def rate_meals(self):
"""Handles meal rating procedure"""
# If only one user is given then query must be altered a bit, otherwise it will throw an error
query_filter = f"IN {self.users}" if len(
self.users) > 1 else f"= '{self.users[0]}'"
# Get data about user AHP preferences
query_ahp_pref = f"SELECT users.name, ahp_pref_name, value FROM users INNER JOIN user_ahp_pref ON users.id=user_ahp_pref.user_id WHERE users.name {query_filter}"
result_ahp_pref = pd.read_sql_query(
query_ahp_pref, self.database).set_index(['name', 'ahp_pref_name'])
# Get data about user other preferences
query_pref = f"SELECT users.name, type_name, subtype, value FROM users INNER JOIN user_pref ON users.id=user_pref.user_id WHERE users.name {query_filter}"
result_pref = pd.read_sql_query(query_pref, self.database).set_index(
['name', 'type_name', 'subtype'])
result_pref = result_pref.sort_index()
# Calculate meal rating for each user
self.meals['Rating'] = 0
user_ratings = []
for user in self.users:
user_raw_preferences = result_ahp_pref.loc[
user, 'typ-kuchnia']['value'], result_ahp_pref.loc[
user, 'kuchnia-smak']['value'], result_ahp_pref.loc[
user, 'typ-smak']['value']
user_AHP = AHP(*user_raw_preferences)
user_preferences = user_AHP.get_preferences(
) # [typ, kuchnia, smak]
# Prepare Data Frame for user rating calculations
user_meals_rating = self.meals.loc[:, ('name', 'Rating')].copy()
user_meals_rating['type_rating'] = 0
user_meals_rating['kitchen_rating'] = 0
user_meals_rating['taste_rating'] = 0
# Calculate score for meal taste
tastes_list = list(result_pref.loc[user, 'smak'].index)
for taste in tastes_list:
user_meals_rating['taste_rating'] += self.meals[
taste] * result_pref.loc[user, 'smak', taste].value
# Calculate score for meal type
types_list = list(result_pref.loc[user, 'typ'].index)
for type_ in types_list:
user_meals_rating['type_rating'] += self.meals[
type_] * result_pref.loc[user, 'typ', type_].value
# Calculate score for meal kitchen
kitchens_list = list(result_pref.loc[user, 'kuchnia'].index)
for kitchen in kitchens_list:
user_meals_rating['kitchen_rating'] += self.meals[
kitchen] * result_pref.loc[user, 'kuchnia', kitchen].value
# Sum scores
for i, rating in zip(range(
0, 3), ['type_rating', 'kitchen_rating', 'taste_rating']):
user_meals_rating['Rating'] += user_meals_rating[
rating] * user_preferences[i]
user_ratings.append(user_meals_rating)
weight_sum = 0
for weight, rating in zip(self.weights, user_ratings):
weight_sum += weight
self.meals['Rating'] += rating['Rating'] * weight
self.meals['Rating'] = self.meals['Rating'] / weight_sum
self.meals_rated = self.meals.loc[:, ('name', 'Rating')].sort_values(
by='Rating', ascending=False)
return self.meals_rated
def test_computes_correct_priority_matrix_for_charisma(alts, crits, goal):
decider = AHP(alternatives=alts, criterias=crits, goal=goal)
# Charisma
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=2,
multiple=5)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=2,
multiple=9)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=2,
multiple=4)
np.testing.assert_array_equal(
decider.crit_mat[2], [[1, 5, 9], [1 / 5, 1, 4], [1 / 9, 1 / 4, 1]])
def test_computes_correct_priority_matrix_for_age(alts, crits, goal):
decider = AHP(alternatives=alts, criterias=crits, goal=goal)
# Age
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=3,
multiple=1 / 3)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=3,
multiple=5)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=3,
multiple=9)
np.testing.assert_array_equal(
decider.crit_mat[3], [[1, 1 / 3, 5], [3, 1, 9], [1 / 5, 1 / 9, 1]])
def test_computes_correct_priority_matrix_for_experience(alts, crits, goal):
decider = AHP(alternatives=alts, criterias=crits, goal=goal)
# Experience
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=0,
multiple=1 / 4)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=0,
multiple=4)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=0,
multiple=9)
np.testing.assert_array_equal(
decider.crit_mat[0], [[1, 1 / 4, 4], [4, 1, 9], [1 / 4, 1 / 9, 1]])
def test_computes_correct_priority_matrix_for_education(alts, crits, goal):
decider = AHP(alternatives=alts, criterias=crits, goal=goal)
# Education
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=1,
multiple=3)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=1,
multiple=1 / 5)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=1,
multiple=1 / 7)
np.testing.assert_array_equal(
decider.crit_mat[1], [[1, 3, 1 / 5], [1 / 3, 1, 1 / 7], [5, 7, 1]])
def ahp():
"""
前端传过来的参数
{
"tableName": firstLayer,
"l1Matrix": ［］,
"l2Matrix": ［］
}
:return:
"""
log_file = "algorithm.log"
logging.basicConfig(filename=log_file,
format="%(asctime)s [ %(levelname)-6s ] %(message)s",
level='INFO')
