# -*- coding: utf-8 -*-
"""
This example demonstrates the use of RemoteGraphicsView to improve performance in
applications with heavy load. It works by starting a second process to handle 
all graphics rendering, thus freeing up the main process to do its work.

In this example, the update() function is very expensive and is called frequently.
After update() generates a new set of data, it can either plot directly to a local
plot (bottom) or remotely via a RemoteGraphicsView (top), allowing speed comparison
between the two cases. IF you have a multi-core CPU, it should be obvious that the 
remote case is much faster.
"""

import initExample ## Add path to library (just for examples; you do not need this)
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
import pyqtgraph.widgets.RemoteGraphicsView
import numpy as np

app = pg.mkQApp()

view = pg.widgets.RemoteGraphicsView.RemoteGraphicsView()
pg.setConfigOptions(antialias=True)  ## this will be expensive for the local plot
view.pg.setConfigOptions(antialias=True)  ## prettier plots at no cost to the main process! 
view.setWindowTitle('pyqtgraph example: RemoteSpeedTest')

label = QtGui.QLabel()
rcheck = QtGui.QCheckBox('plot remote')
rcheck.setChecked(True)
lcheck = QtGui.QCheckBox('plot local')
lplt = pg.PlotWidget()
layout = pg.LayoutWidget()
layout.addWidget(rcheck)
layout.addWidget(lcheck)
layout.addWidget(label)
layout.addWidget(view, row=1, col=0, colspan=3)
layout.addWidget(lplt, row=2, col=0, colspan=3)
layout.resize(800,800)
layout.show()

## Create a PlotItem in the remote process that will be displayed locally
rplt = view.pg.PlotItem()
rplt._setProxyOptions(deferGetattr=True)  ## speeds up access to rplt.plot
view.setCentralItem(rplt)

lastUpdate = pg.ptime.time()
avgFps = 0.0

def update():
    global check, label, plt, lastUpdate, avgFps, rpltfunc
    data = np.random.normal(size=(10000,50)).sum(axis=1)
    data += 5 * np.sin(np.linspace(0, 10, data.shape[0]))
    
    if rcheck.isChecked():
        rplt.plot(data, clear=True, _callSync='off')  ## We do not expect a return value.
                                                      ## By turning off callSync, we tell
                                                      ## the proxy that it does not need to 
                                                      ## wait for a reply from the remote
                                                      ## process.
    if lcheck.isChecked():
        lplt.plot(data, clear=True)
        
    now = pg.ptime.time()
    fps = 1.0 / (now - lastUpdate)
    lastUpdate = now
    avgFps = avgFps * 0.8 + fps * 0.2
    label.setText("Generating %0.2f fps" % avgFps)
        
timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(0)



## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
    import sys
    if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
        QtGui.QApplication.instance().exec_()

# -*- coding: utf-8 -*-
"""
This example demonstrates the use of RemoteGraphicsView to improve performance in
applications with heavy load. It works by starting a second process to handle 
all graphics rendering, thus freeing up the main process to do its work.

In this example, the update() function is very expensive and is called frequently.
After update() generates a new set of data, it can either plot directly to a local
plot (bottom) or remotely via a RemoteGraphicsView (top), allowing speed comparison
between the two cases. IF you have a multi-core CPU, it should be obvious that the 
remote case is much faster.
"""

import initExample ## Add path to library (just for examples; you do not need this)
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
import pyqtgraph.widgets.RemoteGraphicsView
import numpy as np

app = pg.mkQApp()

view = pg.widgets.RemoteGraphicsView.RemoteGraphicsView()
pg.setConfigOptions(antialias=True)  ## this will be expensive for the local plot
view.pg.setConfigOptions(antialias=True)  ## prettier plots at no cost to the main process! 
view.setWindowTitle('pyqtgraph example: RemoteSpeedTest')

label = QtGui.QLabel()
rcheck = QtGui.QCheckBox('plot remote')
rcheck.setChecked(True)
lcheck = QtGui.QCheckBox('plot local')
lplt = pg.PlotWidget()
layout = pg.LayoutWidget()
layout.addWidget(rcheck)
layout.addWidget(lcheck)
layout.addWidget(label)
layout.addWidget(view, row=1, col=0, colspan=3)
layout.addWidget(lplt, row=2, col=0, colspan=3)
layout.resize(800,800)
layout.show()

## Create a PlotItem in the remote process that will be displayed locally
rplt = view.pg.PlotItem()
rplt._setProxyOptions(deferGetattr=True)  ## speeds up access to rplt.plot
view.setCentralItem(rplt)

lastUpdate = pg.ptime.time()
avgFps = 0.0

def update():
    global check, label, plt, lastUpdate, avgFps, rpltfunc
    data = np.random.normal(size=(10000,50)).sum(axis=1)
    data += 5 * np.sin(np.linspace(0, 10, data.shape[0]))
    
    if rcheck.isChecked():
        rplt.plot(data, clear=True, _callSync='off')  ## We do not expect a return value.
                                                      ## By turning off callSync, we tell
                                                      ## the proxy that it does not need to 
                                                      ## wait for a reply from the remote
                                                      ## process.
    if lcheck.isChecked():
        lplt.plot(data, clear=True)
        
    now = pg.ptime.time()
    fps = 1.0 / (now - lastUpdate)
    lastUpdate = now
    avgFps = avgFps * 0.8 + fps * 0.2
    label.setText("Generating %0.2f fps" % avgFps)
        
timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(0)



## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
    import sys
    if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
        QtGui.QApplication.instance().exec_()

# -*- coding: utf-8 -*- This example demonstrates the use of RemoteGraphicsView to improve performance in
 applications with heavy load. It works by starting a second process to handle 
 all graphics rendering, thus freeing up the main process to do its work.
 
 In this example, the update() function is very expensive and is called frequently.
 After update() generates a new set of data, it can either plot directly to a local
 plot (bottom) or remotely via a RemoteGraphicsView (top), allowing speed comparison
 between the two cases. IF you have a multi-core CPU, it should be obvious that the 
 remote case is much faster. ## Add path to library (just for examples; you do not need this) ## this will be expensive for the local plot ## prettier plots at no cost to the main process! ## Create a PlotItem in the remote process that will be displayed locally ## speeds up access to rplt.plot ## We do not expect a return value. ## By turning off callSync, we tell ## the proxy that it does not need to ## wait for a reply from the remote ## process. ## Start Qt event loop unless running in interactive mode or using pyside.