text: #!/usr/bin/env python3
  """An example configuration file
  """
  import sys
  import os
  
  
  # Assuming the cell order in the metadata tables are the same as those in the gene level matrices
  # The output knn matrices follow such order as well 
  
  ka_smooth = 2000 
  knn = 2000 
  date = 200826
  
  
  # # Configs  
  name = 'mop_2mods_atacrna_within_cluster_knn_{}_ka{}_knn{}'.format(date, ka_smooth, knn)
  outdir = '/cndd2/fangming/projects/miniatlas/results'
  output_pcX_all = outdir + '/pcX_all_{}.npy'.format(name)
  output_cells_all = outdir + '/cells_all_{}.npy'.format(name) 
  output_imputed_data_format = outdir + '/imputed_data_{}_{{}}.npy'.format(name)
  output_clst_and_umap = outdir + '/intg_summary_{}.tsv'.format(name)
  output_figures = outdir + '/figures/{}_{{}}.{{}}'.format(name)
  output_cluster_centroids = outdir + '/centroids_{}.pkl'.format(name)
  
  save_knn = True # new required arguments (7/27/2020) 
  output_knn_within = outdir + "/knn_within_{}_{{}}.npz".format(name)
  output_knn_across = outdir + "/knn_across_{}_{{}}_{{}}.npz".format(name)
  # end of new required arguments (7/27/2020)
  
  # required for downsamp (8/7/2020)
  output_cells = outdir + "/cells_{{}}_{}.npy".format(name)
  
  
  
  DATA_DIR = '/cndd/fangming/CEMBA/data/MOp_all/data_freeze_neurons'
  # fixed dataset configs
  sys.path.insert(0, DATA_DIR)
  from __init__datasets import *
  
  meta_f = os.path.join(DATA_DIR, '{0}_metadata.tsv')
  hvftrs_f = os.path.join(DATA_DIR, '{0}_hvfeatures.{1}')
  hvftrs_gene = os.path.join(DATA_DIR, '{0}_hvfeatures.gene')
  hvftrs_cell = os.path.join(DATA_DIR, '{0}_hvfeatures.cell')
  
  mods_selected = [
      # 'snmcseq_gene',
      'snatac_gene',
      'smarter_cells',
      # 'smarter_nuclei',
      # '10x_cells_v2', 
      # '10x_cells_v3',
      # '10x_nuclei_v3',
      # '10x_nuclei_v3_macosko',
      ]
  
  # features_selected = ['smarter_cells']
  # features_selected = ['snmcseq_gene']
  features_selected = ['snatac_gene']
  # check features
  for features_modality in features_selected:
      assert (features_modality in mods_selected)
  
  # within modality
  ps = {'mc': 0.9,
        'atac': 0.1,
        'rna': 0.7,
       }
  drop_npcs = {
        'mc': 0,
        'atac': 0,
        'rna': 0,
       }
  ka_smooth = ka_smooth # default: 5
  
  # across modality
  cross_mod_distance_measure = 'correlation' # cca
  knn = knn 
  relaxation = 3
  n_cca = 30
  
  # PCA
  npc = 50
  # clustering
  k = 30 # default 30 controls clustering
  resolutions = [0.1, 1, 2, 4]
  # umap
  umap_neighbors = 60
  min_dist = 0.5
  