def test_similarity_date():
""" Tests the calculation of the similarity of two products based on a 'date' attribute.
"""
date1 = dt.datetime(2000, 11, 24, 10, 0)
date2 = dt.datetime(2000, 11, 26, 10, 0)
similarity = pm.compute_similarity_for_date(date1, date2, halflife=2)
nose.tools.ok_(abs(similarity - 0.5) < tests.FLOAT_DELTA, "Wrong date similarity")
def _process_non_text_attributes_contributions(context, products, strengths):
""" Adds the contribution of the non-text product attributes to the informed map of strengths.
:param context: The customer context.
:param products: A map {product_id: record} where record is a dict {attribute: value}.
:param strengths: A map {(product, template_product): strength_value} with partially computed strengths
(possibly resulting from the contributions of other product attributes). The contribution
of the current attribute (whose map of terms by product is given as *tfidf_map*) will be added
to this same *strengths* map.
"""
for (product_id, template_id) in strengths:
for attr_type, weight_by_attribute in context.similarity_weights_by_type.items():
if attr_type == pm.TEXT:
continue
for attribute, weight in weight_by_attribute.items():
product_attr_value = products[product_id].get_attribute(attribute)
template_attr_value = products[template_id].get_attribute(attribute)
if product_attr_value is None or template_attr_value is None:
log.warn("Missing atribute [{0}] value product == {1}, template == {2}".format(
attribute, product_attr_value, template_attr_value))
continue
contribution = 0
if attr_type == pm.NUMERIC:
contribution = pm.compute_similarity_for_numeric(product_attr_value, template_attr_value)
elif attr_type == pm.FIXED:
contribution = pm.compute_similarity_for_fixed(product_attr_value, template_attr_value)
elif attr_type == pm.LIST:
contribution = pm.compute_similarity_for_list(product_attr_value, template_attr_value)
elif attr_type == pm.DATE:
contribution = pm.compute_similarity_for_date(product_attr_value, template_attr_value,
context.date_similarity_halflife)
strengths[(product_id, template_id)] += contribution * weight
