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     "metadata": {},
     "source": [
      "Creating a Trace Object"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline \n",
      "\n",
      "import trappy\n",
      "from matplotlib import pyplot as plt\n",
      "\n",
      "trace = trappy.FTrace(\"./trace_stats.dat\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "View the trace"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Execute to view it\n",
      "trappy.plotter.plot_trace(trace)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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        " *    Copyright 2015-2015 ARM Limited\n",
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        " *\n",
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        " * Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "\n",
        " * you may not use this file except in compliance with the License.\n",
        "\n",
        " * You may obtain a copy of the License at\n",
        "\n",
        " *\n",
        "\n",
        " *     http://www.apache.org/licenses/LICENSE-2.0\n",
        "\n",
        " *\n",
        "\n",
        " * Unless required by applicable law or agreed to in writing, software\n",
        "\n",
        " * distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "\n",
        " * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "\n",
        " * See the License for the specific language governing permissions and\n",
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     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "What is a Trigger?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A trigger is the combination of the following:\n",
      "\n",
      "    * A TRAPpy event\n",
      "    * A pivot for the event\n",
      "    * A set of filters\n",
      "    * A value"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Introduction to Triggers "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "* The example below explains how to create a trigger for the event when a particular process is switched in or out.\n",
      "\n",
      "* This uses the <code>trappy.sched.SchedSwitch</code> event in the trace object. This event looks for the unique_word <code>sched_switch</code> in the trace file.\n",
      "\n",
      "* Here is sample line in the text trace that corresponds to the <code>SchedSwitch<code> event.\n",
      "\n",
      "<pre>\n",
      "sched_switch: prev_comm=trace-cmd prev_pid=4731 prev_prio=120 prev_state=1 next_comm=trace-cmd next_pid=4730 next_prio=120\n",
      "</pre>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can see that this event is populated in the above trace object as:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "trace.sched_switch.data_frame.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>__comm</th>\n",
        "      <th>__cpu</th>\n",
        "      <th>__pid</th>\n",
        "      <th>next_comm</th>\n",
        "      <th>next_pid</th>\n",
        "      <th>next_prio</th>\n",
        "      <th>prev_comm</th>\n",
        "      <th>prev_pid</th>\n",
        "      <th>prev_prio</th>\n",
        "      <th>prev_state</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Time</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
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        "      <th>0.000000</th>\n",
        "      <td>ls</td>\n",
