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This package translates CSV date files to DIBS input. DIBS---Dynamic-ISO-Building-Simulator is a simulation program for calculating the space heating, occupancy hot water, cooling and electricity demand of German non-residential buildings. Further the DIBS calculates the heating value based energy uses, the primary energy and the greenhouse gas emission. The underlying resistance-capacity-model is based on the simplified hourly method of ISO 13790:2008.

Project description

DibsDataSourceCSV

Overview

This repository contains a set of utilities utils and a Python file named datasource_csv. The primary purpose of datasource_csv is to provide functionality for handling Excel and CSV files, performing calculations on data and returning objects as results. DataSourceCSVimplements the DataSource interface defined in another module called dibs_computing_core.

File Structure

  • utils/: This directory contains several Python files, each housing methods that are utilized within datasource_csv.
  • datasource_csv.py: This Python file implements the DataSource interface, defined in dibs_computing_core, to interact with Excel and CSV files, converting them into appropriate objects (performing calculations on data and returning objects as results.)

Arguments:

  • path: Path to the file containing building data type of str. (Required)
  • profile_from_norm: type of str. (Optional)
  • gains_from_group_values: type of str. (Optional)
  • usage_from_norm: type of str. (Optional)
  • weather_period: type of str. (Optional)

Usage

To use the functionalities provided by this repository, follow these steps:

  1. Installation: Use pip to install the module. This will automatically install the required dependencies mentioned in pyproject.toml.

    pip install dibs_datasource_csv
    
  2. Importing DatasourceCSV: You can import and use the DataSourceCSV class directly from the terminal or any Python environment.

    python
    
    from dibs_computing_core.iso_simulator.dibs.dibs import DIBS
    from dibs_datasource_csv.datasource_csv import DataSourceCSV
    import dibs_data
    
  3. Performing Simulation: Use the methods provided in dibs class (calculate_result_of_one_building or multi) to perform calculations on your data. The method calculate_result_of_one_building simulates one building and multi simulates multiple building simultaneously for more performance.

    # Example usage
    datasource_csv = DataSourceCSV(path="path_to_your_data", "din18599", "mid", "sia2024", "2007-2021") or 
    datasource_csv = DataSourceCSV(path="path_to_your_data", profile_from_norm="din18599", gains_from_group_values="mid", usage_from_norm="sia2024", weather_period="2007-2021")
    
    dibs = DIBS(datasource_csv)
    
    simulation_time, result_of_all_hours, summary_result = dibs.calculate_result_of_one_building()
    
    # To see the hourly result of the simulated building
    print(result_of_all_hours)
    
    # To see the summary result of the simulated building
    print(summary_result)
    

Contributing

Contributions to this repository are welcome. If you find any bugs, have feature requests, or want to contribute enhancements, feel free to open an issue or submit a pull request.

License

This repository is licensed under the MIT License. Feel free to use, modify, and distribute the code as per the terms of this license.

Acknowledgments

Special thanks to contributors and maintainers who have helped shape and improve this repository. Your efforts are greatly appreciated.

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