Live Data Monitor: PyQtGraph

Question

I am working on a project where I will have to analyse signals coming from a device. I have a library working which gets me data from the device. As of now, I am collecting the data and then plotting it. I am interested in building a live data monitor which can plot a graph in real time. Upon searching, I figured out PyQtGraph is ideal for the task. I am not familiar with Qt, so I am looking for examples which I can modify to my needs. Some examples given in PyQtGraph docs update the plot real-time BUT I need something like a live monitor- where the graph is moving towards the right as it keeps receiving data.

If it it something like a known continuous function, I can update the input x - w*t with t being the time so as to get the wave moving towards right. But this is discrete data, so I am not sure about how to get it working using PyQtGraph. So it would be great if someone could give some pointers on how to go about.

As of now this is what I have

Code

app = QtGui.QApplication([])
#mw = QtGui.QMainWindow()
#mw.resize(800,800)

win = pg.GraphicsWindow(title="Basic plotting examples")
win.resize(1000,600)
win.setWindowTitle('pyqtgraph example: Plotting')

# Enable antialiasing for prettier plots
pg.setConfigOptions(antialias=True)

p6 = win.addPlot(title="Updating plot")
curve = p6.plot(pen='r')
X_axis = numpy.linspace(0,100,12800)
#'data' is my required y_axis containing 12800 values
ydata = np.array_split(data,50)
xdata = np.array_split(X_axis,50)
ptr = 0
def update():
    global curve, data, ptr, p6
    curve.setData(xdata[ptr%50],ydata[ptr%50])
    ptr += 1
timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(1000)

This is updating the data for every 2-second interval, but I want it to move towards the right.

Solution

To make a plot scroll, you have three options:

1. Scroll the raw data and re-plot (see numpy.roll)

   curve = plotItem.plot(data)
   data = np.roll(data, 1)  # scroll data
   curve.setData(data)      # re-plot
   

2. Move the plot curve so that it slides across the view:

   curve = plotItem.plot(data)
   curve.setPos(x, 0)  # Move the curve
   

3. Move the view region such that the plot curve appears to scroll

   curve = plotItem.plot(data)
   plotItem.setXRange(x1, x2)  # Move the view
   

The scrolling-plots example (currently only in the development version) demonstrates each of these:

Comments

[user1955184]

Thanks! In the example you suggested update1 works fine, but there is an error before update2, "plotItem has no attribute setLimits" . Can you please look into that?

[Luke]

setLimits is only available in the development version.

[user1955184]

The moving plot seems to work fine,but the Y axis seems to auto adjust the range erratically. So it looks like the graph is sliding up and down as well. I tried to use setYRange but the problem is that, the graph becomes too small and concise,it doesn't look good and small variations cannot be seen clearly. Is there a way where I can get best of both the worlds?

[user1955184]

Let's say I have minimum value of 1850 and maximum value of 2500. My seYRange is from 1800 to 2500. Most of my data is in 2300-2400 data range, but sometimes it goes to 2200s and once it goes to 1850. So my graph's Y-axis is split into 7 regions (from 1800-2500). And the graph mostly resides only in the 2300-2400 region -which makes it look very small. The Y-interval is 100 units. Is it possible to make it a bit more small - like 25 units? That is instead of 2000-2100-2200,I want 2000-2025-2050...

[Luke]

Ah, I see--you don't want the data larger, you just want the ticks to be more dense. In that case, have a look inside graphicsItems/AxisItem.py, in the __init__() method, you will see self.style['textFillLimits'], which is a set of heuristics used to determine the optimal tick spacing. You can modify those values on any AxisItem..

[SriramK89]

Hey @Luke.. I am also trying to do the same thing as given in the question. But I am unable to get it working in my machine after installing 'pyqt4'. Please help me for installation of this one.