Allow any string name for metadata

pynapple/core/interval_set.py

@@ -22,6 +22,7 @@
 from .metadata_class import _MetadataMixin
 from .time_index import TsIndex
 from .utils import (
+    _convert_iter_to_str,
     _get_terminal_size,
     _IntervalSetSliceHelper,
     check_filename,
@@ -214,10 +215,12 @@
         self.index = np.arange(data.shape[0], dtype="int")
         self.columns = np.array(["start", "end"])
         self.nap_class = self.__class__.__name__
-        if drop_meta:
-            _MetadataMixin.__init__(self)
-        else:
-            _MetadataMixin.__init__(self, metadata)
+        # initialize metadata to get all attributes before setting metadata
+        _MetadataMixin.__init__(self)
+        self._class_attributes = self.__dir__()  # get list of all attributes
+        self._class_attributes.append("_class_attributes")  # add this property
+        if drop_meta is False:
+            self.set_info(metadata)
         self._initialized = True
 
     def __repr__(self):
@@ -229,7 +232,14 @@
         # By default, the first three columns should always show.
 
         # Adding an extra column between actual values and metadata
-        col_names = self._metadata.columns
+        try:
+            metadata = self._metadata
+            col_names = metadata.columns
+        except Exception:
+            # Necessary for backward compatibility when saving IntervalSet as pickle
+            metadata = pd.DataFrame(index=self.index)
+            col_names = []
+
         headers = ["index", "start", "end"]
         if len(col_names):
             headers += [""] + [c for c in col_names]
@@ -249,7 +259,7 @@
                             self.index[0:n_rows, None],
                             self.values[0:n_rows],
                             separator,
-                            self._metadata.values[0:n_rows],
+                            _convert_iter_to_str(metadata.values[0:n_rows]),
                         ),
                         dtype=object,
                     ),
@@ -259,7 +269,7 @@
                             self.index[-n_rows:, None],
                             self.values[0:n_rows],
                             separator,
-                            self._metadata.values[-n_rows:],
+                            _convert_iter_to_str(metadata.values[-n_rows:]),
                         ),
                         dtype=object,
                     ),
@@ -271,7 +281,12 @@
             else:
                 separator = np.empty((len(self), 0))
             data = np.hstack(
-                (self.index[:, None], self.values, separator, self._metadata.values),
+                (
+                    self.index[:, None],
+                    self.values,
+                    separator,
+                    _convert_iter_to_str(metadata.values),
+                ),
                 dtype=object,
             )
 
@@ -286,19 +301,53 @@
     def __setattr__(self, name, value):
         # necessary setter to allow metadata to be set as an attribute
         if self._initialized:
-            _MetadataMixin.__setattr__(self, name, value)
+            if name in self._class_attributes:
+                raise AttributeError(
+                    f"Cannot set attribute '{name}'; IntervalSet is immutable. Use 'set_info()' to set '{name}' as metadata."
+                )
+            else:
+                _MetadataMixin.__setattr__(self, name, value)
         else:
             object.__setattr__(self, name, value)
 
+    def __getattr__(self, name):
+        # Necessary for backward compatibility with pickle
+
+        # avoid infinite recursion when pickling due to
+        # self._metadata.column having attributes '__reduce__', '__reduce_ex__'
+        if name in ("__getstate__", "__setstate__", "__reduce__", "__reduce_ex__"):
+            raise AttributeError(name)
+
+        try:
+            metadata = self._metadata
+        except Exception:
+            metadata = pd.DataFrame(index=self.index)
+
+        if name == "_metadata":
+            return metadata
+        elif name in metadata.columns:
+            return _MetadataMixin.__getattr__(self, name)
+        else:
+            return super().__getattr__(name)
+
     def __setitem__(self, key, value):
-        if (isinstance(key, str)) and (key not in self.columns):
+        if key in self.columns:
+            raise RuntimeError(
+                "IntervalSet is immutable. Starts and ends have been already sorted."
+            )
+        elif isinstance(key, str):
             _MetadataMixin.__setitem__(self, key, value)
         else:
             raise RuntimeError(
                 "IntervalSet is immutable. Starts and ends have been already sorted."
             )
 
