# sciquence.sequences¶

## Cutting & trimming¶

 seq(array) Cut input array into sequences consisting of the same elements nseq(array) Returns sequences consisting of zeros pseq(array) Returns sequences consisting of ones specseq(array, element) Return sequences consisting of specific tag seqi(array) Get list of sequences and corresponding list of indices nseqi(array) Get list of sequences and corresponding list of indices pseqi(array) Get list of sequences and corresponding list of indices chunk(array, chunk_size) Split numpy array into chunks of equal length.

## Comparing¶

 lseq_equal(lseqa, lseqb) Compare two lists of ndarrays

## Input transformations¶

 rnn_input(X, y, window_size[, step]) Prepare input for recurrent neural network. seq2seq_input(X, y, window_size[, step, ...]) Prepare input for sequence2sequence recurrent neural network.

## Searching¶

 mslc Given a length n real sequence, finds the consecutive subsequence of length at most U with the maximum sum in O(n) time. longest_segment Find the longest subsequence which scores above a given threshold in O(n) 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.