def main(input_file, output_dir="", iptc_profile=None, do_fullsize=True, do_minis=True, template_name="", mini_width="", style=""): #tweak do_template and do_export here to controll what output you get
localpath = path.dirname(path.realpath(__file__)) + '/'
config = get_config_file(localpath)
#IMPORT VARIABLES
if not output_dir:
output_dir = localpath+config.get('Directories', 'output_dir')
else:
output_dir = path.expanduser(output_dir)
batch_profile_dir = config.get('Directories', 'batch_profile_dir')
template_dir = config.get('Directories', 'template_dir')
RT_profiles_dir = config.get('Directories', 'RT_profiles_dir')
minis_dir = config.get('Directories', 'minis_dir')
mini_name = config.get('Directories', 'mini_name')
rt_command = config.get('Parameters', 'rt_command')
stock_iptc_profile = config.get('Parameters', 'iptc_profile')
pictures_link_path = config.get('Directories', 'pictures_link_path')
if template_name and 'octopress' in template_name:
style = config.get('Parameters', 'style')
if not mini_width:
mini_width = config.getint('Parameters', 'mini_width')
#END IMPORT VARIABLES
if style == 'NONE':
style = ""
if not iptc_profile:
iptc_profile = batch_profile_dir + stock_iptc_profile
iptc_profile = path.abspath(path.expanduser(iptc_profile))
input_file = path.abspath(path.expanduser(input_file))
batch_profile_dir = localpath + batch_profile_dir
profile_list = []
for lepath, subdirs, files in walk(RT_profiles_dir):
for name in files:
profile_list += [path.join(lepath, name)]
if bool(template_name):
template_file = localpath + template_dir + template_name + '.txt'
the_template = Template(open(template_file, 'r').read())
output_template_file = output_dir + path.splitext(path.basename(input_file))[0] + '-temp'
outfile = save_gen(output_template_file, extension='.txt')
if do_minis:
mini_profile_file = batch_profile_dir + mini_name
mini_temp_profile_location = batch_profile_dir + 'tmp_' + mini_name
mini_temp_profile_file = save_gen(mini_temp_profile_location)
mini_profile = Template(open(mini_profile_file, 'r').read())
mini_temp_profile_file.write(mini_profile.substitute(WIDTH=mini_width))
mini_temp_profile_file.close()
for profile in profile_list:
source = input_file
out_name = path.splitext(path.basename(input_file))[0]+'-'+path.basename(profile)+'.jpg'
out_name_minis = path.splitext(path.basename(input_file))[0]+'-'+path.basename(profile)+'.jpg'
if do_fullsize:
fullsize_destination = output_dir + out_name.replace(" ", "_")
subprocess.call([rt_command, '-o', fullsize_destination, '-p', iptc_profile, '-p', profile, '-j[100]', '-Y', '-c', source])
if do_minis:
minis_folder = output_dir + minis_dir
if not path.isdir(minis_folder):
makedirs(minis_folder)
minis_destination = output_dir + minis_dir + out_name_minis.replace(" ", "_")
subprocess.call([rt_command, '-o', minis_destination, '-p', iptc_profile, '-p', profile, '-p', mini_temp_profile_location, '-j[100]', '-Y', '-c', source])
if bool(template_name):
full_size_link = pictures_link_path+out_name.replace(" ", "_")
mini_path = '/images/photos/minis/'+out_name_minis.replace(" ", "_")
outfile.write(the_template.substitute(STYLE=style, PATH=mini_path, WIDTH = mini_width, HEIGHT=0, CAPTION=path.splitext(profile)[0], LINK=full_size_link))
if do_minis:
remove(mini_temp_profile_location)
def main(
input_file,
output_dir="",
iptc_profile=None,
do_fullsize=True,
do_minis=True,
template_name="",
mini_width="",
style=""
): #tweak do_template and do_export here to controll what output you get
localpath = path.dirname(path.realpath(__file__)) + '/'
config = get_config_file(localpath)
#IMPORT VARIABLES
if not output_dir:
