get_seq_encode_pad {DeepPINCS} | R Documentation

## Vectorization of characters of strings

### Description

A vectorization of characters of strings is necessary. Vectorized characters are padded or truncated.

### Usage

    get_seq_encode_pad(sequences, length_seq, ngram_max = 1, ngram_min = 1,
        lenc = NULL)

### Arguments

`sequences` | SMILE strings or amino acid sequences
`length_seq` | length of input sequences
`ngram_max` | maximum size of an n-gram (default: 1)
`ngram_min` | minimum size of an n-gram (default: 1)
`lenc` | encoded labels for characters, LableEncoder object fitted by "CatEncoders::LabelEncoder.fit" (default: NULL)

### Value

`sequences_encode_pad` | for each SMILES string, an encoded sequence which is padded or truncated
`lenc` | encoded labels for characters
`num_token` | total number of characters

### Author(s)

Dongmin Jung

### See Also

CatEncoders::LabelEncoder.fit, CatEncoders::transform, keras::pad_sequences, stringdist::qgrams, tokenizers::tokenize_ngrams

### Examples

    if (keras::is_keras_available() & reticulate::py_available()) {
        get_seq_encode_pad(example_cpi[1, 2], 10)
    }

[Package DeepPINCS version 1.2.2 Index]