title: How to increase predicted data when estimating parameters of set of complex differential equations by fitting experimental data?
body: <p>I am trying to estimate the parameters of my set of ODEs in my program, always minimizing the error between my experimental data and predicted data.</p>
  <p>The problem is, I can obtain a good prediction and a very good fit, but I can only estimate the same number of points as my experimental data, which returns a very strange output.</p>
  <p>Can you please provide me more information in how can I obtain a more accurate set of predicted points?</p>
  <p>Code can be found below.</p>
  <pre><code>from gekko import GEKKO
  import numpy as np
  import matplotlib.pyplot as plt
  xm = np.array([0,1,2,3,4,5])
  ym = np.array([2.0,1.5,np.nan,2.2,3.0,5.0])
  m = GEKKO(remote=False)
  m.time = xm
  a = m.FV(lb=0.1,ub=2.0)
  a.STATUS=1
  y = m.CV(value=ym,name='y',fixed_initial=False)
  y.FSTATUS=1
  m.Equation(y.dt()==a*y)
  m.options.IMODE = 5
  m.options.SOLVER = 1
  m.solve(disp=True)
  print('Optimized, a = ' + str(a.value[0]))
  plt.figure(figsize=(6,2))
  plt.plot(xm,ym,'bo',label='Meas')
  plt.plot(xm,y.value,'r-',label='Pred')
  plt.ylabel('y')
  plt.ylim([0,6])
  plt.legend()
  plt.show()
  </code></pre>
  <p>If I replace variable m.time to obtain more data predicted with :<br />
  <code>m.time = np.linspace(0,5,30)</code>
  I get the error: <em>raise Exception('Data arrays must have the same length, and match time discretization in dynamic problems')
  Exception: Data arrays must have the same length, and match time discretization in dynamic problems</em></p>