102 lines
2.7 KiB
Python
102 lines
2.7 KiB
Python
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from itertools import product
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import numpy as np
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import pandas as pd
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import csv
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import id3test
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import pprint
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import sys
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import pandas
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from sklearn import tree
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import pydotplus
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from sklearn.tree import DecisionTreeClassifier
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import matplotlib.pyplot as plt
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import matplotlib.image as pltimg
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# stan pola: toCut, toPlow, toWater, toSeed, toFertilize
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# pora dnia: dzień, noc
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# pogoda: sunny, cloudy, rainy, hail
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# temperatura: freezing, cold, mild, hot
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# wiatr: windless, strong wind, gale
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# humidy: low, high
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field_states = ['toPlow', 'toWater', 'toSeed', 'toFertilize', 'toCut']
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day_time = ['Day', 'Night']
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weather = ['Clear Sky', 'Cloudy', 'Rainy', 'Hail']
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temperature = ['Freezing', 'Cold', 'Mild', 'Hot']
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wind = ['Windless', 'Strong Wind', 'Gale']
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humidy = ['Low', 'High']
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output = list(product(field_states, day_time, weather, temperature, wind, humidy))
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dict = []
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for x in range(len(output)):
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while True:
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mField = output[x][0]
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mDay_time = output[x][1]
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mWeather = output[x][2]
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mTemperature = output[x][3]
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mWind = output[x][4]
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mHumidy = output[x][5]
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mDecision = 'null'
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# pora dnia: dzień 2, noc -2
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# pogoda: sunny+3, cloudy+3, rainy-2, hail-5
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# temperatura: freezing -3, cold-1, mild+4, hot+2
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# wiatr: windless +2, strong wind-1, gale-3
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# humidy: low+2, high-3
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if mDay_time == 'Day':
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valDay_time = 2
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else:
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valDay_time = -3
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if mWeather == 'Sunny' or 'Cloudy':
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valWeather = 3
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elif mWeather == 'Rainy':
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valWeather = -2
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else:
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valWeather = -5
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if mTemperature == 'Freezing':
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valTemperature = -3
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elif mTemperature == 'Cold':
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valTemperature = -1
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elif mTemperature == 'Mild':
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valTemperature = 4
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else:
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valTemperature = 2
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if mWind == 'Windless':
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valWind = +2
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elif mWind == 'Strong Wind':
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valWind = -1
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else:
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valWind = -3
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if humidy == 'Low':
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valHumidy = 2
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else:
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valHumidy = -2
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result = valDay_time + valWeather + valTemperature + valWind + valHumidy
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if result >= 0:
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mDecision = "Make Action"
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else:
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mDecision = "Wait"
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break
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dict.append({'Field': mField, 'Day Time': mDay_time, 'Weather': mWeather,
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'Temperature': mTemperature, 'Wind': mWind, 'Humidy': mHumidy, 'Decision': mDecision})
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fields = ['Field', 'Day Time', 'Weather', 'Temperature', 'Wind', 'Humidy', 'Decision']
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filename = "treedata\\data3.csv"
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with open(filename, 'w') as csvfile:
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writer = csv.DictWriter(csvfile, fieldnames=fields)
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writer.writeheader()
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writer.writerows(dict)
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