API reference¶
This page provides an auto-generated summary of skdownscale’s API. For more details and examples, refer to the relevant chapters in the main part of the documentation.
Pointwise methods¶
Xarray Wrappers¶
PointWiseDownscaler(model[, dim]) |
Pointwise downscaling model wrapper |
Linear Models¶
BcsdPrecipitation([time_grouper, …]) |
Classic BCSD model for Precipitation | ||
BcsdTemperature([time_grouper, …]) |
Methods |
||
PureAnalog([n_analogs, kind, thresh, stats, …]) |
|
||
AnalogRegression([n_analogs, kdtree_kwargs, …]) |
|
||
PiecewiseLinearRegression([n_segments, …]) |
Piecewise Linear Regression | ||
QuantileMappingReressor([extrapolate, …]) |
Transform features using quantile mapping. | ||
TrendAwareQuantileMappingRegressor([…]) |
Experimental meta estimator for performing trend-aware quantile mapping |
Transformers¶
LinearTrendTransformer([lr_kwargs]) |
Transform features by removing linear trends. |
QuantileMapper([detrend, lt_kwargs, qt_kwargs]) |
Transform features using quantile mapping. |
Grouping¶
GroupedRegressor(estimator, fit_grouper, …) |
Grouped Regressor |
Groupers¶
DAY_GROUPER(x) |
|
MONTH_GROUPER(x) |
|
PaddedDOYGrouper(df[, offset]) |
Methods |