fix rounding

hyperspy/axes.py

@@ -583,8 +583,6 @@ def value2index(self, value, rounding=round):
         else:
             value = np.asarray(value)
 
-
-
         #Should evaluate on both arrays and scalars. Raises error if there are
         #nan values in array
         if np.all((value >= self.low_value)*(value <= self.high_value)):

hyperspy/misc/array_tools.py

@@ -469,10 +469,13 @@ def numba_closest_index_round(axis_array,value_array):
     #initialise the index same dimension as input, force type to int
     index_array = np.empty_like(value_array,dtype='uint')
     #assign on flat, iterate on flat.
+    rtol=1e-12
+    machineepsilon = np.min(np.abs(np.diff(axis_array)))*rtol
     for i,v in enumerate(value_array.flat):
-        rtol=1e-10
-        machineepsilon = np.min(np.diff(axis_array))*rtol
-        index_array.flat[i] = np.abs(axis_array - v + machineepsilon).argmin()
+        if v>= 0:
+            index_array.flat[i] = np.abs(axis_array - v - machineepsilon).argmin()
+        else:
+            index_array.flat[i] = np.abs(axis_array - v + machineepsilon).argmin()
     return index_array
 
 @njit(cache=True)

hyperspy/tests/axes/test_data_axis.py

@@ -186,6 +186,10 @@ def test_value2index(self):
         assert self.axis.value2index(2.5,rounding=math.floor) == 1
         # Test that output is integer
         assert isinstance(self.axis.value2index(60), (int, np.integer))
+        self.axis.axis = self.axis.axis - 2
+        # test rounding on negative value
+        assert self.axis.value2index(-1.5,rounding=round) == 0
+
 
     def test_value2index_error(self):
         with pytest.raises(ValueError):