def maximum_co_localized_cases(self, case_numbers, slice_variables, p_bounds=None):
new = False
if len(case_numbers) == 0:
return None
intersections = list()
Cases = self(case_numbers)
for i in xrange(len(Cases)):
case = Cases[i]
case_num = case.case_number
case_numbers = self._cyclical_case_as_subcases(case_num, case_numbers)
valid_cases = range(len(case_numbers))
if p_bounds is not None:
lower = VariablePool(names=self.independent_variables)
upper = VariablePool(names=self.independent_variables)
for key in lower:
lower[key] = 1e-20
upper[key] = 1e20
for (key, value) in p_bounds.iteritems():
try:
min_value, max_value = value
except TypeError:
min_value = value
max_value = value
if min_value > max_value:
raise ValueError, "parameter slice bounds are inverted: min is larger than max"
lower[key] = min_value
upper[key] = max_value
## [intersections.append(i) for i in case_numbers if self(i).is_valid()is True]
sets = [set([i]) for i in valid_cases]
for i in xrange(2, len(case_numbers) + 1):
new = True
sets_to_check = sets
sets = []
identifiers = range(0, len(sets_to_check))
comb = itertools.combinations(identifiers, 2)
for j in comb:
current_set = set()
for k in j:
current_set = current_set.union(sets_to_check[k])
if len(current_set) != i:
continue
if current_set in sets:
continue
case_int = CaseColocalization([self(case_numbers[k]) for k in current_set], slice_variables)
pvals = case_int.valid_parameter_set()
if pvals > 0:
if new is True:
intersections = []
new = False
intersections.append([case_numbers[k] for k in current_set])
sets.append(current_set)
return intersections
def co_localize_cases(
self,
case_numbers,
slice_parameters,
constraints=None,
p_bounds=None,
optimize=None,
minimize=True,
project=True,
by_signature=False,
):
cases = self(case_numbers, by_signature=by_signature)
to_colocalize = CaseColocalization(cases, slice_parameters, constraints=constraints)
co_localized = to_colocalize.valid_parameter_set(
p_bounds=p_bounds, optimize=optimize, minimize=minimize, project=project
)
return co_localized
