homework.py
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homework.py
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			"""
			EE-311
			======

			Lab 10: Bayesian inference
			--------------------------

			created by François Marelli on 27.05.2020
			"""


			def bayes_decision(X, pdf_list, prior_list, L):
			"""
			Take a bayesian decision based on maximum a posteriori with loss

			Parameters:
			X: array(N), the measured points
			pdf_list: list of (scipy.stats.rv_continuous), length K (the number of classes), the probability density function of each class (pdf_list[0] = pdf of class 0, etc.)
			prior_list: list of (float [0, 1]), length K (the number of classes) a priori probabilities of each class (prior_list[0] = prior of class 0, etc.)
			L: array(K, M), M being the number of actions: the loss matrix (cost associated to each pair of class/action)

			Returns:
			A: array(N), the chosen action for each sample [0-M]
			"""

			return