def test_initialize_cdesf(self, process, cases_list):
assert process.nyquist == 0
assert process.check_point_cases == 0
assert len(process.process_model_graph.edges) == 0
assert len(process.process_model_graph.nodes) == 0
assert process.cases == []
with pytest.raises(Exception):
assert initialize_graph([])
case4 = Case("4")
case4.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case4.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
})
case4.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
})
process.cases = cases_list
process.cases.insert(0, case4)
process.process_model_graph = initialize_graph(process.cases)
pmg = initialize_graph(cases_list)
for case in cases_list:
case.distances = calculate_case_distances(pmg, case)
def simple_graph(self):
case_list = []
case = Case("1")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
})
case_list.append(case)
case = Case("2")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
})
case_list.append(case)
case = Case("3")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
})
case.add_event({
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 30),
})
case_list.append(case)
graph = initialize_graph(case_list)
return graph
def test_initialize_case_metrics(self, process: CDESF,
cases_list: "list[Case]"):
process.initialize_case_metrics()
assert process.cases == []
process.cases = cases_list
case_3 = process.cases[0]
assert case_3.distances.get("graph") is None
assert case_3.distances.get("graph") is None
case_2 = process.cases[1]
assert case_2.distances.get("graph") is None
assert case_2.distances.get("graph") is None
case_1 = process.cases[2]
assert case_1.distances.get("graph") is None
assert case_1.distances.get("graph") is None
process.initialize_case_metrics()
case_3 = process.cases[0]
assert case_3.distances["graph"] == 0
assert case_3.distances["time"] == 0
case_2 = process.cases[1]
assert case_2.distances["graph"] == 0
assert case_2.distances["time"] == 0
case_1 = process.cases[2]
assert case_1.distances["graph"] == 0
assert case_1.distances["time"] == 0
process.cases = cases_list
process.process_model_graph = initialize_graph(process.cases)
process.initialize_case_metrics()
case_3 = process.cases[0]
# Verify that the distances are applied.
distances_for_case_3 = calculate_case_distances(
process.process_model_graph, case_3)
assert case_3.distances["graph"] == distances_for_case_3["graph"]
assert case_3.distances["time"] == distances_for_case_3["time"]
distances_for_case_2 = calculate_case_distances(
process.process_model_graph, case_2)
case_2 = process.cases[1]
assert case_2.distances["graph"] == distances_for_case_2["graph"]
assert case_2.distances["time"] == distances_for_case_2["time"]
distances_for_case_1 = calculate_case_distances(
process.process_model_graph, case_1)
case_1 = process.cases[2]
assert case_1.distances["graph"] == distances_for_case_1["graph"]
assert case_1.distances["time"] == distances_for_case_1["time"]
def test_check_point_update(self, process, cases_list):
assert process.cp_count == 0
process.check_point_update()
assert process.cp_count == 1
assert process.check_point_cases == 0
assert process.nyquist == 0
assert len(process.process_model_graph.edges) == 0
assert len(process.process_model_graph.nodes) == 0
process.nyquist = 1
process.check_point_update()
assert process.cp_count == 2
assert process.nyquist == 1
assert process.check_point_cases == 0
assert len(process.process_model_graph.edges) == 0
assert len(process.process_model_graph.nodes) == 0
# self.cases > nyquist
# nyquist = 0
# process_model_graph = 0
process.cases = cases_list
process.check_point_cases = 1
process.nyquist = 0
with pytest.raises(Exception):
assert process.check_point_update()
# initialize_graph -> extract_cases_time_and_trace
# Exception("Extracting trace and timestamp list out of a list with no cases")
assert process.cp_count == 3 # even if error, cp_count incremented!!!
