2021-05-30 12:55:49 +02:00
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from UserActType import UserActType
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2021-05-17 15:06:42 +02:00
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import os
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import pandas as pd
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import numpy as np
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from NaturalLanguageUnderstanding import NLU
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nlu = NLU()
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rows = 0
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hits = 0
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2021-05-30 12:55:49 +02:00
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hard_hits = 0
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2021-05-17 15:06:42 +02:00
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for file_name in os.listdir('data'):
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df = pd.read_csv(f'data/{file_name}', sep='\t', names=['interlocutor', 'sentence', 'acts'])
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df = df[df.interlocutor == 'user']
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data = np.array(df)
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for row in data:
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2021-05-30 12:55:49 +02:00
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rows += 1
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2021-05-17 15:06:42 +02:00
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sentence = row[1]
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2021-05-30 12:55:49 +02:00
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acts = row[2].split('&')
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user_act = nlu.parse_user_input(sentence)
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for act in acts:
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if str(user_act) == act.strip(' '):
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hard_hits += 1
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for act in acts:
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if act.split('(')[0].strip(' ') == str(user_act).split('(')[0].strip(' '):
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hits += 1
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2021-05-17 15:06:42 +02:00
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2021-05-30 12:55:49 +02:00
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print(f"Accuracy (intent only): {(hits / rows)*100} ({hits}/{rows})")
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print(f"Accuracy (intent with slots): {(hard_hits / rows)*100} ({hard_hits}/{rows})")
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