New Tree
This commit is contained in:
parent
c7e6433445
commit
ad33c1f01a
425
Tree1.py
Normal file
425
Tree1.py
Normal file
@ -0,0 +1,425 @@
|
||||
|
||||
from sklearn import tree
|
||||
|
||||
class TreeClass:
|
||||
#file = open("probne.pl", 'r').read()
|
||||
#text = ""
|
||||
#for line in file:
|
||||
# text += line
|
||||
|
||||
|
||||
#com = file.replace("\n", "").split(".")
|
||||
#for i, el in enumerate(com):
|
||||
# com[i]=el+"."
|
||||
#com.pop()
|
||||
|
||||
|
||||
#features = {"key1": 4,
|
||||
# "key2": [4, 6],
|
||||
# "key3": {"k": [ 1, 4]}}
|
||||
|
||||
#features["key4"] = [1, 4, 3]
|
||||
#features.update({"key5": "text"})
|
||||
|
||||
#symbol, is_alive, ttl, hydration, soil_level, ready
|
||||
|
||||
#print(com)
|
||||
|
||||
def make_tree(self, plant, pl_stats):
|
||||
|
||||
features = [
|
||||
[1, True, 199, 900, 950],
|
||||
[1, True, 150, 840, 880],
|
||||
[1, True, 149, 780, 770],
|
||||
[1, True, 133, 630, 680],
|
||||
[1, True, 125, 555, 567],
|
||||
[1, True, 112, 920, 834],
|
||||
[1, True, 173, 947, 736],
|
||||
[1, True, 143, 934, 642],
|
||||
[1, True, 126, 928, 521],
|
||||
[1, True, 136, 842, 756],
|
||||
[1, True, 174, 860, 641],
|
||||
[1, True, 186, 826, 531],
|
||||
[1, True, 163, 769, 695],
|
||||
[1, True, 176, 728, 543],
|
||||
[1, True, 146, 684, 528],
|
||||
[1, True, 158, 853, 964],
|
||||
[1, True, 176, 746, 935],
|
||||
[1, True, 169, 661, 961],
|
||||
[1, True, 129, 584, 935],
|
||||
[1, True, 187, 755, 812],
|
||||
[1, True, 194, 642, 836],
|
||||
[1, True, 173, 583, 861],
|
||||
[1, True, 115, 628, 716],
|
||||
[1, True, 123, 592, 756],
|
||||
[1, True, 165, 584, 614],
|
||||
|
||||
[1, True, 3800, 450, 941],
|
||||
[1, True, 290, 340, 958],
|
||||
[1, True, 240, 290, 914],
|
||||
[1, True, 350, 140, 980],
|
||||
[1, True, 451, 68, 926],
|
||||
[1, True, 230, 479, 856],
|
||||
[1, True, 260, 310, 824],
|
||||
[1, True, 568, 256, 834],
|
||||
[1, True, 427, 149, 873],
|
||||
[1, True, 237, 46, 831],
|
||||
[1, True, 341, 416, 784],
|
||||
[1, True, 413, 369, 716],
|
||||
[1, True, 689, 251, 761],
|
||||
[1, True, 746, 183, 743],
|
||||
[1, True, 856, 45, 736],
|
||||
[1, True, 652, 415, 641],
|
||||
[1, True, 931, 346, 694],
|
||||
[1, True, 347, 258, 623],
|
||||
[1, True, 248, 149, 684],
|
||||
[1, True, 354, 24, 617],
|
||||
[1, True, 619, 416, 518],
|
||||
[1, True, 746, 352, 585],
|
||||
[1, True, 456, 271, 544],
|
||||
[1, True, 746, 164, 572],
|
||||
[1, True, 620, 38, 565],
|
||||
|
||||
[1, True, 321, 920, 412],
|
||||
[1, True, 520, 935, 348],
|
||||
[1, True, 364, 961, 259],
|
||||
[1, True, 206, 946, 148],
|
||||
[1, True, 402, 916, 62],
|
||||
[1, True, 660, 850, 461],
|
||||
[1, True, 542, 827, 320],
|
||||
[1, True, 490, 886, 280],
|
||||
[1, True, 640, 851, 140],
|
||||
