetic_parameter
          • dict_based_kinetic_parameter
          • function_based_kinetic_parameter
          • kinetic_parameter
        • noisers
          • additive_noiser
          • adjusting_mean_noiser
          • column_noiser
          • elastic_noiser
          • multi_noiser
          • multiplicative_noiser
          • no_noiser
          • noiser
          • sequential_noiser
        • sparsifier
          • constant_suffix_remover
          • interval_sparsifier
          • keep_extreme_values_sparsifier
          • no_sparsifier
          • random_sample_sparsifier
          • sequential_sparsifier
          • sparsifier
        • species
        • system_model
          • system_model
          • system_model_interface
      • start_prediction

Contributing

  • Contributor’s Guide

About

  • Authors
  • Acknowledgements
  • Please cite us
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logging#

Init file for logging module.

simba_ml.prediction.logging.logging_config

Provides the configuration for logging.

simba_ml.prediction.logging.wandb_logger

Wrapper for wandb logging.
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logging_config
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prediction
Copyright © 2022, Maximilian Kleissl; Björn Heyder; Julian Zabbarov; Lukas Drews
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