output_dir = localpath + config.get('Directories', 'output_dir')
else:
output_dir = path.expanduser(output_dir)
batch_profile_dir = config.get('Directories', 'batch_profile_dir')
template_dir = config.get('Directories', 'template_dir')
RT_profiles_dir = config.get('Directories', 'RT_profiles_dir')
minis_dir = config.get('Directories', 'minis_dir')
mini_name = config.get('Directories', 'mini_name')
rt_command = config.get('Parameters', 'rt_command')
stock_iptc_profile = config.get('Parameters', 'iptc_profile')
pictures_link_path = config.get('Directories', 'pictures_link_path')
if template_name and 'octopress' in template_name:
style = config.get('Parameters', 'style')
if not mini_width:
mini_width = config.getint('Parameters', 'mini_width')
#END IMPORT VARIABLES
if style == 'NONE':
style = ""
if not iptc_profile:
iptc_profile = batch_profile_dir + stock_iptc_profile
iptc_profile = path.abspath(path.expanduser(iptc_profile))
input_file = path.abspath(path.expanduser(input_file))
batch_profile_dir = localpath + batch_profile_dir
profile_list = []
for lepath, subdirs, files in walk(RT_profiles_dir):
for name in files:
profile_list += [path.join(lepath, name)]
if bool(template_name):
template_file = localpath + template_dir + template_name + '.txt'
the_template = Template(open(template_file, 'r').read())
output_template_file = output_dir + path.splitext(
path.basename(input_file))[0] + '-temp'
outfile = save_gen(output_template_file, extension='.txt')
if do_minis:
mini_profile_file = batch_profile_dir + mini_name
mini_temp_profile_location = batch_profile_dir + 'tmp_' + mini_name
mini_temp_profile_file = save_gen(mini_temp_profile_location)
mini_profile = Template(open(mini_profile_file, 'r').read())
mini_temp_profile_file.write(mini_profile.substitute(WIDTH=mini_width))
mini_temp_profile_file.close()
for profile in profile_list:
source = input_file
out_name = path.splitext(path.basename(
input_file))[0] + '-' + path.basename(profile) + '.jpg'
out_name_minis = path.splitext(path.basename(
input_file))[0] + '-' + path.basename(profile) + '.jpg'
if do_fullsize:
fullsize_destination = output_dir + out_name.replace(" ", "_")
subprocess.call([
rt_command, '-o', fullsize_destination, '-p', iptc_profile,
'-p', profile, '-j[100]', '-Y', '-c', source
])
if do_minis:
minis_folder = output_dir + minis_dir
if not path.isdir(minis_folder):
makedirs(minis_folder)
minis_destination = output_dir + minis_dir + out_name_minis.replace(
" ", "_")
subprocess.call([
rt_command, '-o', minis_destination, '-p', iptc_profile, '-p',
profile, '-p', mini_temp_profile_location, '-j[100]', '-Y',
'-c', source
])
if bool(template_name):
full_size_link = pictures_link_path + out_name.replace(" ", "_")
mini_path = '/images/photos/minis/' + out_name_minis.replace(
" ", "_")
outfile.write(
the_template.substitute(STYLE=style,
PATH=mini_path,
WIDTH=mini_width,
HEIGHT=0,
CAPTION=path.splitext(profile)[0],
LINK=full_size_link))
if do_minis:
remove(mini_temp_profile_location)
def main(output_format=False, scrambling_steps_id=False):
import numpy as np
import pandas as pd
from numpy.random import permutation, choice, sample
from os import path, listdir
from itertools import product
from chr_helpers import get_config_file, save_pd_csv, save_gen, save_pd_tsv
from routines import hariri
from string import Template
localpath = path.dirname(path.realpath(__file__)) + '/'
config = get_config_file(localpath)
#IMPORT VARIABLES
sequence_name = config.get('Files', 'sequence_name')
output_subdir = config.get('Directories', 'output_subdir')
stimuli_dir = config.get('Directories', 'stimuli_dir')
templates_dir = config.get('Directories', 'templates_dir')