[1, True, 840, 867, 80],
|
||||
[1, True, 746, 716, 486],
|
||||
[1, True, 142, 769, 364],
|
||||
[1, True, 246, 784, 249],
|
||||
[1, True, 368, 751, 165],
|
||||
[1, True, 6789, 755, 16],
|
||||
[1, True, 1203, 649, 426],
|
||||
[1, True, 924, 685, 310],
|
||||
[1, True, 864, 694, 267],
|
||||
[1, True, 592, 628, 128],
|
||||
[1, True, 482, 673, 38],
|
||||
[1, True, 235, 542, 461],
|
||||
[1, True, 357, 549, 364],
|
||||
[1, True, 751, 502, 288],
|
||||
[1, True, 1452, 589, 176],
|
||||
[1, True, 845, 516, 67],
|
||||
|
||||
[1, True, 37812, 489, 468],
|
||||
[1, True, 3728, 387, 328],
|
||||
[1, True, 1934, 234, 264],
|
||||
[1, True, 13562, 149, 168],
|
||||
[1, True, 698, 84, 61],
|
||||
[1, True, 1789, 475, 386],
|
||||
[1, True, 201, 425, 235],
|
||||
[1, True, 358, 467, 147],
|
||||
[1, True, 942, 491, 37],
|
||||
[1, True, 1056, 367, 241],
|
||||
[1, True, 846, 352, 130],
|
||||
[1, True, 754, 312, 75],
|
||||
[1, True, 564, 210, 138],
|
||||
[1, True, 416, 289, 62],
|
||||
[1, True, 256, 139, 67],
|
||||
[1, True, 1365, 371, 492],
|
||||
[1, True, 954, 254, 452],
|
||||
[1, True, 821, 185, 449],
|
||||
[1, True, 564, 76, 421],
|
||||
[1, True, 648, 276, 305],
|
||||
[1, True, 246, 123, 368],
|
||||
[1, True, 461, 43, 378],
|
||||
[1, True, 368, 185, 249],
|
||||
[1, True, 597, 54, 294],
|
||||
[1, True, 694, 73, 165],
|
||||
|
||||
[1, True, 1454, 948, 921],
|
||||
[1, True, 1888, 838, 868],
|
||||
[1, True, 1126, 741, 756],
|
||||
[1, True, 895, 634, 627],
|
||||
[1, True, 738, 565, 528],
|
||||
[1, True, 814, 974, 842],
|
||||
[1, True, 1413, 961, 751],
|
||||
[1, True, 3628, 958, 657],
|
||||
[1, True, 364, 948, 556],
|
||||
[1, True, 6729, 863, 748],
|
||||
[1, True, 258, 854, 618],
|
||||
[1, True, 352, 814, 550],
|
||||
[1, True, 37822, 779, 670],
|
||||
[1, True, 4315, 752, 546],
|
||||
[1, True, 288, 635, 558],
|
||||
[1, True, 384, 857, 943],
|
||||
[1, True, 476, 741, 938],
|
||||
[1, True, 376, 638, 976],
|
||||
[1, True, 228, 534, 936],
|
||||
[1, True, 534, 749, 855],
|
||||
[1, True, 684, 651, 835],
|
||||
[1, True, 854, 536, 827],
|
||||
[1, True, 1526, 628, 756],
|
||||
[1, True, 924, 524, 712],
|
||||
[1, True, 846, 514, 638],
|
||||
[1, True, 1872, 547, 501],
|
||||
|
||||
[1, False, 6789, 672, 405],
|
||||
[1, False, 37812, 589, 420],
|
||||
[1, False, 3728, 890, 778],
|
||||
[1, False, 799, 734, 634],
|
||||
[1, False, 799, 734, 634],
|
||||
[1, False, 799, 734, 634],
|
||||
|
||||
[0, True, 134, 910, 950],
|
||||
[0, True, 254, 890, 840],
|
||||
[0, True, 124, 763, 746],
|
||||
[0, True, 168, 667, 641],
|
||||
[0, True, 148, 546, 531],
|
||||
[0, True, 261, 916, 843],
|
||||
[0, True, 284, 951, 762],
|
||||
[0, True, 256, 922, 610],
|
||||
[0, True, 123, 956, 552],
|
||||
[0, True, 87, 840, 781],
|
||||
[0, True, 189, 820, 690],
