Difference between revisions of "Using-QtMobility-sensors-and-QML-from-PySide"

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=Using QtMobility sensors and <span class="caps">QML</span> from PySide=
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[[Category:LanguageBindings::PySide]]<br />[[Category:snippets]]<br />[[Category:Developing_with_Qt::Qt Quick]]<br />[[Category:Developing_with_Qt::Qt Quick::QML]]<br />[[Category:Developing_with_Qt::Qt Quick::Tutorial]]<br />[[Category:Developing with Qt::QtMobility]]
  
This [[PySide]] tutorial shows how to use QtMobility <span class="caps">API</span>s to read the accelerometer from Python, scale and smoothen the resulting data and expose it to a <span class="caps">QML</span> application in order to keep an image always upright. In the future, Qt Mobility 1.2 (still not released as of December 2010) will have [http://doc.qt.nokia.com/qt-mobility-snapshot/qml-plugins.html <span class="caps">QML</span> Plugins] ''[doc.qt.nokia.com]'', but right now we have to write some glue code in Python (and one might want to do more with the accelerometer data than just using it in the UI layer, so this will still be relevant when Qt Mobility 1.2 is out).
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= Using QtMobility sensors and QML from PySide =
  
==UnderMeSensi.py==
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This [[PySide]] tutorial shows how to use QtMobility APIs to read the accelerometer from Python, scale and smoothen the resulting data and expose it to a QML application in order to keep an image always upright. In the future, Qt Mobility 1.2 (still not released as of December 2010) will have &quot;QML Plugins&amp;quot;:http://doc.qt.nokia.com/qt-mobility-snapshot/qml-plugins.html, but right now we have to write some glue code in Python (and one might want to do more with the accelerometer data than just using it in the UI layer, so this will still be relevant when Qt Mobility 1.2 is out).
  
===Importing the required modules===
+
== UnderMeSensi.py ==
  
This is basically the same as in the previous tutorials (PySide modules needed, the QtOpenGL module is optional) with the new addition of the QtMobility Sensors <span class="caps">API</span>. On your '''N900''', you have to install the '''python-qtmobility''' metapackage in order to get the right modules.
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=== Importing the required modules ===
  
===The listener / controller===
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This is basically the same as in the previous tutorials (PySide modules needed, the QtOpenGL module is optional) with the new addition of the QtMobility Sensors API. On your '''N900''', you have to install the '''python-qtmobility''' metapackage in order to get the right modules.
  
Next, we need to define a QObject subclass that takes care of receiving events from the accelerometer, scaling and smoothing the value and finally exposing the calculated rotation value as property so that we can access it from within our <span class="caps">QML</span> UI:
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<code><br />import sys
  
===Putting it all together===
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from PySide import QtCore, QtGui, QtDeclarative, QtOpenGL<br />from QtMobility import Sensors<br /></code>
  
We create a new QAccelerometer from the Sensors module, which abstracts away the underlying system accelerometer and sends us easy-to-use events. We then create an instance of our listener class, and connect the '''readingChanged''' signal of the accelerometer (which gets called every time the reading changes, obviously) to the listener’s '''on_reading_changed''' slot. We also have to tell the accelerometer to start reading the sensor and send out events.
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=== The listener / controller ===
  
We then only need to set up our QDeclarativeView as usual, and expose our listener object to the <span class="caps">QML</span> context, so that we can access it from the UI:
+
Next, we need to define a QObject subclass that takes care of receiving events from the accelerometer, scaling and smoothing the value and finally exposing the calculated rotation value as property so that we can access it from within our QML UI:
  
==UnderMeSensi.qml==
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<code><br />class Listener(QtCore.QObject):<br /> def ''init''(self):<br /> QtCore.QObject.''init''(self)<br /> self._initial = True<br /> self._rotation = 0.
  
