def display_recommend():
# Load the user-book ratings
rd = ReadData(500000, 1000, 100)
(sparse_ratings, books_used, deleted_users) = rd.load_ratings_data()
# Obtain the filled matrix using iterative singular value thresholding
a = Algorithms(sparse_ratings)
(ratings_with_nan, filled_ratings) = a.isvt()
# Recommend books to a user who exists in the system: User #59. Changing the user ID will result in error.
books_user = recommend_n_books(sparse_ratings, filled_ratings, books_used,
59)
vd1 = VisualizeData(books_user)
vd1.display_book_info()
# Recommend books to a user who does not exist in the system, using norm calculations: User #1004.
# Changing the user ID will result in error.
rec_n = UsingNorm(sparse_ratings, filled_ratings, books_used, 1004)
books_norm = rec_n.rec_new_user_norm()
vd2 = VisualizeData(books_norm[1])
vd2.display_book_info()
# Recommend books to a user who does not exist in the system, using kmeans clustering: User #1004.
# Changing the user ID will result in error.
rec_km = UsingKMeans(sparse_ratings, filled_ratings, books_used, 1004,
deleted_users)
books_km = rec_km.rec_new_user_kmeans()
vd3 = VisualizeData(books_km)
vd3.display_book_info()
def best_of_experiments(acids_sequence, n, m, folding=None):
"""Take a sequence of acids. Give it a certain folding. Try to fold the
protein m times to improve this folding. Print the resulting score. Repeat
this n times. Return the best result.
"""
print('Start folding:', folding)
best_score = 1
for _ in range(n):
protein = Protein(acids_sequence)
if folding == 'cube_folding':
if not Algorithms.cube_folding(protein, shift='', d3=True):
print("failed to get a cube folding as start")
continue
elif folding == 'random_folding':
if not Algorithms.random_folding(protein):
print("failed to get a random folding as start")
continue
start_score = Algorithms.score(protein)
if not Algorithms.fold_n_times(m, protein):
print("failed to fold n times")
end_score = Algorithms.score(protein)
if end_score < best_score:
best_score = end_score
best_result = [acid.copy() for acid in protein.acids]
print(
'Start with score:\t{}\t\tEnd with score:\t{}\t\tBest score:\t{}'.
format(start_score, end_score, best_score))
protein.acids = best_result
return protein
def run_algorithms(list, algorithm):
# Creating a sort object
sort = Algorithms(list)
if algorithm == 'insertionsort' or algorithm == 'insertsort':
return sort.InsertSort()
elif algorithm == 'selectionsort' or algorithm == 'selectsort':
return sort.SelectSort()
elif algorithm == 'countingsort' or algorithm == 'countsort':
return sort.CountSort()
elif algorithm == 'shellsort':
return sort.ShellSort()
elif algorithm == 'quicksort':
return sort.QuickSort(list, 0, len(list))
elif algorithm == 'mergesort':
return sort.MergeSort(list)
elif algorithm == 'heapsort':
return sort.HeapSort(list)
elif algorithm == 'radixsort':
return sort.RadixSort()
else:
tools.error(algorithm)
sys.exit(2)
def get(self, numbers):
algorithm = Algorithms()
result = []
for num in range(1, int(numbers) + 1):
result.append(algorithm.fizzbuzz(num))
return result
def test_getLinkLoad_createsLoadsValuesOnEveryLink(self):
network = self.__createNetwork()
self.__interceptSeed()
chromosome = dap.createChromosome(network)
linkLoadList = dap.getLinkLoad(network, chromosome)
self.assertEqual(linkLoadList, [91, 63, 44, 101, 61])
def test_getMaximumLoad_returnsTheBiggestValueFromTheList(self):
network = self.__createNetwork()
self.__interceptSeed()
chromosome = dap.createChromosome(network)
linkLoadList = dap.getLinkLoad(network, chromosome)
maximumLoad = dap.getMaximumLoad(linkLoadList, network.links)
self.assertEqual(maximumLoad, -3)
def test_getBestParents_returnsFourChromosomes(self):
network = self.__createNetwork()
configuration = self.testConfiguration()
self.__interceptSeed()
initialGeneration = dap.createFirstGeneration(network, configuration)
controllers = dap.createDAPChromControllers(network, initialGeneration)
controllers.sort(key=lambda c: c.maximumLoad)
bestParents = dap.getBestParents(controllers)
highestMaximumLoads = list(map(lambda x: x.maximumLoad, bestParents))
self.assertEqual(highestMaximumLoads, [-34, -30, -29, -25])
def layoutUi(self):
#
# tool button
self.menu = QtWidgets.QMenu()
self.actionAddResource = QtWidgets.QAction('add resource')
self.actionRemoveResource = QtWidgets.QAction('remove resource')
for item in [self.actionAddResource, self.actionRemoveResource]:
self.menu.addAction(item)
self.toolButton.setMenu(self.menu)
#
# databases
self.installed_path = os.path.join(
os.path.abspath(os.path.dirname(sys.argv[0])), 'installed')
with os.scandir(self.installed_path) as dir:
installed_resources = [d.name for d in dir if d.is_dir()]
self.resourceBox.addItems(installed_resources)
#
self.read_reference_database()
#
# manual setup of 'sort by' combo box
self.sortBox.addItems(['full year', 'season', 'month'])
#
# available algorithms come from package algorithms
self.algorithms = Algorithms()
