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import math
import re
def calculate_score_fullscale(docs, results):
reference = eval(docs["reference_answer_fullscale"])
user = dict(re.findall(r"(\w+):\s+(\d+)", results[0]))
# First check that the emotions specified in the answer match those in the reference
if len(user.items()) != 4:
# print('! Error: 4 emotions were not returned')
# print(user)
return {"eqbench": 0, "percent_parseable": 0}
emotions_dict = {}
for emotion, user_emotion_score in user.items():
for i in range(1, 5):
if emotion == reference[f"emotion{i}"]:
emotions_dict[emotion] = True
if len(emotions_dict) != 4:
print("! Error: emotions did not match reference")
print(user)
return {"eqbench": 0, "percent_parseable": 0}
difference_tally = (
0 # Tally of differerence from reference answers for this question
)
# Iterate over each emotion in the user's answers.
for emotion, user_emotion_score in user.items():
# If this emotion is in the reference, calculate the difference between the user's score and the reference score.
for i in range(1, 5):
if emotion == reference[f"emotion{i}"]:
d = abs(
float(user_emotion_score) - float(reference[f"emotion{i}_score"])
)
# this will be a value between 0 and 10
if d == 0:
scaled_difference = 0
elif d <= 5:
# S-shaped scaling function
# https://www.desmos.com/calculator
# 6.5\cdot\ \frac{1}{\left(1\ +\ e^{\left(-1.2\cdot\left(x-4\right)\right)}\right)}
scaled_difference = 6.5 * (1 / (1 + math.e ** (-1.2 * (d - 4))))
else:
scaled_difference = d
difference_tally += scaled_difference
# Inverting the difference tally so that the closer the answer is to reference, the higher the score.
# The adjustment constant is chosen such that answering randomly produces a score of zero.
adjust_const = 0.7477
final_score = 10 - (difference_tally * adjust_const)
final_score_percent = final_score * 10
return {"eqbench": final_score_percent, "percent_parseable": 100}
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