I have large time-traces that must be inspected visually, so I need a fast scrolling tool.
How can I achieve the fastest Maplotlib/Pyside scrolling?
Right know, I added a PySide scroll-bar to a MPL figure and update the x-range of the plot with set_xlim()
method. This is not fast enough especially because in the final application I have at least 8 time-traces in different subplots that must all scroll together. A figure of the plot is attached.
Is there room for improvement?
Here I attach the demo code that demonstrate the relatively low scrolling. It's long but it's almost all boiler-plate code. The interesting bit (that needs improvement) is in xpos_changed()
method where the plot xlimits are changed.
EDIT: Below I incorporated some micro-optimizations suggested by tcaswell
, but the update speed is not improved.
from PySide import QtGui, QtCore
import pylab as plt
import numpy as np
N_SAMPLES = 1e6
def test_plot():
time = np.arange(N_SAMPLES)*1e-3
sample = np.random.randn(N_SAMPLES)
plt.plot(time, sample, label="Gaussian noise")
plt.title("1000s Timetrace \n (use the slider to scroll and the spin-box to set the width)")
plt.xlabel('Time (s)')
plt.legend(fancybox=True)
q = ScrollingToolQT(plt.gcf(), scroll_step=10)
return q # WARNING: it's important to return this object otherwise
# python will delete the reference and the GUI will not respond!
class ScrollingToolQT(object):
def __init__(self, fig, scroll_step=10):
# Setup data range variables for scrolling
self.fig = fig
self.scroll_step = scroll_step
self.xmin, self.xmax = fig.axes[0].get_xlim()
self.width = 1 # axis units
self.pos = 0 # axis units
self.scale = 1e3 # conversion betweeen scrolling units and axis units
# Save some MPL shortcuts
self.ax = self.fig.axes[0]
self.draw = self.fig.canvas.draw
#self.draw_idle = self.fig.canvas.draw_idle
# Retrive the QMainWindow used by current figure and add a toolbar
# to host the new widgets
QMainWin = fig.canvas.parent()
toolbar = QtGui.QToolBar(QMainWin)
QMainWin.addToolBar(QtCore.Qt.BottomToolBarArea, toolbar)
# Create the slider and spinbox for x-axis scrolling in toolbar
self.set_slider(toolbar)
self.set_spinbox(toolbar)
# Set the initial xlimits coherently with values in slider and spinbox
self.ax.set_xlim(self.pos,self.pos+self.width)
self.draw()
def set_slider(self, parent):
self.slider = QtGui.QSlider(QtCore.Qt.Horizontal, parent=parent)
self.slider.setTickPosition(QtGui.QSlider.TicksAbove)
self.slider.setTickInterval((self.xmax-self.xmin)/10.*self.scale)
self.slider.setMinimum(self.xmin*self.scale)
self.slider.setMaximum((self.xmax-self.width)*self.scale)
self.slider.setSingleStep(self.width*self.scale/4.)
self.slider.setPageStep(self.scroll_step*self.width*self.scale)
self.slider.setValue(self.pos*self.scale) # set the initial position
self.slider.valueChanged.connect(self.xpos_changed)
parent.addWidget(self.slider)
def set_spinbox(self, parent):
self.spinb = QtGui.QDoubleSpinBox(parent=parent)
self.spinb.setDecimals(3)
self.spinb.setRange(0.001,3600.)
self.spinb.setSuffix(" s")
self.spinb.setValue(self.width) # set the initial width
self.spinb.valueChanged.connect(self.xwidth_changed)
parent.addWidget(self.spinb)
def xpos_changed(self, pos):
#pprint("Position (in scroll units) %f\n" %pos)
pos /= self.scale
self.ax.set_xlim(pos, pos+self.width)
self.draw()
def xwidth_changed(self, width):
#pprint("Width (axis units) %f\n" % step)
if width <= 0: return
self.width = width
self.slider.setSingleStep(self.width*self.scale/5.)
self.slider.setPageStep(self.scroll_step*self.width*self.scale)
old_xlim = self.ax.get_xlim()
self.xpos_changed(old_xlim[0]*self.scale)
if __name__ == "__main__":
q = test_plot()
plt.show()
This seems a bit faster/more responsive:
As requested in the comments, here is a pyqtgraph demo which scrolls two large traces together (via mouse).
The documentation isn't complete for the pyqtgraph project but there are some good examples you can view with
python -m pyqtgraph.examples
which should point you in the right direction. The crosshair.py example might be particularly interesting for you.If you go with pyqtgraph, connect your slider widget to the setXRange method in the last line of this demo.