content: import matplotlib.pyplot as plt
  import scipy.interpolate as scinterp
  import numpy as np
  import peakfinding
  import peak_original
  import smoothing
  import plotter
  import random
  import readin
  import sys
  import os
  
  if __name__== '__main__':
      Mbdata = []
      delM15data = []
      path = "/Users/zaidi/Documents/REU/restframe/"
      filenames = os.listdir(path)
      random.shuffle(filenames)
      for filename in filenames:
          current_file = os.path.join(path, filename)
          data= readin.readin_SNrest(filename)
          indB = np.where((data.band == 'B'))
          Bdata = data[indB]
          Bdata = np.sort(Bdata)
          if len(Bdata.phase) > 3:
              spl = scinterp.UnivariateSpline(Bdata.phase, Bdata.mag)
              spl.set_smoothing_factor(2./len(Bdata.phase))
              phase_new = np.arange(Bdata.phase[0], Bdata.phase[-1], 1)
              mag_new = spl(phase_new)
              maxp, minp = peak_original.peakdet(mag_new, 0.5, phase_new)
              if len(minp) > 0 and minp[0][0] < 5 and minp[0][0] > -5:
                  Mb = minp[0][1]
                  delM15 = minp[0][1] - spl(minp[0][0]+15)
                  Mbdata.append(Mb)
                  delM15data.append(delM15) 
                  if delM15 > 0 or delM15 < -5:
                      print minp
                      print filename
                      print spl(minp[0][0] + 15)
                      fig = plt.figure(1)
                      ax = fig.add_subplot(1,1,1)
                      ax.plot(phase_new, mag_new)
                      ax.plot(Bdata.phase, Bdata.mag)
                      if len(minp) > 0:
                          ax.scatter(minp[:,0],minp[:,1])
                      plt.show(fig)
          
          '''
          maxp, minp = peakfinding.peakdetect(mag_new, phase_new, 200, 1.5)
          if len(minp) > 0:
              print minp
              print filename
              fig = plt.figure(1)
              ax = fig.add_subplot(1,1,1)
              #ax.scatter(minp[:,0], minp[:,1],'bo')
              #ax.plot(Bdata.phase, Bdata.mag)
              #plt.show(fig) 
          
          '''
          #interp = smoothing.Interpolate1D(data.phase
      print Mbdata
      print delM15data
      fig = plt.figure(2)
      ax = fig.add_subplot(1,1,1)
      ax.scatter(Mbdata, delM15data)
      plt.show(fig)
  