Example #1
0
def main():
  args, cmd, imported_module = arg.parse_args()

  javac_commands = imported_module.gen_instance(cmd).capture();

  if args.output_directory:
    mkdir(args.output_directory)

  analyze_project(args, javac_commands)
Example #2
0
def main():
    args, cmd, imported_module = arg.parse_args()

    javac_commands = imported_module.gen_instance(cmd).capture()

    if args.output_directory:
        mkdir(args.output_directory)

    analyze_project(args, javac_commands)
Example #3
0
def main():
    args, cmd, capturer = arg.parse_args()

    log.configure_logging(args.output_directory, args.log_to_stderr)
    log.log_header()

    javac_commands, jars = capturer.gen_instance(cmd).capture()

    log.info('Results: %s', pprint.pformat(javac_commands))

    tools.run(args, javac_commands, jars)
Example #4
0
def main():
    args, cmd, capturer = arg.parse_args()

    log.configure_logging(args.output_directory, args.log_to_stderr)
    log.log_header()

    javac_commands, jars = capturer.gen_instance(cmd).capture()

    log.info('Results: %s', pprint.pformat(javac_commands))

    tools.run(args, javac_commands, jars)
def main():
    args, cmd, imported_module = arg.parse_args()
    log.configure_logging(args.output_directory, args.incremental, args.log_to_stderr)

    log_header()

    results = imported_module.gen_instance(cmd).capture()
    logging.info('Results: %s', pprint.pformat(results))

    options = {'print' : print_tool,
               'randoop' : randoop_tool,
               'graphtool' : graph_tool,
    }

    if args.tool:
        options[args.tool](results,args)
Example #6
0
def main():
    args, cmd, imported_module = arg.parse_args()
    log.configure_logging(args.output_directory, args.incremental, args.log_to_stderr)

    log_header()

    javac_commands, jars = imported_module.gen_instance(cmd).capture()
    logging.info('Results: %s', pprint.pformat(javac_commands))

    options = {'soot' : soot_tool,
               'checker' : checker_tool,
               'inference' : inference_tool,
               'print' : print_tool,
               'randoop' : randoop_tool,
               'graphtool' : graph_tool,
    }

    if args.tool:
        options[args.tool](javac_commands,jars,args)
Example #7
0
def main():
    args, cmd, capturer = arg.parse_args()

    log.configure_logging(args.output_directory, args.log_to_stderr)
    log.log_header()

    result = cache.retrieve(cmd, args, capturer)

    if not result:
        print "DLJC: Build command failed."
        sys.exit(1)

    javac_commands, jars, stats = result

    log.info('Results: %s', pprint.pformat(javac_commands))
    output_json(os.path.join(args.output_directory, 'javac.json'), javac_commands)
    output_json(os.path.join(args.output_directory, 'jars.json'), jars)
    output_json(os.path.join(args.output_directory, 'stats.json'), stats)

    tools.run(args, javac_commands, jars)
Example #8
0
def main():
    args, cmd, imported_module = arg.parse_args()
    log.configure_logging(args.output_directory, args.incremental,
                          args.log_to_stderr)

    log_header()

    javac_commands, jars = imported_module.gen_instance(cmd).capture()
    logging.info('Results: %s', pprint.pformat(javac_commands))

    options = {
        'soot': soot_tool,
        'checker': checker_tool,
        'inference': inference_tool,
        'print': print_tool,
        'randoop': randoop_tool,
        'graphtool': graph_tool,
    }

    if args.tool:
        options[args.tool](javac_commands, jars, args)
Example #9
0
        """ For every sign """
        for y in range(self.nbclass):
            """ For every pixel of the image """
            for z in range(len(self.data[0])):
                """ class += (pval(y, z) - val(i, z) """
                tmp[y] += (self.clusters[y].dimensions[z] - img[z])**2
        max = tmp[0]
        id = 0
        for y in range(self.nbclass):
            if tmp[y] < max:
                id = y
        return id


if __name__ == '__main__':
    args = parse_args("kmeans").parse_args(["-r", "-s", "0.01"])
    rand = np.random.randint(0, 10000000)
    print("Fetching data:")
    data, testdata = pre_processed_data(args, rand)
    print("Done")
    print("Fetching labels:")
    label, testlabel = pre_processed_label(args, rand)
    print("Done")
    kmeans = KMEANS(data, 10, label)

    print("Main Loop:")
    for i in range(10):
        print(i)
        print("E:")
        kmeans.E()
        print("Done")