This repository has been archived on 2023-03-25. You can view files and clone it, but cannot push or open issues or pull requests.
mightyscape-1.1-deprecated/extensions/fablabchemnitz/networkx/tests/test_convert_pandas.py

174 lines
7.7 KiB
Python
Raw Normal View History

2020-07-30 01:16:18 +02:00
import pytest
pd = pytest.importorskip("pandas")
import networkx as nx
from networkx.testing import assert_nodes_equal, assert_edges_equal, \
assert_graphs_equal
class TestConvertPandas(object):
def setup_method(self):
self.rng = pd.np.random.RandomState(seed=5)
ints = self.rng.randint(1, 11, size=(3, 2))
a = ['A', 'B', 'C']
b = ['D', 'A', 'E']
df = pd.DataFrame(ints, columns=['weight', 'cost'])
df[0] = a # Column label 0 (int)
df['b'] = b # Column label 'b' (str)
self.df = df
mdf = pd.DataFrame([[4, 16, 'A', 'D']],
columns=['weight', 'cost', 0, 'b'])
self.mdf = df.append(mdf)
def test_exceptions(self):
G = pd.DataFrame(["a"]) # adj
pytest.raises(nx.NetworkXError, nx.to_networkx_graph, G)
G = pd.DataFrame(["a", 0.0]) # elist
pytest.raises(nx.NetworkXError, nx.to_networkx_graph, G)
df = pd.DataFrame([[1, 1], [1, 0]], dtype=int,
index=[1, 2], columns=["a", "b"])
pytest.raises(nx.NetworkXError, nx.from_pandas_adjacency, df)
def test_from_edgelist_all_attr(self):
Gtrue = nx.Graph([('E', 'C', {'cost': 9, 'weight': 10}),
('B', 'A', {'cost': 1, 'weight': 7}),
('A', 'D', {'cost': 7, 'weight': 4})])
G = nx.from_pandas_edgelist(self.df, 0, 'b', True)
assert_graphs_equal(G, Gtrue)
# MultiGraph
MGtrue = nx.MultiGraph(Gtrue)
MGtrue.add_edge('A', 'D', cost=16, weight=4)
MG = nx.from_pandas_edgelist(self.mdf, 0, 'b', True, nx.MultiGraph())
assert_graphs_equal(MG, MGtrue)
def test_from_edgelist_multi_attr(self):
Gtrue = nx.Graph([('E', 'C', {'cost': 9, 'weight': 10}),
('B', 'A', {'cost': 1, 'weight': 7}),
('A', 'D', {'cost': 7, 'weight': 4})])
G = nx.from_pandas_edgelist(self.df, 0, 'b', ['weight', 'cost'])
assert_graphs_equal(G, Gtrue)
def test_from_edgelist_multi_attr_incl_target(self):
Gtrue = nx.Graph([('E', 'C', {0: 'C', 'b': 'E', 'weight': 10}),
('B', 'A', {0: 'B', 'b': 'A', 'weight': 7}),
('A', 'D', {0: 'A', 'b': 'D', 'weight': 4})])
G = nx.from_pandas_edgelist(self.df, 0, 'b', [0, 'b', 'weight'])
assert_graphs_equal(G, Gtrue)
def test_from_edgelist_multidigraph_and_edge_attr(self):
# example from issue #2374
edges = [('X1', 'X4', {'Co': 'zA', 'Mi': 0, 'St': 'X1'}),
('X1', 'X4', {'Co': 'zB', 'Mi': 54, 'St': 'X2'}),
('X1', 'X4', {'Co': 'zB', 'Mi': 49, 'St': 'X3'}),
('X1', 'X4', {'Co': 'zB', 'Mi': 44, 'St': 'X4'}),
('Y1', 'Y3', {'Co': 'zC', 'Mi': 0, 'St': 'Y1'}),
('Y1', 'Y3', {'Co': 'zC', 'Mi': 34, 'St': 'Y2'}),
('Y1', 'Y3', {'Co': 'zC', 'Mi': 29, 'St': 'X2'}),
('Y1', 'Y3', {'Co': 'zC', 'Mi': 24, 'St': 'Y3'}),
('Z1', 'Z3', {'Co': 'zD', 'Mi': 0, 'St': 'Z1'}),
('Z1', 'Z3', {'Co': 'zD', 'Mi': 14, 'St': 'X3'})]
Gtrue = nx.MultiDiGraph(edges)
df = pd.DataFrame.from_dict({
'O': ['X1', 'X1', 'X1', 'X1', 'Y1', 'Y1', 'Y1', 'Y1', 'Z1', 'Z1'],
'D': ['X4', 'X4', 'X4', 'X4', 'Y3', 'Y3', 'Y3', 'Y3', 'Z3', 'Z3'],
'St': ['X1', 'X2', 'X3', 'X4', 'Y1', 'Y2', 'X2', 'Y3', 'Z1', 'X3'],
'Co': ['zA', 'zB', 'zB', 'zB', 'zC', 'zC', 'zC', 'zC', 'zD', 'zD'],
'Mi': [0, 54, 49, 44, 0, 34, 29, 24, 0, 14]})
