NoGrid: allow explict setting of data_shape

src/finam/data/grid_base.py

@@ -70,6 +70,9 @@ class GridBase(ABC):
         """Transformation between compatible grids."""
         return None
 
+    def __repr__(self):
+        return f"{self.name} ({self.dim}D) {self.data_shape}"
+
 
 class Grid(GridBase):
     """Abstract grid specification."""
@@ -187,9 +190,6 @@ class Grid(GridBase):
         """list of str: Axes names of the data."""
         return ["id"]
 
-    def __repr__(self):
-        return f"{self.__class__.__name__} ({self.dim}D) {self.data_shape}"
-
     def compatible_with(self, other, check_location=True):
         """
         Check for compatibility with other Grid.

src/finam/data/grid_spec.py

@@ -28,10 +28,39 @@ def _check_location(grid, data_location):
 
 
 class NoGrid(GridBase):
-    """Indicator for data without a spatial grid."""
+    """
+    Indicator for data without a spatial grid.
+
+    Either dim or data_shape needed.
+
+    Parameters
+    ----------
+    dim : int or None, optional
+        Data dimensionality. Should match the length of data_shape.
+    data_shape : tuple of int or None, optional
+        Data shape. Can contain -1 to indicate flexible axis.
+
+    Raises
+    ------
+    ValueError
+        If none of dim or data_shape are given.
+    ValueError
+        If dim does not match the length of data_shape.
+    """
 
-    def __init__(self, dim=0):
+    def __init__(self, dim=None, data_shape=None):
+        if dim is None and data_shape is None:
+            msg = "NoGrid: either dim or data_shape needed."
+            raise ValueError(msg)
+        if data_shape is None:
+            data_shape = (-1,) * dim
+        if dim is None:
+            dim = len(data_shape)
+        if dim != len(data_shape):
+            msg = "NoGrid: dim needs to match the length of data_shape."
+            raise ValueError(msg)
         self._dim = dim
+        self._data_shape = data_shape
 
     @property
     def dim(self):
@@ -41,10 +70,7 @@ class NoGrid(GridBase):
     @property
     def data_shape(self):
         """tuple: Shape of the associated data."""
-        return tuple()
-
-    def __repr__(self):
-        return f"{self.__class__.__name__} ({self.dim}D)"
+        return self._data_shape
 
     # pylint: disable-next=unused-argument
     def compatible_with(self, other, check_location=True):
@@ -63,7 +89,7 @@ class NoGrid(GridBase):
         bool
             compatibility
         """
-        return isinstance(other, NoGrid) and self.dim == other.dim
+        return isinstance(other, NoGrid) and self.data_shape == other.data_shape
 
     def __eq__(self, other):
         return self.compatible_with(other)

src/finam/data/tools/core.py

@@ -154,22 +154,36 @@ def _check_input_shape(data, info, time_entries):
 
 def _check_input_shape_no_grid(data, info, time_entries):
     if len(data.shape) != info.grid.dim + 1:
-        if len(data.shape) == info.grid.dim:
+        if _no_grid_shape_valid(data.shape, info.grid):
             data = np.expand_dims(data, 0)
         else:
             raise FinamDataError(
-                f"quantify: number of dimensions in data doesn't match expected number. "
-                f"Got {len(data.shape)}, expected {info.grid.dim}"
+                f"Data shape not valid. "
+                f"Got {data.shape}, expected {info.grid.data_shape}"
             )
     else:
+        if not _no_grid_shape_valid(data.shape[1:], info.grid):
+            raise FinamDataError(
+                f"Data shape not valid. "
+                f"Got {data.shape[1:]}, expected {info.grid.data_shape}"
+            )
         if data.shape[0] != time_entries:
             raise FinamDataError(
-                f"quantify: number of time entries in data doesn't match expected number. "
+                f"Number of time entries in data doesn't match expected number. "
                 f"Got {data.shape[0]}, expected {time_entries}"
             )
     return data
 
 
+def _no_grid_shape_valid(data_shape, grid):
+    if len(data_shape) != grid.dim:
+        return False
+    dshp = np.array(data_shape)
+    gshp = np.array(grid.data_shape)
+    check = gshp != -1
+    return np.all(dshp[check] == gshp[check])
+
+
 def has_time_axis(xdata, grid):
     """
     Check if the data array has a time axis.