LipiDetective

User Guide

  • Installation
    • Requirements
    • Install with UV (Recommended)
    • Install from Source with pip
    • Development Setup
    • Verify Installation
  • Quickstart
    • 1. Copy the Config Template
    • 2. Edit the Configuration
    • 3. Run the Prediction
    • 4. View the Results
    • Next Steps
  • Configuration
    • Model Selection
    • CUDA
    • File Paths
      • Validation Split Precedence
      • Environment Variable Overrides
      • Programmatic Access
    • Workflow
    • Training
    • Test
    • Prediction
    • Hyperparameter Tuning
    • Input Embedding
    • Transformer
    • WandB Integration
    • Comment
  • Data Preparation
    • Supported Formats
      • HDF5 (Training & Evaluation)
        • H5Dataset
      • mzML (Prediction)
        • PredictionDataset
    • Converting mzML to HDF5
    • Spectrum Processing
  • Workflows
    • Training
    • Validation
    • Testing
    • Prediction
    • Hyperparameter Tuning
    • Trainer API
      • Trainer
        • Trainer.train_with_validation()
        • Trainer.train_without_validation()
        • Trainer.test()
        • Trainer.predict()
        • Trainer.get_pred_files()
        • Trainer.schedule_tuning()
        • Trainer.tune_model()
        • Trainer.prepare_tune_config()
        • Trainer.check_parameter_for_tuning()
        • Trainer.parse_lipid_dataset_name()
        • Trainer.get_unique_lipids()
        • Trainer.perform_data_split()
        • Trainer.split_data_via_instructions()
        • Trainer.split_data_by_lipid_species()
        • Trainer.run_random_forest()

Reference

  • Models
    • Transformer (Recommended)
      • TransformerNetwork
        • TransformerNetwork.forward()
        • TransformerNetwork.generate_mask()
        • TransformerNetwork.predict()
        • TransformerNetwork.predict_top_3()
        • TransformerNetwork.predict_beam_decode()
        • TransformerNetwork.predict_greedy()
        • TransformerNetwork.return_encoder_embedding()
        • TransformerNetwork.greedy_decode()
        • TransformerNetwork.beam_decode()
        • TransformerNetwork.get_attention_layers()
    • Convolutional Neural Network
      • ConvolutionalNetwork
        • ConvolutionalNetwork.forward()
        • ConvolutionalNetwork.calculate_fc1_size()
    • Feed-Forward Network
      • FeedForwardNetwork
        • FeedForwardNetwork.forward()
    • Random Forest
      • RandomForest
        • RandomForest.run()
        • RandomForest.get_spectrum_data()
        • RandomForest.use_single_classifier()
        • RandomForest.plot_decision_tree()
        • RandomForest.use_triple_classifier()
        • RandomForest.use_triple_regressor()
        • RandomForest.calculate_accuracy()
        • RandomForest.check_classification_accuracy()
        • RandomForest.check_regression_accuracy()
        • RandomForest.write_output_to_file()
        • RandomForest.extract_info_dataset()
        • RandomForest.extract_info_dataset_no_split()
        • RandomForest.extract_features_and_labels()
        • RandomForest.prepare_data()
  • Output & Metrics
    • Training Output
    • Testing Output
    • Prediction Output
    • Tuning Output
    • WandB Integration
    • Custom Evaluation
      • Evaluator
        • Evaluator.evaluate_regression_accuracy()
        • Evaluator.evaluate_custom_transformer_accuracy()
        • Evaluator.generate_prediction_info()
        • Evaluator.find_nearest_headgroup()
        • Evaluator.find_nearest_side_chain()
  • API Reference
    • Models
      • TransformerNetwork
        • TransformerNetwork.forward()
        • TransformerNetwork.generate_mask()
        • TransformerNetwork.predict()
        • TransformerNetwork.predict_top_3()
        • TransformerNetwork.predict_beam_decode()
        • TransformerNetwork.predict_greedy()
        • TransformerNetwork.return_encoder_embedding()
        • TransformerNetwork.greedy_decode()
        • TransformerNetwork.beam_decode()
        • TransformerNetwork.get_attention_layers()
      • ConvolutionalNetwork
        • ConvolutionalNetwork.forward()
        • ConvolutionalNetwork.calculate_fc1_size()
      • FeedForwardNetwork
        • FeedForwardNetwork.forward()
      • RandomForest
        • RandomForest.run()
        • RandomForest.get_spectrum_data()
        • RandomForest.use_single_classifier()
        • RandomForest.plot_decision_tree()
        • RandomForest.use_triple_classifier()
        • RandomForest.use_triple_regressor()
        • RandomForest.calculate_accuracy()
        • RandomForest.check_classification_accuracy()
        • RandomForest.check_regression_accuracy()
        • RandomForest.write_output_to_file()
        • RandomForest.extract_info_dataset()
        • RandomForest.extract_info_dataset_no_split()
        • RandomForest.extract_features_and_labels()
        • RandomForest.prepare_data()
    • Workflow
      • Trainer
        • Trainer.train_with_validation()
        • Trainer.train_without_validation()
        • Trainer.test()
        • Trainer.predict()
        • Trainer.get_pred_files()
        • Trainer.schedule_tuning()
        • Trainer.tune_model()
        • Trainer.prepare_tune_config()
        • Trainer.check_parameter_for_tuning()
        • Trainer.parse_lipid_dataset_name()
        • Trainer.get_unique_lipids()
        • Trainer.perform_data_split()
        • Trainer.split_data_via_instructions()
        • Trainer.split_data_by_lipid_species()
        • Trainer.run_random_forest()
      • H5Dataset
        • H5Dataset.file_path
        • H5Dataset.dataset_names
        • H5Dataset.dataset_len
        • H5Dataset.hdf5_file
        • H5Dataset.config
        • H5Dataset.network_type
        • H5Dataset.decimal_accuracy
        • H5Dataset.lipid_librarian
        • H5Dataset.get_n_highest_peaks()
        • H5Dataset.bin_spectrum()
      • PredictionDataset
        • PredictionDataset.process_input()
        • PredictionDataset.process_mzml()
        • PredictionDataset.process_json()
        • PredictionDataset.get_n_highest_peaks()
      • LightningModule
        • LightningModule.configure_optimizers()
        • LightningModule.training_step()
        • LightningModule.validation_step()
        • LightningModule.test_step()
        • LightningModule.predict_step()
        • LightningModule.get_preds_vs_labels()
        • LightningModule.get_test_preds_vs_labels()
        • LightningModule.get_neural_network()
        • LightningModule.save_model()
    • Helpers
      • LipidLibrary
        • LipidLibrary.get_regression_label()
        • LipidLibrary.get_transformer_label()
        • LipidLibrary.parse_lipid_species_components()
        • LipidLibrary.get_lipid_species_components()
        • LipidLibrary.normalize_precursor_mass()
        • LipidLibrary.translate_tokens_to_name()
        • LipidLibrary.custom_accuracy_scoring()
      • read_yaml()
      • write_yaml()
      • resolve_config_paths()
      • set_seeds()
      • get_project_root()
      • resolve_data_path()
      • resolve_model_path()
      • resolve_output_path()
      • resolve_config_path()
LipiDetective
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