def get_touch_sheets()

in data_loaders.py [0:0]

• 15 lines of code
• 6 McCabe index (conditional complexity)

	def get_touch_sheets(self, location, hand_info):
		sheets = []
		successful = []
		touches = hand_info['touch_success']
		finger_pos = torch.FloatTensor(hand_info['cam_pos'])
		# cycle through fingers in the grasp
		for i in range(4):
			sheet = np.load(location.replace('finger_num', str(i)))
			# if the touch was unsuccessful
			if not touches[i] or sheet.shape[0] == 1:
				sheets.append(finger_pos[i].view(1, 3).expand(25, 3)) # save the finger position instead in every vertex
				successful.append(False) # binary mask for unsuccessful touch
			# if the touch was successful
			else:
				sheets.append(torch.FloatTensor(sheet)) # save the sheet
				successful.append(True) # binary mask for successful touch
		sheets = torch.stack(sheets)
		return sheets, successful