% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/preprocess.R

\name{seq_encoding_lm}

\alias{seq_encoding_lm}

\title{Encodes integer sequence for language model}

\usage{

seq_encoding_lm(

  sequence = NULL,

  maxlen,

  vocabulary,

  start_ind,

  ambiguous_nuc = "zero",

  nuc_dist = NULL,

  quality_vector = NULL,

  return_int = FALSE,

  target_len = 1,

  use_coverage = FALSE,

  max_cov = NULL,

  cov_vector = NULL,

  n_gram = NULL,

  n_gram_stride = 1,

  output_format = "target_right",

  char_sequence = NULL,

  adjust_start_ind = FALSE,

  tokenizer = NULL

)

}

\arguments{

\item{sequence}{Sequence of integers.}

\item{maxlen}{Length of predictor sequence.}

\item{vocabulary}{Vector of allowed characters. Characters outside vocabulary get encoded as specified in \code{ambiguous_nuc}.}

\item{start_ind}{Start positions of samples in \code{sequence}.}

\item{ambiguous_nuc}{How to handle nucleotides outside vocabulary, either \code{"zero"}, \code{"empirical"} or \code{"equal"}.

See \code{\link{train_model}}. Note that \code{"discard"} option is not available for this function.}

\item{nuc_dist}{Nucleotide distribution.}

\item{quality_vector}{Vector of quality probabilities.}

\item{return_int}{Whether to return integer encoding or one-hot encoding.}

\item{target_len}{Number of nucleotides to predict at once for language model.}

\item{use_coverage}{Integer or \code{NULL}. If not \code{NULL}, use coverage as encoding rather than one-hot encoding and normalize.

Coverage information must be contained in fasta header: there must be a string \code{"cov_n"} in the header, where \code{n} is some integer.}

\item{max_cov}{Biggest coverage value. Only applies if \code{use_coverage = TRUE}.}

\item{cov_vector}{Vector of coverage values associated to the input.}

\item{n_gram}{Integer, encode target not nucleotide wise but combine n nucleotides at once. For example for \verb{n=2, "AA" ->  (1, 0,..., 0),}

\verb{"AC" ->  (0, 1, 0,..., 0), "TT" -> (0,..., 0, 1)}, where the one-hot vectors have length \code{length(vocabulary)^n}.}

\item{n_gram_stride}{Step size for n-gram encoding. For AACCGGTT with \code{n_gram = 4} and \code{n_gram_stride = 2}, generator encodes

\verb{(AACC), (CCGG), (GGTT)}; for \code{n_gram_stride = 4} generator encodes \verb{(AACC), (GGTT)}.}

\item{output_format}{Determines shape of output tensor for language model.

Either \code{"target_right"}, \code{"target_middle_lstm"}, \code{"target_middle_cnn"} or \code{"wavenet"}.

Assume a sequence \code{"AACCGTA"}. Output correspond as follows

\itemize{

\item \verb{"target_right": X = "AACCGT", Y = "A"}

\item \verb{"target_middle_lstm": X = (X_1 = "AAC", X_2 = "ATG"), Y = "C"} (note reversed order of X_2)

\item \verb{"target_middle_cnn": X = "AACGTA", Y = "C"}

\item \verb{"wavenet": X = "AACCGT", Y = "ACCGTA"}

}}

\item{char_sequence}{A character string.}

\item{adjust_start_ind}{Whether to shift values in \code{start_ind} to start at 1: for example (5,11,25) becomes (1,7,21).}

\item{tokenizer}{A keras tokenizer.}

}

\value{

A list of 2 tensors.

}

\description{

Helper function for \code{\link{generator_fasta_lm}}.

Encodes integer sequence to input/target list according to \code{output_format} argument.

}

\examples{

\dontshow{if (reticulate::py_module_available("tensorflow")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}

# use integer sequence as input 

z <- seq_encoding_lm(sequence = c(1,0,5,1,3,4,3,1,4,1,2),

maxlen = 5,

vocabulary = c("a", "c", "g", "t"),

start_ind = c(1,3),

ambiguous_nuc = "equal",

target_len = 1,

output_format = "target_right")

x <- z[[1]]

y <- z[[2]]

x[1,,] # 1,0,5,1,3

y[1,] # 4

x[2,,] # 5,1,3,4,

y[2,] # 1

# use character string as input

z <- seq_encoding_lm(sequence = NULL,

maxlen = 5,

vocabulary = c("a", "c", "g", "t"),

start_ind = c(1,3),

ambiguous_nuc = "zero",

target_len = 1,

output_format = "target_right",

char_sequence = "ACTaaTNTNaZ")

x <- z[[1]]

y <- z[[2]]

x[1,,] # actaa

y[1,] # t

x[2,,] # taatn

y[2,] # t

\dontshow{\}) # examplesIf}

}