The key point is to separate data acquisition from data visualization.
If you design your application
for human consumption, then I guess you will have hard time finding a
person who will be able to
distinguish plots updating 100 fps from those updating say 50 fps. Even
if you will manage to find
one, then you will need to find out what he would do with such fast
changing data.
My advise is - collect data as fast as you need/can and think about how
you would transform it
for visualization so that pure humans could analyze and act upon them :)
Regards,
Mikhail
On 3/9/17 23:46, Paul Gross wrote:
Thanks for the responses, sorry I am so late in responding.
I definitely want to thread out all of the data queue operations and
the calculations, but that doesn't really tackle the the problems I am
having with having to paint all of the data points every iteration.
Ideally I would simply be able to append new points to the graph as
quickly as possible.
What would the recommend method of doing this, in real time, be?
Bottom line I need to display a lot of data points (O(100/second) )
without the frame rating dropping drastically as the graph nears its end.
Thanks,
Paul
On Tuesday, February 28, 2017 at 1:17:38 PM UTC-6, Paul Gross wrote:
Hi, I am working on displaying real-time telemetry data using
pyqtgraph. I am quite pleased with the visual results however I am
having issues with the frame rate dropping as more data is
plotted. I am receiving about 100 data points per second. At the
beginning plotting is quite fast but the frame right dives rapidly
as more data is being displayed.
I have fixed the size of the plots and auto-ranging is disabled, I
have tried down sampling and it helps, but not quite enough. I am
looking for the fastest way to plot a large amount of data points
in real-time, as I receive them.
I have found other posts about speed and some of them reference
‘arrayToQPath’, but I am not sure if that is the best way to
approach my issue. My biggest concern is with plotting the data
points as quickly as possible as to not slow down the rest of the
event loop. The current way that I am plotting data in
the‘PlotWidget’ is setting the data of a ‘PlotDataItem’ in the
following manner, where the arguments are either a numpy array or
python list:
‘plot_data_item.curve.setData(data['time'][self.x_min:],
data[data_type][self.x_min:])’. I have tried plotting a new curve
each time, but that seemed to be quite slow. In an ideal world I
would just be able to append points without having to connect all
of the previous points to each other. At some point I want to
reset the plot to an empty plot, but that really isn’t an issue
because this is a rare occurrence in my program. I simply want to
display in real time several minutes of data with multiple
different plots, each of fixed size with no scrolling, panning, or
auto-resizing.
I would not be opposed to threading some of the work out if that
is an option on top of any suggestions you have. Something I am
not entirely clear on is if the GIL is an issue when it comes to
QThreads since they are C++? Will I get any performance boost by
using QThreads in the update function? I am reading from a data
queue in the update function, so ideally that would be taken out
of the loop. That however isn’t my main concern because if I
reset the plots (change the range of data that is taken from my
data list/array the frame right jumps right back up).
I am using the Dev Branch because my application requires PYQt5
and python 3.5.
Any suggestions you have would be greatly appreciated!
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