if ans_out is not None:
fmt = '%.' + str(tolerance) + 'f'
str_ans_corr = fmt % ans_corr
str_ans_out = fmt % ans_out
if str_ans_corr == str_ans_out:
outcome = CORRECT
else:
print >> sys.stderr, "correctness FAILED: %s (correct is %s, output had %s)" % (ppinput(input_graph), str_ans_corr, str_ans_out)
outcome = INCORRECT
# log the result of the correctness check
if rev is not None and run is not None:
if ti is None:
ti = __get_ti(input_graph)
data = CorrResult(ti.dims, ti.min, ti.max, ti.num_verts, ti.num_edges, ti.seed, rev, run, outcome)
try:
DataSet.add_data_to_log_file(data)
print 'logged correctness result to ' + data.get_path()
except DataError, e:
fmt = "Unable to log result to file %s (correct is %s, output had %s): %s"
print >> sys.stderr, fmt % (ppinput(input_graph), str_ans_corr, str_ans_out, e)
return outcome
def main(argv=sys.argv[1:]):
usage = """usage: %prog [options] INPUT_GRAPH OUTPUT_TO_CHECK
Checks the validity of an MST. Exits with code 0 on success. Otherwise, it
prints an error message and exits with a non-zero code. Does not log the result."""
parser = OptionParser(usage)
parser.add_option("-f", "--force-recompute",
# handle -i, -l: collect data for a particular graph(s)
if options.input_graph and options.inputs_list_file:
parser.error('-i and -l are mutually exclusive')
if options.input_graph is not None:
try:
i = extract_input_footer(options.input_graph)
except ExtractInputFooterError, e:
parser.error(e)
input_solns = DataSet({0:InputSolution(i.prec,i.dims,i.min,i.max,i.num_verts,i.num_edges,i.seed)})
elif options.inputs_list_file is not None:
input_solns = DataSet.read_from_file(InputSolution, options.inputs_list_file)
# prepare for a correctness data collection
if options.correctness:
num_on += 1
get_results_for_rev = lambda rev : DataSet.read_from_file(CorrResult, CorrResult.get_path_to(rev))
options.inputs_list_file_arg = '' if options.inputs_list_file is None else ' -l ' + options.inputs_list_file
collect_missing_data = lambda w,x,y,z: collect_missing_correctness_data(w,x,y,z,options.inputs_list_file_arg)
# make sure no more than 1 type of data collection was specified
if num_on > 1:
parser.error('at most one of -c, -d, and -e may be specified')
elif num_on == 0:
# prepare for a performance data collection (default if nothing else is specified)
get_results_for_rev = lambda rev : DataSet.read_from_file(PerfResult, PerfResult.get_path_to(rev))
collect_missing_data = collect_missing_performance_data
# prepare the inputs and revisions for non-weight data collection schemes
if options.num_vertices == 0:
# get all performance inputs if we are not collecting for a single graph
if input_solns is None:
