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