Merge pull request #32 from stonerlab/copilot/stable-make-dataarray-descriptor

Make DataArray a descriptor to enforce Data.data type invariant

Author: gb119

Stoner/core/array.py

@@ -122,6 +122,75 @@ def __array_wrap__(self, obj, context=None, return_scalar=None):
         ret = ma.MaskedArray.__array_wrap__(self, obj, context=context, return_scalar=return_scalar)
         return ret
 
+    # ==============================================================================================================
+    ############################        Descriptor Protocol         ################################################
+    # ==============================================================================================================
+
+    def __set_name__(self, owner, name):
+        """Record the attribute name when the descriptor is assigned as a class attribute.
+
+        Args:
+            owner (type):
+                The class that owns this descriptor.
+            name (str):
+                The attribute name used for this descriptor on the owner class.
+        """
+        self._attr_name = name
+        self._private_name = f"_{name}"
+
+    def __get__(self, obj, objtype=None):
+        """Return the DataArray stored on the owner instance (descriptor getter).
+
+        Args:
+            obj: The owner instance, or ``None`` when accessed on the class itself.
+            objtype: The owner class.
+
+        Returns:
+            DataArray: The stored data array, guaranteed to be at least 2-dimensional,
+                or this descriptor instance when accessed on the class.
+        """
+        if obj is None:
+            return self
+        try:
+            return np.atleast_2d(object.__getattribute__(obj, self._private_name))
+        except AttributeError:
+            return np.atleast_2d(DataArray([]))
+
+    def __set__(self, obj, value):
+        """Store *value* as a :class:`DataArray` on the owner instance (descriptor setter).
+
+        The setter normalises the incoming value so that it is always a 2-D
+        :class:`DataArray`.  Column headers and ``setas`` assignments are
+        preserved from the existing data when the number of columns matches.
+
+        Args:
+            obj: The owner instance.
+            value (array-like): New data to store.
+
+        Raises:
+            ValueError: If *value* has more than 2 dimensions.
+        """
+        nv = value
+        if not nv.shape:  # nv is a scalar - make it a 2D array
+            nv = ma.atleast_2d(nv)
+        elif nv.ndim == 1:  # nv is a vector - make it a 2D array
+            nv = ma.atleast_2d(nv).T
+        elif nv.ndim > 2:
+            raise ValueError(f"DataFile.data should be no more than 2 dimensional not shape {nv.shape}")
+        try:
+            old_data = object.__getattribute__(obj, self._private_name)
+        except AttributeError:
+            old_data = DataArray([])
+        if not isinstance(nv, DataArray):  # nv isn't a DataArray, so preserve setas
+            nv = DataArray(nv)
+            nv._setas = old_data._setas.clone
+        elif old_data.ndim >= 2 and nv.shape[1] == old_data.shape[1]:  # same columns - preserve column_headers and setas
+            ch = old_data.column_headers
+            nv._setas = old_data._setas.clone
+            nv.column_headers = ch
+        nv._setas.shape = nv.shape
+        object.__setattr__(obj, self._private_name, nv)
+
     def _prepare_index(self, ix):
         """Mangle an indexing argument into a standard tuple form."""
         match ix:

Stoner/core/property.py

@@ -72,34 +72,8 @@ def column_headers(self, value):
         """Write the column_headers attribute (delagated to the setas object)."""
         self.data._setas.column_headers = value
 
-    @property
-    def data(self):
-        """Property Accessors for the main numerical data."""
-        return np.atleast_2d(self._data)
-
-    @data.setter
-    def data(self, value):
-        """Set the data attribute, but force it through numpy.ma.masked_array first."""
-        nv = value
-        if not nv.shape:  # nv is a scalar - make it a 2D array
-            nv = ma.atleast_2d(nv)
-        elif nv.ndim == 1:  # nv is a vector - make it a 2D array
-            nv = ma.atleast_2d(nv).T
-        elif nv.ndim > 2:
-            raise ValueError(f"DataFile.data should be no more than 2 dimensional not shape {nv.shape}")
-        if not isinstance(
-            nv, DataArray
-        ):  # nv isn't a DataArray, so preserve setas (does this preserve column_headers too?)
-            nv = DataArray(nv)
-            nv._setas = getattr(self, "_data")._setas.clone
-        elif (
-            nv.shape[1] == self.shape[1]
-        ):  # nv is a DataArray with the same number of columns - preserve column_headers and setas
-            ch = getattr(self, "_data").column_headers
-            nv._setas = getattr(self, "_data")._setas.clone
-            nv.column_headers = ch
-        nv._setas.shape = nv.shape
-        self._data = nv
+    data = DataArray([])
+    """DataArray descriptor that enforces the data attribute is always a :class:`DataArray` instance."""
 
     @property
     def dict_records(self):

Stoner/tools/tests.py

@@ -171,7 +171,7 @@ def isnone(iterator: Optional[IterableType]) -> bool:
 
 
 def isproperty(obj: Any, name: str) -> bool:
-    """Check whether an attribute of an object or class is a property.
+    """Check whether an attribute of an object or class is a property or data descriptor.
 
     Args:
         obj (instance or class):
@@ -181,13 +181,17 @@ def isproperty(obj: Any, name: str) -> bool:
 
     Returns:
         (bool):
-            Whether the name is a property or not.
+            Whether the name is a property or data descriptor or not.
     """
     if not isinstance(obj, type):
         obj = type(obj)
     elif not issubclass(obj, object):
         raise TypeError(f"Can only check for property status on attributes of an object or a class not a {type(obj)}")
-    return hasattr(obj, name) and isinstance(getattr(obj, name), property)
+    for klass in obj.__mro__:
+        if name in klass.__dict__:
+            attr = klass.__dict__[name]
+            return isinstance(attr, property) or (hasattr(attr, "__get__") and hasattr(attr, "__set__"))
+    return False
 
 
 def istuple(obj: Any, *args: type, strict: bool = True) -> bool:

tests/Stoner/mixedmetatest.dat

@@ -1,15 +1,15 @@
-TDI Format 1.5	1	2	3	4
-Stoner.class{String}=Data	0	1	2	3
-t0{Boolean}=True	4	5	6	7
-t1{I32}=1	8	9	10	11
-t10{List}=[1, (1, 2), 'abc']
-t11{List}=[[[1]]]
-t12{Void}=None
-t2{Double Float}=0.2
-t3{Cluster (I32,String)}={'a': 1, 'b': 'abc'}
-t4{Cluster (I32,I32)}=(1, 2)
-t5{1D Array (Invalid Type)}=array([0, 1, 2])
-t6{List}=[1, 2, 3]
-t7{String}=abc
-t8{String}=\\abc\cde
-t9{Double Float}=1e-20
+TDI Format 1.5	1	2	3	4
+Stoner.class{String}=Data	0	1	2	3
+t0{Boolean}=True	4	5	6	7
+t1{I32}=1	8	9	10	11
+t10{List}=[1, (1, 2), 'abc']
+t11{List}=[[[1]]]
+t12{Void}=None
+t2{Double Float}=0.2
+t3{Cluster (I32,String)}={'a': 1, 'b': 'abc'}
+t4{Cluster (I32,I32)}=(1, 2)
+t5{1D Array (Invalid Type)}=array([0, 1, 2])
+t6{List}=[1, 2, 3]
+t7{String}=abc
+t8{String}=\\abc\cde
+t9{Double Float}=1e-20