a b/man/load_prediction.Rd
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/predict.R
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\name{load_prediction}
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\alias{load_prediction}
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\title{Read states from h5 file}
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\usage{
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load_prediction(
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  h5_path,
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  rows = NULL,
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  verbose = FALSE,
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  get_sample_position = FALSE,
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  get_seq = FALSE
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)
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}
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\arguments{
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\item{h5_path}{Path to h5 file.}
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\item{rows}{Range of rows to read. If \code{NULL} read everything.}
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\item{verbose}{Boolean.}
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\item{get_sample_position}{Return position of sample corresponding to state if \code{TRUE}.}
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\item{get_seq}{Return nucleotide sequence if \code{TRUE}.}
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}
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\value{
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A list of data frames, containing model predictions and sequence positions.
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}
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\description{
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Reads h5 file created by  \code{\link{predict_model}} function.
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}
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\examples{
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\dontshow{if (reticulate::py_module_available("tensorflow")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
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# make prediction for single sequence and write to h5 file
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model <- create_model_lstm_cnn(maxlen = 20, layer_lstm = 8, layer_dense = 2, verbose = FALSE)
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vocabulary <- c("a", "c", "g", "t")
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sequence <- paste(sample(vocabulary, 200, replace = TRUE), collapse = "")
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output_file <- tempfile(fileext = ".h5")
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predict_model(output_format = "one_seq", model = model, step = 10,
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              sequence = sequence, filename = output_file, mode = "label")
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load_prediction(h5_path = output_file)
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\dontshow{\}) # examplesIf}
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}