#
# set algorithm aliases
self.algoBox.addItems(self.algorithms.available_algorithms.keys())
class Main:
transactions = []
transactions.append(Transaction(57247, 0.0887, 1))
transactions.append(Transaction(98732, 0.1856, 2))
transactions.append(Transaction(134928, 0.2307, 3))
transactions.append(Transaction(77275, 0.1522, 4))
transactions.append(Transaction(29240, 0.0532, 5))
transactions.append(Transaction(15440, 0.0250, 6))
transactions.append(Transaction(70820, 0.1409, 7))
transactions.append(Transaction(139603, 0.2541, 8))
transactions.append(Transaction(63718, 0.1147, 9))
transactions.append(Transaction(143807, 0.2660, 10))
transactions.append(Transaction(190457, 0.2933, 11))
transactions.append(Transaction(40572, 0.686, 12))
sizes = [
57247, 98732, 134928, 77275, 29240, 15440, 70820, 139603, 63718,
143807, 190457, 40572
]
fees = [
0.0887, 0.1856, 0.2307, 0.1522, 0.0532, 0.0250, 0.1409, 0.2541, 0.1147,
0.2660, 0.2933, 0.0686
]
sizes.sort(reverse=True)
fees.sort(reverse=True)
algo = Algorithms(sizes)
algo.runSort()
print(sizes)
def test_bfs_1():
config = [1, 2, 5, 3, 4, 0, 6, 7, 8]
size = int(math.sqrt(len(config)))
puzzle_state = PuzzleState(config, size)
start_state_hash = Utilities.hashed_state(puzzle_state)
start_state = puzzle_state
def generate_node(node_options):
return Node(**node_options)
def compute_state_cost(state, state_hash):
return 1
def update_stats(max_search_depth = None, increment_expanded = False):
pass
result = Algorithms.search(
expand = Utilities.expand,
goal_state_check = Utilities.goal_state_check,
hashed_state = Utilities.hashed_state,
compute_state_cost = compute_state_cost,
update_stats = update_stats,
generate_node = generate_node,
start_state_hash = start_state_hash,
start_state = start_state,
search_type = "bfs"
)
assert result.state.config == (0, 1, 2, 3, 4, 5, 6, 7, 8)
def data_set_ready(self):
# setup for one data set
self.algorithms = Algorithms()
self.model = Solver(self.data)
self.model.current_data_set = self.current_data_set
self.model.load_data_set()
self.algorithms.set_algorithms(self.model)
def main():
sm = sys.argv[1].lower()
begin_state = sys.argv[2].split(",")
begin_state = tuple(map(int, begin_state))
size = int(math.sqrt(len(begin_state)))
hard_state = PuzzleState(begin_state, size)
args = {
"client_defined_expand": Utilities.expand,
"client_defined_goal_state_check": Utilities.goal_state_check,
"client_defined_hashed_state": Utilities.hashed_state,
"client_defined_compute_state_cost": Utilities.compute_state_cost,
"start_state_hash": sm,
"start_state": hard_state,
}
if sm == "bfs":
result = Algorithms.search_wrapper(
**args,
search_type = "bfs"
)
elif sm == "dfs":
result = Algorithms.search_wrapper(
**args,
search_type = "dfs"
)
elif sm == "ast":
result = Algorithms.search_wrapper(
**args,
search_type = "astar"
)
else:
print("Enter valid command arguments !")
Reporter.write_output(file_name = "output.txt", **result)
def do_all():
algorithms = ["depthfirst", "breadthfirst", "dijkstra", "Astar"]
images = ["tiny", "braid200", "normal", "small", "combo400"]
for a in algorithms:
for i in images:
start(Algorithms().__getitem__(a),
Images().__getitem__(i), i + '_' + a)
def decode_private_key(self, blob):
alg = blob[0]
if Algorithms(alg) != Algorithms.RABIN:
raise ValueError("Wrong key algorithm")
p = bytes_to_int(blob[1:][:len(blob[1:]) // 2])
q = bytes_to_int(blob[1:][len(blob[1:]) // 2:])
return p, q
def decode_private_key(self, blob):
alg = blob[0]
if Algorithms(alg) != Algorithms.RSA:
raise ValueError("Wrong key algorithm")
d_len = bytes_to_int(blob[1:3] if blob[2] != 0 else blob[1:2])
n_len = bytes_to_int(blob[3:5] if blob[4] != 0 else blob[3:4])
return bytes_to_int(blob[5:5+d_len]), bytes_to_int(blob[-n_len:])
def main():
al = Algorithms()
images = Images()
parser = argparse.ArgumentParser()
parser.add_argument("Algorithm",
help="Selected Algorithm to use for pathfinding",
default=al.default,
choices=al.options,
nargs='?')
parser.add_argument("Image",
help="Selected Image for pathfinding",
default=images.default,
choices=images.options,
nargs='?')
parser.add_argument("output_name", nargs='?', default="algorithm")
args = parser.parse_args()
# print(args)
start(al.__getitem__(args.Algorithm), images.__getitem__(args.Image),
args.output_name)
def ac3(initial_puzzle_state):
if (len(initial_puzzle_state) != 81):
raise Exception("Puzzle must be 81 characters long")
return Algorithms.ac3(
initial_puzzle_state=initial_puzzle_state,
client_defined_revise_domains=Sudoku.revise_domains,
client_defined_get_domains_for_index=Sudoku.get_domains_for_index,
client_defined_get_neighbors_for_index=Sudoku.
get_neighbors_for_index,
client_defined_is_puzzle_complete=Sudoku.is_puzzle_complete,
client_defined_unassigned_value="0")
def backtracking_search(initial_puzzle_state):
puzzle_state = initial_puzzle_state
return Algorithms.backtracking_search(
puzzle_state=puzzle_state,
client_defined_get_domains_for_index=Sudoku.get_domains_for_index,
client_defined_get_neighbors_for_index=Sudoku.
