code: def motif_density(
      motif_name,
      seq_length,
      num_seqs,
      min_counts,
      max_counts,
      GC_fraction,
      central_bp=None,
  ):
      """
      returns sequences with motif density, along with embeddings array.
      """
      substring_generator = PwmSamplerFromLoadedMotifs(
          loaded_motifs, motif_name
      )
      if central_bp is not None:
          position_generator = InsideCentralBp(central_bp)
      else:
          position_generator = UniformPositionGenerator()
      quantity_generator = UniformIntegerGenerator(
          min_counts, max_counts
      )
      embedders = [
          RepeatedEmbedder(
              SubstringEmbedder(
                  ReverseComplementWrapper(substring_generator),
                  position_generator,
              ),
              quantity_generator,
          )
      ]
      embed_in_background = EmbedInABackground(
          ZeroOrderBackgroundGenerator(
              seq_length,
              discreteDistribution=get_distribution(GC_fraction),
          ),
          embedders,
      )
      generated_sequences = tuple(
          GenerateSequenceNTimes(
              embed_in_background, num_seqs
          ).generateSequences()
      )
      sequence_arr = np.array(
          [generated_seq.seq for generated_seq in generated_sequences]
      )
      embedding_arr = [
          generated_seq.embeddings
          for generated_seq in generated_sequences
      ]
      return sequence_arr, 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 3 for calling a global function with example usage: motif_density(motif_name, seq_length, num_seqs, min_counts, max_counts, GC_fraction, central_bp) and returns: sequence_arr,  embedding_arr