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Merge branch 'master' into genetic_algorithm

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This commit is contained in:
Kacper Kalinowski 2022-06-10 11:20:51 +02:00
commit 03f983f35b
9 changed files with 270 additions and 88 deletions
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0
data_structures/__init__.py Normal file
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94
decision_tree/tree_as_txt.txt
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@ -1,3 +1,96 @@
<<<<<<< HEAD
|--- feature_2 <= 3.50
| |--- feature_4 <= 3.50
| | |--- feature_0 <= 1.50
| | | |--- class: 0
| | |--- feature_0 > 1.50
| | | |--- feature_3 <= 3.50
| | | | |--- feature_4 <= 2.50
| | | | | |--- class: 1
| | | | |--- feature_4 > 2.50
| | | | | |--- feature_2 <= 2.50
| | | | | | |--- class: 1
| | | | | |--- feature_2 > 2.50
| | | | | | |--- class: 0
| | | |--- feature_3 > 3.50
| | | | |--- feature_3 <= 4.50
| | | | | |--- feature_1 <= 2.50
| | | | | | |--- feature_0 <= 2.50
| | | | | | | |--- feature_1 <= 1.50
| | | | | | | | |--- feature_4 <= 2.50
| | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_4 > 2.50
| | | | | | | | | |--- feature_2 <= 2.00
| | | | | | | | | | |--- class: 1
| | | | | | | | | |--- feature_2 > 2.00
| | | | | | | | | | |--- class: 0
| | | | | | | |--- feature_1 > 1.50
| | | | | | | | |--- class: 0
| | | | | | |--- feature_0 > 2.50
| | | | | | | |--- feature_2 <= 2.50
| | | | | | | | |--- class: 1
| | | | | | | |--- feature_2 > 2.50
| | | | | | | | |--- feature_4 <= 2.50
| | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_4 > 2.50
| | | | | | | | | |--- class: 0
| | | | | |--- feature_1 > 2.50
| | | | | | |--- feature_1 <= 3.50
| | | | | | | |--- feature_0 <= 3.50
| | | | | | | | |--- class: 0
| | | | | | | |--- feature_0 > 3.50
| | | | | | | | |--- feature_4 <= 2.50
| | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_4 > 2.50
| | | | | | | | | |--- feature_2 <= 2.00
| | | | | | | | | | |--- class: 1
| | | | | | | | | |--- feature_2 > 2.00
| | | | | | | | | | |--- class: 0
| | | | | | |--- feature_1 > 3.50
| | | | | | | |--- class: 0
| | | | |--- feature_3 > 4.50
| | | | | |--- class: 0
| |--- feature_4 > 3.50
| | |--- feature_2 <= 1.50
| | | |--- feature_4 <= 4.50
| | | | |--- feature_3 <= 3.50
| | | | | |--- feature_0 <= 1.50
| | | | | | |--- class: 0
| | | | | |--- feature_0 > 1.50
| | | | | | |--- class: 1
| | | | |--- feature_3 > 3.50
| | | | | |--- feature_1 <= 2.50
| | | | | | |--- feature_0 <= 2.50
| | | | | | | |--- class: 0
| | | | | | |--- feature_0 > 2.50
| | | | | | | |--- feature_3 <= 4.50
| | | | | | | | |--- class: 1
| | | | | | | |--- feature_3 > 4.50
| | | | | | | | |--- class: 0
| | | | | |--- feature_1 > 2.50
| | | | | | |--- class: 0
| | | |--- feature_4 > 4.50
| | | | |--- class: 0
| | |--- feature_2 > 1.50
| | | |--- class: 0
|--- feature_2 > 3.50
| |--- feature_1 <= 1.50
| | |--- feature_4 <= 1.50
| | | |--- feature_2 <= 4.50
| | | | |--- feature_0 <= 1.50
| | | | | |--- class: 0
| | | | |--- feature_0 > 1.50
| | | | | |--- feature_3 <= 4.50
| | | | | | |--- class: 1
| | | | | |--- feature_3 > 4.50
| | | | | | |--- class: 0
| | | |--- feature_2 > 4.50
| | | | |--- class: 0
| | |--- feature_4 > 1.50
| | | |--- class: 0
| |--- feature_1 > 1.50
| | |--- class: 0
=======
|--- feature_2 <= 3.50
| |--- feature_4 <= 3.50
| | |--- feature_0 <= 1.50
@ -89,3 +182,4 @@
| | | |--- class: 0
| |--- feature_1 > 1.50
| | |--- class: 0
>>>>>>> genetic_algorithm

