Update after java gui refactor

# Change log

## v2.0.0 (27-2-2026)

After an essential rewrite of the java code, parts of the API of pythermoGIS had to be updated. Since these were breaking, non-backward compatible, changes, a version 2.0.0 is released. 

The most important and noticible change is that the method of setting up the input parameters has changed. Please check out the customized properties page for 

## v1.2.5 (26-1-2026)

A java 17 virtual machine is now automatically installed the first time a pythermogis simulation is run. This uses the [install-jdk](https://pypi.org/project/install-jdk/) python project.

# API Reference

::: pythermogis.thermogis_classes.utc_properties

 No newline at end of file

::: pythermogis.thermogis_classes.properties

 No newline at end of file

To adjust properties of the simulation, you can pass a `utc_properties` instance 

to the calculate_doublet_performance function.

A `utc_properties` instance is a JClass implementation of the Java UTCProperties class. 

It is generated by using the `utc_properties_builder`, upon which custom properties can be set, 

It is generated by using the `thermogis_properties`, upon which custom properties can be set for all calculations in ThermoGIS, 

and used to build an instance of the `utc_properties`.

be aware: The number of parameters is large, and the default values are set to the ThermoGIS base case. 

There are two ways to set the properties of the simulation, by either:

1. Using the `utc_properties_builder` class to set the properties of the simulation, and then building the `utc_properties` instance.

2. Using the `instantiate_utc_properties_from_xml` function to parse a configuration file, which will return a `utc_properties` instance.

1. Using the `instantiate_thermogis_parameters` class to set the properties of the simulation, and then using the `setupUTCParameters` method.

2. Using the `instantiate_thermogis_properties_from_file` function to parse a configuration file, which will return a `thermogis_properties` method.

!!! info "customizing the thermoGIS techno-economic properties"

Common properties to change include:

- `setUseHeatPump(Boolean)`: if true, include a heat-pump when modelling

- `setUseStimulation(Boolean)`: if true, apply reservoir stimulation when simulating a doublet

- `setUseHeatpump(Boolean)`: if true, include a heat-pump when modelling

- `setUseWellStimulation(Boolean)`: if true, apply reservoir stimulation when simulating a doublet

- `setSurfaceTemperature(float)`: The temperature of the surface

- `setTempGradient(float)`: The gradient at which temperature increases with depth, in C/km

- `setDhReturnTemp(float)`: The goal of the direct heat return temperature

- `setStimKhMax(float)`: The maximum transmissivity above which no stimulation will occur (if UseStimulation = True)

Here is an example, where the default utc_properties is used, but the UseHeatPump option is set to True. this is achievied by instantiating a `utc_properties_builder` class, running `.useHeatPump(True)` on that class, and then building the 

`utc_properties` themselves, with the `.build()` method of the `utc_properties_builder`.

Here is an example, where the default utc_properties is used, but the UseHeatpump option is set to True. this is achievied by instantiating a `thermogis_properties` class, running `.useHeatpump(True)` on that class, and then building the 

`utc_properties` themselves, with the `.setupUTCParameters()` method of the `thermogis_properties`.

```python

from pythermogis import calculate_doublet_performance, instantiate_utc_properties_builder

from pythermogis import calculate_doublet_performance, instantiate_thermogis_parameters

import xarray as xr

input_data = xr.Dataset({

    "permeability": 300,

})

utc_properties = instantiate_utc_properties_builder().setUseHeatPump(True).build()

tg_parameters = instantiate_thermogis_parameters()

tg_parameters.setUseHeatpump(True)

utc_properties = tg_parameters.setupUTCParameters()

results = calculate_doublet_performance(input_data, utc_properties=utc_properties)

print(results)

```

unfortunately they are still needed in the xml file to enable parsing.

```python

from src.pythermogis import calculate_doublet_performance_stochastic, instantiate_utc_properties_from_xml

from src.pythermogis import calculate_doublet_performance_stochastic, instantiate_thermogis_properties_from_file

import xarray as xr

input_data = xr.Dataset({

    "ln_permeability_sd": 0.5,

})

utc_properties = instantiate_utc_properties_from_xml("path/to/valid/xml/file")

tg_properties = instantiate_thermogis_properties_from_file("path/to/valid/xml/file")

utc_properties = tg_properties.setupUTCParameters()

results = calculate_doublet_performance_stochastic(input_data, utc_properties=utc_properties)

print(results)

```

  timestamp: 1740946648058

- pypi: ./

  name: pythermogis

  version: 1.2.4

  sha256: 4406d3c4da3a9e6ee46a39b7ce7b61063e676db495638f1f9d992ac174589913

  version: 1.2.5

  sha256: f7faf166eaa5141f37e7e96c2fc7f2c01cf26da4be5fc5164aa0c8c784614e2b

  requires_dist:

  - jpype1>=1.5.2,<2

  - xarray==2024.9.0.*

[project]

name = "pythermogis"

version = "1.2.5"

version = "2.0.0"

description = "This repository is used as a python API for the ThermoGIS Doublet simulations"

authors = [

    { name = "Hen Brett", email = "hen.brett@tno.nl" },