Merge branch '5-clean-up-code-and-make-ready-for-beta-testing' into 'main'

        <entryData>

          <resourceRoots>

            <path value="file://$PROJECT_DIR$/src/resources" />

            <path value="file://$PROJECT_DIR$/pythermogis/resources" />

            <path value="file://$PROJECT_DIR$/pythermogis/resources/java" />

            <path value="file://$PROJECT_DIR$/pythermogis/resources/thermogis_jar" />

          </resourceRoots>

        </entryData>

      </entry>

# PyThermoGIS

# pyThermoGIS

This is a python API to the ThermoGIS Java code calculations

pyThermoGIS is a Python package that provides API access to the ThermoGIS Geothermal simulation (https://www.thermogis.nl/en). The simulations are conducted in java and this code uses the JPype package as a python-java

binding.

It uses xarray (https://docs.xarray.dev/en/stable/index.html) Datasets as input to the simulation and can be combined with the pygridsio package (https://pypi.org/project/pygridsio/) to read in and process 2D rasters

### Install via pip from GitLab

To install `pyThermoGIS` into your own project directly from GitLab, run:

```sh

pip install git+https://gitlab.com/your-repo/pythermogis.git

```

This will fetch the latest version from the public GitLab repository.

## Usage

Here’s a simple example demonstrating how to use `pyThermoGIS` for a single set of input values:

```python

from pythermogis.pythermogis import calculate_doublet_performance

import xarray as xr

# Initialize an input Dataset with the required input variables:

input_data = xr.Dataset({

         "thickness_mean": ((), 300),

         "thickness_sd": ((), 50),

         "ntg": ((), 0.5),

         "porosity": ((), 0.5),

         "depth": ((), 5000),

         "ln_permeability_mean": ((), 5),

         "ln_permeability_sd": ((), 0.5),

     })

# Simulate a Geothermal doublet using the ThermoGIS methodology

doublet_simulation_results = calculate_doublet_performance(input_data)

# Display results

print(doublet_simulation_results)

```

## Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

## License

This project is licensed under the MIT License. See `LICENSE` for details.

## Installation for further development

### Install from Source with Pixi for further Development

To install `pyThermoGIS` from source using Pixi, follow these steps:

1. Clone the repository:

   ```sh

   git clone https://gitlab.com/your-repo/pythermogis.git

   cd pythermogis

   ```

2. Ensure Pixi is installed:

   ```sh

   curl -sSL https://pixi.sh/install.sh | bash

   ```

3. Install dependencies and create an isolated environment:

   ```sh

   pixi install

   ```

4. Activate the environment:

   ```sh

   pixi run python

   ```

import os

from pathlib import Path

from git import Repo

from pydantic import BaseModel, model_validator

class DoubletParameters(BaseModel):

    use_stimulation: bool = False

    use_heat_pump: bool = False

    hp_minimum_injection_temperature: float = 15

    max_cooling_temperature_range: float = 100

    stimKhMax: float = 20

    return_temperature: float = 30

    surface_temperature: float = 10

class Config(BaseModel):

    input_data_path: Path | None

    results_path: Path | None

    DoubletParameters : DoubletParameters

    @model_validator(mode="after")

    def set_paths(self):

        if not self.output_path:

            repo_path = Path(Repo(".", search_parent_directories=True).working_tree_dir)

            self.output_path = repo_path / "models" / self.model_name

        return self

def calculate_temperature_from_gradient(depth, thickness, degrees_per_km, surface_temperature):

def calculate_temperature_from_gradient(depth: float, thickness: float, degrees_per_km: float, surface_temperature: float):

    return surface_temperature + (depth + thickness / 2) * (degrees_per_km * 0.001)