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        "\n==============================================\nReal-time feedback for decoding :: Client Side\n==============================================\n\nThis example demonstrates how to setup a real-time feedback\nmechanism using StimServer and StimClient.\n\nThe idea here is to display future stimuli for the class which\nis predicted less accurately. This allows on-demand adaptation\nof the stimuli depending on the needs of the classifier.\n\nTo run this example, open ipython in two separate terminals.\nIn the first, run rt_feedback_server.py and then wait for the\nmessage\n\n    RtServer: Start\n\nOnce that appears, run rt_feedback_client.py in the other terminal\nand the feedback script should start.\n\nAll brain responses are simulated from a fiff file to make it easy\nto test. However, it should be possible to adapt this script\nfor a real experiment.\n\n\n"
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        "# Author: Mainak Jas <mainak@neuro.hut.fi>\n#\n# License: BSD (3-clause)\n\nfrom mne.realtime import StimClient\nfrom psychopy import visual, core\n\nprint(__doc__)\n\n# Instantiating stimulation client\n\n# Port number must match port number used to instantiate\n# StimServer. Any port number above 1000 should be fine\n# because they do not require root permission.\nstim_client = StimClient('localhost', port=4218)\n\n# create a window\nmywin = visual.Window([800, 600], monitor=\"testMonitor\", units=\"deg\")\n\n# create the stimuli\n\n# right checkerboard stimuli\nright_cb = visual.RadialStim(mywin, tex='sqrXsqr', color=1, size=5,\n                             visibleWedge=[0, 180], radialCycles=4,\n                             angularCycles=8, interpolate=False,\n                             autoLog=False)\n\n# left checkerboard stimuli\nleft_cb = visual.RadialStim(mywin, tex='sqrXsqr', color=1, size=5,\n                            visibleWedge=[180, 360], radialCycles=4,\n                            angularCycles=8, interpolate=False,\n                            autoLog=False)\n\n# fixation dot\nfixation = visual.PatchStim(mywin, color=-1, colorSpace='rgb', tex=None,\n                            mask='circle', size=0.2)\n\n# the most accurate method is using frame refresh periods\n# however, since the actual refresh rate is not known\n# we use the Clock\ntimer1 = core.Clock()\ntimer2 = core.Clock()\n\nev_list = list()  # list of events displayed\n\n# start with right checkerboard stimuli. This is required\n# because the ev_list.append(ev_list[-1]) will not work\n# if ev_list is empty.\ntrig = 4\n\n# iterating over 50 epochs\nfor ii in range(50):\n\n    if trig is not None:\n        ev_list.append(trig)  # use the last trigger received\n    else:\n        ev_list.append(ev_list[-1])  # use the last stimuli\n\n    # draw left or right checkerboard according to ev_list\n    if ev_list[ii] == 3:\n        left_cb.draw()\n    else:\n        right_cb.draw()\n\n    fixation.draw()  # draw fixation\n    mywin.flip()  # show the stimuli\n\n    timer1.reset()  # reset timer\n    timer1.add(0.75)  # display stimuli for 0.75 sec\n\n    # return within 0.2 seconds (< 0.75 seconds) to ensure good timing\n    trig = stim_client.get_trigger(timeout=0.2)\n\n    # wait till 0.75 sec elapses\n    while timer1.getTime() < 0:\n        pass\n\n    fixation.draw()  # draw fixation\n    mywin.flip()  # show fixation dot\n\n    timer2.reset()  # reset timer\n    timer2.add(0.25)  # display stimuli for 0.25 sec\n\n    # display fixation cross for 0.25 seconds\n    while timer2.getTime() < 0:\n        pass\n\nmywin.close()  # close the window\ncore.quit()"
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