def diversity(activity):
transactions = transpose(activity)
unique_transactions = unique(transactions)
buckets = list(map(lambda t: transactions.count(t), unique_transactions))
numerator = reduce(lambda s, n: s + n * (n - 1), buckets, 0)
num_of_transactions = len(transactions)
denominator = num_of_transactions * (num_of_transactions - 1)
try:
return 1 - numerator / denominator
except ZeroDivisionError:
return 0
def _flatten_spectra(spectra):
components = spectra[0]
transactions = spectra[1:]
unique_components = set(components[1:])
for component in unique_components:
positions = _indexes(component, components)
for j, transaction in enumerate(transactions):
if sum([transaction[i] for i in positions]) > 0:
for p in positions:
transactions[j][p] = 1
data = [components] + transactions
component_columns = transpose(data)
return transpose(unique(component_columns))
def _get_classes(spectra):
components = _unique_components(spectra)
classes = unique(list(map(_get_class, components)))
return reduce(_assign_class, components, _parent_dict(classes))
def _get_packages(spectra):
components = _unique_components(spectra)
packages = list(map(_get_package, components))
packages = unique(packages)
return reduce(_assign_package, components, _parent_dict(packages))
def uniqueness(activity):
g = unique(activity)
try:
return len(g) / len(activity)
except ZeroDivisionError:
return 0