Detailed Running
----------------

Code Structure
~~~~~~~~~~~~~~

.. figure:: ../_images/module_algorithm.png
   :alt: "Algorithm of the module"


This module performs the computation of thermodynamic and susceptibility data based on the EoS BQS (Equation of State for Baryon, Charge, and Strangeness) framework. The workflow is implemented within a Docker container, ensuring portability and consistency. The process involves parsing input parameters, performing core computations, and generating output files for further analysis. Below is a step-by-step explanation:

1. **Input Files**:
   - **`config.yaml`**: Specifies the ranges for :math:`T`, :math:`\mu_B`, :math:`\mu_Q`, and :math:`\mu_S` as well as user-defined options for:
     - **Thermodynamics**: Thermodynamic data to be stored in the output.

2. **Preprocessing via Adapter**:
   The adapter processes the input YAML files (`config.yaml``) and generates the intermediate input file `input_ranges.txt`.

3. **Core Computation**:
   The main script `MUSES_wrapper.py` handles the execution of the **4DTExS_EoS** executable of the code. 
   This computation utilizes the `.dat` files generated in the preprocessing step to calculate thermodynamic data on the grid defined by the user.0

4. **Output Files**:
   The results of the computation are saved in a text file placed in the folder of the the `output/` directory, which name contains the ranges of the input parameters.

5. **Postprocessing via Porter**:
   A postprocessing step handled by "Porter" converts the output `.dat` file into CSV format for better compatibility and downstream workflows, 
   `4DTExS_eos_thermodynamics.csv`.

6. **Specifications**:
   Additional configurations and specifications are provided in `specifications.yaml`, which ensures consistency and reproducibility across different setups.

7. **CI/CD Integration**:
   The workflow includes a `manifest.yaml` file for integration with CI/CD pipelines (e.g., GitLab tests), ensuring automated testing and validation.