decision tree integration fix + end text
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parent
4a9d18f710
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26
src/main.py
26
src/main.py
@ -244,24 +244,24 @@ print(len(check_path_A))
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current_node = 0
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step = 1
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comeback = False
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weather = random.choice(['Sunny', 'Rainy', 'Cloudy'])
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temperature = random.choice(['High', 'Medium', 'Low'])
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windspeed = random.choice(['Strong', 'Weak'])
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pollenavailability = random.choice(['Low', 'Medium', 'High'])
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beepopulation = random.choice(['Low','Moderate', 'High'])
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timeofday = random.choice(['Morning', 'Afternoon', 'Evening'])
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weather = random.choice([2, 1, 0])
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temperature = random.choice([0,1,2])
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windspeed = random.choice([1,0])
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pollenavailability = random.choice([0,1,2])
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beepopulation = random.choice([0,1,2])
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timeofday = random.choice([0,1,2])
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if len(check_path_A)>80:
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flowerdistance = 'Far'
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flowerdistance = 1
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elif len(check_path_A)>50:
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flowerdistance = 'Medium'
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flowerdistance = 2
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else:
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flowerdistance = 'Close'
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humidity = random.choice(['High','Normal'])
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flowerdistance = 0
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humidity = random.choice([1,2])
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predictiondata = [[weather, temperature, windspeed, pollenavailability, beepopulation, timeofday, flowerdistance, humidity]]
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feature_cols = ['Weather','Temperature','WindSpeed','PollenAvailability','BeePopulation','TimeOfDay','FlowerDistance','Humidity']
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le = LabelEncoder()
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le.fit(feature_cols)
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encoded_data = pd.DataFrame(predictiondata, columns=feature_cols).apply(le.fit_transform)
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encoded_data = pd.DataFrame(predictiondata, columns=feature_cols)
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prediction = clf.predict(encoded_data)
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font = pygame.font.Font(None,32)
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while True:
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@ -312,6 +312,10 @@ while True:
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current_node = 0
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comeback = True
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elif current_node + 1 == len(path):
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endtext = font.render('ДЕЛО СДЕЛАНО', True, (255,0,0))
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endtext_rect = endtext.get_rect(center=(disX // 2, disY // 2))
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dis.blit(endtext, endtext_rect)
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pygame.display.update()
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pygame.time.wait(1000000)
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if(step == -1 and current_node == 0):
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step *= -1
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