old_contents: import doseresponse as dr
  import numpy as np
  import argparse
  import sys
  import os
  
  parser = argparse.ArgumentParser()
  requiredNamed = parser.add_argument_group('required arguments')
  requiredNamed.add_argument("--data-file", type=str, help="csv file from which to read in data, in same format as provided crumb_data.csv", required=True)
  requiredNamed.add_argument("-m", "--model", type=int, help="For non-hierarchical (put anything for hierarchical):1. fix Hill=1; 2. vary Hill", required=True)
  requiredNamed.add_argument("-d", "--drug", type=int, help="drug index", required=True)
  requiredNamed.add_argument("-c", "--channel", type=int, help="channel index", required=True)
  
  if len(sys.argv)==1:
      parser.print_help()
      sys.exit(1)
  
  args = parser.parse_args()
  
  dr.define_model(args.model)
  num_params = dr.num_params
  
  dr.setup(args.data_file)
  
  top_drug = dr.drugs[args.drug]
  top_channel = dr.channels[args.channel]
  
  temperatures = (np.arange(dr.n+1.)/dr.n)**dr.c
  
  for t in temperatures:
      drug,channel,chain_file,images_dir = dr.nonhierarchical_chain_file_and_figs_dir(args.model, top_drug, top_channel, t)
      if not os.path.isfile(chain_file):
          print "{}, {}, model {}, temp {} - NOT FOUND".format(top_drug, top_channel, args.model, t)
          break
  
  
  
new_contents: import doseresponse as dr
  import numpy as np
  import argparse
  import sys
  import os
  
  parser = argparse.ArgumentParser()
  requiredNamed = parser.add_argument_group('required arguments')
  requiredNamed.add_argument("--data-file", type=str, help="csv file from which to read in data, in same format as provided crumb_data.csv", required=True)
  requiredNamed.add_argument("-m", "--model", type=int, help="For non-hierarchical (put anything for hierarchical):1. fix Hill=1; 2. vary Hill", required=True)
  requiredNamed.add_argument("-d", "--drug", type=int, help="drug index", required=True)
  requiredNamed.add_argument("-c", "--channel", type=int, help="channel index", required=True)
  
  if len(sys.argv)==1:
      parser.print_help()
      sys.exit(1)
  
  args = parser.parse_args()
  
  dr.define_model(args.model)
  num_params = dr.num_params
  
  dr.setup(args.data_file)
  
  top_drug = dr.drugs[args.drug]
  top_channel = dr.channels[args.channel]
  
  temperatures = (np.arange(dr.n+1.)/dr.n)**dr.c
  
  ts = [temperatures[0], temperatures[-1]]
  
  for t in ts:
      drug,channel,chain_file,images_dir = dr.nonhierarchical_chain_file_and_figs_dir(args.model, top_drug, top_channel, t)
      if not os.path.isfile(chain_file):
          print "{}, {}, model {}, temp {} - NOT FOUND".format(top_drug, top_channel, args.model, t)
          break
  
  
  
subject: Check fewer temps per drug+channel