Runner Mode Examples

In Runner mode tasks are organized in a folder containing separate files for the device configuration config.py, task task.py, and parallel code (like an UI) launch.py.

Runner mode can be run with kraken.bat (if you have an activateable conda environment named neurokraken) or kraken.py, which will provide you with a list of all tasks found within the tasks folder to choose from. To run this example add a new folder with a name of your choice like runner_mode_example containing the respective files to tasks. Runner mode can be provided with arguments for dynamic execution, like kraken.bat --task runner_mode_example --keyboard to directly execute the runner_mode_example task in keyboard mode.

The following example is the same as minimal.py above, with the addition of

• a list of datapoints to be prompted upon execution, including subject options

• a UI (launch.py) with a control for the task’s shown color

config.py

# Instead of being bundled with the config.py a subjects dictionary could be loaded from a .json file or remote source
subjects = [{'ID': 'Alpha', 'sex': 'female'},
            {'ID': 'Beta',  'sex': 'female'},
            {'ID': 'Gamma', 'sex': 'male'},
            {'ID': 'Delta', 'sex': 'male'}]

# runner mode can prompt for named datapoints upon execution
ask_for = ['ID', 'weight', 'group']

from neurokraken.configurators import Display, devices
display = Display(size=(800, 600))

cameras = [ ]

serial_in = { }
serial_out = {'led': devices.direct_on(pin=3, start_value=False)}

task.py

from neurokraken.controls import get
from neurokraken import State

get.color = (0, 255, 0)

class Color(State):
    """We will just show the color on a display in this state and blink an LED every 5 seconds"""
    def on_start(self):
        # store relevant variables within the state self
        self.t_last_switch = 0
        self.led_status = False

    def loop_main(self):
        if get.time_ms > self.t_last_switch + 5_000:
            self.led_status = not self.led_status
            get.send_out('led', self.led_status)
            self.t_last_switch = get.time_ms
    
    def loop_visual(self, sketch):
        sketch.background(*get.color)

task = Color()

launch.py

# code that would be executed just before neurokraken.run() can be included in an optional launch.py
# This typically covers UIs and parallel analysis/processing loops like cutie

from py5 import Sketch
import krakengui as gui
from neurokraken.controls import get
import random

def recolor_background():
    get.color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))

class UI(Sketch):
    def settings(self):
        self.size(200, 150)

    def setup(self):
        gui.use_sketch(self)

        gui.Button(label='randomize background', pos=(25, 50), on_click=recolor_background)

    def draw(self):
        self.background(0)
        self.fill(255);     self.stroke(255);     self.text_size(15)
        self.text(f't_ms: {int(get.time_ms)}', 25, 25)
        if get.quitting:
            self.exit_sketch()

    def exiting(self):
        # close end the experiment when the UI window is closed
        get.quit()

# run the UI

ui = UI()
ui.run_sketch(block=False)