        "      <td>2</td>\n",
        "      <td>4734</td>\n",
        "      <td>migration/2</td>\n",
        "      <td>18</td>\n",
        "      <td>0</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4734</td>\n",
        "      <td>120</td>\n",
        "      <td>1024</td>\n",
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        "    <tr>\n",
        "      <th>0.000022</th>\n",
        "      <td>migration/2</td>\n",
        "      <td>2</td>\n",
        "      <td>18</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4732</td>\n",
        "      <td>120</td>\n",
        "      <td>migration/2</td>\n",
        "      <td>18</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0.000107</th>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>1</td>\n",
        "      <td>4731</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4730</td>\n",
        "      <td>120</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4731</td>\n",
        "      <td>120</td>\n",
        "      <td>1</td>\n",
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        "    <tr>\n",
        "      <th>0.000127</th>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>1</td>\n",
        "      <td>4730</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4729</td>\n",
        "      <td>120</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4730</td>\n",
        "      <td>120</td>\n",
        "      <td>1</td>\n",
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        "    <tr>\n",
        "      <th>0.000142</th>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>1</td>\n",
        "      <td>4729</td>\n",
        "      <td>swapper/1</td>\n",
        "      <td>0</td>\n",
        "      <td>120</td>\n",
        "      <td>trace-cmd</td>\n",
        "      <td>4729</td>\n",
        "      <td>120</td>\n",
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        "</table>\n",
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       "text": [
        "               __comm  __cpu  __pid    next_comm  next_pid  next_prio  \\\n",
        "Time                                                                    \n",
        "0.000000           ls      2   4734  migration/2        18          0   \n",
        "0.000022  migration/2      2     18    trace-cmd      4732        120   \n",
        "0.000107    trace-cmd      1   4731    trace-cmd      4730        120   \n",
        "0.000127    trace-cmd      1   4730    trace-cmd      4729        120   \n",
        "0.000142    trace-cmd      1   4729    swapper/1         0        120   \n",
        "\n",
        "            prev_comm  prev_pid  prev_prio  prev_state  \n",
        "Time                                                    \n",
        "0.000000    trace-cmd      4734        120        1024  \n",
        "0.000022  migration/2        18          0           1  \n",
        "0.000107    trace-cmd      4731        120           1  \n",
        "0.000127    trace-cmd      4730        120           1  \n",
        "0.000142    trace-cmd      4729        120           1  "
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, let us suppose we want to create a trigger for the event when the task <code>trace-cmd (pid=4729)</code>\n",
      "is switched in and assign a value of 1 to the Trigger signal. In pseudo code:\n",
      "\n",
      "    if next_pid == 4729:\n",
      "        Trigger_In(t) = 1\n",
