Python tdaracne Examples

Example #1

File: TestSimAnneal.py Project: remtcs/Network-Inference-Workspace

def get_network_results(name, settings, cache):
  print "STARTING", name

  if name in cache.keys():
    print "CACHE HIT"
    return cache[name]

  ko_file, kd_file, ts_file, wt_file, mf_file, goldnet = get_example_data_files(name, settings)

  # Create date string to append to output_dir
  t = datetime.now().strftime("%Y-%m-%d_%H.%M.%S")
  settings["global"]["output_dir"] = settings["global"]["output_dir_save"] + "/" + \
      settings["global"]["experiment_name"] + "-" + t + "-" + name + "/"
  os.mkdir(settings["global"]["output_dir"])

  # Get a list of the multifactorial files

  # Read data into program
  # Where the format is "FILENAME" "DATATYPE"
  mf_storage = ReadData(mf_file[0], "multifactorial")
  knockout_storage = ReadData(ko_file[0], "knockout")
  knockdown_storage = ReadData(kd_file[0], "knockdown")
  wildtype_storage = ReadData(wt_file[0], "wildtype")
  timeseries_storage = ReadData(ts_file[0], "timeseries")
  gene_list = knockout_storage.gene_list

  # Setup job manager
  jobman = JobManager(settings)

  # MCZ
  mczjob = MCZ()
  mczjob.setup(knockout_storage, wildtype_storage, settings, timeseries_storage, knockdown_storage, "MCZ")
  jobman.queueJob(mczjob)

  # CLR
  clrjob = CLR()
  clrjob.setup(knockout_storage, settings, "CLR", "plos", 6)
  jobman.queueJob(clrjob)

  # GENIE3
  mf_storage.combine(knockout_storage)
  mf_storage.combine(wildtype_storage)
  mf_storage.combine(knockdown_storage)
  genie3job = GENIE3()
  genie3job.setup(mf_storage, settings, "GENIE3")
  jobman.queueJob(genie3job)

  ## TLCLR
  tlclrjob = TLCLR()
  tlclrjob.setup(knockout_storage, wildtype_storage, settings, timeseries_storage, knockdown_storage, "TLCLR")
  jobman.queueJob(tlclrjob)

  #if sys.argv[1] != "dream4100":
      #cojob = ConvexOptimization()
      #cojob.setup(knockout_storage, settings, "ConvOpt_T-"+ str(0.01),None, None, 0.01)
      #jobman.queueJob(cojob)

  ### DFG4GRN
  dfg = DFG4GRN()
  settings["dfg4grn"]["eta_z"] = 0.01
  settings["dfg4grn"]["lambda_w"] = 0.001
  settings["dfg4grn"]["tau"] = 3
  dfg.setup(timeseries_storage, TFList(timeseries_storage[0].gene_list), settings, "DFG", 20)
  jobman.queueJob(dfg)

  ### Inferelator

  ### NIR
  nirjob = NIR()
  nirjob.setup(knockout_storage, settings, "NIR", 5, 5)
  jobman.queueJob(nirjob)

  #### TDARACNE
  settings = ReadConfig(settings, "./config/default_values/tdaracne.cfg")
  bjob = tdaracne()
  settings["tdaracne"]["num_bins"] = 4
  bjob.setup(timeseries_storage, settings, "TDARACNE")
  jobman.queueJob(bjob)


  print jobman.queue
  jobman.runQueue()
  jobman.waitToClear(name)
  SaveResults(jobman.finished, goldnet, settings, name)

  cache[name] = jobman.finished[:]

  return cache[name]

Example #2

File: TestBanjo_DFG_TD.py Project: remtcs/Network-Inference-Workspace

settings["global"]["time_series_delta_t"] = delta_t

# Read data into program
timeseries_storage = ReadData(ts_filenames[0], True)

# Get config file for tdaracne
settings = ReadConfig(settings, "./config/default_values/tdaracne.cfg")
settings = ReadConfig(settings, "./config/default_values/banjo.cfg")
settings = ReadConfig(settings, "./config/default_values/dfg4grn.cfg")
# settings = ReadConfig(settings, settings["tdaracne"]["config"])

# Setup job manager
jobman = JobManager(settings)

# Make tdaracne jobs
bjob = tdaracne()
bjob.setup(timeseries_storage, settings, "tdaracne-test-run-1")
jobman.queueJob(bjob)

trans_factors = TFList(timeseries_storage[0].gene_list)
settings["dfg4grn"]["eta_z"] = 0.01
settings["dfg4grn"]["lambda_w"] = 0.001
settings["dfg4grn"]["tau"] = 2
dfg = DFG4GRN()
dfg.setup(timeseries_storage, trans_factors, settings, "dfg4grn-test-run-1")
jobman.queueJob(dfg)

bjob = banjo()
bjob.setup(timeseries_storage, settings, "banjo-test-run-1")
jobman.queueJob(bjob)