openstef_beam.benchmarking#
Runs complete model comparison studies across multiple forecasting targets.
Comparing forecasting models properly requires testing them on many different forecasting scenarios (equipment types, consumption/prosumption, solar/wind parks, regions, seasons). This module automates the entire process: training models, running backtests, calculating metrics, generating reports, and storing results for comparison.
- The complete workflow:
Model training: Train different forecasting approaches on each target
Backtesting: Test all models under realistic conditions
Evaluation: Calculate performance metrics across different scenarios
Analysis: Generate comparison reports and visualizations
Storage: Save results for later analysis and sharing
Functions#
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Load evaluation reports for multiple targets from storage. |
Classes#
Base class for benchmark execution callbacks. |
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Group of callbacks that can be used to aggregate multiple callbacks. |
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Pipeline for comparing results across multiple benchmark runs. |
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Context information passed to forecaster factories during benchmark execution. |
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Orchestrates forecasting model benchmarks across multiple targets. |
Abstract base class for storing and retrieving benchmark results. |
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Base class for benchmark targets with common properties. |
In-memory implementation of BenchmarkStorage for testing and temporary use. |
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File system-based storage implementation for benchmark results. |
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S3-backed storage implementation that combines local and cloud storage. |
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File-based target provider loading from YAML configs and Parquet datasets. |
Callback to ensure strict benchmark execution with immediate error termination. |
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Abstract interface for loading benchmark targets and their associated datasets. |
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Configuration specifying data locations and path templates for target providers. |