xref: /external/trappy/trappy/stats/Trigger.py

#    Copyright 2015-2015 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.
#

"""Trigger is a representation of the following:

    1. Event
    2. An associated value
    3. A set of filters
"""

import types
from trappy.plotter.Utils import listify


class Trigger(object):
    """The tigger is an event relationship which
       accepts a run object to "generate" qualified data

       The filter can either have a function

       def function_based_filter(elem):
            if condition:
                return True
            else:
                return False

      or value

      f = {}
      f["data_column_a"] = function_based_filter
      f["data_column_b"] = value
    """

    def __init__(self, run, template, filters, value, pivot):
        """
            Args:
                run (trappy.Run): A trappy Run object
                template (trappy.Base): A trappy Event to act as a trigger
                filters (dict): Key value filter pairs
                value: Value can be a string or a numeric
                pivot: This is the column around which the data will be
                    pivoted
        """

        self.template = template
        self._filters = filters
        self.value = value
        self._pivot = pivot
        self.run = run

    def generate(self, pivot_val):
        """Generate the trigger data for a given pivot value
           and a run index

            Args:
                pivot_val: The pivot to generate data for
        """


        trappy_event = getattr(self.run, self.template.name)
        data_frame = trappy_event.data_frame

        mask = (data_frame[self._pivot] == pivot_val)
        for key in self._filters:

            operator = self._filters[key]

            if isinstance(operator, types.FunctionType):
                mask = mask & (data_frame[key].apply(operator))
            else:
                value = operator
                mask = apply_filter_kv(key, value, data_frame, mask)

        return data_frame[mask]


def apply_filter_kv(key, value, data_frame, mask):
    """Internal function to apply a key value
       filter to a data_frame and update the initial
       condition provided in mask.

       Returns:
           Mask to index the data frame
    """

    value = listify(value)
    if key not in data_frame.columns:
        return mask
    else:
        for val in value:
            mask = mask & (data_frame[key] == val)
        return mask