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from nose import SkipTest
from nose.tools import assert_true
import networkx as nx
class TestConvertPandas(object):
numpy=1 # nosetests attribute, use nosetests -a 'not numpy' to skip test
@classmethod
def setupClass(cls):
try:
import pandas as pd
except ImportError:
raise SkipTest('Pandas not available.')
def __init__(self, ):
global pd
import pandas as pd
self.r = pd.np.random.RandomState(seed=5)
ints = self.r.random_integers(1, 10, 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
def assert_equal(self, G1, G2):
assert_true( nx.is_isomorphic(G1, G2, edge_match=lambda x, y: x == y ))
def test_from_dataframe_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_dataframe(self.df, 0, 'b', True)
self.assert_equal(G, Gtrue)
def test_from_dataframe_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_dataframe(self.df, 0, 'b', ['weight', 'cost'])
self.assert_equal(G, Gtrue)
def test_from_dataframe_one_attr(self, ):
Gtrue = nx.Graph([('E', 'C', {'weight': 10}),
('B', 'A', {'weight': 7}),
('A', 'D', {'weight': 4})])
G=nx.from_pandas_dataframe(self.df, 0, 'b', 'weight')
self.assert_equal(G, Gtrue)
def test_from_dataframe_no_attr(self, ):
Gtrue = nx.Graph([('E', 'C', {}),
('B', 'A', {}),
('A', 'D', {})])
G=nx.from_pandas_dataframe(self.df, 0, 'b',)
self.assert_equal(G, Gtrue)
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