Apply scaling factor when reading the cube files

cubehandler/cube.py

@@ -75,7 +75,7 @@ def __init__(
             self.cell_n = cell_n
 
     @classmethod
-    def from_file_handle(cls, filehandle, read_data=True):
+    def from_file_handle(cls, filehandle, read_data=True, apply_scaling=True):
         f = filehandle
         c = cls()
         c.title = f.readline().rstrip()
@@ -131,18 +131,24 @@ def from_file_handle(cls, filehandle, read_data=True):
             # data = np.array(f.read().split(), dtype=float)
 
             c.data = c.data.reshape(c.cell_n)
+            if apply_scaling:
+                c.data *= c.scaling_factor
 
         return c
 
     @classmethod
-    def from_file(cls, filepath, read_data=True):
+    def from_file(cls, filepath, read_data=True, apply_scaling=True):
         with open(filepath) as f:
-            c = cls.from_file_handle(f, read_data=read_data)
+            c = cls.from_file_handle(
+                f, read_data=read_data, apply_scaling=apply_scaling
+            )
         return c
 
     @classmethod
-    def from_content(cls, content, read_data=True):
-        return cls.from_file_handle(io.StringIO(content), read_data=read_data)
+    def from_content(cls, content, read_data=True, apply_scaling=True):
+        return cls.from_file_handle(
+            io.StringIO(content), read_data=read_data, apply_scaling=apply_scaling
+        )
 
     def write_cube_file(self, filename, low_precision=False):
 

tests/test_cube.py

@@ -88,6 +88,6 @@ def test_reduce_data_density():
     cube.reduce_data_density(points_per_angstrom=2)
     cube.write_cube_file("low_res.cube", low_precision=True)
     low_res = Cube.from_file("low_res.cube")
-    low_res_integral = np.sum(low_res.data**2) * low_res.dv_au * low_res.scaling_f**2
+    low_res_integral = np.sum(low_res.data**2) * low_res.dv_au
     assert np.abs(low_res_integral - integral) < 0.01
     assert cube.scaling_f == 0.2848452