Updating the example data and docs

from os import path

# the location of the input data: the data can be found in the resources/example_data directory of the repo

input_data_path = Path(path.dirname(__file__), "resources") / "test_input" / "example_data"

input_data_path = Path("path/to/example_data")

# create a directory to write the output files to

output_data_path = Path(path.dirname(__file__), "resources") / "test_output" / "example_data"

output_data_path = Path("path/to/example_data/output")

output_data_path.mkdir(parents=True, exist_ok=True)

# if set to True then simulation is always run, otherwise pre-calculated results are read (if available)

reservoir_properties["ln_permeability_mean"] = np.log(resample_xarray_grid(read_grid(input_data_path / "ROSL_ROSLU__perm.zmap"), new_cellsize=new_cellsize))

reservoir_properties["ln_permeability_sd"] = resample_xarray_grid(read_grid(input_data_path / "ROSL_ROSLU__ln_perm_sd.zmap"), new_cellsize=new_cellsize)

# simulate

# Simulate

# if doublet simulation has already been run then read in results, or run the simulation and write results out

if (output_data_path / "output_results.nc").exists and not run_simulation:

    results = xr.load_dataset(output_data_path / "output_results.nc")

    results = calculate_doublet_performance(reservoir_properties, p_values=[10,20,30,40,50,60,70,80,90])

results.to_netcdf(output_data_path / "output_results.nc") # write doublet simulation results to file

# Plotting

# plot results as maps

variables_to_plot = ["transmissivity","power","capex", "npv"]

p_values_to_plot = [10, 50, 90]