def test_rig(self):
G = nx.Graph()
G.add_nodes_from(['i', 'j', 'k'])
G.add_edge('i','j', {'weight': .9})
a1 = rig(G,
pd.Series({'i':1, 'j':1, 'k':1}),
pd.Series({'i':1, 'j':1, 'k':1}))
a2 = rig(G,
pd.Series({'j':Fraction(1, 2),
'k':Fraction(1, 2)}),
pd.Series({'i':Fraction(1, 3),
'j':Fraction(1, 3),
'k':Fraction(1, 3)}))
a3 = rig(G,
pd.Series({'j':1,'k':1}),
pd.Series({'i':1,'k':1}))
a4 = rig(G,
pd.Series({'i':Fraction(1, 2),
'j':Fraction(1, 2)}),
pd.Series({'i':Fraction(1, 3),
'j':Fraction(1, 3),
'k':Fraction(1, 3)}))
a5 = rig(G,
pd.Series({'i':1,'k':1}),
pd.Series({'i':1,'j':1}))
a6 = rig(G,
pd.Series({'i':Fraction(1, 3),
'j':Fraction(1, 3),
'k':Fraction(1, 3)}),
pd.Series({'j':1}))
a7 = rig(G,
pd.Series({'i':Fraction(1, 3),
'j':Fraction(1, 3),
'k':Fraction(1, 3)}),
pd.Series({'k':1}))
a8 = rig(G,
pd.Series({'i':Fraction(1, 2),
'k':Fraction(1, 2)}),
pd.Series({'j':1}))
a9 = rig(G,
pd.Series({'i':Fraction(1, 2),
'j':Fraction(1, 2)}),
pd.Series({'k':1}))
self.assertLessEqual(a1, a2)
self.assertLessEqual(a2, a3)
self.assertLessEqual(a3, a4)
self.assertLessEqual(a4, a5)
self.assertLessEqual(a5, a6)
self.assertLessEqual(a6, a7)
self.assertLessEqual(a7, a8)
self.assertLessEqual(a8, a9)
def test_rig_pairwise(self):
from rig import rig_component, rig, rig_pairwise
import pandas as pd
import numpy as np
import networkx as nx
import unittest
from fractions import Fraction
import pickle
from functools import partial
from sklearn.metrics.pairwise import pairwise_distances
G = nx.Graph()
G.add_nodes_from(['i', 'j', 'k'])
G.add_edge('i', 'j', {'weight': .9})
X = pd.DataFrame(np.array([[1, 1, 1], [1, 2, 1]]),
columns=['i', 'j', 'k'],
index=['s1', 's2'])
labs = X.columns.values
rig_func = partial(rig, G=G, labs=labs)
# Note cannot work with pandas
dm = pairwise_distances(X.values, metric=rig_func, n_jobs=1)
dm = rig_pairwise(G, X)
# This scenario is broken - 2 get normalized to 1.
x = pd.Series([1, 1, 1], index=['i', 'j', 'k'])
y = pd.Series([1, 1, 2], index=['i', 'j', 'k'])
d = rig(x, y, G)
def test_rig_pairwise(self):
from rig import rig_component, rig, rig_pairwise
import pandas as pd
import numpy as np
import networkx as nx
import unittest
from fractions import Fraction
import pickle
from functools import partial
from sklearn.metrics.pairwise import pairwise_distances
G = nx.Graph()
G.add_nodes_from(['i', 'j', 'k'])
G.add_edge('i','j', {'weight': .9})
X = pd.DataFrame(np.array([[1, 1, 1],
[1, 2, 1]]),
columns=['i', 'j', 'k'],
index=['s1', 's2'])
labs = X.columns.values
rig_func = partial(rig, G=G, labs=labs)
# Note cannot work with pandas
dm = pairwise_distances(X.values, metric=rig_func, n_jobs=1)
dm = rig_pairwise(G, X)
# This scenario is broken - 2 get normalized to 1.
x = pd.Series([1, 1, 1], index=['i', 'j', 'k'])
y = pd.Series([1, 1, 2], index=['i', 'j', 'k'])
d = rig(x, y, G)
def test_rig(self):
G = nx.Graph()
G.add_nodes_from(['i', 'j', 'k'])
G.add_edge('i', 'j', {'weight': .9})
a1 = rig(G, pd.Series({
'i': 1,
'j': 1,
'k': 1
}), pd.Series({
'i': 1,
'j': 1,
'k': 1
}))
a2 = rig(
G, pd.Series({
'j': Fraction(1, 2),
'k': Fraction(1, 2)
}),
pd.Series({
'i': Fraction(1, 3),
'j': Fraction(1, 3),
'k': Fraction(1, 3)
}))
a3 = rig(G, pd.Series({'j': 1, 'k': 1}), pd.Series({'i': 1, 'k': 1}))
a4 = rig(
G, pd.Series({
'i': Fraction(1, 2),
'j': Fraction(1, 2)
}),
pd.Series({
'i': Fraction(1, 3),
'j': Fraction(1, 3),
'k': Fraction(1, 3)
}))
a5 = rig(G, pd.Series({'i': 1, 'k': 1}), pd.Series({'i': 1, 'j': 1}))
a6 = rig(
G,
pd.Series({
'i': Fraction(1, 3),
'j': Fraction(1, 3),
'k': Fraction(1, 3)
}), pd.Series({'j': 1}))
a7 = rig(
G,
pd.Series({
'i': Fraction(1, 3),
'j': Fraction(1, 3),
'k': Fraction(1, 3)
}), pd.Series({'k': 1}))
a8 = rig(G, pd.Series({
'i': Fraction(1, 2),
'k': Fraction(1, 2)
}), pd.Series({'j': 1}))
a9 = rig(G, pd.Series({
'i': Fraction(1, 2),
'j': Fraction(1, 2)
}), pd.Series({'k': 1}))
self.assertLessEqual(a1, a2)
self.assertLessEqual(a2, a3)
self.assertLessEqual(a3, a4)
self.assertLessEqual(a4, a5)
self.assertLessEqual(a5, a6)
self.assertLessEqual(a6, a7)
self.assertLessEqual(a7, a8)
self.assertLessEqual(a8, a9)