(Re)added functionality to process datacubes. Includes testing. Rebased.

photutils/aperture/core.py

@@ -300,6 +300,42 @@ def to_mask(self, method='exact', subpixels=5):
     def _do_photometry(self, data, variance, method='exact', subpixels=5,
                        unit=None):
 
+
+        """
+        data = np.asanyarray(data)
+
+        if mask is not None:
+            mask = np.asanyarray(mask)
+
+            data = copy.deepcopy(data)    # do not modify input data
+            data[mask] = 0
+
+            if error is not None:
+                # do not modify input data
+                error = copy.deepcopy(np.asanyarray(error))
+                error[mask] = 0.
+
+        aperture_sums = []
+        aperture_sum_errs = []
+        output_shape = (1,) if data.ndim==2 else data.shape[0]
+        for mask in self.to_mask(method=method, subpixels=subpixels):
+            data_cutout = mask.cutout(data)
+
+            if data_cutout is None:
+                aperture_sums.append(np.repeat(np.nan, output_shape))
+            else:
+                aperture_sums.append(np.sum(data_cutout * mask.data, axis=(-2,-1)))
+
+            if error is not None:
+                error_cutout = mask.cutout(error)
+
+                if error_cutout is None:
+                    aperture_sum_errs.append(np.repeat(np.nan, output_shape))
+                else:
+                    aperture_var = np.sum(error_cutout ** 2 * mask.data, axis=(-2,-1))
+                    aperture_sum_errs.append(np.sqrt(aperture_var))
+        """
+
         aperture_sums = []
         aperture_sum_errs = []
 
@@ -773,8 +809,8 @@ def _validate_inputs(data, error):
     """
 
     data = np.asanyarray(data)
-    if data.ndim != 2:
-        raise ValueError('data must be a 2D array.')
+    if (data.ndim != 2) and (data.ndim !=3):
+        raise ValueError('data must be a 2D or 3D array.')
 
     if error is not None:
         error = np.asanyarray(error)

photutils/aperture/mask.py

@@ -177,8 +177,8 @@ def cutout(self, data, fill_value=0., copy=False):
         """
 
         data = np.asanyarray(data)
-        if data.ndim != 2:
-            raise ValueError('data must be a 2D array.')
+        if (data.ndim != 2) and (data.ndim != 3):
+            raise ValueError('data must be a 2D or 3D array.')
 
         partial_overlap = False
         if self.bbox.ixmin < 0 or self.bbox.iymin < 0:
@@ -188,20 +188,21 @@ def cutout(self, data, fill_value=0., copy=False):
             # try this for speed -- the result may still be a partial
             # overlap, in which case the next block will be triggered
             if copy:
-                cutout = data[self.bbox.slices].copy()  # preserves Quantity
+                cutout = data[(Ellipsis,)+self.bbox.slices].copy()  # preserves Quantity
             else:
-                cutout = data[self.bbox.slices]
+                cutout = data[(Ellipsis,)+self.bbox.slices]
 
-        if partial_overlap or (cutout.shape != self.shape):
-            slices_large, slices_small = self._overlap_slices(data.shape)
+        if partial_overlap or (cutout.shape[-2:] != self.shape):
+            slices_large, slices_small = self._overlap_slices(data.shape[-2:])
 
             if slices_small is None:
                 return None    # no overlap
 
             # cutout is a copy
-            cutout = np.zeros(self.shape, dtype=data.dtype)
+            output_shape = self.shape if data.ndim==2 else (data.shape[0],)+self.shape
+            cutout = np.zeros(output_shape, dtype=data.dtype)
             cutout[:] = fill_value
-            cutout[slices_small] = data[slices_large]
+            cutout[(Ellipsis,)+slices_small] = data[(Ellipsis,)+slices_large]
 
             if isinstance(data, u.Quantity):
                 cutout = u.Quantity(cutout, unit=data.unit)