     def __getitem__(self, key):
+        try:
+            metadata = _MetadataMixin.__getitem__(self, key)
+        except Exception:
+            metadata = pd.DataFrame(index=self.index)
+
         if isinstance(key, str):
             # self[str]
             if key == "start":
@@ -323,7 +372,6 @@
         elif isinstance(key, Number):
             # self[Number]
             output = self.values.__getitem__(key)
-            metadata = _MetadataMixin.__getitem__(self, key)
             return IntervalSet(start=output[0], end=output[1], metadata=metadata)
         elif isinstance(key, (slice, list, np.ndarray, pd.Series)):
             # self[array_like]

pynapple/core/metadata_class.py

@@ -11,7 +11,7 @@
 
     """
 
-    def __init__(self, metadata=None, **kwargs):
+    def __init__(self, metadata=None):
         """
         Metadata initializer
 
@@ -21,7 +21,6 @@
             List of pandas.DataFrame
         **kwargs : dict
             Dictionary containing metadata information
-
         """
         if self.__class__.__name__ == "TsdFrame":
             # metadata index is the same as the columns for TsdFrame
@@ -31,12 +30,8 @@
             self.metadata_index = self.index
 
         self._metadata = pd.DataFrame(index=self.metadata_index)
-        if len(kwargs):
-            warnings.warn(
-                "initializing metadata with variable keyword arguments may be unsupported in a future version of Pynapple. Instead, initialize using the metadata argument.",
-                FutureWarning,
-            )
-        self.set_info(metadata, **kwargs)
+
+        self.set_info(metadata)
 
     def __dir__(self):
         """
@@ -115,32 +110,48 @@
             raise TypeError(
                 f"Invalid metadata type {type(name)}. Metadata column names must be strings!"
             )
-        if hasattr(self, name) and (name not in self.metadata_columns):
-            # existing non-metadata attribute
-            raise ValueError(
-                f"Invalid metadata name '{name}'. Metadata name must differ from "
-                f"{type(self).__dict__.keys()} attribute names!"
-            )
-        if hasattr(self, "columns") and name in self.columns:
-            # existing column (since TsdFrame columns are not attributes)
-            raise ValueError(
-                f"Invalid metadata name '{name}'. Metadata name must differ from "
-                f"{self.columns} column names!"
-            )
-        if name[0].isalpha() is False:
-            # starts with a number
-            raise ValueError(
-                f"Invalid metadata name '{name}'. Metadata name cannot start with a number"
-            )
+        # warnings for metadata names that cannot be accessed as attributes or keys
+        if name in self._class_attributes:
+            if (self.nap_class == "TsGroup") and (name == "rate"):
+                # special exception for TsGroup rate attribute
+                raise ValueError(
+                    f"Invalid metadata name '{name}'. Cannot overwrite TsGroup 'rate'!"
+                )
+            else:
+                # existing non-metadata attribute
+                warnings.warn(
+                    f"Metadata name '{name}' overlaps with an existing attribute, and cannot be accessed as an attribute or key. Use 'get_info()' to access metadata."
+                )
+        elif hasattr(self, "columns") and name in self.columns:
+            if self.nap_class == "TsdFrame":
+                # special exception for TsdFrame columns
+                raise ValueError(
+                    f"Invalid metadata name '{name}'. Metadata name must differ from {list(self.columns)} column names!"
+                )
+            else:
+                # existing non-metadata column
+                warnings.warn(
+                    f"Metadata name '{name}' overlaps with an existing property, and cannot be accessed as an attribute or key. Use 'get_info()' to access metadata."
+                )
+        # elif name in self.metadata_columns:
+        #     # warnings for metadata that already exists
+        #     warnings.warn(f"Overwriting existing metadata column '{name}'.")
+
+        # warnings for metadata that cannot be accessed as attributes
         if name.replace("_", "").isalnum() is False:
             # contains invalid characters
-            raise ValueError(
-                f"Invalid metadata name '{name}'. Metadata name cannot contain special characters except for underscores"
+            warnings.warn(
+                f"Metadata name '{name}' contains a special character, and cannot be accessed as an attribute. Use 'get_info()' or key indexing to access metadata."
+            )
+        elif (name[0].isalpha() is False) and (name[0] != "_"):
+            # starts with a number
+            warnings.warn(
+                f"Metadata name '{name}' starts with a number, and cannot be accessed as an attribute. Use 'get_info()' or key indexing to access metadata."
             )
 
