def analyze_clustering(cls, separated_decomposed_clusters, distance_matrix,
analysis):
"""
Performs the overlap analysis of a clustering (calculates global measurements).
"""
analysis["total_num_clusters"] = 0
analysis["total_num_elements"] = 0
analysis["overlap"] = OverlapCalculator.calculate_clustering_overlap(
mergeSeparatedClusters(separated_decomposed_clusters),
distance_matrix)
analysis[
"mixed_overlap"] = OverlapCalculator.calculate_clustering_overlap(
mergeSeparatedClusters(
{"mixed": separated_decomposed_clusters["mixed"]}),
distance_matrix)
for cluster_type in separated_decomposed_clusters:
analysis["num_" + cluster_type] = len(
separated_decomposed_clusters[cluster_type])
analysis["total_num_clusters"] += analysis["num_" + cluster_type]
analysis["num_" + cluster_type + "_elements"] = numpy.sum([
len(
getAllElements(
separated_decomposed_clusters[cluster_type][dc_id]))
for dc_id in separated_decomposed_clusters[cluster_type]
])
analysis["total_num_elements"] += analysis["num_" + cluster_type +
"_elements"]
def analyze_clustering(cls, separated_decomposed_clusters, distance_matrix, analysis):
"""
Performs the overlap analysis of a clustering (calculates global measurements).
"""
analysis["total_num_clusters"] = 0
analysis["total_num_elements"] = 0
analysis["overlap"] = OverlapCalculator.calculate_clustering_overlap(mergeSeparatedClusters(separated_decomposed_clusters), distance_matrix)
analysis["mixed_overlap"] = OverlapCalculator.calculate_clustering_overlap(mergeSeparatedClusters({"mixed":separated_decomposed_clusters["mixed"]}), distance_matrix)
for cluster_type in separated_decomposed_clusters:
analysis["num_" + cluster_type] = len(separated_decomposed_clusters[cluster_type])
analysis["total_num_clusters"] += analysis["num_" + cluster_type]
analysis["num_" + cluster_type + "_elements"] = numpy.sum([len(getAllElements(separated_decomposed_clusters[cluster_type][dc_id])) for dc_id in separated_decomposed_clusters[cluster_type]])
analysis["total_num_elements"] += analysis["num_" + cluster_type + "_elements"]
def analyze_clustering(cls, separated_decomposed_clusters, distance_matrix, analysis):
analysis["total_num_clusters"] = 0
analysis["total_num_elements"] = 0
analysis["overlap"] = OverlapCalculator.calculate_global_overlap(mergeSeparatedClusters(separated_decomposed_clusters), distance_matrix, 2, 1)
for cluster_type in separated_decomposed_clusters:
analysis["num_" + cluster_type] = len(separated_decomposed_clusters[cluster_type])
analysis["total_num_clusters"] += analysis["num_" + cluster_type]
analysis["num_" + cluster_type + "_elements"] = numpy.sum([len(getAllElements(separated_decomposed_clusters[cluster_type][dc_id])) for dc_id in separated_decomposed_clusters[cluster_type]])
analysis["total_num_elements"] += analysis["num_" + cluster_type + "_elements"]
return cluster_type
def test_mergeSeparatedClusters(self):
separated_decomposed_clusters = {
'mixed': {
'1': {
'traj_A': [3],
'traj_B': [8, 10]
},
'2': {
'traj_A': [4],
'traj_B': [14, 15]
}
},
'pure': {
'0': {
'traj_A': [0, 1, 2]
},
'3': {
'traj_A': [5, 6]
},
'4': {
'traj_B': [9, 11, 12, 13, 7]
}
}
}
expected = [{
'traj_A': [3],
'traj_B': [8, 10]
},
{
'traj_A': [4],
'traj_B': [14, 15]
},
{
'traj_A': [0, 1, 2]
},
{
'traj_A': [5, 6]
},
{
'traj_B': [9, 11, 12, 13, 7]
}
]
self.assertItemsEqual(expected, mergeSeparatedClusters(separated_decomposed_clusters))
def analyze_clustering(cls, separated_decomposed_clusters, distance_matrix,
analysis):
analysis["total_num_clusters"] = 0
analysis["total_num_elements"] = 0
analysis["overlap"] = OverlapCalculator.calculate_global_overlap(
mergeSeparatedClusters(separated_decomposed_clusters),
distance_matrix, 2, 1)
for cluster_type in separated_decomposed_clusters:
analysis["num_" + cluster_type] = len(
separated_decomposed_clusters[cluster_type])
analysis["total_num_clusters"] += analysis["num_" + cluster_type]
analysis["num_" + cluster_type + "_elements"] = numpy.sum([
len(
getAllElements(
separated_decomposed_clusters[cluster_type][dc_id]))
for dc_id in separated_decomposed_clusters[cluster_type]
])
analysis["total_num_elements"] += analysis["num_" + cluster_type +
"_elements"]
return cluster_type
