code: def simulate_single_motif_detection(
      motif_name, seq_length, num_pos, num_neg, GC_fraction
  ):
      """
      Simulates two classes of seqeuences:
          - Positive class sequence with a motif
            embedded anywhere in the sequence
          - Negative class sequence without the motif
  
      Parameters
      ----------
      motif_name : str
          encode motif name
      seq_length : int
          length of sequence
      num_pos : int
          number of positive class sequences
      num_neg : int
          number of negative class sequences
      GC_fraction : float
          GC fraction in background sequence
  
      Returns
      -------
      sequence_arr : 1darray
          Array with sequence strings.
      y : 1darray
          Array with positive/negative class labels.
      embedding_arr: 1darray
          Array of embedding objects.
      """
      (
          motif_sequence_arr,
          positive_embedding_arr,
      ) = simple_motif_embedding(
          motif_name, seq_length, num_pos, GC_fraction
      )
      (
          random_sequence_arr,
          negative_embedding_arr,
      ) = simple_motif_embedding(None, seq_length, num_neg, GC_fraction)
      sequence_arr = np.concatenate(
          (motif_sequence_arr, random_sequence_arr)
      )
      y = np.array([[True]] * num_pos + [[False]] * num_neg)
      embedding_arr = positive_embedding_arr + negative_embedding_arr
      return sequence_arr, y, embedding_arr
  
file_path: deepchem/contrib/dragonn/simulations.py
imports: from __future__ import absolute_import, division, print_function
  from collections import OrderedDict
  import numpy
  import simdna
  from simdna.synthetic import RepeatedEmbedder, SubstringEmbedder, ReverseComplementWrapper, UniformPositionGenerator, InsideCentralBp, LoadedEncodeMotifs, PwmSamplerFromLoadedMotifs, UniformIntegerGenerator, ZeroOrderBackgroundGenerator, EmbedInABackground, GenerateSequenceNTimes, RandomSubsetOfEmbedders, IsInTraceLabelGenerator, EmbeddableEmbedder, PairEmbeddableGenerator
  from simdna.util import DiscreteDistribution
label_desc: Use image node_id 4 for calling a global function with example usage: simulate_single_motif_detection(motif_name, seq_length, num_pos, num_neg, GC_fraction) and returns: sequence_arr,  y,  embedding_arr