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xarray/core/dataarray.py

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@@ -2232,26 +2232,26 @@ def interp(
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determine which interpolant is used:
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1. **Interpolation along one dimension of 1D data (`method='linear'`)**
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- Uses :py:class:`numpy.interp`, unless `fill_value='extrapolate'` is provided via `kwargs`.
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- Uses :py:class:`numpy.interp`, unless `fill_value='extrapolate'` is provided via `kwargs`.
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2. **Interpolation along one dimension of N-dimensional data (N ≥ 1)**
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- Methods {"linear", "nearest", "zero", "slinear", "quadratic", "cubic", "quintic", "polynomial"}
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use :py:class:`scipy.interpolate.interp1d`, unless conditions permit the use of :py:class:`numpy.interp`
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(as in the case of `method='linear'` for 1D data).
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- If `method='polynomial'`, the `order` keyword argument must also be provided. In this case,
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:py:class:`scipy.interpolate.interp1d` is called with `kind=order`.
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- Methods {"linear", "nearest", "zero", "slinear", "quadratic", "cubic", "quintic", "polynomial"}
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use :py:class:`scipy.interpolate.interp1d`, unless conditions permit the use of :py:class:`numpy.interp`
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(as in the case of `method='linear'` for 1D data).
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- If `method='polynomial'`, the `order` keyword argument must also be provided. In this case,
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:py:class:`scipy.interpolate.interp1d` is called with `kind=order`.
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3. **Special interpolants for interpolation along one dimension of N-dimensional data (N ≥ 1)**
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- Depending on the `method`, the following interpolants from :py:class:`scipy.interpolate` are used:
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- `"pchip"`: :py:class:`scipy.interpolate.PchipInterpolator`
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- `"barycentric"`: :py:class:`scipy.interpolate.BarycentricInterpolator`
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- `"krogh"`: :py:class:`scipy.interpolate.KroghInterpolator`
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- `"akima"` or `"makima"`: :py:class:`scipy.interpolate.Akima1dInterpolator`
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(`makima` is handled by passing `makima` to `method`).
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- Depending on the `method`, the following interpolants from :py:class:`scipy.interpolate` are used:
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- `"pchip"`: :py:class:`scipy.interpolate.PchipInterpolator`
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- `"barycentric"`: :py:class:`scipy.interpolate.BarycentricInterpolator`
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- `"krogh"`: :py:class:`scipy.interpolate.KroghInterpolator`
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- `"akima"` or `"makima"`: :py:class:`scipy.interpolate.Akima1dInterpolator`
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(`makima` is handled by passing `makima` to `method`).
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4. **Interpolation along multiple dimensions of multi-dimensional data**
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- Uses :py:func:`scipy.interpolate.interpn` for methods {"linear", "nearest", "slinear",
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"cubic", "quintic", "pchip"}.
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- Uses :py:func:`scipy.interpolate.interpn` for methods {"linear", "nearest", "slinear",
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"cubic", "quintic", "pchip"}.
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Out-of-range values are filled with NaN, unless specified otherwise via `kwargs` to the numpy/scipy interpolant.
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