Error handling for get_tag

extension_templates/annotation.py

@@ -114,7 +114,7 @@ def __init__(
         # if est.foo == 42:
         #   self.set_tags(handles-missing-data=True)
         # example 2: cloning tags from component
-        #   self.clone_tags(est2, ["enforce-index-type", "handles-missing-data"])
+        #   self.clone_tags(est2, ["enforce_index_type", "handles-missing-data"])
 
     # todo: implement this, mandatory
     def _fit(self, X, Y=None):

extension_templates/classification.py

@@ -69,7 +69,7 @@ class MyTSC(BaseClassifier):
     _tags = {
         "handles-missing-data": False,  # can estimator handle missing data?
         "X-y-must-have-same-index": True,  # can estimator handle different X/y index?
-        "enforce-index-type": None,  # index type that needs to be enforced in X/y
+        "enforce_index_type": None,  # index type that needs to be enforced in X/y
     }
     # in case of inheritance, concrete class should typically set tags
     #  alternatively, descendants can set tags in __init__ (avoid this if possible)
@@ -103,7 +103,7 @@ def __init__(self, est, parama, est2=None, paramb="default", paramc=None):
         # if est.foo == 42:
         #   self.set_tags(handles-missing-data=True)
         # example 2: cloning tags from component
-        #   self.clone_tags(est2, ["enforce-index-type", "handles-missing-data"])
+        #   self.clone_tags(est2, ["enforce_index_type", "handles-missing-data"])
 
     # todo: implement this, mandatory
     def _fit(self, X, y):

extension_templates/dist_kern_panel.py

@@ -92,7 +92,7 @@ def __init__(self, est, parama, est2=None, paramb="default", paramc=None):
         # if est.foo == 42:
         #   self.set_tags(handles-missing-data=True)
         # example 2: cloning tags from component
-        #   self.clone_tags(est2, ["enforce-index-type", "handles-missing-data"])
+        #   self.clone_tags(est2, ["enforce_index_type", "handles-missing-data"])
 
     # todo: implement this, mandatory
     def _transform(self, X, X2=None):

extension_templates/dist_kern_tab.py

@@ -92,7 +92,7 @@ def __init__(self, est, parama, est2=None, paramb="default", paramc=None):
         # if est.foo == 42:
         #   self.set_tags(handles-missing-data=True)
         # example 2: cloning tags from component
-        #   self.clone_tags(est2, ["enforce-index-type", "handles-missing-data"])
+        #   self.clone_tags(est2, ["enforce_index_type", "handles-missing-data"])
 
     # todo: implement this, mandatory
     def _transform(self, X, X2=None):

extension_templates/forecasting.py

@@ -79,7 +79,7 @@ class MyForecaster(BaseForecaster):
         "X_inner_mtype": "pd.DataFrame",  # which types do _fit, _predict, assume for X?
         "requires-fh-in-fit": True,  # is forecasting horizon already required in fit?
         "X-y-must-have-same-index": True,  # can estimator handle different X/y index?
-        "enforce-index-type": None,  # index type that needs to be enforced in X/y
+        "enforce_index_type": None,  # index type that needs to be enforced in X/y
     }
     # in case of inheritance, concrete class should typically set tags
     #  alternatively, descendants can set tags in __init__ (avoid this if possible)
@@ -113,7 +113,7 @@ def __init__(self, est, parama, est2=None, paramb="default", paramc=None):
         # if est.foo == 42:
         #   self.set_tags(handles-missing-data=True)
         # example 2: cloning tags from component
-        #   self.clone_tags(est2, ["enforce-index-type", "handles-missing-data"])
+        #   self.clone_tags(est2, ["enforce_index_type", "handles-missing-data"])
 
     # todo: implement this, mandatory
     def _fit(self, y, X=None, fh=None):

sktime/base/_base.py

@@ -132,25 +132,37 @@ class attribute via nested inheritance and then any overrides
 
         return deepcopy(collected_tags)
 
-    def get_tag(self, tag_name, tag_value_default=None):
+    def get_tag(self, tag_name, tag_value_default=None, raise_error=True):
         """Get tag value from estimator class and dynamic tag overrides.
 
         Parameters
         ----------
         tag_name : str
-            Name of tag value.
-        tag_value_default : any type
-            Default/fallback value if tag is not found.
+            Name of tag to be retrieved
+        tag_value_default : any type, optional; default=None
+            Default/fallback value if tag is not found
+        raise_error : bool
+            whether a ValueError is raised when the tag is not found
 
         Returns
         -------
         tag_value :
             Value of the `tag_name` tag in self. If not found, returns
             `tag_value_default`.
+
+        Raises
+        ------
+        ValueError if raise_error is True and tag_name does not exist
+            i.e., if tag_name is not in self.get_tags().keys()
         """
         collected_tags = self.get_tags()
 