      "\n",
      "We can similarly create a Trigger for the event when the task is switched out:\n",
      "\n",
      "\n",
      "    if prev_pid == 4729:\n",
      "        Trigger_Out(t) = -1\n",
      "        \n",
      "A pivot is the column along which the data is orthogonal. If the data is pivotable it is possibly a super-position of smaller data elements corresponding to each unique pivot value. In our case the pivot value is <code>\"__cpu\"</code> and the data can be split into the scheduler switches happening on the different CPUs"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from trappy.stats.Trigger import Trigger\n",
      "\n",
      "task_pid = 4729\n",
      "\n",
      "trigger_switch_in = Trigger(trace, \n",
      "                            trappy.sched.SchedSwitch,\n",
      "                            pivot = \"__cpu\",\n",
      "                            filters = {\n",
      "                                \"next_pid\" : task_pid\n",
      "                            },\n",
      "                            value = 1)\n",
      "\n",
      "trigger_switch_out = Trigger(trace, \n",
      "                            trappy.sched.SchedSwitch,\n",
      "                            pivot = \"__cpu\",\n",
      "                            filters = {\n",
      "                                \"prev_pid\" : task_pid\n",
      "                            },\n",
      "                            value = -1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Topology and Aggregation"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Creating a CPU (pivot) Topology"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A topology can be explained as a collection of different arrangements of groups of nodes. These different arrangements are called **levels**. Each level has a multiple groups of nodes. For example for a CPU topology can have the following levels:\n",
      "\n",
      "* CPU\n",
      "\n",
      "        [\n",
      "            [cpu0],\n",
      "            [cpu1],\n",
      "            .\n",
      "            .\n",
      "            [cpuN],\n",
      "        ]\n",
      "\n",
      "* Cluster\n",
      "\n",
      "        [\n",
      "            [custer1_cpu1, cluster1_cpu2, ... cluster1_cpuM)],\n",
      "            .\n",
      "            .\n",
      "            .\n",
      "            [custerK_cpu1, clusterK_cpu2, ... clusterK_cpuP)]\n",
      "        ]\n",
      "\n",
      "* System\n",
      "\n",
      "        [\n",
      "            [cpu0,\n",
      "             cpu1,\n",
      "             .\n",
      "             .\n",
      "             .\n",
      "             cpuN]\n",
      "        ]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from trappy.stats.Topology import Topology\n",
      "\n",
      "cluster_0 = [0, 3, 4, 5]\n",
      "cluster_1 = [1, 2]\n",
      "clusters = [cluster_0, cluster_1]\n",
      "\n",
      "topology = Topology(clusters=clusters)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "* Aggregator facilitates the aggregation of signals from different triggers. The aggregator also understands a topology over which the aggregation can be performed and this aggregation can be expressed as a function which takes <code>pandas.Series</code> as an input. For example.\n",
      "\n",
      "\n",
      "        def aggfunc(series):\n",
      "               return modify(series)\n",
