def fill_discount(discount):
if (discount is not None
and discount.starting_date < timezone.now().date()
and discount.ending_date > timezone.now().date()):
if discount.discount_type == FIXED:
discount_price = money_quantize(
Decimal(discount.discount_value))
else:
discount_price = money_quantize(
-current_price * Decimal(discount.discount_value / 100.))
new_price = money_quantize(current_price + discount_price)
price.discount = discount_price
else:
price.discount = None
new_price = current_price
return new_price
def fill_country_reduction(address):
db_countriespayment = CountryPayment.objects.all()
max_pib = db_countriespayment.aggregate(
Max('pib_per_inhabitant'))['pib_per_inhabitant__max']
min_pib = db_countriespayment.aggregate(
Min('pib_per_inhabitant'))['pib_per_inhabitant__min']
try:
country = address.country
own_country_payment = CountryPayment.objects.get(country=country)
except (AttributeError, ObjectDoesNotExist):
price.country_reduction = None
return current_price
factor = COUNTRY_PPP_TO_PERCENT(min_pib, max_pib,
own_country_payment.pib_per_inhabitant)
new_price = money_quantize(current_price * Decimal(factor))
diff_price = money_quantize(new_price - current_price)
price.country_reduction = diff_price
return new_price
def fill_scientific_score(user, order_type):
if order_type == SCIENTIST_ACCOUNT:
price.scientist_score = None
price.scientist_score_reduction = None
return current_price
skeptic_score = SKEPTIC_SCORE_NORMALIZE(user.skeptic_score)
mean_publication_score = MEAN_PUBLICATION_SCORE_NORMALIZE(
user.mean_publication_score)
mean_impact_factor = MEAN_IMPACT_FACTOR_NORMALIZE(
user.mean_impact_factor)
estimator_score = ESTIMATOR_SCORE_NORMALIZE(user.estimator_score)
reviewer_score = REVIEWER_SCORE_NORMALIZE(user.reviewer_score)
mean_score = (skeptic_score + mean_publication_score +
mean_impact_factor + estimator_score +
reviewer_score) / 5.
payment_percent = -0.08 + (1 +
0.08) / (1 +
(mean_score / 0.1214766)**1.137504)
new_price = money_quantize(current_price * Decimal(payment_percent))
diff_price = money_quantize(new_price - current_price)
price.scientist_score = round(mean_score, 2)
price.scientist_score_reduction = diff_price
return new_price
def test_high_premice(self):
self.assertEqual(float(money_quantize(Decimal(12344444444.4))),
12344444444.40)
def test_high_decimal(self):
self.assertEqual(float(money_quantize(Decimal(12.3444444444))), 12.35)
def test_low_limit_decimal(self):
self.assertEqual(float(money_quantize(Decimal(12.000001))), 12.01)
def test_high_limit_decimal(self):
self.assertEqual(float(money_quantize(Decimal(12.9999))), 13.)
def test_no_decimal(self):
self.assertEqual(float(money_quantize(Decimal(12344444444))),
12344444444.)
def fill_taxes(percent):
taxes_amount = money_quantize(current_price * Decimal(percent / 100))
new_price = money_quantize(current_price + taxes_amount)
price.tax_percent = percent
price.tax = taxes_amount
return new_price