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python lambda example

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from activestate. not complete or tested but good ref

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  1. if bootstraps == 1:
  2.   srri = lambda low, high, size: range(size) 
  3. else:
  4.   srri = scipy.random.random_integers
  5.  
  6. for boot in range(bootstraps):      
  7.   for r in range(n1):
  8.     for c in range(n0):
  9.       sample_size = trial_result[r][c].size
  10.       choices = srri(0, sample_size-1, sample_size)
  11.       meas_grid[r,c] = pylab.array(trial_result[r][c][choices],dtype=float).mean()
  12.  
  13.   model_grid[:,:,:,boot], params[:,boot] = \
  14.               process_grid(s0, s1, meas_grid)
  15.  
  16. #Instead of
  17. srri = scipy.random.random_integers
  18. if bootstraps == 1:
  19.  for r in range(n1):
  20.    for c in range(n0):
  21.      meas_grid[r,c] = pylab.array(trial_result[r][c],dtype=float).mean()
  22.  
  23.  model_grid[:,:,:,boot], params[:,boot] = \
  24.               process_grid(s0, s1, meas_grid)
  25. else:
  26.  for boot in range(bootstraps):
  27.    for r in range(n1):
  28.      for c in range(n0):
  29.        sample_size = trial_result[r][c].size
  30.        choices = srri(0, sample_size-1, sample_size)
  31.        meas_grid[r,c] = pylab.array(trial_result[r][c][choices],dtype=float).mean()
  32.  
  33.    model_grid[:,:,:,boot], params[:,boot] = \
  34.               process_grid(s0, s1, meas_grid)
  35.  
  36. #OR
  37. srri = scipy.random.random_integers
  38. for boot in range(bootstraps):
  39.   if bootstraps == 1:
  40.    for r in range(n1):
  41.      for c in range(n0):
  42.        meas_grid[r,c] = pylab.array(trial_result[r][c],dtype=float).mean()
  43.  
  44.     model_grid[:,:,:,boot], params[:,boot] = \
  45.               process_grid(s0, s1, meas_grid)
  46.   else:
  47.    for r in range(n1):
  48.      for c in range(n0):
  49.        sample_size = trial_result[r][c].size
  50.        choices = srri(0, sample_size-1, sample_size)
  51.        meas_grid[r,c] = pylab.array(trial_result[r][c][choices],dtype=float).mean()
  52.  
  53.    model_grid[:,:,:,boot], params[:,boot] = \
  54.               process_grid(s0, s1, meas_grid)

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