154 lines
5.0 KiB
Python
154 lines
5.0 KiB
Python
from sklearn import tree
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import collections
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import subprocess
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class TreeClass:
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#file = open("probne.pl", 'r').read()
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#text = ""
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#for line in file:
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# text += line
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#com = file.replace("\n", "").split(".")
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#for i, el in enumerate(com):
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# com[i]=el+"."
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#com.pop()
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#features = {"key1": 4,
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# "key2": [4, 6],
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# "key3": {"k": [ 1, 4]}}
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#features["key4"] = [1, 4, 3]
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#features.update({"key5": "text"})
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#symbol, is_alive, ttl, hydration, soil_level, ready
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#print(com)
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def make_tree(self, plant, pl_stats):
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features = [[0, True, 60, 90, 95],
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[0, True, 60, 84, 88],
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[0, True, 50, 78, 77],
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[0, True, 45, 63, 68],
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[0, True, 37, 54, 59],
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[0, True, 20, 31, 62],
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[0, True, 18, 75, 39],
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[0, True, 19, 24, 74],
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[0, True, 24, 69, 25],
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[0, True, 15, 45, 85],
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[0, True, 23, 85, 48],
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[0, True, 26, 41, 45],
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[0, True, 21, 35, 32],
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[0, True, 49, 24, 28],
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[0, True, 64, 15, 14],
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[0, True, 84, 4, 8],
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[1, True, 55, 89, 84],
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[1, True, 76, 91, 95],
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[1, True, 45, 72, 71],
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[1, True, 37, 64, 68],
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[1, True, 26, 54, 59],
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[1, True, 58, 42, 46],
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[1, True, 20, 31, 62],
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[1, True, 18, 75, 39],
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[1, True, 19, 24, 74],
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[1, True, 24, 69, 25],
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[1, True, 15, 12, 85],
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[1, True, 23, 85, 18],
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[1, True, 34, 38, 36],
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[1, True, 41, 24, 22],
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[1, True, 34, 38, 36],
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[1, True, 74, 26, 23],
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[1, True, 84, 14, 19],
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[1, True, 95, 7, 4]
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]
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labels = [0, 0, 0, 0, 0, 1, 2, 1, 2, 1, 2, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 1, 2, 1, 2, 1, 2, 3, 3, 3, 3, 3, 3]
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#utwórz drzewo decyzyjne
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t = tree.DecisionTreeClassifier()
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#znajdź wzór na podstawie danych
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t = t.fit(features, labels)#jakieś cechy w środku i decyzje jakie ma podjąć
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#użyj modelu aby dopasować(podjąć decyzję)
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#p = tree.predict([["Cucumber", True, 38, 26, 51]])
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p = t.predict([pl_stats[0], pl_stats[1]], pl_stats[2], pl_stats[3], pl_stats[4])
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if p == 0:
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print("Ready to cut")
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t.Harvest()
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elif p == 1:
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plant.increase_hydration(plant.max_hydration_lvl - plant.hydration)
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elif p == 2:
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plant.increase_soillevel(plant.max_soil_lvl - plant.soil_level)
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elif p == 3:
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plant.increase_hydration(plant.max_hydration_lvl - plant.hydration)
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plant.increase_soillevel(plant.max_soil_lvl - plant.soil_level)
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#wyświetlamy dopasowaną wartość
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print(p)
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T = TreeClass()
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#pass
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"""
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is_life = bool
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type = "POop"
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Timer = 20
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hydration = (0,40)
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soil_level = (0,40)
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water_tank = (0,200)
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soil_tank = (0,100)
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def Harvest():
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pass
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def increase_soil_level():
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pass
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def increase_hydration():
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pass
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if is_life == False:
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print("Roślina uschła")
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else:
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if type == 'P' or type == "O":
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if Timer == 0:
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print("Warzywa nie nadają się już do zbioru")
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elif Timer > 0 and Timer <= 20:
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Harvest()#Zbierz plon
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elif type == 'p':
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if hydration > 20 and soil_level > 20:
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type == 'P'#zmiana literki
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#if Timer == 0:
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# print("Warzywa nie nadają się do zbioru")
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#elif Timer > 0 and Timer <= 20:
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# Harvest()#Zbierz plon
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elif hydration > 20 and (soil_level > 0 and soil_level <= 20):
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if soil_tank > 0:
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increase_soil_level()
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elif (hydration > 0 and hydration <= 20) and soil_level > 20:
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if water_tank > 0:
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increase_hydration()
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elif (hydration > 0 and hydration <= 20) and (soil_level > 0 and soil_level <= 20):
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if water_tank > 0 and soil_tank > 0:
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increase_hydration()
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increase_soil_level()
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elif type == 'o':
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if hydration > 30 and soil_level > 30:
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type == 'O'#zmiana literki
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#if Timer == 0:
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# print("Warzywa nie nadają się do zbioru")
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#elif Timer > 0 and Timer <= 20:
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# Harvest()#Zbierz plon
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elif hydration > 30 and (soil_level > 0 and soil_level <= 30):
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if soil_tank > 0:
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increase_soil_level()
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elif (hydration > 0 and hydration <= 30) and soil_level > 20:
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if water_tank > 0:
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increase_hydration()
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elif (hydration > 0 and hydration <= 30) and (soil_level > 0 and soil_level <= 30):
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if water_tank > 0 and soil_tank > 0:
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increase_hydration()
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increase_soil_level()
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"""
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