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/****************************************************************************
**
** Copyright (C) 2010 Nokia Corporation and/or its subsidiary(-ies).
** All rights reserved.
** Contact: Nokia Corporation (qt-info@nokia.com)
**
** This file is part of the test suite of the Qt Toolkit.
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** contained in the Technology Preview License Agreement accompanying
** this package.
**
** GNU Lesser General Public License Usage
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** General Public License version 2.1 as published by the Free Software
** Foundation and appearing in the file LICENSE.LGPL included in the
** packaging of this file. Please review the following information to
** ensure the GNU Lesser General Public License version 2.1 requirements
** will be met: http://www.gnu.org/licenses/old-licenses/lgpl-2.1.html.
**
** In addition, as a special exception, Nokia gives you certain additional
** rights. These rights are described in the Nokia Qt LGPL Exception
** version 1.1, included in the file LGPL_EXCEPTION.txt in this package.
**
** If you have questions regarding the use of this file, please contact
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** $QT_END_LICENSE$
**
****************************************************************************/
/*!
\page optimizing-performance.html
\target optimizing-performance
\title Optimizing Performance in QML
The Qt Declarative module includes several tools to help measure performance.
\section1 Performance Logging
The declarative module uses the functionality provided by QPerformanceLog to log performance information. To see this information you can add the following to src.pro:
\code
DEFINES += Q_ENABLE_PERFORMANCE_LOG
\endcode
The performance information will be printed to screen on a QML application startup, or when running the viewer can be forced at anytime by pressing 'F3' on the keyboard.
Additional logging can be enabled by adding the relevant categories to qfxperf.h and qfxperf.cpp.
For example, to measure the cost of calculating the size of a text item, you would first define a TextSize category by adding the following:
\code
//in qfxperf.h
Q_DECLARE_PERFORMANCE_METRIC(TextSize);
//in qfxperf.cpp
Q_DEFINE_PERFORMANCE_METRIC(TextSize, "Text Size Calculation");
\endcode
You could then use this category in the code:
\code
void QmlGraphicsText::updateSize()
{
QmlPerfTimer<QmlPerf::TextSize> perf;
...
}
\endcode
Because there is no cost for a QmlPerfTimer when Q_ENABLE_PERFORMANCE_LOG is not defined, this line can persist in the code and be used to help detect performance bottlenecks and regressions. See the QPerformanceLog documentation for more information on this performance framework.
\section1 FPS Measurements
When running the viewer, pressing 'F2' on the keyboard while a QML program is running will cause information on cost-per-frame and frames-per-second (FPS) to be printed to the console.
The information printed includes:
\list
\o \e repaint(): the total time spent painting.
\o \e paint(): the time spent by Qt painting.
\o \e timeBetweenFrames: the total time spent per frame. This number minus repaint() gives a good idea of how much time is spent on things besides painting. A high number here with a low number for repaint() indicates expensive calculations happening each frame.
\endlist
\section1 Improving Performance
The following tips can help decrease startup time for QML-based appications.
\section2 Images
\list
\o Use jpg instead of png for photo-like images. On the N810, this can save 150ms for a large (320x480) image.
\o If you are configuring Qt, configure out any image plugins you don't plan to support (mng and svg are the most expensive). On the N810, this can save 75-100ms startup time. For example:
\code
configure -no-libmng -no-svg -no-libtiff
\endcode
\o In some cases running pngcrush, optipng, gifsicle or other similar tools can give some improvement.
We are also investigating support for the loading of uncompressed images. This will provide opportunites to decrease startup time at the cost of increased storage space.
\endlist
\section2 Fonts
\list
\o Use qpf instead of ttf. When using multiple font sizes and weights on the N810, this can save 125ms startup time compared to a ttf 'clean' run, and 40-50ms on subsequent runs (ttfs are shared by open applications).
\endlist
*/
*/
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