title: How to extract time domain information when recreating the signal by taking the inverse FFT
body: <p>I'm trying to recreate the the original signal from the FFT of a signal sample. When taking Inverse FFT, I'm only getting an amplitude information (only one column). How can I get the corresponding time coordinates? </p>
  
  <p>This is a screen shot of my original signal, recorded from 0 to 10s with step 0.001s. When I take the IFFT, I'm getting the same number of data points as my signal, but can't find the corresponding time information.</p>
  
  <p><img src="https://i.stack.imgur.com/jZeg8.png" alt="This is the plot of 2 signals"></p>
  
  <p>How can I get the correct time information?</p>
  
  <p>I'm including the Python code code I used and a plot of the 2 signals.</p>
  
  <pre><code>#generating signal here
  import numpy as np
  k = float ( 3.1416*2) 
  f1 = 100
  f2 = 150
  f3 = 250
  ds = max(f1,f2,f3)
  ds = float(4*ds)
  dt = 1.000/ds
  lf = min (f1,f2,f3)
  lT = 1.00/lf
  N = 10 # cycles
  totaltime = N*lT
  data = []
  tt = []
  mf = 1/dt 
  print "TotalTime =", totaltime
  for t in np.arange(0.0, totaltime,dt/100 ) :
      #t = tk/mf
  
      print t
      wave1 = np.sin(k*f1*t)
      wave2 = np.sin(k*f2*t)
      wave3 = np.sin(k*f3*t)
      summ = wave1 + wave2 + wave3
      print t,"    ", summ
      tt.append(t)
      data.append(summ)
  print tt
  print data  
  np.savetxt("data.txt",np.c_[tt,data])
  
  
  #######################
  #taking the FFT here
  fourier = []
  tt =[]
  yy=[]
  
  logname = str("data.txt")
  with open (logname,"rb") as wdata:
          for line in wdata     :
          if not line.startswith("#") :
  
          sl = line.split()
          c11 = float(sl[0])
          #c11 = c1*10**(-12)
          c2 = float(sl[1])
          tt.append(c11)
          yy.append(c2)
  n = len(yy)
  n1 = len(tt)
  print "n=",n,"(",n1,")"
  #to calculate the time step , find the difference between 2 time-values
  t0 = float(tt[0]) 
  print "t0=",t0
  
  t1 = float(tt[1])
  print "t1=",t1
  ts = t1 - t0 
  print "ts=", ts
  yf = numpy.fft.fft(yy)
  yf_abso = numpy.abs(yf)
  
  freq = numpy.fft.fftfreq(n,d=ts)
  
  numpy.savetxt('fft-data.txt',numpy.c_[freq,yf_abso])
  
  ######################
  # taking the inverese FFT
  
  filename = str("fft-data.txt") 
  FFTdata =[]
  FREQdata = []
  
  with open (filename,'r') as fftfile :
      for line in fftfile       :
          if not line.startswith("#") :
              split_line = line.split()
              fpoint = float(split_line[1])
              freqz  = float(split_line[0])
              FFTdata.append(fpoint)
              FREQdata.append(freqz)
  
  ireverse = np.fft.ifft(FFTdata)
  reverse  = np.abs(ireverse)
  print type(reverse)  
  np.savetxt ("ireverse.txt", ireverse)
  np.savetxt("reverse.txt", reverse)
  </code></pre>