How to use _get_kernel_data method in autotest

Best Python code snippet using autotest_python Github


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...344 self.parser.add_option('--require-ssp',345 help='Require server-side packaging',346 default=False, action='store_true')347 @staticmethod348 def _get_kernel_data(kernel_list, cmdline):349 # the RPC supports cmdline per kernel version in a dictionary350 kernels = []351 for version in re.split(r'[, ]+', kernel_list):352 if not version:353 continue354 kernel_info = {'version': version}355 if cmdline:356 kernel_info['cmdline'] = cmdline357 kernels.append(kernel_info)358 return kernels359 def parse(self):360 deps_info = topic_common.item_parse_info(attribute_name='dependencies',361 inline_option='dependencies')362 options, leftover = super(job_create, self).parse(363 parse_info=[deps_info])364 if (len(self.hosts) == 0 and not self.one_time_hosts365 and not options.labels and not options.atomic_group):366 self.invalid_syntax('Must specify at least one machine '367 'or an atomic group '368 '(-m, -M, -b, -G or --one-time-hosts).')369 if not options.control_file and not options.test:370 self.invalid_syntax('Must specify either --test or --control-file'371 ' to create a job.')372 if options.control_file and options.test:373 self.invalid_syntax('Can only specify one of --control-file or '374 '--test, not both.')375 if options.kernel:376 self.ctrl_file_data['kernel'] = self._get_kernel_data(377 options.kernel, options.kernel_cmdline)378 if options.control_file:379 try:380 control_file_f = open(options.control_file)381 try:382 control_file_data = finally:384 control_file_f.close()385 except IOError:386 self.generic_error('Unable to read from specified '387 'control-file: %s' % options.control_file)388 if options.kernel:389 # execute() will pass this to the AFE server to wrap this390 # control file up to include the kernel installation steps....

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...16 self.pc_distance = pc_distance17 # Initialize Kernel Size (with Same Width and Height)18 self.kernel_size = kernel_size19 # Get LiDAR Kernel Data20 = self._get_kernel_data(21 frame=sensor_data.get_data()22 )23 pass24 def get_kernel_average_depth(self):25 return np.average( def _get_kernel_data(self, frame):27 """28 :param frame: 2-D ndarray (only 2-D ndarray is supported for now...!)29 """30 assert len(frame.shape) == 231 # u-coordinate compensation32 u_min = np.round(self.c_u - 0.5*self.kernel_size).astype(int)33 u_min = 0 if u_min < 0 else u_min34 u_max = np.round(self.c_u + 0.5*self.kernel_size).astype(int)35 u_max = frame.shape[1] - 1 if u_max >= frame.shape[1] else u_max36 # v-coordinate compensation37 v_min = np.round(self.c_v - 0.5*self.kernel_size).astype(int)38 v_min = 0 if v_min < 0 else v_min39 v_max = np.round(self.c_v + 0.5*self.kernel_size).astype(int)40 v_max = frame.shape[0] - 1 if v_max >= frame.shape[0] else v_max...

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