TNO Intern

Commit 36a4c5a9 authored by Hen Brett's avatar Hen Brett 🐔
Browse files

allowing the user to set the mask value

parent 57c5d147

.pre-commit-config.yaml

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+5 −0
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- repo: https://github.com/astral-sh/ruff-pre-commit

  rev: v0.4.4  # Use latest

  hooks:

    - id: ruff

    - id: ruff-format
 
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pyproject.toml

+20 −0
Original line number Diff line number Diff line
@@ -63,3 +63,23 @@ mkdocs = ">=1.6.1,<2" 
mkdocstrings-python = ">=1.16.12,<2"

dask = ">=2025.5.1,<2026"

narwhals = ">=1.43.1,<2"



[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",

]
 
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src/pythermogis/doublet_simulation/deterministic_doublet.py

+7 −1
Original line number Diff line number Diff line
@@ -10,7 +10,7 @@ from pythermogis.physics.temperature_grid_calculation import calculate_temperatu 
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.
@@ -50,6 +50,12 @@ def calculate_doublet_performance(reservoir_properties: xr.Dataset, utc_properti 
    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

        Any cell that results in:

        1. a failed simulation

        2. failed input validation checks

        will be assigned the mask_value, by default it is 0



    Returns

    -------

    output_data : xr.Dataset

src/pythermogis/thermogis_classes/doublet.py

+32 −15
Original line number Diff line number Diff line
@@ -2,7 +2,7 @@ import numpy as np 
import xarray as xr

from jpype import JClass



def simulate_doublet(output_data: xr.Dataset, reservoir_properties: xr.Dataset, rng_seed: int, utc_properties: JClass) -> xr.Dataset:

def simulate_doublet(output_data: xr.Dataset, reservoir_properties: xr.Dataset, rng_seed: int, utc_properties: JClass, mask_value: float) -> xr.Dataset:

    # Calculate transmissivity scaled by ntg and converted to Dm

    output_data[f"transmissivity_with_ntg"] = (output_data[f"transmissivity"] * reservoir_properties.ntg) / 1e3
@@ -42,7 +42,7 @@ def simulate_doublet(output_data: xr.Dataset, reservoir_properties: xr.Dataset, 
    return output_data





def calculate_performance_of_single_location(mask: float, depth: float, thickness: float, porosity: float, ntg: float, temperature: float, transmissivity: float, transmissivity_with_ntg: float, rng_seed: int, utc_properties: JClass = None) -> float:

def calculate_performance_of_single_location(mask: float, depth: float, thickness: float, porosity: float, ntg: float, temperature: float, transmissivity: float, transmissivity_with_ntg: float, rng_seed: int, utc_properties: JClass = None, mask_value: float = 0.0) -> float:

    """

    Calculate the performance of a doublet at a single location.
@@ -86,16 +86,9 @@ def calculate_performance_of_single_location(mask: float, depth: float, thicknes 
    inj_temp: float [C]

    prd_temp: float [C]

    """



    if np.isnan(thickness) or np.isnan(depth) or np.isnan(porosity) or np.isnan(ntg) or np.isnan(temperature) or np.isnan(transmissivity) or np.isnan(transmissivity_with_ntg):

        return np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan



    if np.isnan(mask):

        return np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan

        #return 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0



    if (temperature<utc_properties.minProdTemp()):

        return np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan

    if not validate_input(depth, mask, ntg, porosity, temperature, thickness, transmissivity,

                   transmissivity_with_ntg, utc_properties):

        return (mask_value,) * 14



    # Instantiate ThermoGIS doublet

    doublet = instantiate_thermogis_doublet(utc_properties, rng_seed)
@@ -104,9 +97,9 @@ def calculate_performance_of_single_location(mask: float, depth: float, thicknes 
    # The Java routine which calculates DoubletPerformance, for more detail on the simulation inspect the Java source code

    doublet.calculateDoubletPerformance(-9999.0, thickness, transmissivity, False)



    if doublet.getUtcPeurctkWh() == -9999.0:  # If calculation was not successful, return all nan

        return np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan

        #return 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0

    # If calculation was not successful, return mask value

    if doublet.getUtcPeurctkWh() == -9999.0:

        return (mask_value,) * 14



    # calculate net-present-value using the utc-cutoffs

    if depth > utc_properties.utcDeepDepth():
@@ -140,6 +133,30 @@ def calculate_performance_of_single_location(mask: float, depth: float, thicknes 
        "cophp"], output_values["pres"], output_values["flow_rate"], output_values["welld"], output_values["inj_temp"], output_values["prd_temp"]





def validate_input(depth: float,

    mask: float,

    ntg: float,

    porosity: float,

    temperature: float,

    thickness: float,

    transmissivity: float,

    transmissivity_with_ntg: float,

    utc_properties: float,

) -> bool:

    if np.any(np.isnan([depth,

                        mask,

                        ntg,

                        porosity,

                        temperature,

                        thickness,

                        transmissivity,

                        transmissivity_with_ntg])):

        return False



    if temperature < utc_properties.minProdTemp():

        return False

    return True



def instantiate_thermogis_doublet(utc_properties, rng_seed: int = None) -> JClass:

    """

    Instantiate a ThermoGIS Doublet class, setting necessary parameters from utc_properties and optionally using a specified random seed.

tests/resources/test_output/exceedance_example/exceedance_probabilities.png

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