get_neighbors_for_index,
client_defined_is_puzzle_complete=Sudoku.is_puzzle_complete,
client_defined_unassigned_value="0",
client_defined_does_puzzle_follow_constraints=Sudoku.
does_puzzle_follow_constraints,
)
def algorithm_evaluation():
rd = ReadData(500000, 1000, 100)
(sparse_ratings, books_used, deleted_users) = rd.load_ratings_data()
# Obtain the filled matrix using iterative singular value thresholding and view mse per iteration
a = Algorithms(sparse_ratings)
(ratings_with_nan, filled_ratings_isvt) = a.isvt()
e = Evaluate(5, 10)
mse_isvt = e.performance_eval_isvt(ratings_with_nan, filled_ratings_isvt)
# Obtain the filled matrix using non-negative matrix factorization and view mse per iteration
filled_ratings_nmf = a.nmf()
mse_nmf = e.performance_eval_nmf(sparse_ratings, filled_ratings_nmf)
# Vary hold-out set and find average mse for each algorithm
hos = [5, 10, 15, 20]
e_isvt = []
e_nmf = []
for i in hos:
e2 = Evaluate(5, i)
mse_isvt = e2.performance_eval_isvt(ratings_with_nan,
filled_ratings_isvt,
plot=False)
e_isvt.append(mse_isvt)
mse_nmf = e2.performance_eval_nmf(sparse_ratings,
filled_ratings_nmf,
plot=False)
e_nmf.append(mse_nmf)
plt.plot(hos, e_isvt, label="Soft Impute")
plt.plot(hos, e_nmf, label="NMF")
plt.xlabel("Hold-Out Set %")
plt.ylabel("Mean Squared Error")
plt.legend()
plt.show()
def performance_eval_nmf(self, sparse, filled, plot=True):
"""
hold out a certain percent of the ratings and observe how well the algorithm approximates those ratings
"""
mse = []
for k in range(self.n_iter):
test = sparse.copy()
a = Algorithms(test)
n_ratings = np.size(sparse) - len(np.where(sparse==0)[0])
holdout_count = int(self.holdout_percent*n_ratings/100)
for subs in range(holdout_count):
m = 0
while m == 0:
i = random.randint(0,len(sparse)-1)
j = random.randint(0,len(sparse[0])-1)
if test[i][j] != 0:
temp = test[i][j]
test[i][j] = 0
if np.all(test[i]==0) or np.all(test[:][j]==0):
test[i][j] = temp
else:
m = 1
completed = a.nmf()
mse.append(mean_squared_error(filled, completed))
if plot:
# plot mean squared error per iteration
x = [i for i in range(1,self.n_iter+1)]
plt.plot(x, mse)
plt.xlabel("Iterations")
plt.ylabel("Mean Squared Error")
plt.title("Non-Negative Matrix Factorization")
plt.show()
return np.average(mse)
def __init__(self, algorithm, data, frame):
n = len(data)
m = max(data)
self.algorithm = algorithm
self.data = data
self.frame = frame
self.sorting_algorithm_ref = Algorithms.reference(algorithm, data)
self.figure, self.ax = plt.subplots()
self.rectangles = self.ax.bar(range(n), self.data, align="edge")
self.ax.set_xlim(0, n)
self.ax.set_ylim(0, m + 10)
self.ax.set_yticklabels([])
self.ax.set_xticklabels([])
self.ax.set_title(self.algorithm.value)
self.text = self.ax.text(0.01, 0.97, "", transform=self.ax.transAxes)
self.iteration = [0]
self.canvas = FigureCanvasTkAgg(self.figure, master=self.frame)
self.anim = None
def test_bfs_wrapper_1():
config = [1, 2, 5, 3, 4, 0, 6, 7, 8]
size = int(math.sqrt(len(config)))
puzzle_state = PuzzleState(config, size)
start_state_hash = Utilities.hashed_state(puzzle_state)
start_state = puzzle_state
result = Algorithms.search_wrapper(
client_defined_expand = Utilities.expand,
client_defined_goal_state_check = Utilities.goal_state_check,
client_defined_hashed_state = Utilities.hashed_state,
start_state_hash = start_state_hash,
start_state = start_state,
search_type = "bfs"
)
assert result["path_to_goal"] == ["Up", "Left", "Left"]
assert result["cost_of_path"] == 3
assert result["search_depth"] == 3
def test_bfs_wrapper_2():
config = [6, 1, 8, 4, 0, 2, 7, 3, 5]
size = int(math.sqrt(len(config)))
puzzle_state = PuzzleState(config, size)
start_state_hash = Utilities.hashed_state(puzzle_state)
start_state = puzzle_state
result = Algorithms.search_wrapper(
client_defined_expand = Utilities.expand,
client_defined_goal_state_check = Utilities.goal_state_check,
client_defined_hashed_state = Utilities.hashed_state,
start_state_hash = start_state_hash,
start_state = start_state,
search_type = "bfs"
)
assert result["path_to_goal"] == [
'Down',
'Right',
'Up',
'Up',
'Left',
'Down',
'Right',
'Down',
'Left',
'Up',
'Left',
'Up',
'Right',
'Right',
'Down',
'Down',
'Left',
'Left',
'Up',
'Up'
]
assert result["cost_of_path"] == 20
assert result["nodes_expanded"] == 54094
assert result["search_depth"] == 20
assert result["max_search_depth"] == 21
def test_astar_wrapper_2():
config = [8, 6, 4, 2, 1, 3, 5, 7, 0]
size = int(math.sqrt(len(config)))
puzzle_state = PuzzleState(config, size)
start_state_hash = Utilities.hashed_state(puzzle_state)
start_state = puzzle_state
result = Algorithms.search_wrapper(
client_defined_expand = Utilities.expand,
client_defined_goal_state_check = Utilities.goal_state_check,
client_defined_hashed_state = Utilities.hashed_state,
client_defined_compute_state_cost = Utilities.compute_state_cost,
start_state_hash = start_state_hash,
start_state = start_state,
search_type = "astar"
)
