Make it easier to change the surface normal in Bragg2DPtycho.from_dataset

src/cdtools/models/bragg_2d_ptycho.py

@@ -258,6 +258,7 @@ def from_dataset(
             obj_padding=200,
             obj_view_crop=None,
             units='um',
+            surface_normal=None
     ):
         wavelength = dataset.wavelength
         det_basis = dataset.detector_geometry['basis']
@@ -278,24 +279,38 @@ def from_dataset(
                         distance,
                         oversampling=oversampling)
 
-        # now we grab the sample surface normal
-        if hasattr(dataset, 'sample_info') and \
-           dataset.sample_info is not None and \
-           'orientation' in dataset.sample_info:
-            surface_normal = dataset.sample_info['orientation'][2]
-        else:
-            surface_normal = np.array([0.,0.,1.])
-
-        # If this information is supplied when the function is called,
-        # then we override the information in the .cxi file
-        if scattering_mode in {'t', 'transmission'}:
+        # Now we define the surface normal
+        # The surface normal definition is based on the following heirarchy:
+        #   manual surface_normal definition > scattering_mode
+        #   > dataset.sample_info['orientation'] > transmission geometry
+        if surface_normal is not None:
+            surface_normal = np.asarray(surface_normal)
+        elif scattering_mode.strip().lower() in {'t', 'transmission'}:
             surface_normal = np.array([0.,0.,1.])
-        elif scattering_mode in {'r', 'reflection'}:
+        elif scattering_mode.strip().lower() in {'r', 'reflection'}:
             outgoing_dir = np.cross(det_basis[:,0], det_basis[:,1])
             outgoing_dir /= np.linalg.norm(outgoing_dir)
             surface_normal = outgoing_dir + np.array([0.,0.,1.])
             surface_normal /= np.linalg.norm(outgoing_dir)
+        elif scattering_mode is not None:
+            raise ValueError(
+                'Scattering mode must be either "transmission" ("t"), "reflection" ("r"), or the default of None.'
+            )
+        elif hasattr(dataset, 'sample_info') and \
+             dataset.sample_info is not None and \
+             'orientation' in dataset.sample_info:
+            # If the scattering_mode has not been defined, we grab
+            # this from the cxi file if its present.
+            surface_normal = dataset.sample_info['orientation'][2]
+        else:
+            surface_normal = np.array([0., 0., 1.])
 
+            # Guard against any surface_normal entries that are not castable
+        # to a length-3 numpy vector, with a sensible error message
+        if not surface_normal.shape == (3,):
+            raise ValueError(
+                '`surface_normal` needs to be a numpy vector with 3 elements. If it was set incorrectly from dataset.sample_info, consider explicitly setting it via the `surface_normal` keyword argument.'
+            )
         # and we use that to generate the probe basis
 
         ew_normal = np.cross(np.array(ew_basis)[:,1],