Nengo.ipynb

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   "source": [
    "import nengo\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
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     "text": [
      "/Users/jim/Documents/notebooks/.env/lib/python2.7/site-packages/IPython/config.py:13: ShimWarning: The `IPython.config` package has been deprecated. You should import from traitlets.config instead.\n",
      "  \"You should import from traitlets.config instead.\", ShimWarning)\n",
      "/Users/jim/Documents/notebooks/.env/lib/python2.7/site-packages/IPython/nbconvert.py:13: ShimWarning: The `IPython.nbconvert` package has been deprecated. You should import from ipython_nbconvert instead.\n",
      "  \"You should import from ipython_nbconvert instead.\", ShimWarning)\n",
      "/Users/jim/Documents/notebooks/.env/lib/python2.7/site-packages/IPython/nbformat.py:13: ShimWarning: The `IPython.nbformat` package has been deprecated. You should import from nbformat instead.\n",
      "  \"You should import from nbformat instead.\", ShimWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Simulation finished in 0:00:01.                                                 \n"
     ]
    }
   ],
   "source": [
    "with nengo.Network() as net:\n",
    "    sin_input = nengo.Node(output=np.sin)\n",
    "    # A population of 100 neurons representing a sine wave\n",
    "    sin_ens = nengo.Ensemble(n_neurons=100, dimensions=1)\n",
    "    nengo.Connection(sin_input, sin_ens)\n",
    "    # A population of 100 neurons representing the square of the sine wave\n",
    "    sin_squared = nengo.Ensemble(n_neurons=100, dimensions=1)\n",
    "    nengo.Connection(sin_ens, sin_squared, function=np.square)\n",
    "    # View the decoded output of sin_squared\n",
    "    squared_probe = nengo.Probe(sin_squared, synapse=0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sim = nengo.Simulator(net)\n",
    "sim.run(5.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.plot(sim.trange(), sim.data[squared_probe])\n",
    "plt.show()"
   ]
  }
 ],
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