assert result["path_to_goal"] == ['Left', 'Up', 'Up', 'Left', 'Down', 'Right', 'Down', 'Left', 'Up', 'Right', 'Right', 'Up', 'Left', 'Left', 'Down', 'Right', 'Right', 'Up', 'Left', 'Down', 'Down', 'Right', 'Up', 'Left', 'Up', 'Left']
assert result["cost_of_path"] == 26
assert result["nodes_expanded"] == 1585
assert result["search_depth"] == 26
assert result["max_search_depth"] == 26
def test_dfs_wrapper_3():
config = [8, 6, 4, 2, 1, 3, 5, 7, 0]
size = int(math.sqrt(len(config)))
puzzle_state = PuzzleState(config, size)
start_state_hash = Utilities.hashed_state(puzzle_state)
start_state = puzzle_state
result = Algorithms.search_wrapper(
client_defined_expand = Utilities.expand,
client_defined_goal_state_check = Utilities.goal_state_check,
client_defined_hashed_state = Utilities.hashed_state,
start_state_hash = start_state_hash,
start_state = start_state,
search_type = "dfs"
)
assert result["path_to_goal"][0] == "Up"
assert result["path_to_goal"][1] == "Up"
assert result["path_to_goal"][2] == "Left"
assert result["cost_of_path"] == 9612
assert result["nodes_expanded"] == 9869
assert result["search_depth"] == 9612
assert result["max_search_depth"] == 9612
def decode(self, blob: bytes) -> Certificate:
offset = 0
alg_id = Algorithms(blob[offset])
offset += 1
"""4 bytes for serial number"""
serial_number = bytes_to_int(blob[offset:offset+4])
offset += 4
pub_key_len = bytes_to_int(blob[offset:offset+4])
offset += 4
public_key = blob[offset:offset+pub_key_len]
offset += pub_key_len
private_key_len = bytes_to_int(blob[offset:offset+4])
offset += 4
private_key = blob[offset:offset+private_key_len]
offset += private_key_len
signature = blob[offset:]
return Certificate(alg_id, public_key, private_key, serial_number, signature)
def getScores(self,
xTrain,
xTest,
yTrain,
yTest,
trainSize=1,
randomSeeds=[1, 2, 3, 4, 5],
selectedAlgorithms=['logReg', 'svm', 'dt', 'rf', 'ann']):
algs = Algorithms()
logReg = algs.logisticRegression()
svm = algs.SVM()
dt = algs.DecisionTree()
rf = algs.RandomForest()
ann = algs.ANN(epochs=5)
# available algorithms ([name, implementation])
algorithms = {
'logReg': ['Logistic Regression', logReg],
'svm': ['SVM', svm],
'dt': ['Decision Tree', dt],
'rf': ['Random Forest', rf],
'ann': ['ANN', ann],
}
predictions = {}
for selected in selectedAlgorithms:
[algName, alg] = algorithms[selected]
noOfSamples, trainScores, testScores = self.calculateAverageScores(
xTrain, xTest, yTrain, yTest, alg, algName, trainSize,
randomSeeds)
predictions[algName] = (trainScores, testScores)
print('\nAverage train/test accuracy:', trainScores[0],
testScores[0], '\n')
return noOfSamples, predictions
def test():
start(Algorithms().__getitem__('dijkstra'),
Images().__getitem__('tiny'), 'test')
class MainWindow(QWidget):
"""
Main window class for capraz_sevkiyat project
"""
def __init__(self):
QWidget.__init__(self)
self.model = None
self.setWindowTitle("Cross Docking Project")
self.setGeometry(400, 400, 400, 400)
self.set_buttons()
self.set_layout()
self.truck_image_list = {}
self.truckDataWindow = None
self.data = DataStore()
self.model = None
self.current_iteration = 1
self.iteration_limit = 100
self.current_data_set = 0
self.algorithms = None
self.solution_choice = None
self.scn = QGraphicsScene()
self.simulation = GraphView(self.scn)
def set_buttons(self):
self.new_data_set_button = QPushButton('New Data Set')
self.load_data_set_button = QPushButton('Load Data Set')
self.save_data_set_button = QPushButton('Save Data Set')
self.truck_data_button = QPushButton('Truck Data')
self.system_data_button = QPushButton('System Data')
self.algorithm_data_button = QPushButton('Algorithm Data')
self.generate_data_set_button = QPushButton('Generate Data Set')
self.show_data_button = QPushButton('Show Data Set')
self.print_gams_button = QPushButton('Print gams output')
self.data_set_ready_button = QPushButton('Data Set Ready')
self.solve_step_button = QPushButton('Solve Next Step')
self.solve_iteration_button = QPushButton('Solve Next Iteration')
self.solve_next_data_set_button = QPushButton('Solve Next Data Set')
self.show_logger_button = QPushButton('Show Logger')
self.show_simulation_button = QPushButton('Show Simulation')
self.show_data_table = QPushButton('Show Run Time Data Table')
self.data_set_number = QSpinBox()
self.data_set_number.setMinimum(0)
self.new_data_set_button.clicked.connect(self.new_data_set)
self.load_data_set_button.clicked.connect(self.load_data)
self.save_data_set_button.clicked.connect(self.save_data)
self.truck_data_button.clicked.connect(self.show_truck_data)
self.system_data_button.clicked.connect(self.show_system_data)
self.algorithm_data_button.clicked.connect(self.show_algorithm_data)
self.generate_data_set_button.clicked.connect(self.generate_data_set)
self.show_data_button.clicked.connect(self.show_data)
self.print_gams_button.clicked.connect(self.print_gams)
self.data_set_ready_button.clicked.connect(self.data_set_ready)
self.show_logger_button.clicked.connect(self.show_logger)
self.show_data_table.clicked.connect(self.show_runtime_table)
self.solve_next_data_set_button.clicked.connect(self.data_set_button)
