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path: root/trappy/plotter/EventPlot.py
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#    Copyright 2015-2016 ARM Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

"""
The EventPlot is used to represent Events with two characteristics:

    - A name, which determines the colour on the plot
    - A lane, which determines the lane in which the event occurred

In the case of a cpu residency plot, the term lane can be equated to
a CPU and the name attribute can be the PID of the task
"""

from trappy.plotter import AttrConf
import uuid
import json
import os
from trappy.plotter.AbstractDataPlotter import AbstractDataPlotter
from trappy.plotter import IPythonConf

if not IPythonConf.check_ipython():
    raise ImportError("Ipython Environment not Found")

from IPython.display import display, HTML
# pylint: disable=R0201
# pylint: disable=R0921


class EventPlot(AbstractDataPlotter):
    """
        Input Data should be of the format
        ::

                { "<name1>" : [
                                 [event_start, event_end, lane],
                                  .
                                  .
                                 [event_start, event_end, lane],
                              ],
                 .
                 .
                 .

                 "<nameN>" : [
                                [event_start, event_end, lane],
                                 .
                                 .
                                [event_start, event_end, lane],
                             ],
                }

        :param data: Input Data
        :type data: dict

        :param keys: List of unique names in the data dictionary
        :type keys: list

        :param domain: Domain of the event data
        :type domain: tuple

        :param lane_prefix: A string prefix to be used to name each lane
        :type lane_prefix: str

        :param num_lanes: Total number of expected lanes
        :type num_lanes: int

        :param summary: Show a mini plot below the main plot with an
            overview of where your current view is with respect to the
            whole trace
        :type summary: bool

        :param stride: Stride can be used if the trace is very large.
            It results in sampled rendering
        :type stride: bool

        :param lanes: The sorted order of lanes
        :type lanes: list
    """

    def __init__(
            self,
            data,
            keys,
            domain,
            lane_prefix="Lane: ",
            num_lanes=0,
            summary=True,
            stride=False,
            lanes=None):

        self._html = []
        self._fig_name = self._generate_fig_name()
        # Function to get the average duration of each event
        avgFunc = lambda x: sum([(evt[1] - evt[0]) for evt in x]) / float(len(x) + 1)
        avg = {k: avgFunc(v) for k, v in data.iteritems()}
        # Filter keys with zero average time
        keys = filter(lambda x : avg[x] != 0, avg)
        graph = {}
        graph["data"] = data
        graph["lanes"] = self._get_lanes(lanes, lane_prefix, num_lanes, data)
        graph["xDomain"] = domain
        graph["keys"] = sorted(keys, key=lambda x: avg[x], reverse=True)
        graph["showSummary"] = summary
        graph["stride"] = AttrConf.EVENT_PLOT_STRIDE
        self._data = json.dumps(graph)



        # Initialize the HTML, CSS and JS Components
        self._add_css()
        self._init_html()

    def view(self):
        """Views the Graph Object"""

        # Defer installation of IPython components
        # to the .view call to avoid any errors at
        # when importing the module. This facilitates
        # the importing of the module from outside
        # an IPython notebook
        IPythonConf.iplot_install("EventPlot")
        display(HTML(self.html()))

    def savefig(self, path):
        """Save the plot in the provided path

        .. warning:: Not Implemented for :mod:`trappy.plotter.EventPlot`
        """

        raise NotImplementedError(
            "Save is not currently implemented for EventPlot")

    def _get_lanes(self,
                   input_lanes,
                   lane_prefix,
                   num_lanes,
                   data):
        """Populate the lanes for the plot"""

        # If the user has specified lanes explicitly
        lanes = []
        if input_lanes:
            lane_map = {}
            for idx, lane in enumerate(input_lanes):
                lane_map[lane] = idx

            for name in data:
                for event in data[name]:
                    lane = event[2]

                    try:
                        event[2] = lane_map[lane]
                    except KeyError:
                        raise RuntimeError("Invalid Lane %s" % lane)

            for idx, lane in enumerate(input_lanes):
                lanes.append({"id": idx, "label": lane})

        else:

            if not num_lanes:
                raise RuntimeError("Either lanes or num_lanes must be specified")

            for idx in range(num_lanes):
                lanes.append({"id": idx, "label": "{}{}".format(lane_prefix, idx)})

        return lanes

    def _generate_fig_name(self):
        """Generate a unqiue name for the figure"""

        fig_name = "fig_" + uuid.uuid4().hex
        return fig_name

    def _init_html(self):
        """Initialize HTML for the plot"""
        div_js = """
        <script>
            var req = require.config( {

                paths: {

                    "EventPlot": '""" + IPythonConf.add_web_base("plotter_scripts/EventPlot/EventPlot") + """',
                    "d3-tip": '""" + IPythonConf.add_web_base("plotter_scripts/EventPlot/d3.tip.v0.6.3") + """',
                    "d3-plotter": '""" + IPythonConf.add_web_base("plotter_scripts/EventPlot/d3.min") + """'
                },
                shim: {
                    "d3-plotter" : {
                        "exports" : "d3"
                    },
                    "d3-tip": ["d3-plotter"],
                    "EventPlot": {

                        "deps": ["d3-tip", "d3-plotter" ],
                        "exports":  "EventPlot"
                    }
                }
            });
            """

        div_js += "var data = {};\n".format(self._data)
        div_js += """
        req(["require", "EventPlot"], function() {
            EventPlot.generate('""" + self._fig_name + """', '""" + IPythonConf.add_web_base("") + """', data);
        });
        </script>
        """

        self._html.append(
            '<div id="{}" class="eventplot">{}</div>'.format(self._fig_name,
                                                             div_js))

    def _add_css(self):
        """Append the CSS to the HTML code generated"""

        base_dir = os.path.dirname(os.path.realpath(__file__))
        css_file = os.path.join(base_dir, "css/EventPlot.css")
        self._html.append("<style>")

        with open(css_file, 'r') as css_fh:
            self._html += [l[:-1] for l in css_fh.readlines()]

        self._html.append("</style>")

    def html(self):
        """Return a Raw HTML string for the plot"""

        return "\n".join(self._html)