Refresh stability issue on windows with different graphic cards (ATI, NVIDIA, INTEL)

Hello,

Matthew (@mdc) and me have been exploring the issue I raised in a previous post. The problem can be summarized by the output of Matthew’s test code below:

> target_H = visual.TextStim(win=win, ori=0,
>     text=u'H',
>     font=police,
>     pos=[0, 0],
>     color=[0,0,0], colorSpace=u'rgb255', height = 0.5)
>     
> framesMax = 200
> times = np.zeros((framesMax,))
> n = 0
> timer = core.Clock()
> win.flip()
> while n < framesMax:
>     timer.reset()
>     target_H.draw()
>     win.flip()
> 
>     times[n] = timer.getTime()
> 
>     n += 1
> 
> #Shutting down:
> win.close()
> 
> pylab.figure(0)
> pylab.plot(np.arange(0, framesMax), times)
> pylab.show()
> 
> core.quit()

Using an NVIDIA GTX on windows, Matthew got the (normal) output below:
perf_plot

I ran the same code on 3 different computers running on windows (psychopy v 1 85 4). The first one has an AMD RADEON R9 200 GPU; the second an INTEL HD 4600 GPU; the third an NVIDIA GeFORCE 920M.
Output from INTEL GPU (60 Hz monitor):
Figure_0
Putput from RADEON (144 Hz monitor):
Figure_0

Same issue with the nvidia card. I wouldn’t be worried if the issue only appeared for the first or first 2 frames of an experiment. However, the timing error seems to appear every time a new object is drawn (would that mean the rt clock is off by a few milliseconds for each trial?). Could you please try to replicate, and shed light on the issue?

1 Like

Just to add to this, we are seeing the same thing with a monitor (ViewSonic XG 2530) running on an AMD Radeon R5 240.