      "       \n",
      "\n",
      "* The elements in the topology should be a superset of the pivot values of the Triggers. In our case the pivot value is <code>\"__cpu\"</code>, so, the Topology corresponds to a CPU topology. \n",
      "\n",
      "### Base Aggregation\n",
      "\n",
      "* Topology.flatten() gives the list of all the nodes in the Topology.\n",
      "* The node in the Topology corresponds to a pivot value in the Trigger\n",
      "* The signals for the pivot value are super imposed and stored in a dictionary."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "topology.flatten()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "[0, 1, 2, 3, 4, 5]"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is an informal pseudo-code for this base aggregation:\n",
      "\n",
      "\n",
      "    base_signals = {}\n",
      "    \n",
      "    for node in topology.flatten():\n",
      "        node_signal = init_signal()\n",
      "            \n",
      "        for trigger in triggers:\n",
      "            node_signal.union(trigger.get_signal_for_pivot_val(node))\n",
      "            \n",
      "        base_signal[node] = node_signal\n",
      "            \n",
      "### Aggregation over the topology\n",
      "\n",
      "\n",
      "The `Aggregator.aggregate` accepts a level parameter:\n",
      "\n",
      "* Each level in the topology contains a group of nodes\n",
      "* These can be accessed as\n",
      "    \n",
      "          topology.get_level(level)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "topology.get_level(\"cluster\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "[[0, 3, 4, 5], [1, 2]]"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is an informal psuedo-code for this aggregation over the Topology:\n",
      "\n",
      "    agg_signal = []\n",
      "    \n",
      "    for group_of_nodes in Topology.get_level(level):\n",
      "        \n",
      "        for node in group_of_nodes:\n",
      "        \n",
      "            group_signal = init_signal()\n",
      "            group_signal += aggfunc(base_signals[node])\n",
      "            \n",
      "        agg_signal.append(group_signal)\n",
      "        \n",
      "            "
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Create the Aggregator"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "from trappy.stats.Aggregator import MultiTriggerAggregator\n",
      "\n",
      "def no_operation_aggfunc(series):\n",
      "    return series\n",
      "\n",
      "triggers = [\n",
      "            trigger_switch_in,\n",
      "            trigger_switch_out\n",
      "           ]\n",
      "\n",
      "\n",
      "vector_agg = MultiTriggerAggregator(triggers, topology, no_operation_aggfunc)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examples of Aggregation"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Aggregate at Cluster level"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "level = \"cluster\"\n",
      "result = vector_agg.aggregate(level=level)\n",
      "\n",
      "\n",
      "# Utility Code for Viewing the data\n",
      "\n",
      "clusters = (str(c) for c in topology.get_level(level))\n",
      "\n",
      "for series, cluster in zip(result, clusters):\n",
      "    plt.figure(figsize=(15,7))\n",
      "    plt.plot(series.index, series.values)\n",
