[FIX] tools: epsilon magnitude

The following rounding is incorrect:
```
>>> float_round(6.6 * 0.175, precision_digits=2)
1.15
```

Indeed, 6.6 * 0.175 = 1.155 ≈ 1.16.

In this specific case, the `epsilon` computed is not sufficient. A
precision of 53 gives:
normalized_value = 115.49999999999997
epsilon = 1.2823075934420547e-14
=> new normalized_value = 115.49999999999999

Bad luck, this is just not enough to tip the value in the right
direction.

However, a precision of 52 is sufficient:
normalized_value = 115.49999999999997
epsilon = 2.5646151868841094e-14
=> new normalized_value = 115.5

The value of 53 was chosen from the `binary64` number format precision.
In case of Python, the corresponding machine epsilon is 2^-52 [1].
Therefore, using 52 instead of 53 does make sense.

It is worth noting that the value of the machine epsilon
2^-52 = 2.2204460492503131e-16, which is still 2 orders of magnitude
below our dynamic estimation.

[1] https://en.wikipedia.org/wiki/Machine_epsilon
[2] `numpy.finfo(float).eps = 2.2204460492503131e-16`

opw-2047368

closes odoo/odoo#35521

Signed-off-by: Nicolas Martinelli (nim) <nim@odoo.com>

1 files changed, 2 insertions, 0 deletions

diff --git a/odoo/addons/base/tests/test_float.py b/odoo/addons/base/tests/test_float.py
index a5f91982303..641c9c2d9e7 100644
--- a/odoo/addons/base/tests/test_float.py
+++ b/odoo/addons/base/tests/test_float.py
@@ -27,6 +27,8 @@ class TestFloatPrecision(TransactionCase):
         try_round(0.0049,'0.00')   # 0.0049 is closer to 0 than to 0.01, so should round down
         try_round(0.005,'0.01')   # the rule is to round half away from zero
         try_round(-0.005,'-0.01') # the rule is to round half away from zero
+        try_round(6.6 * 0.175, '1.16') # 6.6 * 0.175 is rounded to 1.15 with epsilon = 53
+        try_round(-6.6 * 0.175, '-1.16')
 
         def try_zero(amount, expected):
             self.assertEqual(currency.is_zero(amount), expected,