|
||||
[0, True, 222, 813, 560],
|
||||
[0, True, 168, 746, 635],
|
||||
[0, True, 234, 768, 523],
|
||||
[0, True, 155, 624, 516],
|
||||
[0, True, 278, 846, 962],
|
||||
[0, True, 226, 769, 931],
|
||||
[0, True, 184, 647, 951],
|
||||
[0, True, 124, 563, 947],
|
||||
[0, True, 156, 761, 854],
|
||||
[0, True, 178, 632, 846],
|
||||
[0, True, 98, 589, 812],
|
||||
[0, True, 134, 658, 715],
|
||||
[0, True, 169, 528, 762],
|
||||
[0, True, 234, 553, 674],
|
||||
|
||||
[0, True, 300, 450, 920],
|
||||
[0, True, 4580, 350, 961],
|
||||
[0, True, 1290, 240, 923],
|
||||
[0, True, 340, 170, 974],
|
||||
[0, True, 7650, 28, 945],
|
||||
[0, True, 3455, 429, 801],
|
||||
[0, True, 684, 358, 826],
|
||||
[0, True, 569, 214, 836],
|
||||
[0, True, 469, 148, 853],
|
||||
[0, True, 396, 61, 816],
|
||||
[0, True, 769, 462, 756],
|
||||
[0, True, 1584, 367, 761],
|
||||
[0, True, 648, 231, 752],
|
||||
[0, True, 1147, 182, 726],
|
||||
[0, True, 685, 58, 795],
|
||||
[0, True, 596, 486, 634],
|
||||
[0, True, 1462, 368, 614],
|
||||
[0, True, 1062, 245, 658],
|
||||
[0, True, 482, 156, 674],
|
||||
[0, True, 584, 84, 623],
|
||||
[0, True, 469, 421, 574],
|
||||
[0, True, 657, 345, 563],
|
||||
[0, True, 846, 215, 587],
|
||||
[0, True, 769, 156, 532],
|
||||
[0, True, 845, 34, 542],
|
||||
|
||||
[0, True, 358, 941, 468],
|
||||
[0, True, 1354, 932, 394],
|
||||
[0, True, 458, 954, 265],
|
||||
[0, True, 369, 914, 178],
|
||||
[0, True, 946, 954, 62],
|
||||
[0, True, 746, 821, 428],
|
||||
[0, True, 340, 880, 360],
|
||||
[0, True, 410, 812, 220],
|
||||
[0, True, 386, 856, 148],
|
||||
[0, True, 589, 816, 75],
|
||||
[0, True, 950, 765, 420],
|
||||
[0, True, 869, 715, 362],
|
||||
[0, True, 1304, 763, 296],
|
||||
[0, True, 746, 736, 162],
|
||||
[0, True, 684, 712, 84],
|
||||
[0, True, 935, 622, 413],
|
||||
[0, True, 3040, 680, 360],
|
||||
[0, True, 840, 601, 280],
|
||||
[0, True, 765, 682, 164],
|
||||
[0, True, 568, 624, 72],
|
||||
[0, True, 485, 563, 426],
|
||||
[0, True, 385, 531, 368],
|
||||
[0, True, 934, 546, 235],
|
||||
[0, True, 312, 574, 163],
|
||||
[0, True, 468, 513, 63],
|
||||
|
||||
[0, True, 1024, 536, 542],
|
||||
[0, True, 478, 468, 413],
|
||||
[0, True, 369, 345, 368],
|
||||
[0, True, 562, 248, 267],
|
||||
[0, True, 836, 186, 148],
|
||||
[0, True, 745, 54, 36],
|
||||
[0, True, 3400, 550, 460],
|
||||
[0, True, 562, 532, 368],
|
||||
[0, True, 765, 589, 241],
|
||||
[0, True, 1628, 518, 160],
|
||||
[0, True, 740, 560, 49],
|
||||
[0, True, 698, 415, 345],
|
||||
[0, True, 528, 464, 231],
|
||||
[0, True, 694, 432, 184],
|
||||
[0, True, 746, 413, 46],
|
||||
[0, True, 340, 380, 260],
|
||||
[0, True, 840, 300, 190],
|
||||
[0, True, 740, 360, 35],
|
||||
[0, True, 489, 232, 154],
|
||||
[0, True, 568, 254, 63],