      "    plt.title(cluster)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f3e12ce7450>"
       ]
      },
      {
       "metadata": {},
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ZD1QvFNF5LL8Aw0V1/M61j18ENOLHEi27hu6jxBN1QUE3O9Uz0kdvX2KS8seK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voWFKpHwY/1sfdaOjvt7Dv+Vm2qsu8Kp7Mv9izz27W70t4qjxUvii2u+LOKntqXV/vhpG9UZXb8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DZV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\noh8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L9U650wPPI+1VBxJH3pXRQYb3LnsY1u7Oeead+i1vd0b8Kt9V/VXuTj3XJfOfM4Ky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\n0KFDhw4dOnTo0KFDhw4dOnToEKD/D7MnztOKhRiGAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f3e12b81b90>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Aggregate at CPU level"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "level = \"cpu\"\n",
      "result = vector_agg.aggregate(level=level)\n",
      "\n",
      "\n",
      "# Utility Code for Viewing the data\n",
      "\n",
      "cpus = (str(c) for c in topology.get_level(level))\n",
      "\n",
      "for series, cpu in zip(result, cpus):\n",
      "    plt.figure(figsize=(15,7))\n",
      "    plt.plot(series.index, series.values)\n",
      "    plt.title(cpu)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f3e1265bb90>"
       ]
      },
      {
       "metadata": {},
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2Dshnmf8xvUdG/JS84utni7soekRxn+UUJSf4/1mMM1lHt3PIbFuNfWYzi1vV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\nTBYvot1a/EZWpc1s+9a0nUN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+s9s5qPUi/ZiNkNz+POKN6lZtwGZ2KDGZ4VZiXOWJ6HVQ\ndWV8sxkv0VHRI7ILa+uMzswWByxnnCu3jfDsUFncxcqU5cMo1ys5ohIflXYZXXxrVX5WRoYynlnO\nQ3wy//a0ojL1euUego5KfLN4Q/RGZiGhgRmPtwHDxXT8Vn7jp4z4RfSRcyoyRAHkabDk5K9XpnpG\nNDK5mUyKzjM4SBZb/oxnnHfEryJ31sYqT4bTzyvTiFSfy3gyn0D1Vft5OvZa9t1E1WdYHTX+omuZ\nLJn9OqgjQNn1iqxqeaYP+yFZo2M24uf5qnZQbLmCnkqntbUjfpkeio8o9CrtOurb2dHLwuRWdcxk\nQDyjcmU7B8RP4eNpo+Oq+EDHkRkZKm3V55A9/Ygfk8+Xd6iM+Kkdv+jZsoMy4uflQTZdZXsv64gP\nVHzM67khhovp+KERP/SWogMLjMjpEC66lvH2+OwNrQcWPA88cHpIyt56oSC2slTfGmcJQknQs/zu\nu+92HbzOSlv79ssSq6JTVsfXVd9Co0TL/K2XZT5X1Re9cR1pT3ZjULavUHhYWZkvsDfrER/EuyKT\nLWcLmyi6+zxSlY3pieRh8RXRZu0QjeJXc0XEU8HNrmX6jshZXcV11OfR6BU6V+VX6SBdUTwp9Ptv\nNrchm6k8I1qjPpy1tc0XXpbsGQTJ4WWsPBNU8jPjyWxqy9RZMhay58JIFiY/AnWqp0rX6ovqdh72\nmMW+pYVoRjIiPiPf+DFf8OcbYriYjl9lxC9LzD4IlGkiSmJGSZzVR0mMlR3H6e2QMt3T3yhmbz7K\nUcVBcjH7WP2VB0XvK/anTEFRdYpkjm7UjB7zjw7V/bAyn2N2RnWQPbM2U+xnjzPf+CEeys2H+Y4i\nQybTzHS4TO+KbMw/I/rKS6tRWY7j9GJP3c6B0YzaTenUKz4aydV5KvRs+WjuYjIy/0Kxm9HLdFyh\na6UdUMzOxKinW8kT3j/YiJ+iK8JHOmc6MV9l8ZHJMzPiF9mlyxbhZrp5nEgexjuShfHx5Suneir2\nU18UK7Yf8SHVByLdvR962CN+OVxMxy/7xq/S2VOmemYJwdPLcPs5mkuOAgUFaKXjFx3tuSITShhq\nAkE6qnL637VrrV2/rk19ZLIhOyi6oess4VWSrJf//vvzUaGID2tfJhfzx0h2hBvximRR3yb6c9Vn\nULnnn3X4FFsw+3XwN77KN1+KbVE5G6lFdLzcSI6s08Fi7Pr1fIGbTE+PE5VX6GW+wto4s+tILDM/\ni+Kq08vw1ViN+DAdOyjbOah2i2zF2l6xmaJ71PZRXWW6MtIZ6eDLmB2U+EDlkc8gXsr2QpFMqv+g\nmGOx1yFa1VNpW4uT8en4aL2ByIYotrvMjL9/bo2uReVev8wPIjz0HeDoFlNe/4jXBgwX0/E7xz5+\nWUKM6LLAzOirMqCE7esoe/kxGiNvwZVRMo/L+LCkjmx48+atjl9lelwmp4KrHFfbqP/POrqjPpfJ\ng/w+ewDK7Jf5WraKadVnfJkiY3ZEdEdmCqwY8cvwvGwKPpN7VpYZ/1b08riVdqnSq+KMbOegtmUm\nG6JXjR0fi6i9ZhZ3iWhWYyOzGdNVjd8RXa1MiA/Lc6vuc0puyPRENDPZqnp4WT3v1vCqnhbX//c0\nI96ez3Hg9QY63jm3c6jmcmb7ary1VpvqqbRphLfhTriY7RxGV/VEI4H+LaiFUacdxfG4HSIZO14f\n8cu2dEA3k6r8amLOkrga7BmfPtUzGyFgNhyZ6oluwpF+Vd7ZuTIistI/0XUFJ7Mfk6HjrHiwUPWM\nrrH2i9ra64doRzj33VdrW6ZDxBvZGcViVL/6cFaN81H/Rm/GR2VXfDSzZRbj6jR1xs/SRP7lcUbo\nMR1V+1QXsmG0RnGU2BzlaX08+54xo5nxqeKOxgfzAzTKldl9VA90zR7tee9sMbv7elGZrxuVM1sg\n+Vq7c5SObdHhj5lNK89go/GWjXSO+Hok+4Y74eJH/KIHruytDRoW90Fj67HEEZVnCQSdW2CBqE71\nrD7EVHXM9I1oZboxWfpPnepZTWZMR6ZTJZEq8kXn7BuoynSu7JzJWtE5ix3Pw/vqzKqeKv+obtZJ\nUGVR7dea7svMjtmxMrps8ZiuSlyo/qF845fRVOxWoYfKFR9h8rCOnzIyg/hlOKoNVHpZu3ZQ9rar\n0FTaMzqP5Ef0mU2YfSqfH0RyqnJntlJwR3kpnR1ky0pbR/SUqZ4dKi+3/FHhcxxx7va8bRmS10/1\n9DKhDhXSzV+v+EXG5+ZNrDerE/338u+pnjlcTMfvHPv4RUHj/6OAQrw9rnJj8cCSYL82urhLpMtI\ncsh4VeyC+GT2UUb8sjZQdVR1UniP4B5HbUQEyYX8QJEn4onwM/tF/C3OtWvzi7so/Ks2UH2nYr/e\nttWpnpkOFRlVneyR0VBlsJD5N7MjwlV1r+g54yuj7V3xeZWO0m4r6ESxXI3DCE+xg4ob6YpkG9E1\nqvHV0rwAACAASURBVB/xq7R1ZivVVxU5PO7998cdm8xOmU1G/CKyB5Mn4pO1DfOV6IWVvV6Z6olk\nQXVZe0V4VVyL73GyUV/Vx6L6kRwbbsHFdPxWfeMXXfNvGKLRE5Y07Zt0lsSOI/8+yuN76HjXrp2+\n8VOmeqJjJL+XSfmey+tcmXde+UbK/qojftF1xNO/WYvs4Nva0mc2z/Rm8o90DrI2rMijJPII18uA\nYsS2g/I2seoznr9vP2QDy9vLy2Ios5/Fjb4TUeJTaRdkc+Qz0ZtudD3C8byQnTw+8281N3m5vZxV\nelGMR7yUGLf/kX9neox8j8NGLlhcVuMd0WGxjPzFy49wKrkts1mmRwd2D1Db1fuc4j+Z3ZHc1Sna\nyFa27L77TvdgNDqjxFPmP962WZxbiKZNopyU6YtmiPXz6IWV52n5RDJ52ih/qDGu+EVkF4QbtaUS\n15EtovtH1BYbMFxMx2/Vqp6Ro6Hgs+fshhLVz25qkXwe0I3pOOZW9UQ3ACZTlmAYLnuQRLhM1ps3\n82/8Kjcb1AZMN3acnQbm9e8/ZfELX45oIp5KOyBbMlszeaN6yk2l4jNKuzG9Ij1YW6v26z/09hTx\nRXJ6mSM6mZ4RvsJXoc14MP9GuttzFvNKuzB6SF/2MMp4qqP3qoxMp4oNo/bJdLQ4vryia4corkd1\nU23G6itxUtHVl3eZIlmtvEq8RfUzX63YtdPJFldjvhXRVvKHv6a88LE0UOyjMn8d0WVTPVFdRF9p\nk9EYR3gj8YZ8HeEiWVj8I/tvuKCOX/aNn3Ug9kYhCh50g4/qdchoe7wKvahulDAqUz2j85E35SMJ\nOsLxuqg3sl6/MuIXyZW1f0RDoc/szXizN4H2BhMl2qrMnm6mF6qDRj0jmap+k91UEK2Mf2WkhF2r\n6OVliuSaHb3OjsgGqj0zG7A4UGVU/JvJo8bkueghe0c8s+8ZI74ZjpdDGQGv0EPniE6HmTyNjrP3\nrqwNR/ME0lWxpyq3pVuZYaD4KhvttnXYPrpK+yHaIz4b8bbfy0XyKzQzX+/n2ewUVObpVhZ3ydpL\n8YtIz4yfPbIprtEPjWBGdtnAYa/qCQIAnWfDzJaWxVMSEZum4HmqCdZDx52Z6lmRX50ekyWJCIcl\nuUgW+1PfOGbJX+XN7ODpjybSjH42FW7UP5F+Xg7WZtmP3dA7VKeRMP0YLuIfxabnrYwkj9hP6Qhk\nMYF0Vl9sePzKqLmVGcmT6aIsXpTFpD16mUboRTp626Aj46lOa/XXRx/0FXpK7GQ8I7uyzhDii+xW\n8aeqzZj+1nYRzw7VTi6z/0hboxyI6Cg4XlY744bpmsVTZndb1+sYyWrBTkNFbWj/Z9MbIzmsf0cv\nrHo9+41f9OxqZa7EQWSDql/MxFtlqqevi3T01zfEcPEjfiyJReUsoUT/WfKtPFApAeuB1Rtd3AXZ\nhslv7aBMF/G4bISB4aLj6FTPaluodvD0lLeWih09jeo0IlUvpB+LI1+/aj+kY8dRvvGr+EzFBkr8\ndkD+W7WfulBRpkO1vhIPjB6qm12PjrPbOayKu1F6LJY8L2U7B4Vv5GeZ/yt6WHpMxwjHH6sr1mZx\njeoz22U2i+wU8czyhNLJ9eVWtohP5SXxrD9H9SPbZCN+Cn9EO5IjwrE2i+h6m0b4/jwri/6rq1t6\nGT0de12xCSpDdRDeaLxlK7uq+vhz304b7oSL6fipq3r6MhZ0amBlN5nsDYYtQ2/BfB1Ur/8f/cbP\n8mQJOTtmtJGOFT4ZTpRwlU6Al3/UDihxVeqypOtpqhtcV/RS9EX+nr2AUeih88o+UYrPKDaodiBn\n/djar7KwSUTLyzQqK9MhktvjRG+WVV0q2zlUjkwnRe9RWZgdR7eimYlTNRZX6GjL1CmBKk0bq+fK\nbcg2lndks0qHPipTZFPtoOjvZazcCzNdlXhS8kI/r9zbM7yq/T1tW56NfEUyMbpe3wg/ay9mV0Sr\nGm/qiJ/Cx9e3xw13wsV0/PqIX19GuEOWqJADowRjadlravKIcPyP1bGA6h3HrameoyN+1cCsHM+F\n6/WvbOAe/dQbidpuCu9RG/VEe44N3EfawdefkSWiw1bHq+gXyaxey6a8jPpvdJNWv/lCx0pb+pEP\nVM/LyaZuzcq00r8jvWZHha08yFaRfyCbKB0/ZcpV5l+I/0jssk591q4V367IpMZEhmuPI/Sydq3Y\nDeH7OqO6zMaHnXGjjPid0+4R79buXHE0slv0P3q2ZDY/DvytW6+vTvXM9LXyZO218tkG4VSneqqD\nHnvEL4eL6fjZET/rbJFDogDxyatD9maF/Wx9dN3SrT48RXoex60Rv5XbOTAds4Q8gjtT55zbOahy\n+p9682R6o4fx1vJvoDwPZYoPskW1zZSfx/XtU32bOCKz8iIgmo7q7cTsVpGl466YtsxsjPgifIvn\ndc3eIqu8/a8yop3Z3tNQ2yfD6aB2rhAO6+Qq/lfRw3fYED3FrxSeUbtGuo7w83KfK7ehTi7i2UHd\ni1Lxkco1Nh1XOTKfiegp39jP2t3bVpmS2IF94xfRjmgh+h6nsp2Dr2v/+2/8Ks+KyG7qvQPx8bLY\no7rlUiZzZBdftuF2uJjFXVbt4zc74mfL0ZxxFtxMbg8+mH1dZaqnMq+