Pad this dataset along one or more dimensions. .. warning:: This function is experimental and its behaviour is likely to change especially regarding padding of dimension coordinates (or IndexVariables). When using one of the modes ("edge", "reflect", "symmet
(
self,
pad_width: Mapping[Any, int | tuple[int, int]] | None = None,
mode: PadModeOptions = "constant",
stat_length: (
int | tuple[int, int] | Mapping[Any, tuple[int, int]] | None
) = None,
constant_values: T_DatasetPadConstantValues | None = None,
end_values: int | tuple[int, int] | Mapping[Any, tuple[int, int]] | None = None,
reflect_type: PadReflectOptions = None,
keep_attrs: bool | None = None,
**pad_width_kwargs: Any,
)
| 8999 | return polyfit_impl(self, dim, deg, skipna, rcond, w, full, cov) |
| 9000 | |
| 9001 | def pad( |
| 9002 | self, |
| 9003 | pad_width: Mapping[Any, int | tuple[int, int]] | None = None, |
| 9004 | mode: PadModeOptions = "constant", |
| 9005 | stat_length: ( |
| 9006 | int | tuple[int, int] | Mapping[Any, tuple[int, int]] | None |
| 9007 | ) = None, |
| 9008 | constant_values: T_DatasetPadConstantValues | None = None, |
| 9009 | end_values: int | tuple[int, int] | Mapping[Any, tuple[int, int]] | None = None, |
| 9010 | reflect_type: PadReflectOptions = None, |
| 9011 | keep_attrs: bool | None = None, |
| 9012 | **pad_width_kwargs: Any, |
| 9013 | ) -> Self: |
| 9014 | """Pad this dataset along one or more dimensions. |
| 9015 | |
| 9016 | .. warning:: |
| 9017 | This function is experimental and its behaviour is likely to change |
| 9018 | especially regarding padding of dimension coordinates (or IndexVariables). |
| 9019 | |
| 9020 | When using one of the modes ("edge", "reflect", "symmetric", "wrap"), |
| 9021 | coordinates will be padded with the same mode, otherwise coordinates |
| 9022 | are padded using the "constant" mode with fill_value dtypes.NA. |
| 9023 | |
| 9024 | Parameters |
| 9025 | ---------- |
| 9026 | pad_width : mapping of hashable to tuple of int |
| 9027 | Mapping with the form of {dim: (pad_before, pad_after)} |
| 9028 | describing the number of values padded along each dimension. |
| 9029 | {dim: pad} is a shortcut for pad_before = pad_after = pad |
| 9030 | mode : {"constant", "edge", "linear_ramp", "maximum", "mean", "median", \ |
| 9031 | "minimum", "reflect", "symmetric", "wrap"}, default: "constant" |
| 9032 | How to pad the DataArray (taken from numpy docs): |
| 9033 | |
| 9034 | - "constant": Pads with a constant value. |
| 9035 | - "edge": Pads with the edge values of array. |
| 9036 | - "linear_ramp": Pads with the linear ramp between end_value and the |
| 9037 | array edge value. |
| 9038 | - "maximum": Pads with the maximum value of all or part of the |
| 9039 | vector along each axis. |
| 9040 | - "mean": Pads with the mean value of all or part of the |
| 9041 | vector along each axis. |
| 9042 | - "median": Pads with the median value of all or part of the |
| 9043 | vector along each axis. |
| 9044 | - "minimum": Pads with the minimum value of all or part of the |
| 9045 | vector along each axis. |
| 9046 | - "reflect": Pads with the reflection of the vector mirrored on |
| 9047 | the first and last values of the vector along each axis. |
| 9048 | - "symmetric": Pads with the reflection of the vector mirrored |
| 9049 | along the edge of the array. |
| 9050 | - "wrap": Pads with the wrap of the vector along the axis. |
| 9051 | The first values are used to pad the end and the |
| 9052 | end values are used to pad the beginning. |
| 9053 | |
| 9054 | stat_length : int, tuple or mapping of hashable to tuple, default: None |
| 9055 | Used in 'maximum', 'mean', 'median', and 'minimum'. Number of |
| 9056 | values at edge of each axis used to calculate the statistic value. |
| 9057 | {dim_1: (before_1, after_1), ... dim_N: (before_N, after_N)} unique |
| 9058 | statistic lengths along each dimension. |