# self.cases > nyquist
# nyquist = 1
# process_model_graph = 0
case3 = cases_list[0]
process.cases = cases_list
process.check_point_cases = 1
process.nyquist = 1
process.check_point_update()
assert process.cp_count == 4
assert process.cases == [case3]
assert process.check_point_cases == 0
assert process.nyquist == 1
assert len(process.process_model_graph.edges) == 3
assert len(process.process_model_graph.nodes) == 4
check_point_graph = initialize_graph(process.cases)
for node1, node2, _ in process.process_model_graph.edges.data():
assert (process.process_model_graph[node1][node2] ==
check_point_graph[node1][node2])
assert (process.process_model_graph[node1][node2]["weight"] ==
check_point_graph[node1][node2]["weight"])
assert (process.process_model_graph[node1][node2]["time"] ==
check_point_graph[node1][node2]["time"])
# self.cases > nyquist
# nyquist = 1
# process_model_graph = 1
process.process_model_graph = initialize_graph([cases_list[2]])
pmg = process.process_model_graph
assert pmg["activityA"]["activityB"]
assert pmg["activityB"]["activityC"]
with pytest.raises(Exception):
assert pmg["activityC"]["activityD"]
assert pmg["activityD"]["activityE"]
case3 = cases_list[0]
process.cases = cases_list
process.check_point_cases = 1
process.nyquist = 1
process.check_point_update()
assert process.cp_count == 5
assert process.cases == [case3]
assert process.check_point_cases == 0
assert process.nyquist == 1
assert len(process.process_model_graph.edges) == 3
assert len(process.process_model_graph.nodes) == 4
assert pmg["activityA"]["activityB"]
assert pmg["activityB"]["activityC"]
assert pmg["activityC"]["activityD"]
check_point_graph = initialize_graph(process.cases)
for node1, node2, _ in process.process_model_graph.edges.data():
pmg[node1][node2]["weight"] *= 0.95
pmg[node1][node2]["weight"] += check_point_graph[node1][node2][
"weight"]
pmg[node1][node2]["time"] += check_point_graph[node1][node2][
"time"]
pmg = normalize_graph(pmg)
assert (process.process_model_graph[node1][node2]["weight"] ==
pmg[node1][node2]["weight"])
assert (
process.process_model_graph[node1][node2]["weight_normalized"]
== pmg[node1][node2]["weight_normalized"])
assert (process.process_model_graph[node1][node2]["time"] ==
pmg[node1][node2]["time"])
assert (
process.process_model_graph[node1][node2]["time_normalized"] ==
pmg[node1][node2]["time_normalized"])
# self.cases > nyquist
# nyquist = 2
# process_model_graph = 1
case2 = cases_list[1]
case3 = cases_list[0]
process.process_model_graph = initialize_graph([cases_list[1]])
pmg = process.process_model_graph
assert pmg["activityA"]["activityB"]
with pytest.raises(Exception):
assert pmg["activityC"]["activityD"]
assert pmg["activityD"]["activityE"]
process.cases = cases_list
process.check_point_cases = 1
process.nyquist = 2
process.check_point_update()
assert process.cp_count == 6
assert process.cases == [case3, case2]
assert process.check_point_cases == 0
assert process.nyquist == 1 * 2
assert len(process.process_model_graph.edges) == 3
assert len(process.process_model_graph.nodes) == 4
assert process.process_model_graph["activityA"]["activityB"]
assert process.process_model_graph["activityB"]["activityC"]
assert process.process_model_graph["activityC"]["activityD"]
check_point_graph = initialize_graph(process.cases)
for node1, node2, _ in process.process_model_graph.edges.data():
pmg[node1][node2]["weight"] *= 0.95
pmg[node1][node2]["weight"] += check_point_graph[node1][node2][
"weight"]
pmg[node1][node2]["time"] += check_point_graph[node1][node2][
"time"]
pmg = normalize_graph(pmg)
assert (process.process_model_graph[node1][node2]["weight"] ==
pmg[node1][node2]["weight"])
assert (
process.process_model_graph[node1][node2]["weight_normalized"]
== pmg[node1][node2]["weight_normalized"])
assert (process.process_model_graph[node1][node2]["time"] ==
pmg[node1][node2]["time"])
assert (
process.process_model_graph[node1][node2]["time_normalized"] ==
pmg[node1][node2]["time_normalized"])
# self.cases > nyquist
# nyquist = 2
# process_model_graph = 2
case2 = cases_list[1]
case3 = cases_list[0]
process.process_model_graph = initialize_graph(
[cases_list[1], cases_list[2]])
pmg = process.process_model_graph
assert pmg["activityA"]["activityB"]
assert pmg["activityB"]["activityC"]
with pytest.raises(Exception):
assert pmg["activityC"]["activityD"]
assert pmg["activityD"]["activityE"]
process.cases = cases_list
process.check_point_cases = 1
process.nyquist = 2
process.check_point_update()
assert process.cp_count == 7
assert process.cases == [case3, case2]
assert process.check_point_cases == 0
assert process.nyquist == 1 * 2
assert len(process.process_model_graph.edges) == 3
assert len(process.process_model_graph.nodes) == 4
assert process.process_model_graph["activityA"]["activityB"]
assert process.process_model_graph["activityB"]["activityC"]
assert process.process_model_graph["activityC"]["activityD"]
check_point_graph = initialize_graph(process.cases)
for node1, node2, _ in process.process_model_graph.edges.data():
pmg[node1][node2]["weight"] *= 0.95
pmg[node1][node2]["weight"] += check_point_graph[node1][node2][
"weight"]
pmg[node1][node2]["time"] += check_point_graph[node1][node2][
"time"]
pmg = normalize_graph(pmg)
assert (process.process_model_graph[node1][node2]["weight"] ==
pmg[node1][node2]["weight"])
assert (