-        return collected_tags.get(tag_name, tag_value_default)
+        tag_value = collected_tags.get(tag_name, tag_value_default)
+
+        if raise_error and tag_name not in collected_tags.keys():
+            raise ValueError(f"Tag with name {tag_name} could not be found.")
+
+        return tag_value
 
     def set_tags(self, **tag_dict):
         """Set dynamic tags to given values.

sktime/classification/base.py

@@ -74,6 +74,7 @@ class BaseClassifier(BaseEstimator):
 
     _tags = {
         "coerce-X-to-numpy": True,
+        "coerce-X-to-pandas": False,
     }
 
     def __init__(self):

sktime/forecasting/base/_base.py

@@ -71,7 +71,7 @@ class BaseForecaster(BaseEstimator):
         "X_inner_mtype": "pd.DataFrame",  # which types do _fit/_predict, support for X?
         "requires-fh-in-fit": True,  # is forecasting horizon already required in fit?
         "X-y-must-have-same-index": True,  # can estimator handle different X/y index?
-        "enforce-index-type": None,  # index type that needs to be enforced in X/y
+        "enforce_index_type": None,  # index type that needs to be enforced in X/y
     }
 
     def __init__(self):

sktime/forecasting/model_selection/_tune.py

@@ -65,7 +65,7 @@ def __init__(
             "y_inner_mtype",
             "X_inner_mtype",
             "X-y-must-have-same-index",
-            "enforce-index-type",
+            "enforce_index_type",
         ]
 
         self.clone_tags(forecaster, tags_to_clone)

sktime/registry/_tags.py

@@ -94,7 +94,7 @@
         "do X/y in fit/update and X/fh in predict have to be same indices?",
     ),
     (
-        "enforce-index-type",
+        "enforce_index_type",
         ["forecaster", "classifier", "regressor"],
         "type",
         "passed to input checks, input conversion index type to enforce",

sktime/transformations/base.py

@@ -1,7 +1,7 @@
-#!/usr/bin/env python3 -u
 # -*- coding: utf-8 -*-
+"""Base class template for transformers."""
 
-__author__ = ["Markus Löning"]
+__author__ = ["mloning"]
 __all__ = [
     "BaseTransformer",
     "_SeriesToPrimitivesTransformer",
@@ -34,14 +34,25 @@
 
 
 class BaseTransformer(BaseEstimator):
-    """Transformer base class"""
+    """Transformer base class."""
+
+    # default tag values - these typically make the "safest" assumption
+    _tags = {
+        "univariate-only": False,  # can the transformer handle multivariate X?
+        "handles-missing-data": False,  # can estimator handle missing data?
+        "X-y-must-have-same-index": False,  # can estimator handle different X/y index?
+        "enforce_index_type": None,  # index type that needs to be enforced in X/y
+        "fit-in-transform": True,  # is fit empty and can be skipped? Yes = True
+        "transform-returns-same-time-index": False,
+        # does transform return have the same time index as input X
+        "skip-inverse-transform": False,  # is inverse-transform skipped when called?
+    }
 
     def __init__(self):
         super(BaseTransformer, self).__init__()
 
     def fit(self, Z, X=None):
-        """
-        Fit transformer to X and y.
+        """Fit transformer to X and y.
 
         By default, fit is empty. Fittable transformations overwrite fit method.
 
@@ -60,7 +71,7 @@ def fit(self, Z, X=None):
         return self
 
     def transform(self, Z, X=None):
-        """Transform data. Returns a transformed version of X."""
+        """Transform data. Returns a transformed version of Z."""
         raise NotImplementedError("abstract method")
 
     def fit_transform(self, Z, X=None):
@@ -98,28 +109,32 @@ def fit_transform(self, Z, X=None):
 
 
 class _SeriesToPrimitivesTransformer(BaseTransformer):
-    """Transformer base class for series to primitive(s) transforms"""
+    """Transformer base class for series to primitive(s) transforms."""
 
     def transform(self, Z: Series, X=None) -> Primitives:
+        """Transform data. Returns a transformed version of Z."""
         raise NotImplementedError("abstract method")
 
 
 class _SeriesToSeriesTransformer(BaseTransformer):
-    """Transformer base class for series to series transforms"""
+    """Transformer base class for series to series transforms."""
 
     def transform(self, Z: Series, X=None) -> Series:
+        """Transform data. Returns a transformed version of Z."""
         raise NotImplementedError("abstract method")
 
 
 class _PanelToTabularTransformer(BaseTransformer):
-    """Transformer base class for panel to tabular transforms"""
+    """Transformer base class for panel to tabular transforms."""
 
     def transform(self, X: Panel, y=None) -> Tabular:
+        """Transform data. Returns a transformed version of X."""
         raise NotImplementedError("abstract method")
 
 
 class _PanelToPanelTransformer(BaseTransformer):
-    """Transformer base class for panel to panel transforms"""
+    """Transformer base class for panel to panel transforms."""
 
     def transform(self, X: Panel, y=None) -> Panel:
+        """Transform data. Returns a transformed version of X."""
         raise NotImplementedError("abstract method")