def test_distance_based_on_molecular_formula():
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[0], normalize=False), 0)
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[0], normalize=True), 0)
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[1], normalize=False),
58.0)
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[1], normalize=True),
0.6590909090909091)
def test_distance_based_on_molecular_formula():
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[0], normalize=False), 0
)
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[0], normalize=True), 0
)
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[1], normalize=False), 58.0
)
assert_equal(
distance_based_on_molecular_formula(TEST_MODEL.metabolites[0], TEST_MODEL.metabolites[1], normalize=True),
0.6590909090909091,
)
def test_distance_based_on_molecular_formula(
self): # from network_analysis.util
met1 = Metabolite("H2O", formula="H2O")
met2 = Metabolite("H2O2", formula="H2O2")
met3 = Metabolite("C6H12O6", formula="C6H12O6")
self.assertEqual(
distance_based_on_molecular_formula(met1, met2, normalize=False),
1)
self.assertEqual(
distance_based_on_molecular_formula(met1, met2, normalize=True),
1. / 7)
self.assertEqual(
distance_based_on_molecular_formula(met2, met3, normalize=False),
20)
self.assertEqual(
distance_based_on_molecular_formula(met2, met3, normalize=True),
20. / 28)
self.assertEqual(
distance_based_on_molecular_formula(met1, met3, normalize=False),
21)
self.assertEqual(
distance_based_on_molecular_formula(met1, met3, normalize=True),
21. / 27)
def reactions_to_network(reactions, max_distance=0.3):
"""Convert a list of reactions into a networkx graph.
Parameters
----------
reactions : list
The list of reactions.
max_distance : float, optional
A threshold on the normalized distance between two compounds. If distance is above this threshold,
no edge between those compounds will be created.
Returns
-------
networkx.MultiDiGraph
See Also
--------
distance_based_on_molecular_formula
"""
edges = list()
for reaction in reactions:
substrates = list(reaction.reactants)
for substrate in substrates:
products = list(reaction.products)
for product in products:
try:
distance = distance_based_on_molecular_formula(
substrate, product, normalize=True)
except ValueError:
distance = 0.
if distance <= max_distance:
if reaction.reversibility:
edges.append(
(product, substrate, dict(reaction=reaction)))
edges.append(
(substrate, product, dict(reaction=reaction)))
elif reaction.lower_bound > 0:
edges.append(
(substrate, product, dict(reaction=reaction)))
else:
edges.append(
(product, substrate, dict(reaction=reaction)))
multi_graph = nx.MultiDiGraph(edges)
return multi_graph
def test_distance_based_on_molecular_formula(self): # from network_analysis.util
met1 = Metabolite("H2O", formula="H2O")
met2 = Metabolite("H2O2", formula="H2O2")
met3 = Metabolite("C6H12O6", formula="C6H12O6")
assert distance_based_on_molecular_formula(met1, met2, normalize=False) == 1
assert distance_based_on_molecular_formula(met1, met2, normalize=True) == 1. / 7
assert distance_based_on_molecular_formula(met2, met3, normalize=False) == 20
assert distance_based_on_molecular_formula(met2, met3, normalize=True) == 20. / 28
assert distance_based_on_molecular_formula(met1, met3, normalize=False) == 21
assert distance_based_on_molecular_formula(met1, met3, normalize=True) == 21. / 27
def test_distance_based_on_molecular_formula(self): # from network_analysis.util
met1 = Metabolite("H2O", formula="H2O")
met2 = Metabolite("H2O2", formula="H2O2")
met3 = Metabolite("C6H12O6", formula="C6H12O6")
self.assertEqual(distance_based_on_molecular_formula(met1, met2, normalize=False), 1)
self.assertEqual(distance_based_on_molecular_formula(met1, met2, normalize=True), 1. / 7)
self.assertEqual(distance_based_on_molecular_formula(met2, met3, normalize=False), 20)
self.assertEqual(distance_based_on_molecular_formula(met2, met3, normalize=True), 20. / 28)
self.assertEqual(distance_based_on_molecular_formula(met1, met3, normalize=False), 21)
self.assertEqual(distance_based_on_molecular_formula(met1, met3, normalize=True), 21. / 27)
def reactions_to_network(reactions, max_distance=0.3):
"""Convert a list of reactions into a networkx graph.
Parameters
----------
reactions : list
The list of reactions.
max_distance : float, optional
A threshold on the normalized distance between two compounds. If distance is above this threshold, no edge between
those compounds will be created.
Returns
-------
networkx.MultiDiGraph
See Also
--------
distance_based_on_molecular_formula
"""
edges = list()
for reaction in reactions:
substrates = list(reaction.reactants)
for substrate in substrates:
products = list(reaction.products)
for product in products:
try:
distance = distance_based_on_molecular_formula(substrate, product, normalize=True)
except ValueError:
distance = 0.
if distance <= max_distance:
if reaction.reversibility:
edges.append((product, substrate, dict(reaction=reaction)))
edges.append((substrate, product, dict(reaction=reaction)))
elif reaction.lower_bound > 0:
edges.append((substrate, product, dict(reaction=reaction)))
else:
edges.append((product, substrate, dict(reaction=reaction)))
multi_graph = nx.MultiDiGraph(edges)
return multi_graph