This one is really trivial: Have an enclosing rectangle (which fills the whole screen) and then an image centered into it that shows the PySide logo, gets scaled a bit (so that it fits the screen nicely) and finally has its '''rotation''' property set to the rotation property of '''listener''' (this is the key part here – it will update the image’s rotation everytime the listener’s rotation property changes).
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def get_rotation(self):<br /> return self._rotation
  
==How the example app looks like==
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def set_rotation(self, rotation):<br /> if self._initial:<br /> self._rotation = rotation<br /> self._initial = False<br /> else:<br /> # Smooth the accelermeter input changes<br /> self._rotation *= .8<br /> self.''rotation += .2*rotation
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<br /> self.on_rotation.emit()
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<br /> on_rotation = QtCore.Signal()<br /> rotation = QtCore.Property(float, get_rotation, set_rotation,  notify=on_rotation)
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<br /> &amp;#64;QtCore.Slot()<br /> def on_reading_changed(self):<br /> accel = self.sender()<br /> # Scale the x axis reading to keep the image roughly steady<br /> self.rotation = accel.reading().x()*7<br /></code>
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<br />h3. Putting it all together
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<br />We create a new QAccelerometer from the Sensors module, which abstracts away the underlying system accelerometer and sends us easy-to-use events. We then create an instance of our listener class, and connect the '''readingChanged''' signal of the accelerometer (which gets called every time the reading changes, obviously) to the listener's '''on_reading_changed''' slot. We also have to tell the accelerometer to start reading the sensor and send out events.
 +
<br />We then only need to set up our QDeclarativeView as usual, and expose our listener object to the QML context, so that we can access it from the UI:
 +
<br /><code><br />app = QtGui.QApplication(sys.argv)
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<br />accel = Sensors.QAccelerometer()<br />listener = Listener()<br />accel.readingChanged.connect(listener.on_reading_changed)<br />accel.start()
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<br />view = QtDeclarative.QDeclarativeView()<br />glw = QtOpenGL.QGLWidget()<br />view.setViewport(glw)<br />view.setResizeMode(QtDeclarative.QDeclarativeView.SizeRootObjectToView)<br />view.rootContext().setContextProperty('listener', listener)<br />view.setSource(file.replace('.py', '.qml'))<br />view.showFullScreen()
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<br />app.exec''()<br /></code>
  
Copy the files '''UnderMeSensi.py''' and '''UnderMeSensi.qml''' to your N900 and download the file [http://www.pyside.org/wp-content/themes/openbossa/images/logo.png logo.png] ''[pyside.org]'' as '''images/pysidelogo.png''' (or use a custom image of your choosing and set the '''source:''' path/URL in the <span class="caps">QML</span> file correctly. On an N900, it looks like this:
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== UnderMeSensi.qml ==
  
[[Image:5231046791_e21f00d175.jpg|Example app running on a N900]]
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This one is really trivial: Have an enclosing rectangle (which fills the whole screen) and then an image centered into it that shows the PySide logo, gets scaled a bit (so that it fits the screen nicely) and finally has its '''rotation''' property set to the rotation property of '''listener''' (this is the key part here - it will update the image's rotation everytime the listener's rotation property changes).
  
The example app in action: [http://youtu.be/DpVpSZSOcGM Video of the example on YouTube] ''[youtu.be]''
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<code><br />import Qt 4.7
  
===Categories:===
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Rectangle {<br /> width: 800<br /> height: 480
  
* [[:Category:Developing-with-Qt|Developing with Qt]]
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Image {<br /> source: &quot;images/pysidelogo.png&amp;quot;<br /> fillMode: Image.PreserveAspectFit<br /> width: parent.width/2<br /> height: parent.height/2<br /> anchors.centerIn: parent<br /> rotation: listener.rotation<br /> }<br />}<br /></code>
** [[:Category:Developing-with-Qt::QtMobility|QtMobility]]
 
* [[:Category:Developing with Qt|Developing_with_Qt]]
 
** [[:Category:Developing with Qt::Qt-Quick|Qt Quick]]
 
* [[:Category:Developing with Qt::Qt-Quick::QML|QML]]
 
  
* [[:Category:Developing with Qt::Qt-Quick::Tutorial|Tutorial]]
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== How the example app looks like ==
  
* [[:Category:LanguageBindings|LanguageBindings]]
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Copy the files '''UnderMeSensi.py''' and '''UnderMeSensi.qml''' to your N900 and download the file &quot;logo.png&amp;quot;:http://www.pyside.org/wp-content/themes/openbossa/images/logo.png as '''images/pysidelogo.png''' (or use a custom image of your choosing and set the '''source:''' path/URL in the QML file correctly. On an N900, it looks like this:
** [[:Category:LanguageBindings::PySide|PySide]]
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* [[:Category:snippets|snippets]]
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[[Image:http://farm6.static.flickr.com/5090/5231046791_e21f00d175.jpg|Example app running on a N900]]
 +
 
 +
The example app in action: &quot;Video of the example on YouTube&amp;quot;:http://youtu.be/DpVpSZSOcGM

Revision as of 09:56, 24 February 2015






Using QtMobility sensors and QML from PySide

This PySide tutorial shows how to use QtMobility APIs to read the accelerometer from Python, scale and smoothen the resulting data and expose it to a QML application in order to keep an image always upright. In the future, Qt Mobility 1.2 (still not released as of December 2010) will have "QML Plugins&quot;:http://doc.qt.nokia.com/qt-mobility-snapshot/qml-plugins.html, but right now we have to write some glue code in Python (and one might want to do more with the accelerometer data than just using it in the UI layer, so this will still be relevant when Qt Mobility 1.2 is out).