|
||||
[0, True, 950, 189, 92],
|
||||
[0, True, 368, 436, 584],
|
||||
[0, True, 465, 381, 523],
|
||||
[0, True, 649, 225, 548],
|
||||
[0, True, 968, 145, 568],
|
||||
[0, True, 1205, 29, 519],
|
||||
[0, True, 382, 365, 492],
|
||||
[0, True, 594, 237, 459],
|
||||
[0, True, 846, 164, 425],
|
||||
[0, True, 715, 56, 445],
|
||||
[0, True, 1306, 284, 364],
|
||||
[0, True, 563, 134, 385],
|
||||
[0, True, 469, 72, 318],
|
||||
[0, True, 746, 164, 296],
|
||||
[0, True, 528, 64, 205],
|
||||
[0, True, 674, 58, 169],
|
||||
|
||||
[0, True, 1524, 924, 938],
|
||||
[0, True, 1892, 896, 865],
|
||||
[0, True, 1246, 736, 762],
|
||||
[0, True, 895, 648, 623],
|
||||
[0, True, 726, 537, 584],
|
||||
[0, True, 648, 934, 864],
|
||||
[0, True, 1423, 922, 746],
|
||||
[0, True, 3728, 987, 678],
|
||||
[0, True, 458, 934, 514],
|
||||
[0, True, 6789, 855, 759],
|
||||
[0, True, 254, 843, 628],
|
||||
[0, True, 367, 865, 564],
|
||||
[0, True, 37812, 789, 668],
|
||||
[0, True, 4365, 769, 534],
|
||||
[0, True, 299, 630, 555],
|
||||
[0, True, 368, 852, 937],
|
||||
[0, True, 468, 716, 925],
|
||||
[0, True, 374, 648, 986],
|
||||
[0, True, 216, 526, 925],
|
||||
[0, True, 528, 746, 851],
|
||||
[0, True, 648, 632, 816],
|
||||
[0, True, 846, 528, 853],
|
||||
[0, True, 1506, 648, 731],
|
||||
[0, True, 954, 520, 749],
|
||||
[0, True, 846, 543, 616],
|
||||
[0, True, 1892, 532, 500],
|
||||
|
||||
[0, False, 190, 240, 740],
|
||||
[0, False, 240, 690, 250],
|
||||
[0, False, 150, 120, 850],
|
||||
[0, False, 230, 850, 180],
|
||||
[0, False, 2345, 21, 342],
|
||||
[0, False, 2561, 244, 532]
|
||||
]
|
||||
|
||||
labels = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
|
||||
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
|
||||
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
|
||||
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
|
||||
5, 5, 5, 5, 5, 5,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
|
||||
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
|
||||
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
|
||||
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
|
||||
5, 5, 5, 5, 5, 5]
|
||||
#utwórz drzewo decyzyjne
|
||||
t = tree.DecisionTreeClassifier()
|
||||
|
||||
#znajdź wzór na podstawie danych
|
||||
t = t.fit(features, labels)#jakieś cechy w środku i decyzje jakie ma podjąć
|
||||
|
||||
#użyj modelu aby dopasować(podjąć decyzję)
|
||||
#p = tree.predict([["Cucumber", True, 38, 26, 51]])
|
||||
p = t.predict([[pl_stats["name"], pl_stats["is_alive"], pl_stats["ttl"], pl_stats["hydration"], pl_stats["soil_level"]]])
|
||||
|
||||
return p
|
||||
|
||||
#file = open("features.txt", 'r').read()
|
||||
#com = file.split("\n")
|
||||
#print(com)
|
||||
|
||||
#for i, el in enumerate(com):