process.process_model_graph[node1][node2]["weight_normalized"]
== pmg[node1][node2]["weight_normalized"])
assert (process.process_model_graph[node1][node2]["time"] ==
pmg[node1][node2]["time"])
assert (
process.process_model_graph[node1][node2]["time_normalized"] ==
pmg[node1][node2]["time_normalized"])
def test_train(self, denstream: DenStream):
# anomalous_denstream = DenStream(2, 0.15, 0.3, 0.1, 4, 1000)
cases_list = []
case = Case("5")
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
case.add_event(
{
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 30),
}
)
case.add_event(
{
"concept:name": "activityE",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 40),
}
)
cases_list.append(case)
case = Case("3")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
case.add_event(
{
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 30),
}
)
cases_list.append(case)
case = Case("1")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
cases_list.append(case)
case = Case("4")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
cases_list.append(case)
case = Case("2")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
cases_list.append(case)
pmg = initialize_graph(cases_list)
for case in cases_list:
case.distances = calculate_case_distances(pmg, case)
def test_dbscan(self, denstream: DenStream, cases_list):
graph = initialize_graph(cases_list)
for case in cases_list:
case.distances = calculate_case_distances(graph, case)
def test_add_point(self, denstream: DenStream):
case_list = []
case_1 = Case("1")
case_1.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_1.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
case_1.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
case_list.append(case_1)
case_2 = Case("2")
case_2.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_2.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
case_list.append(case_2)
graph = initialize_graph(case_list)
case_3 = Case("3")
case_3.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_3.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
}
)
case_3.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
case_3.add_event(
{
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 30),
}
)
case_3.distances = calculate_case_distances(graph, case_3)
micro_cluster = MicroCluster(10, 2, 0, 0.15)
micro_cluster.cf1 = np.array([0.5, -0.5])
micro_cluster.cf2 = np.array([0.5, -0.1])
micro_cluster.weight = 10
denstream.p_micro_clusters.append(micro_cluster)
micro_cluster = MicroCluster(11, 2, 0, 0.15)
micro_cluster.cf1 = np.array([0.0, 0.0])
micro_cluster.cf2 = np.array([0.0, 0.0])
micro_cluster.weight = 5
denstream.o_micro_clusters.append(micro_cluster)
denstream.mc_id = 2
mc_id = denstream.add_point(case_3)
assert mc_id == 2
assert len(denstream.o_micro_clusters) == 2
assert denstream.o_micro_clusters[1].radius == 0
assert denstream.o_micro_clusters[1].weight == 1
assert np.all(denstream.o_micro_clusters[1].cf1 == case_3.point)
assert np.all(denstream.o_micro_clusters[1].cf2 == case_3.point * case_3.point)
cf = denstream.o_micro_clusters[1].cf1.copy()
cf2 = denstream.o_micro_clusters[1].cf2.copy()
mc_id = denstream.add_point(case_3)
assert mc_id == 2
assert len(denstream.o_micro_clusters) == 1
assert len(denstream.p_micro_clusters) == 2
assert denstream.p_micro_clusters[1].weight == 2
assert np.all(denstream.p_micro_clusters[1].cf1 == cf + case_3.point)
assert np.all(
denstream.p_micro_clusters[1].cf2 == cf2 + case_3.point * case_3.point
)
def simple_graph_with_attributes(self):
case_list = []
case = Case("1")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
"attribute_one": 10,
"attribute_two": 5,
"color": "red",
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
"attribute_one": 0,
"attribute_two": 7,
"color": "green",
}
)
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
"attribute_one": 2,
"attribute_two": 4,
"color": "green",
}
)
case_list.append(case)
case = Case("2")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
"attribute_one": 3,
"attribute_two": 10,
"color": "blue",
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
"attribute_one": 6,
"attribute_two": 2,
"color": "green",
}
)
case_list.append(case)
case = Case("3")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
"attribute_one": 8,
"attribute_two": 4,
"color": "red",
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 10),
"attribute_one": 1,
"attribute_two": 12,
"color": "blue",
}
)
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
"attribute_one": 2,
"attribute_two": 2,
"color": "blue",
}
)
case.add_event(
{
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 30),
"attribute_one": 1,
"attribute_two": 1,
"color": "blue",
}
)
case_list.append(case)
graph = initialize_graph(case_list, ["attribute_one", "attribute_two", "color"])
return graph
def test_calculate_case_distances(self):
case_list = []
case = Case("1")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity D",
"time:timestamp": datetime(2015, 5, 10, 8, 33, 20),
}
)
case.add_event(
{
"concept:name": "Activity E",
"time:timestamp": datetime(2015, 5, 10, 14, 6, 40),
}
)
case_list.append(case)
case = Case("2")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 1, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 14, 40, 00),
}
)
case.add_event(
{
"concept:name": "Activity D",
"time:timestamp": datetime(2015, 5, 10, 15, 5, 00),
}
)
