1ec0207376e3dcece97812f8ae40bc8d7ec9b208,stimulus_presentation/generate_spatial_gratings.py,,,#,25

Before Change

// next make an outlet
outlet = StreamOutlet(info)

trials = pd.read_csv("/home/hubert/Downloads/electrode-benchmark 2/stimulus.csv",
                     index_col=0)

start = time()

n_trials = len(trials)
record_duration = np.float32(options.duration)


// graphics
mywin = visual.Window([1920, 1080], monitor="testMonitor", units="deg",
                      fullscr=True)
grating = visual.GratingStim(win=mywin, mask="circle", size=40, sf=4)
fixation = visual.GratingStim(win=mywin, size=0.2, pos=[0, 0], sf=0,
                              rgb=[1, 0, 0])

rs = np.random.RandomState(42)

core.wait(2)

for ii, trial in trials.iterrows():

    // onset
    fre = trials["Frequency"].iloc[ii]
    contrast = trials["Contrast"].iloc[ii]
    ori = trials["Orientation"].iloc[ii]
    grating.sf = 4 * fre + 0.1
    grating.ori = ori
    grating.contrast = contrast
    grating.draw()
    fixation.draw()

    // Send marker
    outlet.push_sample([fre + 1, contrast, ori], local_clock())
    mywin.flip()

    // offset
    core.wait(trials["Duration"].iloc[ii])
    fixation.draw()
    outlet.push_sample([fre + 3, contrast, ori], local_clock())
    mywin.flip()

After Change

record_duration = np.float32(options.duration)

// Setup trial list
frequency = np.random.binomial(1, 0.5, n_trials)
contrast = np.ones(n_trials, dtype=int)
orientation = np.random.randint(0, 4, n_trials) * 45

trials = pd.DataFrame(dict(frequency=frequency,
                           contrast=contrast,
                           orientation=orientation))

// graphics
mywin = visual.Window([1920, 1080], monitor="testMonitor", units="deg",

Instances