d/Uc3GGU+ePYgXcH1SWh0\nOwemW8QL4TIcpi/jkeGObueAypQ2i2goN14kG4tN+1/5fqDqM5HM2Y0H2TXKJ/bI3lpG9LKtDDL9\nbBm70aJ6TAcUQ9G1jDbidRzaixzPV5FXiU3VXp52JbfZetVVPRGOMh0MXUc8Pb6Sz5hvqdMfPS11\nhCD7r9isHzOeWZ5gunrwfoR08CP0kU5IpoiO4vtI3k4nW9wlkpH5kfIiJZIjqtNavKqnMgKIfIG1\ne6XNbRtG94hqHmG+Ff1ntme+H9GP9p7tdNg9IYtnJd9cOlzkiF/UMVOnejKni5xwtD7irQRBxNvr\nt2Kqp/LmXwneCi6TJ5PF6z8yhSjiPTsNrMoz4q2MNq6YCjfqlxFdNnpWsVGEc//9t/uo1Tfjs7L9\nEE+Vrmrj6mqAanl0XRklsUemq+rrio3V0RImD6pT8WumZ2aL1e09o4cy4pHRU3TM6FzVdg6jOo74\nFLo2u4KpaoeojStyIpnUWS+zUz0rsWJpo2teZ6SLKiOyZYSjvLRDdS3Y7RxG2v+qbV+dlaP4qNVp\nA4aL6fhV9vFjwcuc2v5HzhnRQG/kIlmiIfOIf8TbHkenekayeVnQtUw29c2R5cFGTLLEpK6EyJI2\nkj/TzbebkkDtMRspipKn8jE9azs2gjwzdS3CG4kRizuyT5TiMywHKH6btdvo9BxlcZdMP5S31Bcb\nii6+nMVXRtvTrWznkMkZyTFCb2WMW57VRUA8TSUfo/ayMJvPIhv666hdWR7x8iu+ivxxxGZRLM36\ncBabnmc1l3iZsjiO4pbJZcsq2zlU40nxY6SHhUqeikapIv+LdI1GvpBsSP+I9kyMzzyvKM8/KIdF\n9LJ2ROfINhsuqONXGfFjo3/KcHlEPwpgJbgtbhTozMmjgO//z7GdA+If4VZuIqqOiixdh+o+fpEd\nMt5V3RSeCh2k++x2DhHdEZ8YabOqvCNTiRh/xX8V32EyZzIxnErbZvRUf2b+6esz/85oMl+05cwG\nSPdM/4x/lZ6iN6Jjy0dH/BTaih9kvqHK4XGj/9WpnpmvMBx7vWIzWyfDZfWzUbBMn4iH2jYZ7SxG\nGb2ItqqrQrsaaxEdi8s2cEf/fRkaefK6VUb8ok6Vr4f8hT27KvHMeCJcZvvqqp7enqhDvUf8crio\nb/yU7Ry8w6GbVuSYlmaWJC1OZbhdeYvn5YjkGd3OIdJfnd7B5B7BnalTmeqJ+KDEpMrJ/EDRKcJB\n0yezjhB7Q6v452w7Kz/UHl7efq064lflj9ovmyKErlXtVh3xU+2s2Lx6jOyEZGK0mC4rF3dR/Lvq\n17ZsdHr4aHvP6BHllOw+NOPbarsqfpvZYTS3jfL0tju3D7P6vo0znAqvbARMGfGbtbvHqYxgIpsg\n/MxvPK4tV7aV8nUjun5BmtHZI2p8ZP7AbH/zJl95uxKH3i7IdhtuwUWN+K1Y3EVxNBTk/hi9wUCy\neEBJzAIL4NZO3/ipUz09TVX+KOBX4M7WqSzuEkFk2w4V3dCNMeON6Hk9LG71GygPzM8r7YD0VGJF\neUDJHixGfEaVGdXr4HPPSHxEN3/lrXGmH9LJ12NyRDr4674sooNoM10qK11mManqNhrjWaxnMV7d\n1LzDSHxa+hm9LGaRvIxOdXQza1f13oV0rLZr5NMRTmu1RZq8rp6HkjOZHTK9rTzMZzy949BmZIzk\nRIbjefhyC9F2DixPoJzYr0Xl/ZxN7+2yoLoeWJka4xGd0ee1SJ5+TV1sLostLy/iueEWXEzHLxvx\nQ87kzzOns7QQXVQf3bCjhM3qKPTOMdWzqmNF/hl6ttzqv2pxl1m5Gb0RnlGZ8obVl6/2S4Uu8i9E\nH9Ed+caP+fdo+zGcmXj2NlCnLbP4HZG1qj/TMftltqiuWqvGUiUWVP1n/WhmmvqIHlVdR+RAdKq+\nrcSLquMKe3i5Mx/Otq5gtDx+RX+kY9aOmY38sb+YU3WdaetRXL81Ajt6uTsoLzyOI34BjTql0bNr\nB7u4SyQne3b1ZcpL0FnbZ1PzR3zM67khhovo+B0H7vhlb4iiZGf/WxxbJ6tny6I3cug/etsYOTkK\nmuOYm+rJ5Gd8GY6KG5WjOkwWNOJXGYXKEquStNRkq+qN2kKZ6unlzd5wj7aD8paW2Q/9/BtlNkVM\nlTWijeRib9gj3qosSG7bZurUv8yGikyqnyI7RCOBKm3WDtUtDpT2t/9H6KE2V2zI6K2c6pnpwUbM\nRm3GdPX/V690mfnbjM2ye4C3nf/NrGCaye1zvL/GaGdHRs/j9I7fzFTPiCazu8XJOmQd0IwFNrrH\nfBrpOLMNjb3uO36V5zKUj1blkmhUMMvXmYyoE8xGcjec4CK+8fuVXzklmfvuO883fmyaiD/PkoXH\n7cP8WTKOgPHq2zkoUz09b68LshHTMZJbwUVJfUQWJeEq02RmdGPXos5YRW+PWxklyGhbnNl2QPIy\nOX15hIOm8lZk9bSjmwprP88XyV9px5npcEw/Jb69fopPdmAPgxlfJcYqU5kzvTyO8sJNiSWE66fq\nZfav5K5IXqbHCl0jXpV8Zumoi1+ofqjaoWIzZvtIL6RDpZMb0VLi8Ti0e5ca91ZfZKNIntHtHBB9\nK4enqRyZ/sxHIxwriy/3kE31ROUZjr+eDXjM2j7CZX6mrjKO9EJ2ZfG14QQXMeLXt3JorT7V05f7\nNxeWRgc7pxslQJQ0EW4kj+UVBQEK5OOYX9zFy+BxKjeG6k3E8lffnHsbZN/4Rbwqdsh0Ux70mEzZ\nGzpb1+qrvFlEvp75dEQvawcF19svuiF4HOUbvxH+ldiMbIN4Km+jfZkf8at835b9Ml0j2TJ7WrmZ\nHIz3OUb8lHYbpRe1vxLrkVy2rjpKgPwv09leizqQ7D7E5EH/ma+t7Awh3Rh/xWYqT287/6u2axaT\nI3ZQ4oPJZesgeSojfiieItkim7K2RnpE3/gxfNS2Hi+SNcrdyOZIJlum3rftNfSiomr7DNfWyV7o\nsJj0+ke8NmC4iBG/vpVDa1e3qmdE35dngWNxmfNHMrR2O32v88w3fiyRRnJbnCwprcRF9u4dg8r0\nOPS2GsmXyctw2IMBklOZWrNig+vML5V2QHpaXoivKq/yjZ8iK+NfwUHxq06xYbitjS32ociryJbh\ned6RDB6vIms/Kv7N5Km+wBqh53GVqVQzI7xIj0xnVX52RPGl8urnle0cEF/PX713qTZTH4Iz21V1\ntTJ5mZG8mS5IzsqLTRbrxzG2gbvyHMD8AdHzvFu7c4VMi8/sicqi8n5e3cAdye+vq34TXRuhUW2f\nbDXTigzWXqjTvOEWXPyIH3v4i86VNzp+xA8dKzgdqvRY2YMP5h2/7M3dCh0ruKx9KvTVffzY2071\nDWImJ+KFErvCK6KvbuegyGyPqlyI7mzHGdEZ3SB2lL+Xw+aBEd6oHaMHsGpHgOmAeDP/VNp1ZOQY\nlUfHkc5QdM23mxrrMz4f2ZLRUV5aqf7neSkdYMVvkc6RTVa0a1XGDKdis1meSrtGdEblnvHn6Jmg\nOnI6ss/qqrZmnVMmS2Zri+P5IL0y//bARvwqi7tk7aW8yFBszzrd1cW4lGeUiNeGO2GP+CXOyhJZ\nh+wtF6KTBdVx3Lm6FKvjAdXrdB94QN/OQbkhRPKvxmV2rdBXp3pm9Gd0i9plhqc9eh7KKqaZrzOd\nVtmiiut17efRg4VqXyaHMnqhtF9l2pHi6yMPx4qto6P6llh9uMx0VX1m5R5oUd0Reqyc8czkqa7q\nmfHN5PV81LZUdETtbds1W/0x46u0OcIbsZkfgUO28/+VdmV8ER9GZ8RWUZ2KrOoMFCQbkp+NfCp+\n3cGP+Fk66qiUwge1OXvhHJ13mSs+HuEwvSrxrdi+MtUzOkYDLL18A4eLH/FjARuVjwQ2oqtOs2AB\nlE07iAK2tTVTPRXbeTnVqYkIFyXhc0/1rNpB1Y3pxHhW38iNdHTV9lX083UyXqhcnY7HOn4Vn1Hk\nYP6Q+QySJXpwZDGzYjuHKO8gPK9fxjc6evzovEJ7dKpnFpMsNkfoWbkquc1en+noe9pKu6t+bK+P\n2tXLoU5/ZHwR7cw/VJtVXnKwa5UFL5hfZj6rxrbXO+Kh+Iy/VpnqyfivGLlEPqDMWIjktmURXV8/\n6wBV9/GrtC2LcVY3irORqZ5qx5/RQueRfTac4CI6fsqI3zmnekYJIuIdTTFiuJkcLPn3VT2ri7sw\nWSKZKjffLIlHMilJHeFUOkKsg40e2jPdmF7oiG5GLPn2ssoDVEbb24FN6fB1Zn0jixF7Q7Xtm9m3\n+oAUxT3DYXaq8IvkVaf+Mf2YXTKbqDEfyZF1kJBPerpscZfR3OTpVOmNxLhit9FvOkdijuk6EpdZ\nzvF01G1ZmB7IDjO5TYmJSC7mw5VtOnyZP6ovyZBMaq6KZGT3oV6W3Y+UfDrqx15+D3amFaJrgenr\n/c8C8u/oecPTivKLrWufc6O6ES67rsa3ymflBu6R/hswXMRUTzvid//9tztG9pYiSpoW39LoECXE\nkZvGcWjD955nxNufV6Z6Rr9MbkXHij0Qn1FZ7qUN3BnOLE/b3qsWd1nZDkhPxW5Z+85M9YzKW5t7\nCKy2X6XuyHYOmZ9VZfPXK6MgkcxVWVb4N5NhFb0RXh5n1eI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neip5YdVUz0xHVJZN9ezH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HAAAg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\noFSaioeuzmowrtqW1a3gVpOKasCv6lLboRsw0F8lA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7SZ5zt+Ojzf8Xt5e88Nly0CHZBR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x4yrattp+/DH2SfVDhP85h3UBXOUgexC2LLfmjBsvtY7sn+hGvu+m5qNt+T/y7Rnx43Qu/IxO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\nFNPd/izLU7lTafrCE1fvTt+TeSb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LRuX56KPrfb5bQ9M+rOJmbes5evbv09O58FMErrs/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\ngg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f3e12b81750>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f3e128a9590>"
       ]
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       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f3e128a9a10>"
       ]
      },
      {
       "metadata": {},
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       "text": [
        "<matplotlib.figure.Figure at 0x7f3e12a7d4d0>"
       ]
      },
      {
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       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f3e12a611d0>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Aggregator Function can return Scalars"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An aggregator function can return a scalar, for example the number of \"switch ins\". Each value in the result has a one-to-one correspondence with the groups in `Topology.get_level(level)`"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def num_switch_ins(series):\n",
      "    return len(series[series == 1])\n",
      "\n",
      "scalar_agg = MultiTriggerAggregator(triggers, topology, num_switch_ins)\n",
      "\n",
      "print scalar_agg.aggregate(level=\"cpu\")\n",
      "print scalar_agg.aggregate(level=\"cluster\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[0, 364, 0, 0, 0, 0]\n",
        "[0, 364]\n"
       ]
      }
     ],
     "prompt_number": 11
    }
   ],
   "metadata": {}
  }
 ]
}