case_list.append(case)
case = Case("3")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 13, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 13, 00),
}
)
case_list.append(case)
case = Case("4")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
}
)
case_list.append(case)
case = Case("5")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_list.append(case)
case = Case("6")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 15, 30, 00),
}
)
case.add_event(
{
"concept:name": "Activity F",
"time:timestamp": datetime(2015, 5, 10, 15, 30, 00),
}
)
case_list.append(case)
case = Case("7")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity F",
"time:timestamp": datetime(2015, 5, 11, 8, 00, 00),
}
)
case_list.append(case)
case = Case("8")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity F",
"time:timestamp": datetime(2015, 5, 10, 11, 46, 40),
}
)
case_list.append(case)
case = Case("9")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity F",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_list.append(case)
case = Case("10")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity F",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_list.append(case)
case = Case("11")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case_list.append(case)
graph = initialize_graph(case_list)
case = Case("12")
case.add_event(
{
"concept:name": "Activity A",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "Activity B",
"time:timestamp": datetime(2015, 5, 10, 9, 18, 20),
}
)
case.add_event(
{
"concept:name": "Activity C",
"time:timestamp": datetime(2015, 5, 10, 10, 8, 20),
}
)
distances = calculate_case_distances(graph, case)
assert distances.get("graph") == pytest.approx(0.05)
assert distances.get("time") == pytest.approx(-1.42, rel=1e-2)
def test_update():
case_list = []
micro_cluster = MicroCluster(0, 2, 0, 0.15)
case = Case("1")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 33, 20),
}
)
case.add_event(
{
"concept:name": "activityE",
"time:timestamp": datetime(2015, 5, 10, 14, 6, 40),
}
)
case_list.append(case)
case = Case("2")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 1, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 14, 40, 00),
}
)
case.add_event(
{
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 15, 5, 00),
}
)
case_list.append(case)
graph = initialize_graph(case_list)
case = Case("3")
case.add_event(
{
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
}
)
case.add_event(
{
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 13, 00),
}
)
case.add_event(
{
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 13, 00),
}
)
case.distances = calculate_case_distances(graph, case)
cf = micro_cluster.cf1.copy()
cf2 = micro_cluster.cf2.copy()
weight = micro_cluster.weight
micro_cluster.update(case)
assert np.all(micro_cluster.cf1 == cf + case.point)
assert np.all(micro_cluster.cf2 == cf2 + case.point * case.point)
assert micro_cluster.weight == weight + 1
case = case_list[0]
case.distances = calculate_case_distances(graph, case)
cf = micro_cluster.cf1.copy()
cf2 = micro_cluster.cf2.copy()
weight = micro_cluster.weight
micro_cluster.update(case)
assert np.all(micro_cluster.cf1 == cf + case.point)
assert np.all(micro_cluster.cf2 == cf2 + case.point * case.point)
assert micro_cluster.weight == weight + 1
def complex_graph(self):
case_list = []
case = Case("1")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 8, 33, 20),
})
case.add_event({
"concept:name": "activityE",
"time:timestamp": datetime(2015, 5, 10, 14, 6, 40),
})
case_list.append(case)
case = Case("2")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 1, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 14, 40, 00),
})
case.add_event({
"concept:name": "activityD",
"time:timestamp": datetime(2015, 5, 10, 15, 5, 00),
})
case_list.append(case)
case = Case("3")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 13, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 13, 00),
})
case_list.append(case)
case = Case("4")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 20),
})
case_list.append(case)
case = Case("5")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case_list.append(case)
case = Case("6")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 15, 30, 00),
})
case.add_event({
"concept:name": "activityF",
"time:timestamp": datetime(2015, 5, 10, 15, 30, 00),
})
case_list.append(case)
case = Case("7")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityF",
"time:timestamp": datetime(2015, 5, 11, 8, 00, 00),
})
case_list.append(case)
case = Case("8")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityF",
"time:timestamp": datetime(2015, 5, 10, 11, 46, 40),
})
case_list.append(case)
case = Case("9")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityF",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case_list.append(case)
case = Case("10")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityF",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case_list.append(case)
case = Case("11")
case.add_event({
"concept:name": "activityA",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityB",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case.add_event({
"concept:name": "activityC",
"time:timestamp": datetime(2015, 5, 10, 8, 00, 00),
})
case_list.append(case)
graph = initialize_graph(case_list)
return graph