self.solve_iteration_button.clicked.connect(self.iteration_button)
self.solve_step_button.clicked.connect(self.step_button)
self.data_set_number.valueChanged.connect(self.set_data_set_number)
def set_layout(self):
self.data_set_layout = QGridLayout()
self.data_set_layout.addWidget(self.new_data_set_button, 1 ,1)
self.data_set_layout.addWidget(self.load_data_set_button, 1 ,2)
self.data_set_layout.addWidget(self.save_data_set_button, 1 ,3)
self.data_set_layout.addWidget(self.truck_data_button, 2 ,1)
self.data_set_layout.addWidget(self.system_data_button, 2 ,2)
self.data_set_layout.addWidget(self.algorithm_data_button, 2 ,3)
self.data_set_layout.addWidget(self.generate_data_set_button, 3, 1)
self.data_set_layout.addWidget(self.show_data_button, 3, 2)
self.data_set_layout.addWidget(self.print_gams_button, 3, 3)
self.data_set_layout.addWidget(self.data_set_ready_button, 4, 1)
self.solver_layout = QGridLayout()
self.solver_layout.addWidget(self.solve_step_button, 1, 1)
self.solver_layout.addWidget(self.solve_iteration_button, 1, 2)
self.solver_layout.addWidget(self.solve_next_data_set_button, 1, 3)
self.solver_layout.addWidget(self.data_set_number, 1, 4)
self.interaction_layout = QGridLayout()
self.interaction_layout.addWidget(self.show_logger_button, 1, 1)
self.interaction_layout.addWidget(self.show_simulation_button, 1, 3)
self.interaction_layout.addWidget(self.show_data_table, 1, 4)
self.layout = QVBoxLayout()
self.layout.addLayout(self.data_set_layout)
self.layout.addLayout(self.solver_layout)
self.layout.addLayout(self.interaction_layout)
self.setLayout(self.layout)
self.pause_bool = False
def new_data_set(self):
"""
:return:
"""
self.data = DataStore()
def load_data(self):
"""
loads prev saved data
:return:
"""
file_name, _ = QFileDialog.getOpenFileName(self, 'Open file', '/home')
self.data = pickle.load(open(file_name, 'rb'))
def save_data(self):
"""
saves current data
:return:
"""
file_name, _ = QFileDialog.getSaveFileName(self, 'Save file', '/home')
pickle.dump(self.data, open(file_name, 'wb'))
def generate_data_set(self):
# ask if sure
self.data.arrival_times = []
self.data.boundaries = []
self.model = Solver(self.data)
for i in range(len(self.data.data_set_list)):
self.model.current_data_set = i
self.model.set_data()
def show_data(self):
self.data_show = ShowData(self.data)
self.data_show.exec_()
def print_gams(self):
file_name, _ = QFileDialog.getSaveFileName(self, 'Open file', '/home')
for i in range(len(self.data.data_set_list)):
gams_writer(file_name + str(i), i, self.data )
def show_truck_data(self):
"""
shows data about the trucks
:return:
"""
self.truckDataWindow = TruckDataWindow(self.data)
self.truckDataWindow.exec_()
def show_system_data(self):
"""
shows data set
:return:
"""
self.dataWindow = DataSetWindow(self.data)
self.dataWindow.exec_()
def show_algorithm_data(self):
pass
def data_set_ready(self):
# setup for one data set
self.algorithms = Algorithms()
self.model = Solver(self.data)
self.model.current_data_set = self.current_data_set
self.model.load_data_set()
self.algorithms.set_algorithms(self.model)
def show_logger(self):
self.logger = LogData()
root = logging.getLogger()
root.setLevel(logging.INFO)
ch = logging.StreamHandler(self.logger)
ch.setLevel(logging.INFO)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
root.addHandler(ch)
self.logger.show()
logging.info('Logger Started')
def data_set_button(self):
self.solution_choice = 'data_set'
self.solve_dataset()
def iteration_button(self):
self.solution_choice = 'iteration'
self.solution_type_choice()
self.solve_dataset()
def step_button(self):
self.solution_choice = 'step'
self.solution_type_choice()
self.solve_dataset()
def set_data_set_number(self):
self.current_data_set = self.data_set_number.value()
def solve_dataset(self):
"""
solves one data set
:return:
"""
logging.info('Data Set Number: {0}'.format(self.current_data_set))
self.model.current_data_set = self.current_data_set
if self.data_set_bool:
#print('one_set')1
if self.current_iteration == 1 and self.model.current_time == 0:
self.model.load_data_set()
self.solve_iteration()
if self.current_data_set == len(self.data.data_set_list):
# print('finish')
self.current_iteration = 1
self.current_data_set = 0
self.trial_time = 0
else:
while self.current_data_set < len(self.data.data_set_list):
if self.pause_bool:
break
self.model.load_data_set()
self.solve_iteration()
# print(self.current_data_set)
self.current_data_set = 0
def solve_iteration(self):
"""
solves one iteration
:return:
"""
if self.iteration_bool:
if self.model.current_time == 0:
if self.current_iteration == 1:
self.algorithms.start()
self.model.set_sequence(self.algorithms.solution_sequence)
self.solve_whole_step()
self.model.reset()
self.algorithms.next()
self.model.set_sequence(self.algorithms.solution_sequence)
else:
self.algorithms.next()
self.model.set_sequence(self.algorithms.solution_sequence)
self.solve_step()
if self.current_iteration == self.iteration_limit:
self.log_results()
self.current_iteration = 1
else:
while self.current_iteration < self.iteration_limit:
if self.pause_bool:
break
if self.model.current_time == 0:
if self.current_iteration == 1:
self.algorithms.start()
else:
self.algorithms.next()
self.model.set_sequence(self.algorithms.solution_sequence)
# next sequence
self.solve_step()
self.current_iteration = 1
self.log_results()
def solve_step(self):
if self.step_bool:
self.solve_one_step()
else:
self.solve_whole_step()
def solve_whole_step(self):
"""
solves one iterations
:return:
"""
while not self.model.finish:
# if self.model.current_time > 800:
#
# break
if self.pause_bool:
break
self.model.next_step()
#finished
for truck in itertools.chain(self.model.outbound_trucks.values(), self.model.compound_trucks.values()):
truck.calculate_error()
if self.runtime_table:
self.runtime_table.update_tables()
self.runtime_table.activateWindow()
#add reset
self.model.finish = False
self.algorithms.solution_sequence['error'] = self.add_errors()
self.model.reset()
if self.current_iteration > 1:
self.algorithms.calculate()
self.current_iteration += 1
def solve_one_step(self):
"""
goes one time step forward
:return:
"""
self.model.next_step()
# self.simulation.update_image()
if self.runtime_table:
self.runtime_table.update_tables()
self.runtime_table.activateWindow()
if self.model.finish:
#finished
logging.info("Finished iteration {0}".format(self.current_iteration))
for truck in self.model.outbound_trucks.values():
truck.calculate_error()
self.add_errors()
self.model.reset()
# add reset
self.current_iterpation += 1
self.model.finish = False
# update algorithm
self.algorithms.solution_sequence['error'] = self.add_errors()
self.algorithms.calculate()
def add_errors(self):
"""
adds absolute values of the errors
:return:
"""
total_error = 0
for truck in itertools.chain(self.model.outbound_trucks.values(), self.model.compound_trucks.values()):
total_error += abs(truck.error)
logging.info("Error: {0}\n".format(total_error))
return total_error
def show_runtime_table(self):
"""
shows data table of the
:return:
"""
self.runtime_table = TruckDataTable(self.algorithms, self.model)
self.runtime_table.show()
def simulation_cycle(self):
i = 0
for inbound_trucks in self.model.inbound_trucks.values():
truck_name = inbound_trucks.truck_name
self.truck_image_list[truck_name] = self.scn.addPixmap(self.truckPixmap)
self.truck_image_list[truck_name].scale(0.2,0.2)
self.truck_image_list[truck_name].setPos(-600,i*100)
i = i +1
self.simulation.show()
def solution_type_choice(self):
"""
update bools for the choosen solution type
:return:
"""
if self.solution_choice == 'solve':
self.solve_bool = True
self.data_set_bool = False
self.iteration_bool = False
self.step_bool = False
elif self.solution_choice == 'data_set':
self.solve_bool = True
self.data_set_bool = True
self.iteration_bool = False
self.step_bool = False
self.data_set_ready()
elif self.solution_choice == 'iteration':
self.solve_bool = True
self.data_set_bool = True
self.iteration_bool = True
self.step_bool = False
elif self.solution_choice == 'step':
self.solve_bool = True
self.data_set_bool = True
self.iteration_bool = True
self.step_bool = True
def print_simulation_data(self):
logging.info("Iteration Number: {0}\n".format(self.current_iteration))
logging.info("Inbound Sequence: {0}\n".format(self.algorithms.solution_sequence['inbound']))
logging.info("Outbound Sequence: {0}\n".format(self.algorithms.solution_sequence['outbound']))
logging.info("Error value: {0}\n".format(self.algorithms.solution_sequence['error']))
def log_results(self):
logging.info("Best result:")
logging.info("Inbound Sequence: {0}\n".format(self.algorithms.best_sequence['inbound']))
logging.info("Outbound Sequence: {0}\n".format(self.algorithms.best_sequence['outbound']))
logging.info("Error value: {0}\n".format(self.algorithms.best_sequence['error']))
def decode_public_key(self, blob):
alg = blob[0]
if Algorithms(alg) != Algorithms.RABIN:
raise ValueError("Wrong key algorithm")
return bytes_to_int(blob[1:])
def init_algorithms(self):
self.algorithms = Algorithms(self)
def create_battles(self):
for target in self.targets:
self.battles.append(
Algorithms.subsets_sum_for_attack(self.possible_moves, target))
class GeneralInfo(QWidget):
"""
General information screen in main gui
"""
def __init__(self, status_bar):
"""
init text screen for info
:return:
"""
QWidget.__init__(self)
self.data = None
self.infoText = QTextEdit()
self.infoText.setReadOnly(True)
self.scn = QGraphicsScene()
self.simulation = GraphView(self.scn)
self.status_bar = status_bar
# solution types
self.solution_list = {}
self.solution_list['iteration'] = self.solve_iteration
self.solution_list['step'] = self.solve_step
self.solution_list['data_set'] = self.solve_dataset
self.solution_list['solve'] = self.solve
self.solution_type = 'iteration'
# cycle booleans
self.solve_bool = False
self.step_bool = False
self.iteration_bool = False
self.data_set_bool = False
self.pause_bool = False
# buttons
self.play_button = QPushButton("Play")
self.play_button.setIcon(self.style().standardIcon(QStyle.SP_MediaPlay))