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decision_tree/tree_model
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last_map.nparr
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10
main_test.py Normal file
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@ -0,0 +1,10 @@
from map import map_utils
from path_search_algorthms import a_star, a_star_utils
import numpy
file = open('last_map.nparr', 'rb')
array = numpy.load(file)
file.close
actions = a_star.search_path(12, 0, a_star_utils.Rotation.UP, 1, 5, array)
print(actions)

71
neurone/main.py Normal file
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@ -0,0 +1,71 @@
import pybrain3
import pickle
import matplotlib.pylab as plt
from numpy import ravel
from pybrain3.tools.shortcuts import buildNetwork
from pybrain3.datasets import SupervisedDataSet
from pybrain3.supervised.trainers import BackpropTrainer
from pybrain3.tools.xml.networkwriter import NetworkWriter
from pybrain3.tools.xml.networkreader import NetworkReader
# https://www.machinelearningmastery.ru/how-to-configure-the-number-of-layers-and-nodes-in-a-neural-network/
class SupervisedDataSetModel():
def __init__(self, metrics:int = 4,
predictions:int = 1,
input_layer:int = 4,
hidden_layer:int = 3,
output_layer:int = 1):
# 4 метрики, 1 предикшн
self.metrics = metrics
self.predictions = predictions
self.input_layer = input_layer
self.hidden_layer = hidden_layer
self.output_layer = output_layer
self.ds = SupervisedDataSet(metrics, predictions)
def activateModel(self):
self.net = buildNetwork(self.input_layer, self.hidden_layer, self.output_layer, bias=True)
self.trainer = BackpropTrainer(self.net, dataset=self.ds, momentum=0.1, learningrate=0.01, verbose=True, weightdecay=0.01)
self.trnerr, self.valerr = self.trainer.trainUntilConvergence()
plt.plot(self.trnerr, 'b', self.valerr, 'r')
plt.show()
def addDataToModel(self, input:list, target:list):
self.ds.addSample(inp=input, target=target)
def predict(self, data:list):
y = self.net.activate(data)
print(y)
return y
def saveModel(self):
fileObject = open('model.txt', 'wb')
pickle.dump(self.net, fileObject)
fileObject.close()
def getModel():
fileObject = open('model.txt', 'rb')
net2 = pickle.load(fileObject)
fileObject.close()
return net2
model = SupervisedDataSetModel()
# model.addDataToModel([2, 3, 80, 1], [5])
# model.addDataToModel([5, 5, 50, 2], [4])
# model.addDataToModel([10, 7, 40, 3], [3])
# model.addDataToModel([15, 9, 20, 4], [2])
# model.addDataToModel([20, 11, 10, 5], [1])
# model.activateModel()
# model.saveModel()
# USE MODEL - >
model = getModel()
print(model.activate([2, 3, 80, 1]))

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neurone/model.txt Normal file
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13
path_search_algorthms/a_star_utils.py
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@ -3,6 +3,7 @@ from enum import Enum
from map import map_utils
from settings import *
class Rotation(Enum):
UP = 0
RIGHT = 1
@ -13,18 +14,20 @@ class Rotation(Enum):
def __int__(self):
return self.value
class Node:
def __init__(self, x: int, y: int, rotation: Rotation):
self.x = x
self.y = y
self.g_cost = 0
self.h_cost = 0
self.parent = 0
self.rotation = rotation
self.parent: Node | bool = False
self.rotation: Rotation = rotation
def f_cost(self):
return self.g_cost + self.h_cost
def get_neighbours(node, searched_list, array):
neighbours = []
for offset_x in range(-1, 2):
@ -41,6 +44,7 @@ def get_neighbours(node, searched_list, array):
neighbours.append(neighbour)
return neighbours
# move cost schema:
# - move from tile to tile: 10
# - add extra 10 (1 rotation) if it exists
@ -54,6 +58,7 @@ def get_h_cost(start_node: Node, target_node: Node):
return cost
# move cost schema:
# - move from tile to tile: 10
# - every rotation 90*: 10
@ -67,6 +72,7 @@ def get_neighbour_cost(start_node: Node, target_node: Node) -> int:
else:
return 30
# translate rotation change to move
def get_move(start_node: Node, target_node: Node):
rotate_change = get_rotate_change(start_node.rotation, target_node.rotation)
@ -79,10 +85,12 @@ def get_move(start_node: Node, target_node: Node):
else:
return ["left", "forward"]
# simple calc func
def get_rotate_change(rotationA: Rotation, rotationB: Rotation) -> int:
return int(rotationA) - int(rotationB)
# get new rotation for target_node as neighbour of start_node
def get_needed_rotation(start_node: Node or bool, target_node: Node) -> Rotation:
if(start_node == False):
@ -100,4 +108,3 @@ def get_needed_rotation(start_node: Node or bool, target_node: Node) -> Rotation