Add support for single images in PyFAI integrators

src/PyHyperScattering/PFEnergySeriesIntegrator.py

@@ -39,6 +39,7 @@ def integrateSingleImage(self,img):
         #    get the energy and locate the matching integrator
         #    use that integrator to reduce
         #    return single reduced frame
+
         #print(f'    img.energy is a {type(img.energy)}, len = {len(img.energy)} and is {img.energy}') 
         #print(f'    img.system is a {type(img.system)}, len = {len(img.energy)} and is {img.system}')
         #print(f'    img.system.levels: {img.indexes["system"].names}')
@@ -72,10 +73,12 @@ def integrateSingleImage(self,img):
             except IndexError:
                 en = float(img.energy)
             except AttributeError:
-                en = img.energy[0]
-                warnings.warn(f'Using the first energy value of {img.energy}, check that this is correct.',stacklevel=2)
+                try:
+                    en = img.energy[0]
+                    warnings.warn(f'Using the first energy value of {img.energy}, check that this is correct.',stacklevel=2)
+                except IndexError:
+                    en = float(img.energy)
 
-
         try:
             self.integrator = self.integrator_stack[en]
         except KeyError:
@@ -86,7 +89,7 @@ def integrateSingleImage(self,img):
                 return res.interp(q=self.dest_q)
             else:
                 return res
-        except TypeError:
+        except (TypeError,AttributeError):
             return res
     def setupIntegrators(self,energies):
         '''
@@ -119,7 +122,7 @@ def integrateImageStack_dask(self,img_stack,chunksize=5):
         # idx_name_to_use = 'energy'#indexes[0]
         # idx_val_to_use = img_stack.indexes[idx_name_to_use]
 
-        
+
         if 'energy' in indexes:
             dim_to_chunk = 'energy'
         else:
@@ -193,6 +196,8 @@ def integrateImageStack_legacy(self,img_stack):
             if img_stack.__getattr__(indexes[0]).to_pandas().drop_duplicates().shape[0] != img_stack.__getattr__(indexes[0]).shape[0]:
                 warnings.warn(f'Axis {indexes[0]} contains duplicate conditions.  This is not supported and may not work.  Try adding additional coords to separate image conditions',stacklevel=2)
             data_int = data.groupby(indexes[0],squeeze=False).progress_apply(self.integrateSingleImage)
+        elif len(indexes) == 0:
+            data_int = self.integrateSingleImage(data).isel(image_num=0)
         else:
             #some kinda logic to check for existing multiindexes and stack into them appropriately maybe
             data = data.stack({'pyhyper_internal_multiindex':indexes})

src/PyHyperScattering/PFGeneralIntegrator.py

@@ -152,6 +152,8 @@ def integrateImageStack_legacy(self,data):
 
         if len(indexes) == 1:
             data_int = data.groupby(indexes[0],squeeze=False).progress_map(self.integrateSingleImage)
+        elif len(indexes) == 0:
+            data_int = self.integrateSingleImage(data).isel(image_num=0)
         else:
             #some kinda logic to check for existing multiindexes and stack into them appropriately maybe
             data = data.stack({'pyhyper_internal_multiindex':indexes})
@@ -471,6 +473,12 @@ def calibrationFromTemplateXRParams(self, raw_xr):
         self.pixel1 = raw_xr.pixel1
         self.pixel2 = raw_xr.pixel2
 
+        try:
+            self.energy = float(raw_xr.energy)
+        except TypeError:
+            pass
+
+
         if self.mask is None:
             self.mask = np.zeros((len(raw_xr.pix_y),len(raw_xr.pix_x)))
             warnings.warn(f'Since mask was none, creating an empty mask with shape {self.mask.shape}',stacklevel=2)