Читать книгу Informatics and Machine Learning. From Martingales to Metaheuristics онлайн

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In the results for Shannon entropy on dinucleotides, we still do not see clear signs of nonrandomness. Similarly, let us try trinucleotide level. There are 64 (4 × 4 × 4) trinucleotides that we must now get counts on:

-------------------- prog1.py addendum 7 --------------------- stats = {} order = 3 for index in range(order-1,seqlen): xmer = "" for xmeri in range(0,order): xmer+=result[index-(order-1)+xmeri] if xmer in stats: stats[xmer]+=1 else: stats[xmer]=1 for i in sorted(stats): print("%dx'%s'" % (stats[i],i)) ---------------- end prog1.py addendum 7 ---------------------

Still do not see real clear signs of non‐random at tribase‐level! So let us try 6‐nucleotide level. There are 4096 6‐nucleotides that we must now get counts on:

----------------- prog1.py addendum 8 ------------------------ def shannon_order( seq, order ): stats = {} seqlen = len(seq) for index in range(order-1,seqlen): xmer = "" for xmeri in range(0,order): xmer+=result[index-(order-1)+xmeri] if xmer in stats: stats[xmer]+=1 else: stats[xmer]=1 nonzerocounts = len(stats) print("nonzerocounts=") print(nonzerocounts) counts = np.empty((0)) for i in sorted(stats): counts = np.append(counts,stats[i]+0.0) probs = count_to_freq(counts) value = shannon(probs) print "The shannon entropy at order", order, "is:", value, "." shannon_order(result,6) ------------------- end prog1.py addendum 8 ------------------