|
||||
# com[i]=el+"."
|
||||
|
||||
# if p == 0:
|
||||
# print("Ready to cut")
|
||||
# return 0
|
||||
# # t.Harvest()
|
||||
# elif p == 1:
|
||||
# plant.increase_hydration(plant.max_hydration_lvl - plant.hydration)
|
||||
# elif p == 2:
|
||||
# plant.increase_soillevel(plant.max_soil_lvl - plant.soil_level)
|
||||
# elif p == 3:
|
||||
# plant.increase_hydration(plant.max_hydration_lvl - plant.hydration)
|
||||
# plant.increase_soillevel(plant.max_soil_lvl - plant.soil_level)
|
||||
|
||||
#wyświetlamy dopasowaną wartość
|
||||
# print(p)
|
||||
|
||||
T = TreeClass()
|
||||
|
||||
#pass
|
||||
"""
|
||||
is_life = bool
|
||||
type = "POop"
|
||||
Timer = 20
|
||||
hydration = (0,40)
|
||||
soil_level = (0,40)
|
||||
water_tank = (0,200)
|
||||
soil_tank = (0,100)
|
||||
def Harvest():
|
||||
pass
|
||||
def increase_soil_level():
|
||||
pass
|
||||
def increase_hydration():
|
||||
pass
|
||||
|
||||
if is_life == False:
|
||||
print("Roślina uschła")
|
||||
else:
|
||||
if type == 'P' or type == "O":
|
||||
if Timer == 0:
|
||||
print("Warzywa nie nadają się już do zbioru")
|
||||
elif Timer > 0 and Timer <= 20:
|
||||
Harvest()#Zbierz plon
|
||||
elif type == 'p':
|
||||
if hydration > 20 and soil_level > 20:
|
||||
type == 'P'#zmiana literki
|
||||
#if Timer == 0:
|
||||
# print("Warzywa nie nadają się do zbioru")
|
||||
#elif Timer > 0 and Timer <= 20:
|
||||
# Harvest()#Zbierz plon
|
||||
elif hydration > 20 and (soil_level > 0 and soil_level <= 20):
|
||||
if soil_tank > 0:
|
||||
increase_soil_level()
|
||||
elif (hydration > 0 and hydration <= 20) and soil_level > 20:
|
||||
if water_tank > 0:
|
||||
increase_hydration()
|
||||
elif (hydration > 0 and hydration <= 20) and (soil_level > 0 and soil_level <= 20):
|
||||
if water_tank > 0 and soil_tank > 0:
|
||||
increase_hydration()
|
||||
increase_soil_level()
|
||||
elif type == 'o':
|
||||
if hydration > 30 and soil_level > 30:
|
||||
type == 'O'#zmiana literki
|
||||
#if Timer == 0:
|
||||
# print("Warzywa nie nadają się do zbioru")
|
||||
#elif Timer > 0 and Timer <= 20:
|
||||
# Harvest()#Zbierz plon
|
||||
elif hydration > 30 and (soil_level > 0 and soil_level <= 30):
|
||||
if soil_tank > 0:
|
||||
increase_soil_level()
|
||||
elif (hydration > 0 and hydration <= 30) and soil_level > 20:
|
||||
if water_tank > 0:
|
||||
increase_hydration()
|
||||
elif (hydration > 0 and hydration <= 30) and (soil_level > 0 and soil_level <= 30):
|
||||
if water_tank > 0 and soil_tank > 0:
|
||||
increase_hydration()
|
||||
increase_soil_level()
|
||||
"""
|
||||
Loading…
Reference in New Issue
Block a user