[ENH] hcrystalball forecaster adapter

CODEOWNERS

@@ -72,6 +72,7 @@ sktime/forecasting/fbprophet.py @aiwalter
 sktime/forecasting/bats.py @aiwalter
 sktime/forecasting/tbats.py @aiwalter
 sktime/forecasting/arima.py @HYang1996
+sktime/forecasting/adapters/_hcrystalball.py @MichalChromcak
 sktime/forecasting/statsforecast.py @FedericoGarza
 sktime/forecasting/structural.py @juanitorduz
 sktime/forecasting/model_selection/_split @koralturkk

docs/source/api_reference/forecasting.rst

@@ -309,6 +309,19 @@ Online and stream forecasting
     UpdateRefitsEvery
     DontUpdate
 
+Adapters to other forecasting framework packages
+------------------------------------------------
+
+Generic framework adapters that expose other frameworks in the ``sktime`` interface.
+
+.. currentmodule:: sktime.forecasting.adapters
+
+.. autosummary::
+    :toctree: auto_generated/
+    :template: class.rst
+
+    HCrystalBallAdapter
+
 Model selection and tuning
 --------------------------
 

sktime/forecasting/adapters/__init__.py

@@ -0,0 +1,7 @@
+# -*- coding: utf-8 -*-
+"""Module containing adapters to other forecasting framework packages."""
+# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
+
+__all__ = ["HCrystalBallAdapter"]
+
+from sktime.forecasting.adapters._hcrystalball import HCrystalBallAdapter

sktime/forecasting/adapters/_hcrystalball.py

@@ -0,0 +1,186 @@
+# -*- coding: utf-8 -*-
+# !/usr/bin/env python3 -u
+# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
+"""Adapter for using HCrystalBall forecastsers in sktime."""
+
+__author__ = ["MichalChromcak"]
+
+import pandas as pd
+from sklearn.base import clone
+
+from sktime.forecasting.base import BaseForecaster
+from sktime.utils.validation._dependencies import _check_soft_dependencies
+
+_check_soft_dependencies("hcrystalball", severity="warning")
+
+
+def _check_fh(fh, cutoff):
+    if fh is not None:
+        if not fh.is_all_out_of_sample(cutoff):
+            raise NotImplementedError(
+                "in-sample prediction are currently not implemented"
+            )
+
+
+def _check_index(index):
+    if not isinstance(index, pd.DatetimeIndex):
+        raise NotImplementedError(
+            "`HCrystalBallForecaster` currently only supports `pd.DatetimeIndex`. "
+            "Please convert the data index to `pd.DatetimeIndex`."
+        )
+    return index
+
+
+def _adapt_y_X(y, X):
+    """Adapt fit data to HCB compliant format.
+
+    Parameters
+    ----------
+    y : pd.Series
+        Target variable
+    X : pd.Series, pd.DataFrame
+        Exogenous variables
+
+    Returns
+    -------
+    tuple
+        y_train - pd.Series with datetime index
+        X_train - pd.DataFrame with datetime index
+                  and optionally exogenous variables in columns
+
+    Raises
+    ------
+    ValueError
+        When neither of the argument has Datetime or Period index
+    """
+    index = _check_index(y.index)
+    X = pd.DataFrame(index=index) if X is None else X
+    return y, X
+
+
+def _get_X_pred(X_pred, index):
+    """Translate forecast horizon interface to HCB native dataframe.
+
+    Parameters
+    ----------
+    X_pred : pd.DataFrame
+        Exogenous data for predictions
+    index : pd.DatetimeIndex
+        Index generated from the forecasting horizon
+
+    Returns
+    -------
+    pd.DataFrame
+        index - datetime
+        columns - exogenous variables (optional)
+    """
+    if X_pred is not None:
+        _check_index(X_pred.index)
+
+    X_pred = pd.DataFrame(index=index) if X_pred is None else X_pred
+    return X_pred
+
+
+def _adapt_y_pred(y_pred):
+    """Translate wrapper prediction to sktime format.
+
+    From Dataframe to series.
+
+    Parameters
+    ----------
+    y_pred : pd.DataFrame
+
+    Returns
+    -------
+    pd.Series : Predictions in form of series
+    """
+    return y_pred.iloc[:, 0]
+
+
+class HCrystalBallAdapter(BaseForecaster):
+    """Adapter for using `hcrystalball` forecasters in sktime.
+
+    Adapter class - wraps any forecaster from `hcrystalball`
+    and allows using it as an `sktime` `BaseForecaster`.
+
+    Parameters
+    ----------
+    model : The HCrystalBall forecasting model to use.
+    """
+
+    _tags = {
+        "ignores-exogeneous-X": True,
+        "requires-fh-in-fit": False,
+        "handles-missing-data": False,
+        "python_dependencies": "hcrystalball",
+    }
+
+    def __init__(self, model):
+
+        self.model = model
+        super(HCrystalBallAdapter, self).__init__()
+
+    def _fit(self, y, X=None, fh=None):
+        """Fit to training data.
+
+        Parameters
+        ----------
+        y : pd.Series
+            Target time series with which to fit the forecaster.
+        fh : int, list or np.array, optional (default=None)
+            The forecast horizon with the steps ahead to predict.
+        X : pd.DataFrame, optional (default=None)
+            Exogenous variables are ignored
+
+        Returns
+        -------
+        self : returns an instance of self.
+        """
+        y, X = _adapt_y_X(y, X)
+        self.model_ = clone(self.model)
+        self.model_.fit(X, y)
+
+        return self
+
+    def _predict(self, fh=None, X=None):
+        """Make forecasts for the given forecast horizon.
+
+        Parameters
+        ----------
+        fh : int, list or np.array
+            The forecast horizon with the steps ahead to predict
+        X : pd.DataFrame, optional (default=None)
+            Exogenous variables (ignored)
+
+        Returns
+        -------
+        y_pred : pd.Series
+            Point predictions for the forecast
+        """
+        X_pred = _get_X_pred(X, index=fh.to_absolute(self.cutoff).to_pandas())
+        y_pred = self.model_.predict(X=X_pred)
+        return _adapt_y_pred(y_pred)
+
+    @classmethod
+    def get_test_params(cls, parameter_set="default"):
+        """Return testing parameter settings for the estimator.
+
+        Parameters
+        ----------
+        parameter_set : str, default="default"
+            Name of the set of test parameters to return, for use in tests. If no
+            special parameters are defined for a value, will return `"default"` set.
+
+        Returns
+        -------
+        params : dict or list of dict
+        """
+        if _check_soft_dependencies("hcrystalball", severity="none"):
+            from hcrystalball.wrappers import HoltSmoothingWrapper
+
+            params = {"model": HoltSmoothingWrapper()}
+
+        else:
+            params = {"model": 42}
+
+        return params

sktime/tests/test_softdeps.py

@@ -46,7 +46,10 @@
 # estimators excepted from checking that get_test_params does not import soft deps
 # this is ok, in general, for adapters to soft dependency frameworks
 # since such adapters will import estimators from the adapted framework
-EXCEPTED_FROM_GET_PARAMS_CHECK = ["PyODAnnotator"]
+EXCEPTED_FROM_GET_PARAMS_CHECK = [
+    "PyODAnnotator",  # adapters always require soft dep. Here: pyod
+    "HCrystalBallAdapter",  # adapters always require soft dep. Here: hcrystalball
+]
 
 
 def _is_test(module):