TNO Intern

Commit feb83fe5 authored by Hen Brett's avatar Hen Brett 🐔
Browse files

allowing the mask_value to be set by the user

parent b5d29763

src/pythermogis/doublet_simulation/deterministic_doublet.py

+1 −1
Original line number Diff line number Diff line
@@ -106,7 +106,7 @@ def calculate_doublet_performance(reservoir_properties: xr.Dataset, utc_properti 
        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)

    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")

src/pythermogis/thermogis_classes/doublet.py

+3 −2
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, mask_value: float) -> xr.Dataset:

def simulate_doublet(output_data: xr.Dataset, reservoir_properties: xr.Dataset, rng_seed: int, utc_properties: JClass, mask_value: float = np.nan) -> 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
@@ -17,7 +17,8 @@ def simulate_doublet(output_data: xr.Dataset, reservoir_properties: xr.Dataset, 
                                        output_data.transmissivity,

                                        output_data.transmissivity_with_ntg,

                                        rng_seed,

                                        kwargs={"utc_properties": utc_properties},

                                        kwargs={"utc_properties": utc_properties,

                                                "mask_value": mask_value},

                                        dask="parallelized",

                                        input_core_dims=[[], [], [], [], [], [], [], [],[]],

                                        output_core_dims=[[], [], [], [], [], [], [], [], [], [], [], [], [], []],