erap129’s gists

erap129 / auto_feature_generation.py

Created September 27, 2021 12:08

NASA RUL project - automatic feature generation

	all_rollings_df_X = all_rollings_df.drop(columns=['RUL'])

	extracted_features = extract_features(all_rollings_df_X,
	column_id="instance_id", column_sort="time",
	n_jobs=4, default_fc_parameters=tsfresh.feature_extraction.settings.MinimalFCParameters())
	impute(extracted_features)
	features_filtered = select_features(extracted_features, y_train_rolling, n_jobs=4)

	def get_last_window_from_unit(group_df):
	res_df = group_df[[x for x in test_df.columns if 'sensor_' in x]].iloc[-10:]

erap129 / manual_feature_generation.py

Created September 27, 2021 12:11

NASA RUL project - manual feature generation

	def avg_diff(series):
	return np.mean(np.diff(series))

	all_rollings_grouped = all_rollings_df_X.drop(columns=['time']).groupby('instance_id').agg(['mean', avg_diff, 'std', 'max', 'min'])

	test_df_grouped = test_df.sort_values(['unit_number', 'time']).groupby('unit_number').\
	apply(lambda group_df: group_df[[x for x in test_df.columns if 'sensor_' in x]].\
	iloc[-WINDOW_SIZE:]).reset_index()
	test_df_aggregated = test_df_grouped.drop(columns=['level_1']).groupby('unit_number').agg(['mean', avg_diff, 'std', 'max', 'min'])

erap129 / pytorch_dataloader.py

Last active September 28, 2021 16:39

NASA RUL project - pytorch data loader

	from torch.utils.data import TensorDataset

	class RULDataModule(pl.LightningDataModule):
	def __init__(self, X_train, y_train, X_val, y_val, X_test, y_test,
	batch_size):
	super().__init__()
	self.X_train = X_train
	self.y_train = y_train
	self.X_val = X_val
	self.y_val = y_val

erap129 / pytorch_lstm_model.py

Created September 27, 2021 13:07

NASA RUL project - LSTM model

	class RULModel(nn.Module):
	def __init__(self, n_features, n_hidden=256, n_layers=3):
	super().__init__()
	self.lstm = nn.LSTM(
	input_size=n_features,
	hidden_size=n_hidden,
	num_layers=n_layers,
	batch_first=True,
	dropout=0.75
	)

erap129 / train_lstm.py

Created September 27, 2021 14:26

NASA RUL project - lstm training

	checkpoint_callback = ModelCheckpoint(
	dirpath='checkpoints',
	filename='best-checkpoint',
	save_top_k=1,
	verbose=True,
	monitor='val_loss',
	mode='min'
	)

	logger = TensorBoardLogger('lightning_logs', name='RUL')

erap129 / get_lstm_results.py

Last active September 28, 2021 07:30

NASA RUL project - get lstm results

	from tqdm import tqdm

	def get_predictions_and_labels_lstm(dataset):
	predictions = []
	labels = []
	for item in tqdm(test_dataset):
	X, y = item
	_, output = trained_model(X.unsqueeze(dim=0))
	predictions.append(output.item())
	labels.append(y.item())

erap129 / FD001_head.csv

Created October 6, 2021 09:32

NASA RUL project - FD001 head

We can make this file beautiful and searchable if this error is corrected: It looks like row 6 should actually have 29 columns, instead of 15 in line 5.

	,unit_number,time,sensor_1,sensor_2,sensor_3,sensor_4,sensor_5,sensor_6,sensor_7,sensor_8,sensor_9,sensor_10,sensor_11,sensor_12,sensor_13,sensor_14,sensor_15,sensor_16,sensor_17,sensor_18,sensor_19,sensor_20,sensor_21,sensor_22,sensor_23,sensor_24,sensor_25,sensor_26
	0,1,1,-0.0007,-0.0004,100.0,518.67,641.82,1589.7,1400.6,14.62,21.61,554.36,2388.06,9046.19,1.3,47.47,521.66,2388.02,8138.62,8.4195,0.03,392,2388,100.0,39.06,23.419,,
	1,1,2,0.0019,-0.0003,100.0,518.67,642.15,1591.82,1403.14,14.62,21.61,553.75,2388.04,9044.07,1.3,47.49,522.28,2388.07,8131.49,8.4318,0.03,392,2388,100.0,39.0,23.4236,,
	2,1,3,-0.0043,0.0003,100.0,518.67,642.35,1587.99,1404.2,14.62,21.61,554.26,2388.08,9052.94,1.3,47.27,522.42,2388.03,8133.23,8.4178,0.03,390,2388,100.0,38.95,23.3442,,
	3,1,4,0.0007,0.0,100.0,518.67,642.35,1582.79,1401.87,14.62,21.61,554.45,2388.11,9049.48,1.3,47.13,522.86,2388.08,8133.83,8.3682,0.03,392,2388,100.0,38.88,23.3739,,
	4,1,5,-0.0019,-0.0002,100.0,518.67,642.37,1582.85,1406.22,14.62,21.61,554.0,2388.06,9055.15

erap129 / main_window_1.py

Created January 15, 2022 15:28

image_tracer_main_window_1

	class MainWindow(QMainWindow):
	def __init__(self):
	super(MainWindow, self).__init__()

	self.setWindowTitle("Image Tracer")

	main_layout = QVBoxLayout()
	top_bar_layout = QHBoxLayout()
	image_bar_layout = QHBoxLayout()
	self.source_filename = None

erap129 / image_tracer_main_window.py

Created January 15, 2022 15:33

	select_image_button = QPushButton('Select Image')
	process_image_button = QPushButton('Process!')
	select_image_button.clicked.connect(self.choose_source_image)
	process_image_button.clicked.connect(self.process_image)
	for btn in [select_image_button, process_image_button]:
	btn.setFixedHeight(30)
	btn.setFixedWidth(100)
	self.r_select = QSpinBox()
	self.g_select = QSpinBox()
	self.b_select = QSpinBox()

erap129 / image_tracer_main_window_3.py

Created January 15, 2022 15:47

	top_bar_layout.addWidget(select_image_button)
	top_bar_layout.addWidget(self.r_select)
	top_bar_layout.addWidget(self.g_select)
	top_bar_layout.addWidget(self.b_select)
	top_bar_layout.addWidget(self.threshold_select)
	top_bar_layout.addWidget(process_image_button)

	self.source_image = ImageWidget()
	self.result_image = ImageWidget()
	self.source_image.setMaximumSize(self.max_img_width, self.max_img_height)

Elad Rapaport erap129