UnderMeSensi.py

Importing the required modules

This is basically the same as in the previous tutorials (PySide modules needed, the QtOpenGL module is optional) with the new addition of the QtMobility Sensors API. On your N900, you have to install the python-qtmobility metapackage in order to get the right modules.

<br />import sys

from PySide import QtCore, QtGui, QtDeclarative, QtOpenGL<br />from QtMobility import Sensors<br />

The listener / controller

Next, we need to define a QObject subclass that takes care of receiving events from the accelerometer, scaling and smoothing the value and finally exposing the calculated rotation value as property so that we can access it from within our QML UI:

<br />class Listener(QtCore.QObject):<br /> def ''init''(self):<br /> QtCore.QObject.''init''(self)<br /> self._initial = True<br /> self._rotation = 0.

def get_rotation(self):<br /> return self._rotation

def set_rotation(self, rotation):<br /> if self._initial:<br /> self._rotation = rotation<br /> self._initial = False<br /> else:<br /> # Smooth the accelermeter input changes<br /> self._rotation *= .8<br /> self.''rotation += .2*rotation
<br /> self.on_rotation.emit()
<br /> on_rotation = QtCore.Signal()<br /> rotation = QtCore.Property(float, get_rotation, set_rotation,  notify=on_rotation)
<br /> &amp;#64;QtCore.Slot()<br /> def on_reading_changed(self):<br /> accel = self.sender()<br /> # Scale the x axis reading to keep the image roughly steady<br /> self.rotation = accel.reading().x()*7<br />


h3. Putting it all together
We create a new QAccelerometer from the Sensors module, which abstracts away the underlying system accelerometer and sends us easy-to-use events. We then create an instance of our listener class, and connect the readingChanged signal of the accelerometer (which gets called every time the reading changes, obviously) to the listener's on_reading_changed slot. We also have to tell the accelerometer to start reading the sensor and send out events.
We then only need to set up our QDeclarativeView as usual, and expose our listener object to the QML context, so that we can access it from the UI:


<br />app = QtGui.QApplication(sys.argv)
<br />accel = Sensors.QAccelerometer()<br />listener = Listener()<br />accel.readingChanged.connect(listener.on_reading_changed)<br />accel.start()
<br />view = QtDeclarative.QDeclarativeView()<br />glw = QtOpenGL.QGLWidget()<br />view.setViewport(glw)<br />view.setResizeMode(QtDeclarative.QDeclarativeView.SizeRootObjectToView)<br />view.rootContext().setContextProperty('listener', listener)<br />view.setSource(file.replace('.py', '.qml'))<br />view.showFullScreen()
<br />app.exec''()<br />

UnderMeSensi.qml

This one is really trivial: Have an enclosing rectangle (which fills the whole screen) and then an image centered into it that shows the PySide logo, gets scaled a bit (so that it fits the screen nicely) and finally has its rotation property set to the rotation property of listener (this is the key part here - it will update the image's rotation everytime the listener's rotation property changes).

<br />import Qt 4.7

Rectangle {<br /> width: 800<br /> height: 480

Image {<br /> source: &quot;images/pysidelogo.png&amp;quot;<br /> fillMode: Image.PreserveAspectFit<br /> width: parent.width/2<br /> height: parent.height/2<br /> anchors.centerIn: parent<br /> rotation: listener.rotation<br /> }<br />}<br />

How the example app looks like

Copy the files UnderMeSensi.py and UnderMeSensi.qml to your N900 and download the file "logo.png&quot;:logo.png as images/pysidelogo.png (or use a custom image of your choosing and set the source: path/URL in the QML file correctly. On an N900, it looks like this:

Example app running on a N900

The example app in action: "Video of the example on YouTube&quot;:http://youtu.be/DpVpSZSOcGM