modified the LArray.percent() method because it may lead to negative values if the array contains integer values close to the highest integer value available

Author: alixdamman

larray/core/array.py

@@ -3789,8 +3789,7 @@ def percent(self, *axes):
              BE  40.0  60.0
              FO  20.0  80.0
         """
-        # dividing by self.sum(*axes) * 0.01 would be faster in many cases but I suspect it loose more precision.
-        return self * 100 / self.sum(*axes)
+        return self * 100.0 / self.sum(*axes)
 
     # aggregate method decorator
     def _decorate_agg_method(npfunc, nanfunc=None, commutative=False, by_agg=False, extra_kwargs=[],

larray/tests/test_array.py

@@ -2484,15 +2484,15 @@ def test_percent(array):
     reg = array.sum(age, sex, regions)
 
     percent = reg.percent()
-    assert_array_equal(percent, reg * 100 / reg.sum(geo, lipro))
+    assert_array_equal(percent, (reg * 100.0 / reg.sum(geo, lipro)))
     assert percent.shape == (3, 15)
 
     percent = reg.percent(geo)
-    assert_array_equal(percent, reg * 100 / reg.sum(geo))
+    assert_array_equal(percent, (reg * 100.0 / reg.sum(geo)))
     assert percent.shape == (3, 15)
 
     percent = reg.percent(geo, lipro)
-    assert_array_equal(percent, reg * 100 / reg.sum(geo, lipro))
+    assert_array_equal(percent, (reg * 100.0 / reg.sum(geo, lipro)))
     assert percent.shape == (3, 15)
     assert round(abs(percent.sum() - 100.0), 7) == 0