try:
from ahp import AHP
request_data = request.json
tableName = request_data["tableName"]
l1 = request_data.get("l1Matrix")
l2 = request_data.get("l2Matrix")
l1_factors, l2_factors = len(l1[0]), len(l2[0])
if not l1:
print("read the first layer Matrix fail, please check")
return
if l1_factors != len(l2):
print("the second layer's Matrix Number not equal the first layer Factors")
return
l1_Weight = []
for mat in l1:
a = AHP(mat)
w = a.get_Weight()
l1_Weight.append(w)
l2_Weight = []
for mat in l2:
a = AHP(mat)
w = a.get_Weight()
l2_Weight.append(w)
score = np.dot(np.array(l2_Weight).T, np.array(l1_Weight).T)
print("ok")
except NotImplementedError as e:
raise e
response_data = {"res": score,
"code": "200",
"msg": "ok!"}
return jsonify(response_data)
from ahp import AHP
if __name__ == "__main__":
ASK_QUESTIONS = False
# Main objective/goal to be achieved
goal = "Deciding where to eat"
# The alternatives (final decisions)
alternatives = ["Pizza Hut", "Domino's"]
# The criterias to judge the alternatives
criterias = ["Distance", "Price", "Cuisine"]
ahp_decider = AHP(alternatives, criterias, goal)
if ASK_QUESTIONS:
# Baseline prioritisation walk through (prints out questions in terminal)
ahp_decider.prioritise()
else:
# Add your prioritisations
ahp_decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=0,
multiple=5)
ahp_decider.compare_criterias_wrt_goal(criterias=(1, 2), multiple=5)
pass
# Returns the index of alternatives array
# that is the best result (based on the
# prior comparisons made)
result = ahp_decider.decide()
def test_computes_correct_priority_matrix_for_goal(alts, crits, goal):
decider = AHP(alternatives=alts, criterias=crits, goal=goal)
# Criterias vs goal
decider.compare_criterias_wrt_goal(criterias=(0, 1), multiple=4)
decider.compare_criterias_wrt_goal(criterias=(0, 2), multiple=3)
decider.compare_criterias_wrt_goal(criterias=(0, 3), multiple=7)
decider.compare_criterias_wrt_goal(criterias=(1, 2), multiple=1 / 3)
decider.compare_criterias_wrt_goal(criterias=(1, 3), multiple=3)
decider.compare_criterias_wrt_goal(criterias=(3, 2), multiple=1 / 5)
np.testing.assert_array_equal(decider.goal_mat,
[[1, 4, 3, 7], [1 / 4, 1, 1 / 3, 3],
[1 / 3, 3, 1, 5], [1 / 7, 1 / 3, 1 / 5, 1]])
def test_computes_correct_priority_vecs(alts, crits, goal):
decider = AHP(alternatives=alts, criterias=crits, goal=goal)
# Experience
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=0,
multiple=1 / 4)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=0,
multiple=4)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=0,
multiple=9)
# Education
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=1,
multiple=3)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=1,
multiple=1 / 5)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=1,
multiple=1 / 7)
# Charisma
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=2,
multiple=5)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=2,
multiple=9)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=2,
multiple=4)
# Age
decider.compare_alternatives_wrt_criteria(alternatives=(0, 1),
criteria=3,
multiple=1 / 3)
decider.compare_alternatives_wrt_criteria(alternatives=(0, 2),
criteria=3,
multiple=5)
decider.compare_alternatives_wrt_criteria(alternatives=(1, 2),
criteria=3,
multiple=9)
# Criterias vs goal
decider.compare_criterias_wrt_goal(criterias=(0, 1), multiple=4)
decider.compare_criterias_wrt_goal(criterias=(0, 2), multiple=3)
decider.compare_criterias_wrt_goal(criterias=(0, 3), multiple=7)
decider.compare_criterias_wrt_goal(criterias=(1, 2), multiple=1 / 3)
decider.compare_criterias_wrt_goal(criterias=(1, 3), multiple=3)
decider.compare_criterias_wrt_goal(criterias=(3, 2), multiple=1 / 5)
assert decider.decide() == 1
def start_ahp(self, data):
ahp = AHP(data)
return ahp.start()
def decide(
name: str,
goal: str,
alternatives: List[str],
save: bool = Option(default=False,
help="Saves Decision problem graph as pdf file")):
print("save=", save)
global dp
dp = AHP(goal=goal, alternatives=alternatives)
dp.input_values()
print("**********************")
print("result = ", dp.decide())
print("**********************")
if save:
dp.draw()
dp.draw_result()
dp.view(filename="graph")
from ahp import AHP
example = AHP(method='',
precision=3,
alternatives=['Tom', 'Dick', 'Harry'],
criteria=['Experiência', 'Educação', 'Carisma', 'Idade'],
sub_criteria={},
matrix={
'Experiência': [[1, 1 / 4, 4], [4, 1, 9], [1 / 4, 1 / 9, 1]],
'Educação': [[1, 3, 1 / 5], [1 / 3, 1, 1 / 7], [5, 7, 1]],
'Carisma': [[1, 5, 9], [1 / 5, 1, 4], [1 / 9, 1 / 4, 1]],
'Idade': [[1, 1 / 3, 5], [3, 1, 9], [1 / 5, 1 / 9, 1]],
'criterios': [[1, 4, 3, 7], [1 / 4, 1, 1 / 3, 3],
[1 / 3, 3, 1, 5], [1 / 7, 1 / 3, 1 / 5, 1]]
},
log=True)
example.local_priorities()