new_contents: # Analyze thermal conductivity results
  # Date: June 2017
  # Author: Kutay B. Sezginel
  import os
  import numpy as np
  from teemof.read import avg_kt, get_kt, read_runs, read_legend
  
  
  def analyze_trial_set(trial_set_dir, xkey='mass2', sort=True, t0=10, t1=20):
      """ Read thermal conductivity for a set of trials, get approximate kt values """
      trial_error, trial_std, x_data, y_data = [], [], [], []
      for trial in os.listdir(trial_set_dir):
          # Read each direction and and each run for given trial (30 data list)
          trial_dir = os.path.join(trial_set_dir, trial)
          run_data, time, runs_id = read_runs(trial_dir, verbose=False)
  
          # Get avg kt for each direction and each run
          run_kt = []
          for d in run_data:
              run_avg = get_kt(d, time, t0=10, t1=20)
              run_kt.append(run_avg)
  
          # Calculate standard deviation and error
          run_std = np.std(run_kt)
          trial_std.append(run_std)
  
          min_kt, max_kt = min(run_kt), max(run_kt)
          trial_error.append([min_kt, max_kt])
  
          # Get average thermal conductivity for trial
          avg_data = avg_kt(run_data)
          trial_kt = get_kt(avg_data, time, t0=t0, t1=t1)
          y_data.append(trial_kt)
  
          x_value = read_legend(trial_dir, key=xkey)
          x_data.append(x_value)
  
      if sort:
          x = [i[0] for i in sorted(zip(x_data, y_data))]
          y = [i[1] for i in sorted(zip(x_data, y_data))]
      else:
          x, y = x_data, y_data
  
      return dict(x=x, y=y, err=trial_error, std=trial_std)
  
subject: Add thermal conductivity trend analysis library.