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Revert "[FIX] product,float_utils: perform ceiling via float_round with new rounding_method UP" 

This reverts commit d4972ffdb6.

Seems to break some cases, at least in _product_reserve from stock/stock.py

Actual use case:

SELECT product_uom, sum(product_qty) AS product_qty FROM stock_move WHERE location_dest_id=%s AND location_id<>%s AND product_id=3645 AND state='done' GROUP BY product_uom;
returning 1 | 6

SELECT product_uom,-sum(product_qty) AS product_qty FROM stock_move WHERE location_id=%s AND location_dest_id<>%s AND product_id=%s AND state in ('done', 'assigned') GROUP BY product_uom;
returning 1 | -6

results += cr.dictfetchall()
    total = 0.0
    results2 = 0.0
    for r in results:
        amount = uom_obj._compute_qty(cr, uid, r['product_uom'], r['product_qty'], context.get('uom', False))
        results2 += amount
        total += amount
Total = 1, amount = -5

It should actually be
Total = 0, amount = -6
This commit is contained in:
Denis Ledoux 2014-09-26 21:21:06 +02:00
parent ceff8ef899
commit 333852e19d
3 changed files with 13 additions and 34 deletions
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5
addons/product/_common.py
View File

@ -20,6 +20,9 @@
##############################################################################
from openerp import tools
import math
def rounding(f, r):
# TODO for trunk: log deprecation warning
# _logger.warning("Deprecated rounding method, please use tools.float_round to round floats.")
@ -29,4 +32,4 @@ def rounding(f, r):
def ceiling(f, r):
if not r:
return f
return tools.float_round(f, precision_rounding=r, rounding_method='UP')
return math.ceil(f / r) * r

13
openerp/addons/base/test/base_test.yml
View File

@ -198,8 +198,8 @@
-
!python {model: res.currency}: |
from tools import float_compare, float_is_zero, float_round, float_repr
def try_round(amount, expected, precision_digits=3, float_round=float_round, float_repr=float_repr, rounding_method='HALF-UP'):
result = float_repr(float_round(amount, precision_digits=precision_digits, rounding_method=rounding_method),
def try_round(amount, expected, precision_digits=3, float_round=float_round, float_repr=float_repr):
result = float_repr(float_round(amount, precision_digits=precision_digits),
precision_digits=precision_digits)
assert result == expected, 'Rounding error: got %s, expected %s' % (result, expected)
try_round(2.6745, '2.675')
@ -213,15 +213,6 @@
try_round(457.4554, '457.455')
try_round(-457.4554, '-457.455')
# Try some rounding value with rounding method UP instead of HALF-UP
# We use 8.175 because when normalizing 8.175 with precision_digits=3 it gives
# us 8175,0000000001234 as value, and if not handle correctly the rounding UP
# value will be incorrect (should be 8,175 and not 8,176)
try_round(8.175, '8.175', rounding_method='UP')
try_round(8.1751, '8.176', rounding_method='UP')
try_round(-8.175, '-8.175', rounding_method='UP')
try_round(-8.1751, '-8.175', rounding_method='UP')
# Extended float range test, inspired by Cloves Almeida's test on bug #882036.
fractions = [.0, .015, .01499, .675, .67499, .4555, .4555, .45555]
expecteds = ['.00', '.02', '.01', '.68', '.67', '.46', '.456', '.4556']

29
openerp/tools/float_utils.py
View File

@ -29,11 +29,10 @@ def _float_check_precision(precision_digits=None, precision_rounding=None):
return 10 ** -precision_digits
return precision_rounding
def float_round(value, precision_digits=None, precision_rounding=None, rounding_method='HALF-UP'):
"""Return ``value`` rounded to ``precision_digits`` decimal digits,
minimizing IEEE-754 floating point representation errors, and applying
the tie-breaking rule selected with ``rounding_method``, by default
HALF-UP (away from zero).
def float_round(value, precision_digits=None, precision_rounding=None):
"""Return ``value`` rounded to ``precision_digits``
decimal digits, minimizing IEEE-754 floating point representation
errors, and applying HALF-UP (away from zero) tie-breaking rule.
Precision must be given by ``precision_digits`` or ``precision_rounding``,
not both!
@ -42,9 +41,6 @@ def float_round(value, precision_digits=None, precision_rounding=None, rounding_
:param float precision_rounding: decimal number representing the minimum
non-zero value at the desired precision (for example, 0.01 for a
2-digit precision).
:param rounding_method: the rounding method used: 'HALF-UP' or 'UP', the first
one rounding up to the closest number with the rule that number>=0.5 is
rounded up to 1, and the latest one always rounding up.
:return: rounded float
"""
rounding_factor = _float_check_precision(precision_digits=precision_digits,
@ -56,7 +52,7 @@ def float_round(value, precision_digits=None, precision_rounding=None, rounding_
# we normalize the value before rounding it as an integer, and de-normalize
# after rounding: e.g. float_round(1.3, precision_rounding=.5) == 1.5
# TIE-BREAKING: HALF-UP (for normal rounding)
# TIE-BREAKING: HALF-UP
# We want to apply HALF-UP tie-breaking rules, i.e. 0.5 rounds away from 0.
# Due to IEE754 float/double representation limits, the approximation of the
# real value may be slightly below the tie limit, resulting in an error of
@ -70,19 +66,8 @@ def float_round(value, precision_digits=None, precision_rounding=None, rounding_
normalized_value = value / rounding_factor # normalize
epsilon_magnitude = math.log(abs(normalized_value), 2)
epsilon = 2**(epsilon_magnitude-53)
if rounding_method == 'HALF-UP':
normalized_value += cmp(normalized_value,0) * epsilon
rounded_value = round(normalized_value) # round to integer
# TIE-BREAKING: UP (for ceiling operations)
# When rounding the value up, we instead subtract the epsilon value
# as the the approximation of the real value may be slightly *above* the
# tie limit, this would result in incorrectly rounding up to the next number
elif rounding_method == 'UP':
normalized_value -= cmp(normalized_value,0) * epsilon
rounded_value = math.ceil(normalized_value) # ceil to integer
normalized_value += cmp(normalized_value,0) * epsilon
rounded_value = round(normalized_value) # round to integer
result = rounded_value * rounding_factor # de-normalize
return result