Merge branch 'issue-67-tempnan' into 'main'

*.egg-info

build

dist

tests/resources/test_output

 No newline at end of file

[project]

name = "pythermogis"

version = "1.1.0"

version = "1.1.1"

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

authors = [

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

    "jpype1>=1.5.2,<2",

    "xarray==2024.9.0.*",

    "pandas>=2.2.3,<3",

    "pytz>=2024.1,<2025", "build>=1.2.2.post1,<2", "pygridsio>=0.3.27,<0.4"]

    "pytz>=2024.1,<2025",

    "build>=1.2.2.post1,<2",

    "pygridsio>=0.3.27,<0.4"]

[tool.pytest.ini_options]

mkdocstrings-python = ">=1.16.12,<2"

dask = ">=2025.5.1,<2026"

narwhals = ">=1.43.1,<2"

pre-commit = ">=4.3.0,<5"

[tool.ruff]

line-length = 88

target-version = "py313"

[tool.ruff.lint]

select = [

    # pycodestyle (style guide violations)

    "E",

    # Pyflakes (bug detection)

    "F",

    # pyupgrade (modern Python syntax)

    "UP",

    # flake8-bugbear (common bugs and design issues)

    "B",

    # flake8-simplify (simplifiable constructs)

    "SIM",

    # isort (import sorting)

    "I",

]

from pythermogis.thermogis_classes.utc_properties import instantiate_utc_properties_builder

def calculate_doublet_performance(reservoir_properties: xr.Dataset, utc_properties = None, rng_seed: int = None, chunk_size: int = None, print_execution_duration: bool = False) -> xr.Dataset:

def calculate_doublet_performance(reservoir_properties: xr.Dataset, utc_properties = None, rng_seed: int = None, chunk_size: int = None, print_execution_duration: bool = False, mask_value: float = np.nan) -> xr.Dataset:

    """

    Perform a deterministic Doublet performance simulation.

        Optional variables:

        - transmissivity, units: Dm, if provided then permeability is ignored.

        - temperature : If not provided, temperature is estimated using the depth and a temperature gradient from `utc_properties`.

        - mask : If provided, all non-NaN values will result in setting corresponding output values to zero.

        - mask : If provided, all non-NaN values will result in setting corresponding output values to mask_value.

    utc_properties : JClass

        A Java class specifying the properties of the doublet being simulated

    print_execution_duration : bool

        False by default, If set to True print the time in seconds it took to simulate across all reservoir properties

    mask_value : float

        0.0 by default, Any cell that results in a failed simulation or corresponds to a

        non-nan value in the mask parameter will be assigned the mask value

    Returns

    -------

    output_data : xr.Dataset

        - "transmissivity"

        - "transmissivity_with_ntg"

    """

    if print_execution_duration: start = timeit.default_timer()

    if print_execution_duration:

        start = timeit.default_timer()

    validate_input(reservoir_properties)

        reservoir_properties = auto_chunk_dataset(reservoir_properties, chunk_size)

    output_data = reservoir_properties.copy()

    output_data = simulate_doublet(output_data, reservoir_properties, rng_seed, utc_properties)

    if chunk_size is not None: output_data.load() # If chunking has occurred then the data must be de-chunked

    if print_execution_duration: print(f"Doublet simulation took {timeit.default_timer() - start:.1f} seconds")

    output_data = simulate_doublet(output_data, reservoir_properties, rng_seed, utc_properties, mask_value=mask_value)

    if chunk_size is not None:

        output_data.load() # If chunking has occurred then the data must be de-chunked

    if print_execution_duration:

        print(f"Doublet simulation took {timeit.default_timer() - start:.1f} seconds")

    return output_data

    for variable in ["thickness", "porosity", "ntg", "depth"]:

        if variable not in reservoir_properties:

            missing_variables.append(variable)

    if len(missing_variables) > 0:

        raise ValueError(f"provided reservoir properties Dataset does not contain the following required variables: {missing_variables}")

    if "permeability" not in reservoir_properties and "transmissivity" not in reservoir_properties:

        raise ValueError(f"provided reservoir properties Dataset must provide either permeability or transmissivity variables, currently neither are provided")

    if "permeability" in reservoir_properties and "transmissivity" in reservoir_properties:

        warnings.warn("Both reservoir permeability and transmissivity provided; however the doublet simulation will use only the provided transmissivity and ignore permeability (transmissivity = permeability * thickness)")