     def _check_metadata_column_names(self, metadata=None, **kwargs):
         """
-        Check that metadata column names don't conflict with existing attributes, don't start with a number, and don't contain invalid characters.
+        Throw warnings when metadata names cannot be accessed as attributes or keys.
         """
 
         if metadata is not None:

pynapple/core/time_series.py

@@ -33,6 +33,7 @@
 from .time_index import TsIndex
 from .utils import (
     _concatenate_tsd,
+    _convert_iter_to_str,
     _get_terminal_size,
     _split_tsd,
     _TsdFrameSliceHelper,
@@ -949,11 +950,22 @@
 
         self.columns = pd.Index(c)
         self.nap_class = self.__class__.__name__
-        _MetadataMixin.__init__(self, metadata)
+        # initialize metadata for class attributes
+        _MetadataMixin.__init__(self)
+        # get current list of attributes
+        self._class_attributes = self.__dir__()
+        self._class_attributes.append("_class_attributes")
+        # set metadata
+        self.set_info(metadata)
         self._initialized = True
 
     @property
     def loc(self):
+        # add deprecation warning
+        warnings.warn(
+            "'loc' will be deprecated in a future version. Use bracket indexing instead.",
+            DeprecationWarning,
+        )
         return _TsdFrameSliceHelper(self)
 
     def __repr__(self):
@@ -1030,7 +1042,9 @@
                         np.hstack(
                             (
                                 col_names[:, None],
-                                self._metadata.values[0:max_cols].T,
+                                _convert_iter_to_str(
+                                    self._metadata.values[0:max_cols].T
+                                ),
                                 ends,
                             ),
                             dtype=object,
@@ -1045,7 +1059,12 @@
     def __setattr__(self, name, value):
         # necessary setter to allow metadata to be set as an attribute
         if self._initialized:
-            _MetadataMixin.__setattr__(self, name, value)
+            if name in self._class_attributes:
+                raise AttributeError(
+                    f"Cannot set attribute: '{name}' is a reserved attribute. Use 'set_info()' to set '{name}' as metadata."
+                )
+            else:
+                _MetadataMixin.__setattr__(self, name, value)
         else:
             super().__setattr__(name, value)
 
@@ -1056,7 +1075,15 @@
         # self._metadata.column having attributes '__reduce__', '__reduce_ex__'
         if name in ("__getstate__", "__setstate__", "__reduce__", "__reduce_ex__"):
             raise AttributeError(name)
-        if name in self._metadata.columns:
+
+        try:
+            metadata = self._metadata
+        except (AttributeError, RecursionError):
+            metadata = pd.DataFrame(index=self.columns)
+
+        if name == "_metadata":
+            return metadata
+        elif name in metadata.columns:
             return _MetadataMixin.__getattr__(self, name)
         else:
             return super().__getattr__(name)
@@ -1096,18 +1123,18 @@
                     "When indexing with a Tsd, it must contain boolean values"
                 )
             key = key.d
-        elif isinstance(key, str) and (key in self.metadata_columns):
-            return _MetadataMixin.__getitem__(self, key)
         elif (
             isinstance(key, str)
             or hasattr(key, "__iter__")
             and all([isinstance(k, str) for k in key])
         ):
-            if all(k in self.metadata_columns for k in key):
-                return _MetadataMixin.__getitem__(self, key)
+            if all(k in self.columns for k in key):
+                with warnings.catch_warnings():
+                    # ignore deprecated warning for loc
+                    warnings.simplefilter("ignore")
+                    return self.loc[key]
             else:
-                return self.loc[key]
-
+                return _MetadataMixin.__getitem__(self, key)
         else:
             if isinstance(key, pd.Series) and key.index.equals(self.columns):
                 # if indexing with a pd.Series from metadata, transform it to tuple with slice(None) in first position