diff options
Diffstat (limited to 'src/python/test/pyeclib_test.py')
| -rw-r--r-- | src/python/test/pyeclib_test.py | 20 |
1 files changed, 15 insertions, 5 deletions
diff --git a/src/python/test/pyeclib_test.py b/src/python/test/pyeclib_test.py index cabf28e..bc69a23 100644 --- a/src/python/test/pyeclib_test.py +++ b/src/python/test/pyeclib_test.py @@ -198,6 +198,7 @@ def test_get_fragment_partition( whole_file_bytes = fp.read() fragments = pyeclib_c.encode(handle, whole_file_bytes) + # print(fragments) for i in range(iterations): missing_fragments = random.sample(fragments, 3) @@ -246,7 +247,8 @@ def test_get_required_fragments(num_data, num_parity, w, ec_type): # # MDS codes need any k fragments # - if ec_type in ["rs_vand", "rs_cauchy_orig"]: + # if ec_type in ["rs_vand_isa_l", "rs_vand", "rs_cauchy_orig"]: + if ec_type in ["rs_vand_isa_l"]: expected_fragments = [i for i in range(num_data + num_parity)] missing_fragments = [] @@ -282,13 +284,17 @@ def get_throughput(avg_time, size_str): return (format(throughput, '.10g')) +#num_datas = [12, 12, 12] +#num_parities = [2, 3, 4] num_datas = [12, 12, 12] -num_parities = [2, 3, 4] +num_parities = [3, 4, 4] iterations = 100 -rs_types = [("rs_vand", 16), ("rs_cauchy_orig", 4)] -xor_types = [("flat_xor_4", 12, 6, 4), ( - "flat_xor_4", 10, 5, 4), ("flat_xor_3", 10, 5, 3)] +# rs_types = [("rs_vand", 16), ("rs_vand_isa_l", 16), ("rs_cauchy_orig", 4)] +rs_types = [("rs_vand_isa_l", 8)] +#xor_types = [("flat_xor_4", 12, 6, 4), ( +# "flat_xor_4", 10, 5, 4), ("flat_xor_3", 10, 5, 3)] +xor_types = [] sizes = ["101-K", "202-K", "303-K"] @@ -319,17 +325,21 @@ for (ec_type, w) in rs_types: for i in range(len(num_datas)): for size_str in sizes: + print("%d encode\n" % i) test_get_fragment_partition( num_datas[i], num_parities[i], w, ec_type, size_str, iterations) + print("1 encode\n") for i in range(len(num_datas)): for size_str in sizes: test_fragments_to_string( num_datas[i], num_parities[i], w, ec_type, size_str) + print("2 encode\n") for i in range(len(num_datas)): test_get_required_fragments(num_datas[i], num_parities[i], w, ec_type) + print("3 encode\n") for i in range(len(num_datas)): for size_str in sizes: avg_time = time_encode( |