TNO Intern

Commit 95b2a133 authored by Florian Knappers's avatar Florian Knappers
Browse files

cleanup

parent f99cb4c5

src/pythermogis/workflow/utc/utc.py

+71 −80
Original line number Diff line number Diff line
@@ -9,7 +9,15 @@ from pythermogis.transmissivity.calculate_thick_perm_trans import ( 
    calculate_transmissivity,

)

from pythermogis.workflow.utc.configuration import UTCConfiguration

from pythermogis.workflow.utc.doublet import DoubletInput, calculate_doublet_performance

from pythermogis.workflow.utc.doublet import (

    DoubletInput,

    DoubletOutput,

    calculate_doublet_performance,

)



OUTPUT_NAMES = list(DoubletOutput._fields)

NAN_OUTPUTS = DoubletOutput(*[np.nan] * len(OUTPUT_NAMES))

ZERO_OUTPUTS = DoubletOutput(*[0.0] * len(OUTPUT_NAMES))





def run_utc_workflow(config: UTCConfiguration) -> xr.DataTree:
@@ -77,76 +85,6 @@ def compute_results_for_aquifer( 
    config: UTCConfiguration,

    temperature_model: xr.Dataset,

):

    output_names = [

        "power",

        "hppower",

        "capex",

        "var_opex",

        "fixed_opex",

        "opex",

        "utc",

        "npv",

        "hprod",

        "cop",

        "cophp",

        "pres",

        "flow",

        "welld",

        "breakthrough",

        "cooling",

        "production_temp",

        "injection_temp",

    ]



    def cell_calculation(

        unknown_input_value,

        thickness,

        transmissivity,

        transmissivity_with_ntg,

        ntg,

        depth,

        porosity,

        temperature,

    ):

        inputs = [

            unknown_input_value,

            thickness,

            transmissivity,

            transmissivity_with_ntg,

            ntg,

            depth,

            porosity,

            temperature,

        ]

        if any(np.isnan(v) for v in inputs):

            return tuple(np.nan for _ in output_names)



        if transmissivity_with_ntg < config.kh_cutoff:

            return tuple(0 for _ in output_names)



        doublet_input = DoubletInput(

            unknown_input_value=float(unknown_input_value),

            thickness=float(thickness),

            transmissivity=float(transmissivity),

            transmissivity_with_ntg=float(transmissivity_with_ntg),

            ntg=float(ntg),

            depth=float(depth),

            porosity=float(porosity / 100),

            temperature=float(temperature),

        )



        try:

            result = calculate_doublet_performance(config, doublet_input)

        except ValueError:

            return tuple(np.nan for _ in output_names)



        if result.utc > 1000:

            result = result._replace(utc=1000)



        return (

            tuple(result) if result is not None else tuple(np.nan for _ in output_names)

        )



    # apply hc mask

    hc_mask = aquifer_ds["hc_accum"] != 0

    vars_to_mask = [
@@ -170,11 +108,11 @@ def compute_results_for_aquifer( 


    for p_value in config.p_values:

        # calc transmissivity(_with_ntg)

        hydro = compute_hydro_properties_mc(aquifer_ds, p_value)

        aquifer_ds["transmissivity"] = hydro["transmissivity"]

        aquifer_ds["transmissivity_with_ntg"] = hydro["transmissivity_with_ntg"]

        aquifer_ds["thickness"] = hydro["thickness"]

        aquifer_ds["permeability"] = hydro["permeability"]

        stoch_results = apply_stochastics(aquifer_ds, p_value)

        aquifer_ds["transmissivity"] = stoch_results["transmissivity"]

        aquifer_ds["transmissivity_with_ntg"] = stoch_results["transmissivity_with_ntg"]

        aquifer_ds["thickness"] = stoch_results["thickness"]

        aquifer_ds["permeability"] = stoch_results["permeability"]



        results = xr.apply_ufunc(

            cell_calculation,
@@ -186,14 +124,15 @@ def compute_results_for_aquifer( 
            aquifer_ds["depth"],

            aquifer_ds["porosity"],

            aquifer_ds["temperature"],

            kwargs={"config": config},

            input_core_dims=[[]] * 8,

            output_core_dims=[[] for _ in output_names],

            output_core_dims=[[] for _ in OUTPUT_NAMES],

            vectorize=True,

            dask="parallelized",

            output_dtypes=[np.float64] * len(output_names),

            output_dtypes=[np.float64] * len(OUTPUT_NAMES),

        )



        for name, result in zip(output_names, results, strict=True):

        for name, result in zip(OUTPUT_NAMES, results, strict=True):

            aquifer_ds[f"{name}_p{p_value}"] = result



    aquifer_ds.compute()
@@ -203,7 +142,7 @@ def compute_results_for_aquifer( 
    return aquifer_ds





def compute_hydro_properties_mc(

def apply_stochastics(

    aquifer_ds: xr.Dataset,

    p_value: float,

    n_samples: int = 10_000,
@@ -239,3 +178,55 @@ def compute_hydro_properties_mc( 
        },

        coords=aquifer_ds.coords,

    )





def cell_calculation(

    unknown_input_value: float,

    thickness: float,

    transmissivity: float,

    transmissivity_with_ntg: float,

    ntg: float,

    depth: float,

    porosity: float,

    temperature: float,

    config: UTCConfiguration,

) -> DoubletOutput:

    inputs = [

        unknown_input_value,

        thickness,

        transmissivity,

        transmissivity_with_ntg,

        ntg,

        depth,

        porosity,

        temperature,

    ]

    if any(np.isnan(v) for v in inputs):

        return NAN_OUTPUTS



    if transmissivity_with_ntg < config.kh_cutoff:

        return ZERO_OUTPUTS



    doublet_input = DoubletInput(

        unknown_input_value=unknown_input_value,

        thickness=thickness,

        transmissivity=transmissivity,

        transmissivity_with_ntg=transmissivity_with_ntg,

        ntg=ntg,

        depth=depth,

        porosity=porosity / 100,

        temperature=temperature,

    )



    try:

        result = calculate_doublet_performance(config, doublet_input)

    except ValueError:

        return NAN_OUTPUTS



    if result is None:

        return NAN_OUTPUTS



    if result.utc > 1000:

        result = result._replace(utc=1000)



    return result