# Source code for fontTools.misc.classifyTools

    """ fontTools.misc.classifyTools.py -- tools for classifying things.
    """

    class Classifier(object):

    	"""
    	Main Classifier object, used to classify things into similar sets.
    	"""

    	def __init__(self, sort=True):

    		self._things = set() # set of all things known so far
    		self._sets = [] # list of class sets produced so far
    		self._mapping = {} # map from things to their class set
    		self._dirty = False
    		self._sort = sort

    	def add(self, set_of_things):
    		"""
    		Add a set to the classifier.  Any iterable is accepted.
    		"""
    		if not set_of_things:
    			return

    		self._dirty = True

    		things, sets, mapping = self._things, self._sets, self._mapping

    		s = set(set_of_things)
    		intersection = s.intersection(things) # existing things
    		s.difference_update(intersection) # new things
    		difference = s
    		del s

    		# Add new class for new things
    		if difference:
    			things.update(difference)
    			sets.append(difference)
    			for thing in difference:
    				mapping[thing] = difference
    		del difference

    		while intersection:
    			# Take one item and process the old class it belongs to
    			old_class = mapping[next(iter(intersection))]
    			old_class_intersection = old_class.intersection(intersection)

    			# Update old class to remove items from new set
    			old_class.difference_update(old_class_intersection)

    			# Remove processed items from todo list
    			intersection.difference_update(old_class_intersection)

    			# Add new class for the intersection with old class
    			sets.append(old_class_intersection)
    			for thing in old_class_intersection:
    				mapping[thing] = old_class_intersection
    			del old_class_intersection

    	def update(self, list_of_sets):
    		"""
    		Add a a list of sets to the classifier.  Any iterable of iterables is accepted.
    		"""
    		for s in list_of_sets:
    			self.add(s)

    	def _process(self):
    		if not self._dirty:
    			return

    		# Do any deferred processing
    		sets = self._sets
    		self._sets = [s for s in sets if s]

    		if self._sort:
    			self._sets = sorted(self._sets, key=lambda s: (-len(s), sorted(s)))

    		self._dirty = False

    	# Output methods

    	def getThings(self):
    		"""Returns the set of all things known so far.

    		The return value belongs to the Classifier object and should NOT
    		be modified while the classifier is still in use.
    		"""
    		self._process()
    		return self._things

    	def getMapping(self):
    		"""Returns the mapping from things to their class set.

    		The return value belongs to the Classifier object and should NOT
    		be modified while the classifier is still in use.
    		"""
    		self._process()
    		return self._mapping

    	def getClasses(self):
    		"""Returns the list of class sets.

    		The return value belongs to the Classifier object and should NOT
    		be modified while the classifier is still in use.
    		"""
    		self._process()
    		return self._sets

    def classify(list_of_sets, sort=True):
    	"""
    	Takes a iterable of iterables (list of sets from here on; but any
    	iterable works.), and returns the smallest list of sets such that
    	each set, is either a subset, or is disjoint from, each of the input
    	sets.

    	In other words, this function classifies all the things present in
    	any of the input sets, into similar classes, based on which sets
    	things are a member of.

    	If sort=True, return class sets are sorted by decreasing size and
    	their natural sort order within each class size.  Otherwise, class
    	sets are returned in the order that they were identified, which is
    	generally not significant.

    	>>> classify([]) == ([], {})
    	True
    	>>> classify([[]]) == ([], {})
    	True
    	>>> classify([[], []]) == ([], {})
    	True
    	>>> classify([[1]]) == ([{1}], {1: {1}})
    	True
    	>>> classify([[1,2]]) == ([{1, 2}], {1: {1, 2}, 2: {1, 2}})
    	True
    	>>> classify([[1],[2]]) == ([{1}, {2}], {1: {1}, 2: {2}})
    	True
    	>>> classify([[1,2],[2]]) == ([{1}, {2}], {1: {1}, 2: {2}})
    	True
    	>>> classify([[1,2],[2,4]]) == ([{1}, {2}, {4}], {1: {1}, 2: {2}, 4: {4}})
    	True
    	>>> classify([[1,2],[2,4,5]]) == (
    	...     [{4, 5}, {1}, {2}], {1: {1}, 2: {2}, 4: {4, 5}, 5: {4, 5}})
    	True
    	>>> classify([[1,2],[2,4,5]], sort=False) == (
    	...     [{1}, {4, 5}, {2}], {1: {1}, 2: {2}, 4: {4, 5}, 5: {4, 5}})
    	True
    	>>> classify([[1,2,9],[2,4,5]], sort=False) == (
    	...     [{1, 9}, {4, 5}, {2}], {1: {1, 9}, 2: {2}, 4: {4, 5}, 5: {4, 5},
    	...     9: {1, 9}})
    	True
    	>>> classify([[1,2,9,15],[2,4,5]], sort=False) == (
    	...     [{1, 9, 15}, {4, 5}, {2}], {1: {1, 9, 15}, 2: {2}, 4: {4, 5},
    	...     5: {4, 5}, 9: {1, 9, 15}, 15: {1, 9, 15}})
    	True
    	>>> classes, mapping = classify([[1,2,9,15],[2,4,5],[15,5]], sort=False)
    	>>> set([frozenset(c) for c in classes]) == set(
    	...     [frozenset(s) for s in ({1, 9}, {4}, {2}, {5}, {15})])
    	True
    	>>> mapping == {1: {1, 9}, 2: {2}, 4: {4}, 5: {5}, 9: {1, 9}, 15: {15}}
    	True
    	"""
    	classifier = Classifier(sort=sort)
    	classifier.update(list_of_sets)
    	return classifier.getClasses(), classifier.getMapping()

    if __name__ == "__main__":
    	import sys, doctest
    	sys.exit(doctest.testmod(optionflags=doctest.ELLIPSIS).failed)