text: import numpy as np
  
  from process import load_names, merge_datasets
  from scanorama import process_data, find_alignments_table
  from time_align import time_align_correlate, time_align_visualize
  
  NAMESPACE = 'mono_macro'
  
  data_names = [
      'data/macrophage/monocytes_1',
      'data/macrophage/monocytes_2',
      'data/macrophage/monocytes_3',
      'data/macrophage/monocytes_4',
      'data/pbmc/10x/cd14_monocytes',
      'data/macrophage/mcsf_day3_1',
      'data/macrophage/mcsf_day3_2',
      'data/macrophage/mcsf_day6_1',
      'data/macrophage/mcsf_day6_2',
  ]
  
  if __name__ == '__main__':
      datasets, genes_list, n_cells = load_names(data_names)
  
      monocytes, mono_genes = datasets[:4], genes_list[:4]
      monocytes, mono_genes = merge_datasets(monocytes, mono_genes)
      datasets = [ monocytes[0] ] + datasets[4:]
      genes_list = [ mono_genes ] + genes_list[4:]
      data_names = [ 'data/macrophage/monocytes_seqwell' ] + data_names[4:]
      
      datasets, genes = merge_datasets(datasets, genes_list)
      datasets_dimred, genes = process_data(datasets, genes)
  
      _, A, _ = find_alignments_table(datasets_dimred)
      
      time = np.array([ 0, 0, 3, 3, 6, 6 ]).reshape(-1, 1)
      time_align_correlate(A, time)
  
      x = np.array([ 0, 0, 1, 1, 2, 2 ]).reshape(-1, 1)
      y = [ -.1, .1, -.1, .1, -.1, .1 ]
      time_align_visualize(A, x, y, namespace=NAMESPACE)
  