Beispiel #1
0
def aggregate(self, experimentID, user):
  """
    Aggregate the GFP scores and send report
  """
  gfps = GFP.objects.filter(experiment_id=experimentID)
  log.debug("RUNNING aggregate: initialize method")

  algorithm = Algorithm()
  algorithm = algorithm.getAlgorithm("NV")
  algorithm.loadDataAggregate()
  algorithm.aggregate(gfps, experimentID)

  experiment = Experiment.objects.filter(id=experimentID)
  log.debug("RUNNING aggregate: start report")
  report = Report(experimentID)
  filename = REPORT_DIR + "sapling_gfp_report_" + slugify(experiment[0].Name) + "_" + str(experimentID) + ".pdf"
  report.generateReport(filename)
  del report

  subject = "SAPLING report: " + experiment[0].Name
  body = "Dear " + user.first_name + " "+ user.last_name + ",\n\n"
  body += "Please find attached a report of your experiment " + experiment[0].Name + ".\n\n"
  body += "Regards,\n SAPLING"

  email = EmailMessage(subject=subject, body=body, from_email="*****@*****.**", to=[user.email])
  reportname = "sapling_gfp_report_" + slugify(experiment[0].Name) + "_" + str(experimentID) + ".pdf"
  handle = open(filename, 'rb')
  email.attach(reportname, handle.read(), "application/pdf")

  enrichname = "Enrichment_GeneList_GO_" + str(experimentID) + ".csv"
  filename = REPORT_DIR + "Enrichment_GeneList_GO_" + str(experimentID) + ".csv"
  handle = open(filename, 'rb')
  email.attach(enrichname, handle.read(), "text/csv")

  email.send()
  handle.close()

  log.debug("DONE Aggregate")
Beispiel #2
0
def predict(self, gfpID, user):
  """
    annotation: list of gene symbols
  """
  log.debug("Start time: %s" % timezone.now().strftime('%d/%m/%Y %H:%M:%S'))

  gfp = GFP.objects.filter(id=gfpID)
  gfp = gfp[0]

  log.debug("RUNNING: initialize method")
  self.update_state(state='RUNNING', meta='Initialize method')
  if not ProcessManagement.objects.filter(gfp_id=gfpID, experiment_id=gfp.experiment_id).exists():
    ProcessManagement.objects.create(gfp_id=gfpID, experiment_id=gfp.experiment_id, \
      State= "RUNNING: initialize method", Name=gfp.Network+"_"+gfp.Algorithm)
  else:
    ProcessManagement.objects.filter(gfp_id=gfpID, experiment_id=gfp.experiment_id).update(State= \
      "RUNNING: initialize method")

  algorithm = Algorithm()
  algorithm = algorithm.getAlgorithm(gfp.Algorithm)

  log.debug("RUNNING: load files")
  self.update_state(state='RUNNING', meta='Load files')
  ProcessManagement.objects.filter(gfp_id=gfpID, experiment_id=gfp.experiment_id).update(State= \
    "RUNNING: load files")

  algorithm.loadData(gfpID)

  log.debug("RUNNING: run method")
  self.update_state(state='RUNNING', meta='Run method')
  ProcessManagement.objects.filter(gfp_id=gfpID, experiment_id=gfp.experiment_id).update(State= \
    "RUNNING: run method")
  algorithm.run()

  log.debug("RUNNING: save predictions")
  self.update_state(state='RUNNING', meta='Save predictions')
  ProcessManagement.objects.filter(gfp_id=gfpID, experiment_id=gfp.experiment_id).update( \
    State="RUNNING: save predictions")

  algorithm.save(gfpID)

  log.debug("RUNNING: enrichment")
  algorithm.enrichment(gfp.experiment_id, gfpID)

  ProcessManagement.objects.filter(gfp_id=gfpID, experiment_id=gfp.experiment_id).update( \
    State="FINISHED")
  log.debug("FINISHED")

  gfps = GFP.objects.filter(experiment_id=gfp.experiment_id)

  processes = ProcessManagement.objects.filter(experiment_id=gfp.experiment_id)

  flag = True
  if len(processes) != len(gfps):
    flag = False
  else:
    for process in processes:
      if process.State != "FINISHED":
        flag = False
        break

  log.debug("Experiment flag: %s", str(flag))

  ## Create report and aggregate
  if flag:
    log.debug("REPORT EMAIL")

    gfps = GFP.objects.filter(experiment_id=gfp.experiment_id)

    # Aggregation of GFPs
    algorithm.aggregate(gfps, gfp.experiment_id)

    experiment = Experiment.objects.filter(id=gfp.experiment_id)
    log.debug("RUNNING: start report")
    report = Report(gfp.experiment_id)
    filename = REPORT_DIR + "sapling_gfp_report_" + slugify(experiment[0].Name) + "_" \
		+ str(gfp.experiment_id) + ".pdf"
    log.debug("RUNNING: %s" % filename)
    report.generateReport(filename)
    del report

    subject = "SAPLING report: " + experiment[0].Name
    body = "Dear " + user.first_name + " "+ user.last_name + ",\n\n"
    body += "Please find attached a report of your experiment " + experiment[0].Name + ".\n\n"
    body += "Regards,\n SAPLING"
	
    email = EmailMessage(subject=subject, body=body, from_email="*****@*****.**", to=[user.email])
    reportname = "sapling_gfp_report_" + slugify(experiment[0].Name) + "_" + str(gfp.experiment_id) + ".pdf"
    handle = open(filename, 'rb')
    email.attach(reportname, handle.read(), "application/pdf")

    enrichname = "Enrichment_GeneList_GO_" + str(gfp.experiment_id) + ".csv"
    filename = REPORT_DIR + "Enrichment_GeneList_GO_" + str(gfp.experiment_id) + ".csv"
    handle = open(filename, 'rb')
    email.attach(enrichname, handle.read(), "text/csv")

    email.send()
    handle.close()
    log.debug("DONE")