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Collapse duplicated accessor methods #69

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61 changes: 29 additions & 32 deletions src/xarray_regrid/regrid.py
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Original file line number Diff line number Diff line change
@@ -1,12 +1,14 @@
from collections.abc import Hashable
from typing import Any, overload
from typing import Any, Literal, overload

import numpy as np
import xarray as xr

from xarray_regrid.methods import conservative, flox_reduce, interp
from xarray_regrid.utils import format_for_regrid

InterpMethod = Literal["linear", "nearest", "cubic"]


@xr.register_dataarray_accessor("regrid")
@xr.register_dataset_accessor("regrid")
Expand Down Expand Up @@ -40,9 +42,7 @@ def linear(
Returns:
Data regridded to the target dataset coordinates.
"""
ds_target_grid = validate_input(self._obj, ds_target_grid, time_dim)
ds_formatted = format_for_regrid(self._obj, ds_target_grid)
return interp.interp_regrid(ds_formatted, ds_target_grid, "linear")
return self._interp(ds_target_grid, "linear", time_dim)

def nearest(
self,
Expand All @@ -59,9 +59,7 @@ def nearest(
Returns:
Data regridded to the target dataset coordinates.
"""
ds_target_grid = validate_input(self._obj, ds_target_grid, time_dim)
ds_formatted = format_for_regrid(self._obj, ds_target_grid)
return interp.interp_regrid(ds_formatted, ds_target_grid, "nearest")
return self._interp(ds_target_grid, "nearest", time_dim)

def cubic(
self,
Expand All @@ -78,9 +76,17 @@ def cubic(
Returns:
Data regridded to the target dataset coordinates.
"""
return self._interp(ds_target_grid, "cubic", time_dim)

def _interp(
self,
ds_target_grid: xr.Dataset,
method: InterpMethod,
time_dim: str | None,
) -> xr.DataArray | xr.Dataset:
ds_target_grid = validate_input(self._obj, ds_target_grid, time_dim)
ds_formatted = format_for_regrid(self._obj, ds_target_grid)
return interp.interp_regrid(ds_formatted, ds_target_grid, "cubic")
return interp.interp_regrid(ds_formatted, ds_target_grid, method)

def conservative(
self,
Expand Down Expand Up @@ -160,27 +166,7 @@ def most_common(
Returns:
Regridded data.
"""
ds_target_grid = validate_input(self._obj, ds_target_grid, time_dim)

if isinstance(self._obj, xr.Dataset):
msg = (
"The 'most common value' regridder is not implemented for\n",
"xarray.Dataset, as it requires specifying the expected labels.\n"
"Please select only a single variable (as DataArray),\n"
" and regrid it separately.",
)
raise ValueError(msg)

ds_formatted = format_for_regrid(self._obj, ds_target_grid, stats=True)

return flox_reduce.compute_mode(
ds_formatted,
ds_target_grid,
values,
time_dim,
fill_value,
anti_mode=False,
)
return self._mode(ds_target_grid, values, time_dim, fill_value, anti_mode=False)

def least_common(
self,
Expand Down Expand Up @@ -212,14 +198,25 @@ def least_common(
Returns:
Regridded data.
"""
return self._mode(ds_target_grid, values, time_dim, fill_value, anti_mode=True)

def _mode(
self,
ds_target_grid: xr.Dataset,
values: np.ndarray,
time_dim: str | None,
fill_value: None | Any,
anti_mode: bool,
) -> xr.DataArray:
ds_target_grid = validate_input(self._obj, ds_target_grid, time_dim)

if isinstance(self._obj, xr.Dataset):
label = "least common value" if anti_mode else "most common value"
msg = (
"The 'least common value' regridder is not implemented for\n",
f"The '{label}' regridder is not implemented for\n"
"xarray.Dataset, as it requires specifying the expected labels.\n"
"Please select only a single variable (as DataArray),\n"
" and regrid it separately.",
" and regrid it separately."
)
raise ValueError(msg)

Expand All @@ -231,7 +228,7 @@ def least_common(
values,
time_dim,
fill_value,
anti_mode=True,
anti_mode=anti_mode,
)

def stat(
Expand Down