def test_get_id_values(self):
"""Tests get_id_values function."""
test1 = io.StringIO('1\t1.0\n2\t2.0\n3\t3.0')
expected1 = [(1, 1.0), (2, 2.0), (3, 3.0)]
actual1 = list(vertex_analysis.get_id_values(test1))
self.assertEqual(actual1, expected1)
test2 = io.StringIO('')
expected2 = []
actual2 = list(vertex_analysis.get_id_values(test2))
self.assertEqual(actual2, expected2)
test3 = io.StringIO('1\t1.0\t1.0\n2\t2.0\t2.0\n3\t3.0\t3.0')
expected3 = [(1, 1.0, 1.0), (2, 2.0, 2.0), (3, 3.0, 3.0)]
actual3 = list(vertex_analysis.get_id_values(test3))
self.assertEqual(actual3, expected3)
'--student-archive-path', dest='student_archive_path',
help='Path of the student archive file.', required=True)
parser.add_argument(
'--swig-module-path', dest='swig_module_path',
help='Directory containing the swig modules.',
action=ReadableDirectory, required=True)
parser.set_defaults()
args = parser.parse_args()
show_unnormalized = 'frequency' in args.distributions
show_normalized = 'normalized' in args.distributions
# segment the data
vertex_lines = vertex_analysis.get_id_values(args.file)
students_wrapper = StudentContainerWrapper(
args.swig_module_path, args.student_archive_path)
segmenter = StudentContainerWrapper.SEGMENTERS[args.segmenter]
mapped_lines = vertex_analysis.map_to_segments(
vertex_lines, segmenter, students_wrapper)
segments = vertex_analysis.reduce_to_segments(mapped_lines)
# filter out small segments
filtered_segments = {segment: values for segment, values in segments.items()
if values.size >= args.threshold}
# set up the histogram for various colors
size = ((12, 8) if show_unnormalized and show_normalized
else (12, 4))
fig = matplotlib.pyplot.figure(figsize=size)
parser.add_argument(
'--swig-module-path', dest='swig_module_path',
help='Directory containing the swig modules.',
action=readable_directory.ReadableDirectory, required=True)
args = parser.parse_args()
unweighted = args.weightedness == 'unweighted'
weighted = args.weightedness == 'weighted'
# get container of students
students = StudentContainerWrapper(
args.swig_module_path, args.student_archive_path)
# get the weights of individual segments
lines = list(vertex_analysis.get_id_values(args.file))
mapped_to_segments = vertex_analysis.map_to_segments(
lines, StudentContainerWrapper.SEGMENTERS[args.field], students)
reduced_data = vertex_analysis.reduce_to_in_out(
mapped_to_segments, args.in_segment)
if unweighted:
actual_segments = {key: len(data) for key, data in reduced_data.items()}
elif weighted:
actual_segments = {key: sum(data) for key, data in reduced_data.items()}
print(actual_segments)
population_segments = segment.get_segment_counts(students, args.field)
print(population_segments[args.in_segment])
population = len(students)
'--student-archive-path', dest='student_archive_path',
help='Path of the student archive file.', required=True)
parser.add_argument(
'--swig-module-path', dest='swig_module_path',
help='Directory containing the swig modules.',
action=ReadableDirectory, required=True)
args = parser.parse_args()
# segment the network for analysis
students_wrapper = StudentContainerWrapper(
args.swig_module_path, args.student_archive_path)
segmenter = StudentContainerWrapper.SEGMENTERS[args.segmenter]
for vertex_file in args.files:
vertex_lines = vertex_analysis.get_id_values(vertex_file)
segmented_lines = list(vertex_analysis.map_to_segments(
vertex_lines, segmenter, students_wrapper))
total_connections = len(segmented_lines)
values_sum = vertex_analysis.accumulate(segmented_lines, sum)
segments = vertex_analysis.reduce_to_segments(segmented_lines)
# calculate the diversity of the segments
diversity_index = 0
if args.weightedness == 'unweighted':
diversity_index = calculate_unweighted_index(
segments.values(), total_connections)
elif args.weightedness == 'weighted':
diversity_index = calculate_weighted_index(
segments.values(), values_sum)
required=True)
parser.add_argument('--swig-module-path',
dest='swig_module_path',
help='Directory containing the swig modules.',
action=ReadableDirectory,
required=True)
args = parser.parse_args()
# segment the network for analysis
students_wrapper = StudentContainerWrapper(args.swig_module_path,
args.student_archive_path)
segmenter = StudentContainerWrapper.SEGMENTERS[args.segmenter]
for vertex_file in args.files:
vertex_lines = vertex_analysis.get_id_values(vertex_file)
segmented_lines = list(
vertex_analysis.map_to_segments(vertex_lines, segmenter,
students_wrapper))
total_connections = len(segmented_lines)
values_sum = vertex_analysis.accumulate(segmented_lines, sum)
segments = vertex_analysis.reduce_to_segments(segmented_lines)
# calculate the diversity of the segments
diversity_index = 0
if args.weightedness == 'unweighted':
diversity_index = calculate_unweighted_index(
segments.values(), total_connections)
elif args.weightedness == 'weighted':
diversity_index = calculate_weighted_index(segments.values(),