G1 = nx.from_pandas_edgelist(df, source='O', target='D',
edge_attr=True,
create_using=nx.MultiDiGraph)
G2 = nx.from_pandas_edgelist(df, source='O', target='D',
edge_attr=['St', 'Co', 'Mi'],
create_using=nx.MultiDiGraph)
assert_graphs_equal(G1, Gtrue)
assert_graphs_equal(G2, Gtrue)
def test_from_edgelist_one_attr(self):
Gtrue = nx.Graph([('E', 'C', {'weight': 10}),
('B', 'A', {'weight': 7}),
('A', 'D', {'weight': 4})])
G = nx.from_pandas_edgelist(self.df, 0, 'b', 'weight')
assert_graphs_equal(G, Gtrue)
def test_from_edgelist_int_attr_name(self):
# note: this also tests that edge_attr can be `source`
Gtrue = nx.Graph([('E', 'C', {0: 'C'}),
('B', 'A', {0: 'B'}),
('A', 'D', {0: 'A'})])
G = nx.from_pandas_edgelist(self.df, 0, 'b', 0)
assert_graphs_equal(G, Gtrue)
def test_from_edgelist_invalid_attr(self):
pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist,
self.df, 0, 'b', 'misspell')
pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist,
self.df, 0, 'b', 1)
# see Issue #3562
edgeframe = pd.DataFrame([[0, 1], [1, 2], [2, 0]], columns=['s', 't'])
pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist,
edgeframe, 's', 't', True)
pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist,
edgeframe, 's', 't', 'weight')
pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist,
edgeframe, 's', 't', ['weight', 'size'])
def test_from_edgelist_no_attr(self):
Gtrue = nx.Graph([('E', 'C', {}),
('B', 'A', {}),
('A', 'D', {})])
G = nx.from_pandas_edgelist(self.df, 0, 'b',)
assert_graphs_equal(G, Gtrue)
def test_from_edgelist(self):
# Pandas DataFrame
g = nx.cycle_graph(10)
G = nx.Graph()
G.add_nodes_from(g)
G.add_weighted_edges_from((u, v, u) for u, v in g.edges())
edgelist = nx.to_edgelist(G)
source = [s for s, t, d in edgelist]
target = [t for s, t, d in edgelist]
weight = [d['weight'] for s, t, d in edgelist]
edges = pd.DataFrame({'source': source,
'target': target,
'weight': weight})
GG = nx.from_pandas_edgelist(edges, edge_attr='weight')
assert_nodes_equal(G.nodes(), GG.nodes())
assert_edges_equal(G.edges(), GG.edges())
GW = nx.to_networkx_graph(edges, create_using=nx.Graph)
assert_nodes_equal(G.nodes(), GW.nodes())
assert_edges_equal(G.edges(), GW.edges())
def test_from_adjacency(self):
nodelist = [1, 2]
dftrue = pd.DataFrame([[1, 1], [1, 0]], dtype=int,
index=nodelist, columns=nodelist)
G = nx.Graph([(1, 1), (1, 2)])
df = nx.to_pandas_adjacency(G, dtype=int)
pd.testing.assert_frame_equal(df, dftrue)
def test_roundtrip(self):
# edgelist
Gtrue = nx.Graph([(1, 1), (1, 2)])
df = nx.to_pandas_edgelist(Gtrue)
G = nx.from_pandas_edgelist(df)
assert_graphs_equal(Gtrue, G)
# adjacency
adj = {1: {1: {'weight': 1}, 2: {'weight': 1}}, 2: {1: {'weight': 1}}}
Gtrue = nx.Graph(adj)
df = nx.to_pandas_adjacency(Gtrue, dtype=int)
G = nx.from_pandas_adjacency(df)
assert_graphs_equal(Gtrue, G)
def test_from_adjacency_named(self):
# example from issue #3105
data = {"A": {"A": 0, "B": 0, "C": 0},
"B": {"A": 1, "B": 0, "C": 0},
"C": {"A": 0, "B": 1, "C": 0}}
dftrue = pd.DataFrame(data)
df = dftrue[["A", "C", "B"]]
G = nx.from_pandas_adjacency(df, create_using=nx.DiGraph())
df = nx.to_pandas_adjacency(G, dtype=int)
pd.testing.assert_frame_equal(df, dftrue)