sciquence.sequences.max_avg_seq¶
-
sciquence.sequences.max_avg_seq()¶ Given a length n real sequence, finding the consecutive subsequence of length at least L with the maximum average can be done in O(n log L) time. In other words, function maximizes subsequence average, keeping its length equal or greater given value L
Parameters: - A (ndarray) – List of float numbers
- L (int) – Minimal subsequence length
Returns: - start (int) – First slice index of found subsequence
- stop (int) – Second slice index of found subsequence
Examples
>>> from sciquence.sequences import max_avg_seq >>> import numpy as np >>> X = np.array([-1, -2, -3, -23, -45, -3, -4, 5, 50, 67, 1, 3, 4, 5]) >>> max_avg_seq(X, 3) (7, 10) >>> print X[7:10] [ 5 50 67] # We change 50 into -50 >>> Z = np.array([-1, -2, -3, -23, -45, -3, -4, 5, -50, 67, 1, 3, 4, 5]) (9, 12) >>> print Z[9:12] [67 1 3] # In last example, we replace -3 with 600 >>> V = np.array([-1, -2, 600, -23, -45, -3, -4, 5, -50, 67, 1, 3, 4, 5]) (0, 3) >>> print V[0:3] [ -1 -2 600]
References
Lin Y.L., Jiang T., Chaoc K.M. (2002). Efficient algorithms for locating the length-constrained heaviest segments with applications to biomolecular sequence analysis