self.stop_button = QPushButton("Stop")
self.stop_button.setIcon(self.style().standardIcon(QStyle.SP_MediaStop))
self.pause_button = QPushButton("Pause")
self.pause_button.setIcon(self.style().standardIcon(QStyle.SP_MediaPause))
self.solution_type_combo = QComboBox()
self.solution_type_combo.addItems(self.solution_list.keys())
self.new_data_set_button = QPushButton("New Data Set")
self.play_button.setDisabled(True)
self.stop_button.setDisabled(True)
self.pause_button.setDisabled(True)
self.solution_type_combo.setDisabled(True)
self.play_button.clicked.connect(self.solve)
self.pause_button.clicked.connect(self.pause)
# setup layout
self.layout = QGridLayout()
self.data_set_layout = QGridLayout()
self.data_set_layout.addWidget(self.new_data_set_button)
self.layout.addLayout(self.data_set_layout, 1,1)
# self.layout.addWidget(self.infoText, 1, 1, 1)
# self.layout.addWidget(self.simulation, 1, 2)
self.h_layout = QHBoxLayout()
self.h_layout.addWidget(self.play_button)
self.h_layout.addWidget(self.stop_button)
self.h_layout.addWidget(self.pause_button)
self.h_layout.addWidget(self.solution_type_combo)
self.layout.addLayout(self.h_layout, 2, 1)
# self.layout.addWidget(self.simulation, 1, 2)
self.setLayout(self.layout)
self.model = None
self.data = DataStore()
self.current_iteration = 1
self.iteration_limit = 100
self.current_data_set = 0
self.data_string = ''
self.algorithms = Algorithms()
self.algo_screen = ChooseAlgo()
self.trial_time = 0
def init_solution(self, data=DataStore()):
"""
Starts solution for a data set
:param data: data store
:return:
"""
self.play_button.setDisabled(False)
self.stop_button.setDisabled(False)
self.pause_button.setDisabled(False)
self.solution_type_combo.setDisabled(False)
self.data = data
self.model = Solver(self.data)
self.simulation.init_image(self.model)
self.print_start_data()
numbers = {'inbound': self.data.number_of_inbound_trucks, 'outbound': self.data.number_of_outbound_trucks,
'compound': self.data.number_of_compound_trucks, 'receive': self.data.number_of_receiving_doors,
'shipping': self.data.number_of_shipping_doors}
self.algorithms.set_algorithms(self.model)
self.model.set_data(0)
def solution_type_choice(self):
"""
update bools for the choosen solution type
:return:
"""
choice = self.solution_type_combo.currentText()
if choice == 'solve':
self.solve_bool = True
self.data_set_bool = False
self.iteration_bool = False
self.step_bool = False
elif choice == 'data_set':
self.solve_bool = True
self.data_set_bool = True
self.iteration_bool = False
self.step_bool = False
elif choice == 'iteration':
self.solve_bool = True
self.data_set_bool = True
self.iteration_bool = True
self.step_bool = False
elif choice == 'step':
self.solve_bool = True
self.data_set_bool = True
self.iteration_bool = True
self.step_bool = True
def choose_algorithm(self):
"""
choose and algorithm
:return:
"""
self.algo_screen.exec_()
self.iteration_limit = self.algo_screen.iteration_number
#get algorithm
def pause(self):
self.pause_bool = True
def solve(self):
"""
solves all of the data sets
:return:
"""
self.pause_bool = False
self.solution_type_choice()
# print('solve')
self.solve_dataset()
def solve_dataset(self):
"""
solves one data set
:return:
"""
if self.data_set_bool:
#print('one_set')1
if self.current_iteration == 1 and self.model.current_time == 0:
self.model.set_data(self.current_data_set)
self.solve_iteration()
if self.current_data_set == len(self.data.data_set_list):
# print('finish')
self.current_iteration = 1
self.current_data_set = 0
self.trial_time = 0
else:
while self.current_data_set < len(self.data.data_set_list):
if self.pause_bool:
break
self.model.set_data(self.current_data_set)
self.solve_iteration()
self.current_data_set += 1
# print(self.current_data_set)
self.current_data_set = 0
def solve_iteration(self):
"""
solves one iteration
:return:
"""
if self.iteration_bool:
#print('one_iteration')
if self.model.current_time == 0:
if self.current_iteration == 1:
print('start')
self.algorithms.start()
self.model.set_sequence(self.algorithms.solution_sequence)
self.solve_whole_step()
self.algorithms.next()
self.model.set_sequence(self.algorithms.solution_sequence)
else:
self.algorithms.next()
self.model.set_sequence(self.algorithms.solution_sequence)
self.print_simulation_data()
self.solve_step()
if self.current_iteration == self.iteration_limit:
self.current_data_set += 1
self.current_iteration = 1
else:
while self.current_iteration < self.iteration_limit:
if self.pause_bool:
break
self.print_simulation_data()
if self.model.current_time == 0:
if self.current_iteration == 1:
self.algorithms.start()
else:
self.algorithms.next_sequence()
self.model.set_sequence(self.algorithms.solution_sequence)
# next sequence
self.solve_step()
self.current_iteration += 1
#print(self.current_iteration)
self.current_iteration = 1
#print('whole_iteration')
def solve_step(self):
if self.step_bool:
self.solve_one_step()
else:
self.solve_whole_step()
def solve_whole_step(self):
"""
solves one iterations
:return:
"""
while not self.model.finish:
if self.model.current_time > 800:
print('time limit')
break
if self.pause_bool:
break
self.model.next_step()
#finished
for truck in itertools.chain(self.model.outbound_trucks.values(), self.model.compound_trucks.values()):
truck.calculate_error()
#add reset
self.model.finish = False
self.algorithms.solution_sequence['error'] = self.add_errors()
self.model.reset_trucks()
if self.current_iteration > 1:
self.algorithms.calculate()
self.current_iteration += 1
#self.print_results()
def solve_one_step(self):
"""
goes one time step forward
:return:
"""
self.model.next_step()
self.simulation.update_image()
if self.model.finish:
#finished
for truck in self.model.outbound_trucks.values():
truck.calculate_error()
self.model.reset_trucks()
# add reset
self.add_errors()
#self.print_results()
self.current_iteration += 1
self.model.finish = False
self.algorithms.current_sequence['error'] = self.add_errors()
self.algorithms.calculate()
def add_errors(self):
"""
adds absolute values of the errors
:return:
"""
total_error = 0
for truck in itertools.chain(self.model.outbound_trucks.values(), self.model.compound_trucks.values()):
total_error += abs(truck.error)
print('total error', total_error)
return total_error
def print_start_data(self):
"""
prints the configuration info one time
:return:
"""
self.infoText.clear()
self.data_string = ''
self.data_string += "Number of inbound Trucks: {0}\n".format(self.data.number_of_inbound_trucks)
self.data_string += "Number of outbound Trucks: {0}\n".format(self.data.number_of_outbound_trucks)
self.data_string += "Number of compound Trucks: {0}\n".format(self.data.number_of_compound_trucks)
self.data_string += "Number of receiving doors: {0}\n".format(self.data.number_of_receiving_doors)
self.data_string += "Number of shipping doors: {0}\n".format(self.data.number_of_shipping_doors)
#
# data set
self.infoText.setText(self.data_string)
def step_time(self):
pass
def next_iteration(self):
"""
increase iteration if limit not reached
:return:
"""
if self.current_iteration < self.iteration_limit:
self.current_iteration += 1
else:
self.current_iteration = 0
self.next_data_set()
def next_data_set(self):
pass
def print_simulation_data(self):
self.infoText.clear()
self.data_string = ''
self.data_string += "Iteration Number: {0}\n".format(self.current_iteration)
self.data_string += "Inbound Sequence: {0}\n".format(self.algorithms.solution_sequence['inbound'])
self.data_string += "Outbound Sequence: {0}\n".format(self.algorithms.solution_sequence['outbound'])
# time
# data set number
# error value
# sequence
self.infoText.setText(self.data_string)
def print_results(self):
self.infoText.clear()
for truck in self.model.outbound_trucks.values():
print('bounds', truck.bounds)
print('error', truck.error)
print('finish', truck.finish_time)
def __init__(self, status_bar):
"""
init text screen for info
:return:
"""
QWidget.__init__(self)
self.data = None
self.infoText = QTextEdit()
self.infoText.setReadOnly(True)
self.scn = QGraphicsScene()
self.simulation = GraphView(self.scn)
self.status_bar = status_bar
# solution types
self.solution_list = {}
self.solution_list['iteration'] = self.solve_iteration
self.solution_list['step'] = self.solve_step
self.solution_list['data_set'] = self.solve_dataset
self.solution_list['solve'] = self.solve
self.solution_type = 'iteration'
# cycle booleans
self.solve_bool = False
self.step_bool = False
self.iteration_bool = False
self.data_set_bool = False
self.pause_bool = False
# buttons
self.play_button = QPushButton("Play")
self.play_button.setIcon(self.style().standardIcon(QStyle.SP_MediaPlay))
self.stop_button = QPushButton("Stop")
self.stop_button.setIcon(self.style().standardIcon(QStyle.SP_MediaStop))
self.pause_button = QPushButton("Pause")
self.pause_button.setIcon(self.style().standardIcon(QStyle.SP_MediaPause))
self.solution_type_combo = QComboBox()
self.solution_type_combo.addItems(self.solution_list.keys())
self.new_data_set_button = QPushButton("New Data Set")
self.play_button.setDisabled(True)
self.stop_button.setDisabled(True)
self.pause_button.setDisabled(True)
self.solution_type_combo.setDisabled(True)
self.play_button.clicked.connect(self.solve)
self.pause_button.clicked.connect(self.pause)
# setup layout
self.layout = QGridLayout()
self.data_set_layout = QGridLayout()
self.data_set_layout.addWidget(self.new_data_set_button)
self.layout.addLayout(self.data_set_layout, 1,1)
# self.layout.addWidget(self.infoText, 1, 1, 1)
# self.layout.addWidget(self.simulation, 1, 2)
self.h_layout = QHBoxLayout()
self.h_layout.addWidget(self.play_button)
self.h_layout.addWidget(self.stop_button)
self.h_layout.addWidget(self.pause_button)
self.h_layout.addWidget(self.solution_type_combo)
self.layout.addLayout(self.h_layout, 2, 1)
# self.layout.addWidget(self.simulation, 1, 2)
self.setLayout(self.layout)
self.model = None
self.data = DataStore()
self.current_iteration = 1
self.iteration_limit = 100
self.current_data_set = 0
self.data_string = ''
self.algorithms = Algorithms()
self.algo_screen = ChooseAlgo()
self.trial_time = 0
