1515from numpy .typing import ArrayLike , NDArray
1616from mhkit .utils import unorm
1717
18+
1819# pylint: disable=too-many-lines
1920# pylint: disable=possibly-used-before-assignment
2021def get_all_time (data : (netCDF4 .Dataset , xr .Dataset )) -> NDArray :
@@ -163,6 +164,7 @@ def _convert_time(
163164
164165 return converted_value
165166
167+
166168# pylint: disable=unused-variable
167169# pylint: disable=too-many-locals
168170# pylint: disable=too-many-branches
@@ -1050,7 +1052,10 @@ def list_variables(data: Union[netCDF4.Dataset, xr.Dataset, xr.DataArray]) -> Li
10501052 f"xarray DataArray. Got: { type (data )} "
10511053 )
10521054
1053- def calculate_grid_convergence_index (fine_grid , coarse_grid , refinement_ratio ,factor_of_safety = 1.25 , order = 2 ):
1055+
1056+ def calculate_grid_convergence_index (
1057+ fine_grid , coarse_grid , refinement_ratio , factor_of_safety = 1.25 , order = 2
1058+ ):
10541059 """
10551060 Calculate the Grid Convergence Index (GCI) between two grid sizes. https://www.grc.nasa.gov/WWW/wind/valid/tutorial/spatconv.html
10561061
@@ -1060,7 +1065,7 @@ def calculate_grid_convergence_index(fine_grid, coarse_grid, refinement_ratio,fa
10601065 Results from the finer grid.
10611066 coarse_grid: numpy.ndarray
10621067 Results from the coarser grid.
1063- refinement_ratio: float
1068+ refinement_ratio: float
10641069 Refinement ratio between the grids.
10651070 order: int
10661071 Order of accuracy (default is 2).
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