def test_debug(self):
"""
Test the debugging output of the MorseComplex
"""
self.setup()
test_file = "mc_test_debug.txt"
sys.stdout = open(test_file, "w")
self.test_object = topopy.MorseComplex(debug=True, graph=self.graph)
self.test_object.build(self.X, self.Y)
sys.stdout.close()
lines = ["Graph Preparation:", "Decomposition:"]
with open(test_file, "r") as fp:
debug_output = fp.read()
for line in lines:
self.assertIn(line, debug_output)
os.remove(test_file)
# Restore stdout
sys.stdout = sys.__stdout__
def test_load_data_and_build(self):
"""
Tests that loading the same test data from file yields an
equivalent result
"""
self.setup()
test_object = topopy.MorseComplex()
np.savetxt(
"test_file.csv",
np.hstack((self.X, np.atleast_2d(self.Y).T)),
delimiter=",",
header="x0,x1,y",
)
test_object.load_data_and_build("test_file.csv", delimiter=",")
os.remove("test_file.csv")
self.assertDictEqual(
self.test_object.merge_sequence,
test_object.merge_sequence,
"loading from file should produce the same merge sequence",
)
self.assertDictEqual(
dict(self.test_object.base_partitions),
dict(test_object.base_partitions),
"loading from file should produce the base partitions.",
)
def setup(self):
"""
Setup function will create a fixed point set and parameter
settings for testing different aspects of this library.
"""
self.X = generate_test_grid_2d(40)
self.Y = gerber(self.X)
self.graph = ngl.EmptyRegionGraph(max_neighbors=10)
self.norm_x = {}
scaler = sklearn.preprocessing.MinMaxScaler()
self.norm_x["feature"] = scaler.fit_transform(np.atleast_2d(self.X))
self.norm_x["zscore"] = sklearn.preprocessing.scale(self.X,
axis=0,
with_mean=True,
with_std=True,
copy=True)
self.norm_x["none"] = self.X
# Methods covered here:
# __init__
# build
# __set_data
self.test_object = topopy.MorseComplex(debug=False, graph=self.graph)
self.test_object.build(self.X, self.Y)
gold_path = os.path.join("topopy", "tests", "mc_gold.json")
with open(gold_path, "r") as data_file:
gold_json = data_file.read()
gold_json = json.loads(gold_json)
self.gold = gold_json
def test_get_partitions(self):
"""
Test the ability to retrieve partition labels for individual
query points and the entire dataset if not specified
"""
self.setup()
gold_stable_partitions = {}
for i, max_label in enumerate(self.gold["Partitions"]):
if max_label not in gold_stable_partitions:
gold_stable_partitions[max_label] = []
gold_stable_partitions[max_label].append(i)
partitions = self.test_object.get_partitions()
self.assertEqual(
4,
len(partitions),
"The number of partitions without specifying the persistence "
"should be the same as requesting the base (0) persistence level",
)
self.assertDictEqual(
gold_stable_partitions,
partitions,
"The base partitions of the stable manifolds should match",
)
test_p = 0.5
merge_pattern = {}
# Initialize every extrema to point to itself
for merge in self.gold["Hierarchy"]:
merge_pattern[merge["Dying"]] = merge["Dying"]
# Now point to the correct label for the specified persistence
for merge in self.gold["Hierarchy"]:
if merge["Persistence"] < test_p:
if merge["Surviving"] not in merge_pattern:
merge_pattern[merge["Surviving"]] = merge["Surviving"]
merge_pattern[merge["Dying"]] = merge_pattern[
merge["Surviving"]]
gold_stable_partitions = {}
for i, max_label in enumerate(self.gold["Partitions"]):
max_label = merge_pattern[max_label]
if max_label not in gold_stable_partitions:
gold_stable_partitions[max_label] = []
gold_stable_partitions[max_label].append(i)
partitions = self.test_object.get_partitions(test_p)
self.assertEqual(
1,
len(partitions),
"The number of partitions without specifying the persistence "
"should be the same as requesting the base (0) persistence level",
)
self.assertDictEqual(
gold_stable_partitions,
partitions,
"The partitions of the stable manifolds should match at the "
"test level p={}".format(test_p),
)
self.test_object = topopy.MorseComplex()
partitions = self.test_object.get_partitions()
self.assertEqual(
{},
partitions,
"Requesting partitions on an unbuilt object should return an "
"empty dictionary",
)