PsychoPy data

# -*- coding: utf-8 -*-
"""
Created on Sun Dec 20 21:33:01 2015

@author: erik  marsja se
Full script for the tutorial on http://www.marsja.se/trialhandler-a-psychopy-tutorial/
"""

from psychopy import data, visual, core, event

visual_targets = [digit for digit in xrange(1,9)]

targets_responses = []
for target in visual_targets:

   if target %2 == 0:
        correct_response = 'x'

   else:
        correct_response = 'z'

   targets_responses.append({'Target':target, 'CorrectResponse':correct_response})


trials = data.TrialHandler(targets_responses,20, method='random')

trials.data.addDataType('Response')
trials.data.addDataType('Accuracy')

experiment_window = visual.Window(size=(800,600),winType='pyglet',fullscr=False,
                        screen=0, monitor='testMonitor',
                        color="black", colorSpace='rgb')


screen_text = visual.TextStim(experiment_window,text=None,
                              alignHoriz="center", color = 'white')

trial_timer = core.Clock()

for trial in trials:
    current_time = 0
    trial_still_running = True
    trial_timer.reset()
    while trial_still_running:
        current_time = trial_timer.getTime()

        if current_time <=.4:
            screen_text.setText('+')
            screen_text.draw()

        if current_time >= .4 and current_time <=.8:
            screen_text.setText(trial['Target'])
            screen_text.draw()

        if current_time >= .8 and current_time <=1.8:
            screen_text.setText('+')
            screen_text.draw()

            responded = event.getKeys()
            if responded:
                print responded

                if trial['CorrectResponse'] == responded[0]:
                    accuracy = 1
                else: accuracy = 0

        if current_time >= 1.8:
            if not responded:
                accuracy = 0

            trial_still_running = False
        experiment_window.flip()

    trials.data.add('Accuracy', accuracy)
    trials.data.add('Response', responded[0])

trials.saveAsExcel(fileName='data.csv',
                  sheetName = 'rawData',
                  stimOut=[],
                  dataOut=['all_raw'])

experiment_window.close()
core.quit()