Remove unused items in tools/

tools/python_charts/webrtc/data_helper.py

-#!/usr/bin/env python
-#  Copyright (c) 2011 The WebRTC project authors. All Rights Reserved.
-#
-#  Use of this source code is governed by a BSD-style license
-#  that can be found in the LICENSE file in the root of the source
-#  tree. An additional intellectual property rights grant can be found
-#  in the file PATENTS.  All contributing project authors may
-#  be found in the AUTHORS file in the root of the source tree.
-
-__author__ = 'kjellander@webrtc.org (Henrik Kjellander)'
-
-class DataHelper(object):
-  """
-  Helper class for managing table data.
-  This class does not verify the consistency of the data tables sent into it.
-  """
-
-  def __init__(self, data_list, table_description, names_list, messages):
-    """ Initializes the DataHelper with data.
-
-    Args:
-      data_list: List of one or more data lists in the format that the
-        Google Visualization Python API expects (list of dictionaries, one
-        per row of data). See the gviz_api.DataTable documentation for more
-        info.
-      table_description: dictionary describing the data types of all
-        columns in the data lists, as defined in the gviz_api.DataTable
-        documentation.
-      names_list: List of strings of what we're going to name the data
-        columns after. Usually different runs of data collection.
-      messages: List of strings we might append error messages to.
-    """
-    self.data_list = data_list
-    self.table_description = table_description
-    self.names_list = names_list
-    self.messages = messages
-    self.number_of_datasets = len(data_list)
-    self.number_of_frames = len(data_list[0])
-
-  def CreateData(self, field_name, start_frame=0, end_frame=0):
-    """ Creates a data structure for a specified data field.
-
-    Creates a data structure (data type description dictionary and a list
-    of data dictionaries) to be used with the Google Visualization Python
-    API. The frame_number column is always present and one column per data
-    set is added and its field name is suffixed by _N where N is the number
-    of the data set (0, 1, 2...)
-
-    Args:
-      field_name: String name of the field, must be present in the data
-        structure this DataHelper was created with.
-      start_frame: Frame number to start at (zero indexed). Default: 0.
-      end_frame: Frame number to be the last frame. If zero all frames
-        will be included. Default: 0.
-
-    Returns:
-      A tuple containing:
-      - a dictionary describing the columns in the data result_data_table below.
-        This description uses the name for each data set specified by
-        names_list.
-
-        Example with two data sets named 'Foreman' and 'Crew':
-        {
-         'frame_number': ('number', 'Frame number'),
-         'ssim_0': ('number', 'Foreman'),
-         'ssim_1': ('number', 'Crew'),
-         }
-      - a list containing dictionaries (one per row) with the frame_number
-        column and one column of the specified field_name column per data
-        set.
-
-        Example with two data sets named 'Foreman' and 'Crew':
-        [
-         {'frame_number': 0, 'ssim_0': 0.98, 'ssim_1': 0.77 },
-         {'frame_number': 1, 'ssim_0': 0.81, 'ssim_1': 0.53 },
-        ]
-    """
-
-    # Build dictionary that describes the data types
-    result_table_description = {'frame_number': ('string', 'Frame number')}
-    for dataset_index in range(self.number_of_datasets):
-      column_name = '%s_%s' % (field_name, dataset_index)
-      column_type = self.table_description[field_name][0]
-      column_description = self.names_list[dataset_index]
-      result_table_description[column_name] = (column_type, column_description)
-
-    # Build data table of all the data
-    result_data_table = []
-    # We're going to have one dictionary per row.
-    # Create that and copy frame_number values from the first data set
-    for source_row in self.data_list[0]:
-      row_dict = {'frame_number': source_row['frame_number']}
-      result_data_table.append(row_dict)
-
-    # Pick target field data points from the all data tables
-    if end_frame == 0:  # Default to all frames
-      end_frame = self.number_of_frames
-
-    for dataset_index in range(self.number_of_datasets):
-      for row_number in range(start_frame, end_frame):
-        column_name = '%s_%s' % (field_name, dataset_index)
-        # Stop if any of the data sets are missing the frame
-        try:
-          result_data_table[row_number][column_name] = \
-          self.data_list[dataset_index][row_number][field_name]
-        except IndexError:
-          self.messages.append("Couldn't find frame data for row %d "
-          "for %s" % (row_number, self.names_list[dataset_index]))
-          break
-    return result_table_description, result_data_table
-
-  def GetOrdering(self, table_description):  # pylint: disable=R0201
-    """ Creates a list of column names, ordered alphabetically except for the
-      frame_number column which always will be the first column.
-
-      Args:
-        table_description: A dictionary of column definitions as defined by the
-          gviz_api.DataTable documentation.
-      Returns:
-        A list of column names, where frame_number is the first and the
-        remaining columns are sorted alphabetically.
-    """
-    # The JSON data representation generated from gviz_api.DataTable.ToJSon()
-    # must have frame_number as its first column in order for the chart to
-    # use it as it's X-axis value series.
-    # gviz_api.DataTable orders the columns by name by default, which will
-    # be incorrect if we have column names that are sorted before frame_number
-    # in our data table.
-    columns_ordering = ['frame_number']
-    # add all other columns:
-    for column in sorted(table_description.keys()):
-      if column != 'frame_number':
-        columns_ordering.append(column)
-    return columns_ordering
-
-  def CreateConfigurationTable(self, configurations):  # pylint: disable=R0201
-    """ Combines multiple test data configurations for display.
-
-    Args:
-      configurations: List of one ore more configurations. Each configuration
-      is required to be a list of dictionaries with two keys: 'name' and
-      'value'.
-      Example of a single configuration:
-      [
-        {'name': 'name', 'value': 'VP8 software'},
-        {'name': 'test_number', 'value': '0'},
-        {'name': 'input_filename', 'value': 'foreman_cif.yuv'},
-      ]
-    Returns:
-      A tuple containing:
-      - a dictionary describing the columns in the configuration table to be
-        displayed. All columns will have string as data type.
-        Example:
-        {
-          'name': 'string',
-          'test_number': 'string',
-          'input_filename': 'string',
-         }
-      - a list containing dictionaries (one per configuration) with the
-        configuration column names mapped to the value for each test run:
-
-        Example matching the columns above:
-        [
-         {'name': 'VP8 software',
-          'test_number': '12',
-          'input_filename': 'foreman_cif.yuv' },
-         {'name': 'VP8 hardware',
-          'test_number': '5',
-          'input_filename': 'foreman_cif.yuv' },
-        ]
-    """
-    result_description = {}
-    result_data = []
-
-    for configuration in configurations:
-      data = {}
-      result_data.append(data)
-      for values in configuration:
-        name = values['name']
-        value = values['value']
-        result_description[name] = 'string'
-        data[name] = value
-    return result_description, result_data