import heapq
 
class KNN:
	def __init__(self, reference, distanceFn, K):
		self.reference = reference
		self.distanceFn = distanceFn
		self.k = K
		self.k_nearest = []
 
	def observe(self, query):
		distances = self.distanceFn(query, self.reference)
 
		for distance, patch in zip(distances, query):
			min_dist = float('inf')
			for dist in distance:
				if dist<min_dist:
					min_dist = dist
			heapq.heappush(self.k_nearest, (min_dist, patch))
			if len(self.k_nearest)>k:
				heapq.heappop(self.k_nearest)
 
	@property	
	def nearest_k(self):
		self.k_nearest.sort()
		nearest_k_return = [patch for _, patch in self.k_nearest]
		return np.array(sorted(nearest_k))

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