Picture-Word-N1/04 Analysis/raw_data/stim-pc/stim.py

# this file contains functions used in both the localiser task and main task

import os
from itertools import groupby
import csv
import codecs
import numpy as np
from random import randint
from psychopy import visual
import PIL

# function to make noise images green
def greenify_noise(im):
    im_arr = np.array(im, dtype=np.uint8)
    im_arr[:, :, [0, 2]] = 127
    targ = im_arr[:, :, 1] < 127
    im_arr[:, :, 0][targ] = im_arr[:, :, 1][targ]
    im_arr[:, :, 2][targ] = im_arr[:, :, 1][targ]
    im_gr = PIL.Image.fromarray(np.uint8(im_arr))
    return(im_gr)

# function to append a trial's data (in dictionary format) to csv
def write_csv(fileName, thisTrial):

    full_path = os.path.abspath(fileName)
    directory = os.path.dirname(full_path)

    if not os.path.exists(directory):
        os.makedirs(directory)

    if not os.path.isfile(full_path):
        with codecs.open(full_path, 'ab+', encoding='utf8') as f:
            csv.writer(f, delimiter=',').writerow(thisTrial.keys())
            csv.writer(f, delimiter=',').writerow(thisTrial.values())
    else:
        with codecs.open(full_path, 'ab+', encoding='utf8') as f:
            csv.writer(f, delimiter=',').writerow(thisTrial.values())

# function to get the lengths of consecutive runs (useful for limiting number of consecutive trial types)
def get_consec_lens(x):
    return [ len(list(v)) for k, v in groupby(list(x)) ]

# functions for precise frame-wise timing
def ms_2_flips(ms = 100, Hz = 60, round_func = np.round):
    return int(round_func(ms / (1/Hz*1000)))

def display_n_flips(win, stim, n_flips = 10, port = None, trigg = None):
    for frame_n in range(n_flips):
        stim.draw()
        if frame_n == 0:
            if trigg is not None:
                win.callOnFlip(port.setData, data=trigg)
        win.flip()

def display_x_ms(win, stim, ms = 100, Hz = 60, round_func = np.round, port = None, trigg = None):
    display_n_flips(win, stim, ms_2_flips(ms, Hz, round_func), port, trigg)

def display_jitter_ms(win, stim, min_ms = 100, max_ms = 500, Hz = 60, round_func = np.round, port = None, trigg = None):
    flips_min = ms_2_flips(min_ms, Hz, round_func)
    flips_max = ms_2_flips(max_ms, Hz, round_func)
    n_flips = randint(flips_min, flips_max)
    display_n_flips(win, stim, n_flips, port, trigg)
    return(n_flips, n_flips*(1/Hz*1000))

def display_list_n_flips(win, stim_list, n_flips = 10, port = None, trigg = None):
    for frame_n in range(n_flips):
        for stim_i in stim_list:
            stim_i.draw()
        if frame_n == 0:
            if trigg is not None:
                win.callOnFlip(port.setData, data=trigg)
        win.flip()

def display_list_ms(win, stim_list, ms = 100, Hz = 60, round_func = np.round, port = None, trigg = None):
    display_list_n_flips(win, stim_list, ms_2_flips(ms, Hz, round_func), port, trigg)

def display_list_jitter_ms(win, stim_list, min_ms = 100, max_ms = 500, Hz = 60, round_func = np.round, port = None, trigg = None):
    flips_min = ms_2_flips(min_ms, Hz, round_func)
    flips_max = ms_2_flips(max_ms, Hz, round_func)
    n_flips = randint(flips_min, flips_max)
    display_list_n_flips(win, stim_list, n_flips, port, trigg)
    return(n_flips, n_flips*(1/Hz*1000))

# function that returns a list containing the objects in the Thaler et al. fixation point
# can then draw the list contents in a loop
def thaler_list_fix(win, units='deg', circlesColor=[1,1,1], circlesColorSpace='rgb', outerCircleDiameter=0.6, innerCircleDiameter=0.2, pos = (0, 0)):

    crossColor=win.color.tolist()
    crossColorSpace=win.colorSpace
    
    outerCircle = visual.Circle(win, units=units, pos=pos, radius=outerCircleDiameter/2, lineColor=circlesColor, fillColor=circlesColor, fillColorSpace=circlesColorSpace, lineColorSpace=circlesColorSpace)
    crossVertical = visual.Rect(win, units=units, pos=pos, height=outerCircleDiameter*1.1, width=innerCircleDiameter/2, lineColor=None, fillColor=crossColor, fillColorSpace=crossColorSpace, lineColorSpace=crossColorSpace)
    crossHorizontal = visual.Rect(win, units=units, pos=pos, height=innerCircleDiameter/2, width=outerCircleDiameter*1.1, lineColor=None, fillColor=crossColor, fillColorSpace=crossColorSpace, lineColorSpace=crossColorSpace)
    innerCircle = visual.Circle(win, units=units, pos=pos, radius=innerCircleDiameter/2, lineColor=circlesColor, fillColor=circlesColor, fillColorSpace=circlesColorSpace, lineColorSpace=circlesColorSpace)

    return [outerCircle, crossVertical, crossHorizontal, innerCircle]