old_contents: #make_composite_plots.py
  
  #Will Barnes
  #21 April 2015
  
  #Import needed modules
  import sys
  import pickle
  import argparse
  import numpy as np
  import matplotlib.pyplot as plt
  sys.path.append('../')
  from solarnmf_plotting import MakeBSSPlots
  
  #Parse command line arguments
  parser = argparse.ArgumentParser(description='Run NMF method for specific channel over multiple cuts for range of source guesses')
  parser.add_argument("-c","--channel",type=int,help="AIA detector channel")
  parser.add_argument("-pl","--p_lower",type=int,help="Lower bound for source guess")
  parser.add_argument("-pu","--p_upper",type=int,help="Upper bound for source guess")
  parser.add_argument("-n","--n_cuts",type=int,help="Number of cuts per channel time series")
  parser.add_argument("-l","--loop_location",help="AR time series location")
  args = parser.parse_args()
  
  #Define parent directory and file format
  parent_dir = '/data/datadrive2/AIA_fm_spectra/solarnmf_ts_analysis/ts_'+args.loop_location+'/'+str(args.channel)+'/'
  fn = 'channel'+str(args.channel)+'_cut%d_q%d'
  
  #Define constant parameters
  angle = 45.0
  input_type = 'timeseries'
  data_option = 'data'
  q = np.arange(args.p_lower,args.p_upper+1,1)
  
  #Begin loops
  for i in range(args.n_cuts):
      for j in range(len(q)):
          #Read in the data
          #try:
              with open(parent_dir+fn%(i,q[j])+'.uva','rb') as f:
                  u,v,A,T,Tmat,div = pickle.load(f)
              #Print status
              print "Building plots for cut %d, q=%d"%(i,q[j]) 
              #Declare instance and plot
              plotter = MakeBSSPlots(data_option,input_type,u,v,A,T,div,Tmat=Tmat,angle=angle,ny=T.shape[0],nx=T.shape[0])
              plotter.plot_obs_pred_total_sources_ts(print_fig_filename=parent_dir+'plots/'+fn+'.eps'%(i,q[j]))
          #except:
              #print "Cannot build plot. Incomplete data set."
              #continue
new_contents: #make_composite_plots.py
  
  #Will Barnes
  #21 April 2015
  
  #Import needed modules
  import sys
  import pickle
  import argparse
  import numpy as np
  import matplotlib.pyplot as plt
  sys.path.append('../')
  from solarnmf_plotting import MakeBSSPlots
  
  #Parse command line arguments
  parser = argparse.ArgumentParser(description='Run NMF method for specific channel over multiple cuts for range of source guesses')
  parser.add_argument("-c","--channel",type=int,help="AIA detector channel")
  parser.add_argument("-pl","--p_lower",type=int,help="Lower bound for source guess")
  parser.add_argument("-pu","--p_upper",type=int,help="Upper bound for source guess")
  parser.add_argument("-n","--n_cuts",type=int,help="Number of cuts per channel time series")
  parser.add_argument("-l","--loop_location",help="AR time series location")
  args = parser.parse_args()
  
  #Define parent directory and file format
  parent_dir = '/data/datadrive2/AIA_fm_spectra/solarnmf_ts_analysis/ts_'+args.loop_location+'/'+str(args.channel)+'/'
  fn = 'channel'+str(args.channel)+'_cut%d_q%d'
  
  #Define constant parameters
  angle = 45.0
  input_type = 'timeseries'
  data_option = 'data'
  q = np.arange(args.p_lower,args.p_upper+1,1)
  
  #Begin loops
  for i in range(args.n_cuts):
      for j in range(len(q)):
          #Read in the data
          try:
              with open(parent_dir+fn%(i,q[j])+'.uva','rb') as f:
                  u,v,A,T,Tmat,div = pickle.load(f)
              #Print status
              print "Building plots for cut %d, q=%d"%(i,q[j]) 
              #Declare instance and plot
              plotter = MakeBSSPlots(data_option,input_type,u,v,A,T,div,Tmat=Tmat,angle=angle,ny=T.shape[0],nx=T.shape[0])
              plotter.plot_obs_pred_total_sources_ts(print_fig_filename=parent_dir+'plots/'+fn%(i,q[j])+'.eps')
          except:
              print "Cannot build plot. Incomplete data set."
              continue
subject: debug for plot script