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[REVIEW] Add un-renumbering to connected components and update tests #771

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Mar 20, 2020
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[REVIEW] Add un-renumbering to connected components and update tests #771

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b298ee9
add unrenumbering to connected components and update tests
Iroy30 Mar 19, 2020
2e663af
change to previous column names
Iroy30 Mar 19, 2020
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@
- PR #753 ECG Error
- PR #758 Fix for graph comparison failure
- PR #761 Added flag to not treat deprecation warnings as errors, for now
- PR #771 Added unrenumbering in wcc and scc. Updated tests to compare vertices of largest component

# cuGraph 0.12.0 (04 Feb 2020)

Expand Down
15 changes: 11 additions & 4 deletions python/cugraph/components/connectivity_wrapper.pyx
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Expand Up @@ -24,6 +24,7 @@ from cudf._lib.utils cimport table_from_dataframe
from libc.stdint cimport uintptr_t
from cugraph.structure.symmetrize import symmetrize
from cugraph.structure.graph import Graph as type_Graph
from cugraph.utilities.unrenumber import unrenumber

import cudf
import cudf._lib as libcudf
Expand Down Expand Up @@ -61,8 +62,8 @@ def weakly_connected_components(input_graph):
num_verts = g.adjList.offsets.size - 1

df = cudf.DataFrame()
df['labels'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))
df['vertices'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))
df['label'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))
df['vertex'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))

cdef cudf_table* tbl = table_from_dataframe(df)

Expand All @@ -72,6 +73,9 @@ def weakly_connected_components(input_graph):

del tbl

if input_graph.renumbered:
df = unrenumber(input_graph.edgelist.renumber_map, df, 'vertex')

return df


Expand All @@ -98,8 +102,8 @@ def strongly_connected_components(input_graph):
num_verts = g.adjList.offsets.size - 1

df = cudf.DataFrame()
df['labels'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))
df['vertices'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))
df['label'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))
df['vertex'] = cudf.Series(np.zeros(num_verts, dtype=np.int32))

cdef cudf_table* tbl = table_from_dataframe(df)

Expand All @@ -109,4 +113,7 @@ def strongly_connected_components(input_graph):

del tbl

if input_graph.renumbered:
df = unrenumber(input_graph.edgelist.renumber_map, df, 'vertex')

return df
77 changes: 35 additions & 42 deletions python/cugraph/tests/test_connectivity.py
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Expand Up @@ -14,7 +14,7 @@
import gc
from itertools import product
import time

from collections import defaultdict
import pytest

import cugraph
Expand Down Expand Up @@ -53,7 +53,6 @@ def networkx_weak_call(M):
# same parameters as in NVGRAPH
result = nx.weakly_connected_components(Gnx)
t2 = time.time() - t1

print('Time : ' + str(t2))

labels = sorted(result)
Expand All @@ -69,10 +68,10 @@ def cugraph_weak_call(cu_M):
t2 = time.time() - t1
print('Time : '+str(t2))

result = df['labels'].to_array()

labels = sorted(result)
return labels
label_vertex_dict = defaultdict(list)
for i in range(len(df)):
label_vertex_dict[df['label'][i]].append(df['vertex'][i])
return label_vertex_dict


def networkx_strong_call(M):
Expand All @@ -97,16 +96,15 @@ def cugraph_strong_call(cu_M):
# cugraph Pagerank Call
G = cugraph.DiGraph()
G.from_cudf_edgelist(cu_M, source='0', destination='1')
print(G.number_of_vertices())
t1 = time.time()
df = cugraph.strongly_connected_components(G)
t2 = time.time() - t1
print('Time : '+str(t2))

result = df['labels'].to_array()

labels = sorted(result)
return labels
label_vertex_dict = defaultdict(list)
for i in range(len(df)):
label_vertex_dict[df['label'][i]].append(df['vertex'][i])
return label_vertex_dict


# these should come w/ cugraph/python:
Expand All @@ -119,27 +117,6 @@ def cugraph_strong_call(cu_M):
'../datasets/email-Eu-core.csv']


# vcount how many `val`s in ls container:
#
def counter_f(ls, val):
return sum(1 for x in ls if x == val)


# return number of uniques values in lst container:
#
def get_n_uniqs(lst):
return len(set(lst))


# gets unique values of list and then counts the
# occurences of each unique value within list;
# note: because of using set(), the "keys"
# (unique values) will be sorted in set(lst)
#
def get_uniq_counts(lst):
return [counter_f(lst, uniq_val) for uniq_val in set(lst)]


# Test all combinations of default/managed and pooled/non-pooled allocation
@pytest.mark.parametrize('managed, pool',
list(product([False, True], [False, True])))
Expand Down Expand Up @@ -167,18 +144,26 @@ def test_weak_cc(managed, pool, graph_file):
# while cugraph returns a component label for each vertex;

nx_n_components = len(netx_labels)
cg_n_components = get_n_uniqs(cugraph_labels)
cg_n_components = len(cugraph_labels)

# Comapre number of components
assert nx_n_components == cg_n_components

lst_nx_components_lens = [len(c) for c in sorted(netx_labels, key=len)]
lst_nx_components = sorted(netx_labels, key=len, reverse=True)
lst_nx_components_lens = [len(c) for c in lst_nx_components]

# get counts of uniques:
#
lst_cg_components_lens = sorted(get_uniq_counts(cugraph_labels))
cugraph_vertex_lst = cugraph_labels.values()
lst_cg_components = sorted(cugraph_vertex_lst, key=len, reverse=True)
lst_cg_components_lens = [len(c) for c in lst_cg_components]

# Compare lengths of each component
assert lst_nx_components_lens == lst_cg_components_lens

# Compare vertices of largest component
nx_vertices = sorted(lst_nx_components[0])
cg_vertices = sorted(lst_cg_components[0])
assert nx_vertices == cg_vertices


# Test all combinations of default/managed and pooled/non-pooled allocation
@pytest.mark.parametrize('managed, pool',
Expand Down Expand Up @@ -207,14 +192,22 @@ def test_strong_cc(managed, pool, graph_file):
# while cugraph returns a component label for each vertex;

nx_n_components = len(netx_labels)
cg_n_components = get_n_uniqs(cugraph_labels)
cg_n_components = len(cugraph_labels)

# Comapre number of components
assert nx_n_components == cg_n_components

lst_nx_components_lens = [len(c) for c in sorted(netx_labels, key=len)]
lst_nx_components = sorted(netx_labels, key=len, reverse=True)
lst_nx_components_lens = [len(c) for c in lst_nx_components]

# get counts of uniques:
#
lst_cg_components_lens = sorted(get_uniq_counts(cugraph_labels))
cugraph_vertex_lst = cugraph_labels.values()
lst_cg_components = sorted(cugraph_vertex_lst, key=len, reverse=True)
lst_cg_components_lens = [len(c) for c in lst_cg_components]

# Compare lengths of each component
assert lst_nx_components_lens == lst_cg_components_lens

# Compare vertices of largest component
nx_vertices = sorted(lst_nx_components[0])
cg_vertices = sorted(lst_cg_components[0])
assert nx_vertices == cg_vertices