Is it possible in Psychopy to keep old images on the screen and new ones to be rendered late? I used to program PyGame and found that I could do this, but now I can’t find this method with Psychopy programming.Win.flip () refreshes the entire interface, not individual objects or locations. So can we do that with Psychopy?
win.flip(clearBuffer = False)
https://www.psychopy.org/api/visual/window.html#psychopy.visual.Window.flip
but there probably aren’t many uses for this. Setting the .autoDraw attribute of your individual stimuli might better achieve what you want.
Thank you a lot,and I can’t wait to try it,but my computer is not with me now.
first pic code represent old object，and second pic code represent new object，but " the TypeError: ‘attributeSetter’ object is not callable " in the end.
I’m so confused.
Hi,
It should probably be:
tar_stim.autoDraw = True
i.e. no brackets are needed.
PS for future posts, please provide your code as complete text rather than images (especially cropped images) - it makes it much easier to copy and paste suggestions from your post.
There is another question that how to clear the last trial all pics, in other words, I just want to old pics autodraw in an internal trial when codes run in the next trial all pics clear? Thanks for your help and patience.
Sorry, I don’t quite understand what you want to do. Could you break down the description into many more explicit steps?
It’s hard to know without seeing your code. This could be a result of not clearing the auto draw setting of some stimuli, or not clearing the buffer on your last win.flip().
We really need to see a (minimal) example of your code to see what is going on.
for i in range(t):
x = ls_randx[0]
y = ls_randy[0]
X = cell_w * x + x4
Y = cell_w * y + y4
jiaodu = random.choice(jiaodulist)
tar_stim1 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori='0')
tar_stim1.autoDraw = True
# normal
s = random.randint(t + d, 6)
for i in range(t + d, s + 1):
x = ls_randx[i]
y = ls_randy[i]
X = cell_w * x + x1
Y = cell_w * y + y1
jiaodu = random.choice(jiaodulist)
tar_stim2 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori=jiaodu)
tar_stim2.autoDraw = True
# win.flip()
for i in range(s + 1, 8):
x = ls_randx[i]
y = ls_randy[i]
X = cell_w * x + x1
Y = cell_w * y + y1
jiaodu = random.choice(jiaodulist)
tar_stim3 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori=jiaodu)
tar_stim3.autoDraw = True
win.flip()
win.flip()
# salient
for i in range(d):
x = ls_randx[1]
y = ls_randy[1]
X = cell_w * x + x3
Y = cell_w * y + y3
jiaodu = random.choice(jiaodulist)
tar_stim = visual.ImageStim(win, image='红色干扰.png', pos=(X, Y), ori=jiaodu)
tar_stim.draw()
core.wait(0.100)
win.flip()
Rtime.reset()
tar_resp = event.waitKeys(maxsize, ['z', 'slash'])
Rt = Rtime.getTime()
win.setColor(gray)
win.flip()I think the question is that how to clear the buffer.
An extra win.flip() will clear the buffer (at the cost of a frame)
This is an internal loop function and wherever I add win. flip(), it does not work.
I don’t think this code is doing what is intended. Do you see how, despite being embedded in a loop, only one stimulus will be exist at the end of it (tar_stim1), yet it has been instantiated multiple times for no apparent purpose (and this will be slow and time-consuming, when instead, it could have just been created once).
- What is the above code intended to do?
- What does
trepresent?
I guess we need to establish that before going further into the code.
if t==0 and d==1:#no target , one salience dis
# normal dis
s = random.randint(1, 6)
for i in range(1, s + 1):
x = ls_randx[i]
y = ls_randy[i]
X = cell_w * x+x1
Y = cell_w * y+y1
jiaodu = random.choice(jiaodulist)
tar_stim1= visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori=jiaodu)
# tar_stim.draw()
tar_stim1.autoDraw=True
# win.flip()
for i in range(s + 1, 8):
x = ls_randx[i]
y = ls_randy[i]
X = cell_w * x+x2
Y = cell_w * y+y2
jiaodu = random.choice(jiaodulist)
tar_stim2 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori=jiaodu)
# tar_stim2.autoDraw=True
tar_stim2.autoDraw=True
# win.flip()
win.flip()
core.wait(0.100)
# 凸显干扰
for i in range(1):
x = ls_randx[0]
y = ls_randy[0]
X = cell_w * x+x3
Y = cell_w * y+y3
jiaodu = random.choice(jiaodulist)
tar_stim = visual.ImageStim(win, image='红色干扰.png', pos=(X, Y), ori=jiaodu)
tar_stim.draw()
# core.wait(0.100)
win.flip()
else:
for i in range(t):
x = ls_randx[0]
y = ls_randy[0]
X = cell_w * x + x4
Y = cell_w * y + y4
jiaodu = random.choice(jiaodulist)
tar_stim1 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori='0')
tar_stim1.autoDraw = True
# 一般干扰
s = random.randint(t + d, 6)
for i in range(t + d, s + 1):
x = ls_randx[i]
y = ls_randy[i]
X = cell_w * x + x1
Y = cell_w * y + y1
jiaodu = random.choice(jiaodulist)
tar_stim2 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori=jiaodu)
tar_stim2.autoDraw = True
# win.flip()
for i in range(s + 1, 8):
x = ls_randx[i]
y = ls_randy[i]
X = cell_w * x + x1
Y = cell_w * y + y1
jiaodu = random.choice(jiaodulist)
tar_stim3 = visual.ImageStim(win, image='蓝.png', pos=(X, Y), ori=jiaodu)
tar_stim3.autoDraw = True
win.flip()
win.flip()
core.wait(0.100)
# 凸显干扰
for i in range(d):
x = ls_randx[1]
y = ls_randy[1]
X = cell_w * x + x3
Y = cell_w * y + y3
jiaodu = random.choice(jiaodulist)
tar_stim = visual.ImageStim(win, image='红色干扰.png', pos=(X, Y), ori=jiaodu)
tar_stim.draw()
# core.wait(0.100)
win.flip()
t presents target number and d present dis num.