new_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  
  """Copyright © 2014 German Neuroinformatics Node (G-Node)
  
   All rights reserved.
  
   Redistribution and use in source and binary forms, with or without
   modification, are permitted under the terms of the BSD License. See
   LICENSE file in the root of the Project.
  
   Author: Jan Grewe <jan.grewe@g-node.org>
  
   This tutorial shows how to store a voltage trace and mark in this the
   interval in which a stimulus was presented. The stimulus itself is
   linked to this interval as an untagged Feature.
  
   See https://github.com/G-node/nix/wiki for more information.
  
  """
  
  import nix
  import lif
  import numpy as np
  import scipy.signal as signal
  import matplotlib.pylab as plt
  
  
  def fake_neuron(stepsize=0.001, offset=.8):
      stimulus = np.random.randn(80000) * 2.5
      b, a = signal.butter(8, 0.125)
      stimulus = signal.filtfilt(b, a, stimulus)
      s = np.hstack((np.zeros(10000), stimulus, np.zeros(10000)))
      lif_model = lif.lif(stepsize=stepsize, offset=offset)
      time, v, spike_times = lif_model.run_stimulus(s)
      stimulus_onset = 10000*stepsize
      stimulus_duration = len(stimulus)*stepsize
      return time, v, stimulus, stimulus_onset, stimulus_duration
      
  
  def plot_data(tag):
      data_array = tag.references[0]
      voltage = data_array[:]
      
      x_axis = data_array.dimensions[0]
      time = np.arange(0, data_array.data_extent[0])
      time = time * x_axis.sampling_interval + (x_axis.offset if x_axis.offset else 0.0)
      
      stimulus_onset = tag.position
      stimulus_duration = tag.extent
  
      stimulus_array = tag.features[0].data
      stimulus = stimulus_array[:]
      
      stim_time_dim = stimulus_array.dimensions[0]
      stimulus_time = np.arange(0, stimulus_array.data_extent[0])
      stimulus_time = stimulus_time * stim_time_dim.sampling_interval + (stim_time_dim.offset if stim_time_dim.offset else 0.0)
     
      response_axis = plt.subplot2grid((2, 2), (0, 0), rowspan=1, colspan=2)
      response_axis.tick_params(direction='out')
      response_axis.spines['top'].set_color('none')
      response_axis.spines['right'].set_color('none')
      response_axis.xaxis.set_ticks_position('bottom')
      response_axis.yaxis.set_ticks_position('left')
  
      stimulus_axis = plt.subplot2grid((2, 2), (1, 0), rowspan=1, colspan=2)
      stimulus_axis.tick_params(direction='out')
      stimulus_axis.spines['top'].set_color('none')
      stimulus_axis.spines['right'].set_color('none')
      stimulus_axis.xaxis.set_ticks_position('bottom')
      stimulus_axis.yaxis.set_ticks_position('left')
      
      response_axis.plot(time, voltage, color='dodgerblue', label=data_array.name, zorder=1)
      response_axis.set_xlabel(x_axis.label + ((" [" + x_axis.unit + "]") if x_axis.unit else ""))
      response_axis.set_ylabel(data_array.label + ((" [" + data_array.unit + "]") if data_array.unit else ""))
      response_axis.set_xlim(0, np.max(time))
      response_axis.set_ylim((1.2 * np.min(voltage), 1.2 * np.max(voltage)))
      response_axis.barh(1.2 * np.min(voltage), stim_duration, (1.2*np.max(voltage)) - (1.2*np.min(voltage)),
                         stim_onset, color='silver', alpha=0.25, zorder=0, label="stimulus epoch")
      response_axis.legend()
      
      stimulus_axis.plot(stimulus_time, stimulus, color="slategray", label="stimulus")
      stimulus_axis.set_xlabel(stim_time_dim.label + ((" [" + stim_time_dim.unit + "]") if stim_time_dim.unit else ""))
      stimulus_axis.set_ylabel(stimulus_array.label + ((" [" + stimulus_array.unit + "]") if stimulus_array.unit else ""))
      stimulus_axis.set_xlim(np.min(stimulus_time), np.max(stimulus_time))
      stimulus_axis.set_ylim(1.2 * np.min(stimulus), 1.2 * np.max(stimulus))
      stimulus_axis.legend()
      
      plt.subplots_adjust(left=0.15, top=0.875, bottom=0.1, right=0.98, hspace=0.45, wspace=0.25)
      plt.show()
  
  
  if __name__ == '__main__':
      stepsize = 0.0001 # s
      time, voltage, stimulus, stim_onset, stim_duration = fake_neuron(stepsize=0.0001)
     
      # create a new file overwriting any existing content
      file_name = 'untagged_feature.h5'
      file = nix.File.open(file_name, nix.FileMode.Overwrite)
  
      # create a 'Block' that represents a grouping object. Here, the recording session.
      # it gets a name and a type 
      block = file.create_block("block name", "nix.session")
  
      # create a 'DataArray' to take the membrane voltage
      data = block.create_data_array("membrane voltage", "nix.regular_sampled.time_series", data=voltage)
      data.label = "membrane voltage"
      time_dim = data.append_sampled_dimension(stepsize)
      time_dim.label = "time"
      time_dim.unit = "s"
     
      # create a stimulus DataArray
      stim = block.create_data_array("stimulus", "nix.regular_sampled.time_series", data=stimulus)
      stim.label = "stimulus current"
      stim.unit = "nA"
      time_dim = stim.append_sampled_dimension(stepsize)
      time_dim.label = "time"
      time_dim.unit = "s"
      
      # create a Tag
      tag = block.create_tag("stimulus presentation", "nix.epoch.stimulus_presentation", [stim_onset])
      tag.extent = [stim_duration]
      tag.references.append(data)
  
      # set stimulus as untagged feature of the tag
      tag.create_feature(stim, nix.LinkType.Untagged)
  
      # let's plot the data from the stored information
      plot_data(tag)
      file.close()
  
subject: add untagged example code