def test_symmetrize_unweighted(managed, pool, graph_file): gc.collect() rmm.reinitialize(managed_memory=managed, pool_allocator=pool) assert (rmm.is_initialized()) cu_M = utils.read_csv_file(graph_file + '.csv') sym_sources, sym_destinations = cugraph.symmetrize(cu_M['0'], cu_M['1']) # # Check to see if all pairs in sources/destinations exist in # both directions # # Try this with join logic. Note that if we create data frames # we can join the data frames (using the DataFrame.merge function). # The symmetrize function should contain every edge that was contained # in the input data. So if we join the input data with the output # the length of the data frames should be equal. # sym_df = cudf.DataFrame() sym_df['src_s'] = sym_sources sym_df['dst_s'] = sym_destinations orig_df = cudf.DataFrame() orig_df['src'] = cu_M['0'] orig_df['dst'] = cu_M['1'] compare(orig_df['src'], orig_df['dst'], None, sym_df['src_s'], sym_df['dst_s'], None)
def test_symmetrize_unweighted(graph_file): gc.collect() cu_M = utils.read_csv_file(graph_file) sym_sources, sym_destinations = cugraph.symmetrize(cu_M["0"], cu_M["1"]) # # Check to see if all pairs in sources/destinations exist in # both directions # # Try this with join logic. Note that if we create data frames # we can join the data frames (using the DataFrame.merge function). # The symmetrize function should contain every edge that was contained # in the input data. So if we join the input data with the output # the length of the data frames should be equal. # sym_df = cudf.DataFrame() sym_df["src_s"] = sym_sources sym_df["dst_s"] = sym_destinations orig_df = cudf.DataFrame() orig_df["src"] = cu_M["0"] orig_df["dst"] = cu_M["1"] compare( orig_df["src"], orig_df["dst"], None, sym_df["src_s"], sym_df["dst_s"], None, )
def test_symmetrize_weighted(graph_file): gc.collect() cu_M = utils.read_csv_file(graph_file) sym_src, sym_dst, sym_w = cugraph.symmetrize(cu_M["0"], cu_M["1"], cu_M["2"]) compare(cu_M["0"], cu_M["1"], cu_M["2"], sym_src, sym_dst, sym_w)
def test_symmetrize_weighted(graph_file): gc.collect() cu_M = utils.read_csv_file(graph_file+'.csv') sym_src, sym_dst, sym_w = cugraph.symmetrize(cu_M['0'], cu_M['1'], cu_M['2']) compare(cu_M['0'], cu_M['1'], cu_M['2'], sym_src, sym_dst, sym_w)
def test_mg_symmetrize(graph_file, client_connection): gc.collect() ddf = utils.read_dask_cudf_csv_file(graph_file) sym_src, sym_dst = cugraph.symmetrize(ddf["src"], ddf["dst"]) # convert to regular cudf to facilitate comparison df = ddf.compute() compare(df["src"], df["dst"], None, sym_src.compute(), sym_dst.compute(), None)
def test_symmetrize_weighted(managed, pool, graph_file): gc.collect() rmm.reinitialize(managed_memory=managed, pool_allocator=pool) assert (rmm.is_initialized()) cu_M = utils.read_csv_file(graph_file + '.csv') sym_src, sym_dst, sym_w = cugraph.symmetrize(cu_M['0'], cu_M['1'], cu_M['2']) compare(cu_M['0'], cu_M['1'], cu_M['2'], sym_src, sym_dst, sym_w)
def test_symmetrize_unweighted(graph_file): gc.collect() cu_M = utils.read_csv_file(graph_file) sym_sources, sym_destinations = cugraph.symmetrize(cu_M["0"], cu_M["1"]) # # Check to see if all pairs in sources/destinations exist in # both directions # compare( cu_M["0"], cu_M["1"], None, sym_sources, sym_destinations, None, )