Expyriment timing check

xpyriment_timing_check.opensesame

# Generated by OpenSesame 0.27~pre31 (Frisky Freud)
# Fri Nov 30 17:42:30 2012 (posix)
# <http://www.cogsci.nl/opensesame>

set foreground "white"
set subject_parity "even"
set font_size "18"
set description "Default description"
set title "Xpyriment timing check"
set font_bold "no"
set sampler_backend "legacy"
set coordinates "relative"
set height "768"
set mouse_backend "xpyriment"
set width "1024"
set compensation "0"
set font_family "mono"
set keyboard_backend "legacy"
set background "black"
set subject_nr "0"
set canvas_backend "xpyriment"
set start "experiment"
set synth_backend "legacy"
set font_italic "no"

define keyboard_response keyboard_response
	set description "Collects keyboard responses"
	set timeout "infinite"
	set flush "yes"

define sequence experiment
	set flush_keyboard "yes"
	set description "Runs a number of items in sequence"
	run timing_check "always"
	run keyboard_response "always"

define inline_script timing_check
	___run__
	from openexp.canvas import canvas
	import numpy as np

	speed = 2 # Rotation speed
	soa = 50 # SOA

	my_canvas1 = canvas(self.experiment)
	my_canvas1.circle(my_canvas1.xcenter()+100, my_canvas1.ycenter(), 50)

	my_canvas2 = canvas(self.experiment)
	my_canvas2.circle(my_canvas2.xcenter()-100, my_canvas2.ycenter(), 50)

	# Rotate the canvas and record timestamps
	l = []
	for i in range(0, 100):
		l.append(my_canvas1.show())
		self.sleep(soa)
		l.append(my_canvas2.show())
		self.sleep(soa)

	# Determine the actual SOA
	_l = []
	for i in range(len(l)-1):
		_l.append(l[i+1]-l[i])

	# Calculate the mean SOA and the standard deviation
	a = np.array(_l)
	m = a.mean()
	std = a.std()

	# Report the results
	my_canvas1.clear()
	my_canvas1.text('M=%.2f, STD=%.2f' % (m, std))
	my_canvas1.show()
	__end__
	set _prepare ""
	set description "Executes Python code"