Picture-Word-N1/02 Stimuli/03-generate_example_localiser_img.py

from PIL import ImageEnhance
import pandas as pd
import os.path as op
import matplotlib.pyplot as plt
import matplotlib as mpl
from random import choices, seed, sample

# functions taken from https://github.com/jackedtaylor/randphase
from randphase import draw
from randphase import phase

seed_nr = 999
seed(seed_nr)

experiment_font = 'cour.ttf'
bacs_font = 'BACS2serif.otf'
strings = pd.read_csv('localiser_stim.csv')

font_size = 36

n_examples = 10
min_char = min([len(x) for x in strings.string])
max_char = max([len(x) for x in strings.string])

if (max_char-min_char+1 < n_examples):
    print('Too mamy examples for limits of word length?')

example_strings = []
for len_i in range(min_char, min_char+n_examples):
    rel_strings = strings[strings.Length == len_i]
    string_i = sample(rel_strings.string.tolist(), 1)[0]
    example_strings.append(string_i)

fig_height = round((n_examples*0.7 + 1)/2.5)

fig, axs = plt.subplots(n_examples, 3, figsize=(6.5, fig_height))

largest_img_width = 0

for item_nr_idx in range(n_examples):
    
    word_str = str(example_strings[item_nr_idx])
    word_img = draw.text(word_str, font=experiment_font, size=font_size, crop_x='font', crop_y='font')
    
    bacs_img = draw.text(word_str, font=bacs_font, size=font_size, crop_x='font', crop_y='font')
    
    noise_img = phase.randomise(word_img, noise='permute', contrast_adj=0.5)
    
    axs[item_nr_idx, 0].imshow(word_img)
    axs[item_nr_idx, 1].imshow(bacs_img)
    axs[item_nr_idx, 2].imshow(noise_img)
    
    if word_img.size[0] > largest_img_width:
        largest_img_width = word_img.size[0]

for item_nr in range(n_examples):
    for col_nr in range(3):
        axs[item_nr, col_nr].set_axis_off()
        # centre-align with consistent sizing
        xl = axs[item_nr, col_nr].get_xlim()
        xl_adj = (largest_img_width - xl[1])/2
        axs[item_nr, col_nr].set(xlim=[-xl_adj, xl[1]+xl_adj])

title_font_dict = {'fontsize': 12}
title_padding = 7.5
axs[0,0].set_title('Words', fontdict=title_font_dict, pad=title_padding)
axs[0,1].set_title('False-Font\nStrings', fontdict=title_font_dict, pad=title_padding)
axs[0,2].set_title('Phase-Shuffled\nWords', fontdict=title_font_dict, pad=title_padding)
fig.subplots_adjust(wspace=0.1, hspace=0.1)

mpl.rcParams['savefig.pad_inches'] = 0

fig.savefig(fname=op.join('fig', 'example_localiser_images.png'), dpi=600, bbox_inches='tight')