old_contents: #!/usr/bin/env python
  
  """
  Generate sample olfactory model stimulus.
  """
  
  import numpy as np
  import h5py
  
  osn_num = 1375
  
  dt = 1e-4 # time step
  Ot = 2000 # number of data point during reset period
  Rt = 1000 # number of data point during odor delivery period
  Nt = 4*Ot + 3*Rt # number of data points in time
  t  = np.arange(0, dt*Nt, dt)
  
  I       = 0.5195 # amplitude of odorant concentration
  u_on    = I*np.ones(Ot, dtype=np.float64)
  u_off   = np.zeros(Ot, dtype=np.float64)
  u_reset = np.zeros(Rt, dtype=np.float64)
  u       = np.concatenate((u_off, u_reset, u_on, u_reset, u_off, u_reset, u_on))
  u_all   = np.transpose(np.kron(np.ones((osn_num, 1)), u))
  
  with h5py.File('olfactory_input.h5', 'w') as f:
      f.create_dataset('real', (Nt, osn_num),
                       dtype=np.float64,
                       data=u_all)
  
new_contents: #!/usr/bin/env python
  
  """
  Generate sample olfactory model stimulus.
  """
  
  import numpy as np
  import h5py
  
  osn_num = 1375
  
  dt = 1e-4 # time step
  Ot = 2000 # number of data point during reset period
  Rt = 1000 # number of data point during odor delivery period
  Nt = 4*Ot + 3*Rt # number of data points in time
  t  = np.arange(0, dt*Nt, dt)
  
  I       = 0.5195 # amplitude of odorant concentration
  u_on    = I*np.ones(Ot, dtype=np.float64)
  u_off   = np.zeros(Ot, dtype=np.float64)
  u_reset = np.zeros(Rt, dtype=np.float64)
  u       = np.concatenate((u_off, u_reset, u_on, u_reset, u_off, u_reset, u_on))
  u_all   = np.transpose(np.kron(np.ones((osn_num, 1)), u))
  
  with h5py.File('olfactory_input.h5', 'w') as f:
      f.create_dataset('array', (Nt, osn_num),
                       dtype=np.float64,
                       data=u_all)
  
subject: Use 'array' rather than 'real' for data array name in olfactory stimulus generation script.