scrambling_id = config.get('Decoding', 'scrambling_id')
scrambling_a_id = config.get('Decoding', 'scrambling_a_id')
scrambling_b_id = config.get('Decoding', 'scrambling_b_id')
fearful_id = config.get('Decoding', 'fearful_id')
happy_id = config.get('Decoding', 'happy_id')
female_id = config.get('Decoding', 'female_id')
male_id = config.get('Decoding', 'male_id')
easy_em_id = config.get('Decoding', 'easy_em_id')
hard_em_id = config.get('Decoding', 'hard_em_id')
if scrambling_steps_id:
pass
else: scrambling_steps_id = [int(i) for i in config.get('Decoding', 'scrambling_steps_id').split(',')]
scrambling_steps_prefix = config.get('Decoding', 'scrambling_steps_prefix')
make_blocks = config.getboolean('Parameters', 'make_blocks')
block_size = config.getint('Parameters', 'block_size')
if output_format:
pass
else: output_format = [str(i) for i in config.get('Parameters', 'output_format').split(',')]
keep_oldsequence = config.getboolean('Parameters', 'keep_oldsequence')
#END IMPORT VARIABLES
scrambling_steps_id_withprefix = [scrambling_steps_prefix+str(i) for i in scrambling_steps_id]
local_dir = path.dirname(path.realpath(__file__)) + '/'
output_dir = local_dir + output_subdir
#check for already existing sequence file
if keep_oldsequence and path.isfile(output_dir + '.' + sequence_name + '-last_exported_sequence.csv'):
sequence = pd.DataFrame.from_csv(output_dir + '.' + sequence_name + '-last_exported_sequence.csv')
print('Keeping old sequence found at '+output_dir + '.' + sequence_name + '-last_exported_sequence.csv . Please unset "keep_oldsequence" in '+path.dirname(path.realpath(__file__))+'/gen.cfg to avoid this.')
else:
### START CREATING THE NEW STIMLIST DATAFRAME
scrambling_steps_id_withprefix = [scrambling_steps_prefix+str(i) for i in scrambling_steps_id]
stimuli_dir = path.expanduser(stimuli_dir) # expands the path if it is specified with tilde for "home"
stimlist = permutation(listdir(stimuli_dir))
sequence = pd.DataFrame([]) # blank dataframe to add the stimuli lists to
if make_blocks:
sequence_name = sequence_name + '_' + str(block_size) + 'block'
# 100% emotion trials
for variable_categories in product([male_id, female_id], [[happy_id, fearful_id],[fearful_id,happy_id]]):
top_stimuli = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][0] in a and easy_em_id in a and scrambling_id not in a]
distractors = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][1] in a and easy_em_id in a and scrambling_id not in a]
subsequence = hariri(top_stimuli, top_stimuli, distractors, suffix_characters=11) # with suffix identifier skipping because we don't want the same person twice in a slide
sequence = pd.concat([sequence, subsequence], ignore_index=True)
# 40% emotion trials
for variable_categories in product([male_id, female_id], [[happy_id, fearful_id],[fearful_id,happy_id]]):
top_stimuli = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][0] in a and easy_em_id in a and scrambling_id not in a]
distractors = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][1] in a and hard_em_id in a and scrambling_id not in a]
targets = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][0] in a and hard_em_id in a and scrambling_id not in a]
subsequence = hariri(top_stimuli, targets, distractors, suffix_characters=11) # with suffix identifier skipping because we don't want the same person twice in a slide
sequence = pd.concat([sequence, subsequence], ignore_index=True)
# scrambling trials
for variable_categories in product(scrambling_steps_id_withprefix, [[scrambling_a_id, scrambling_b_id]]):
top_stimuli = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][0] in a and easy_em_id in a]
distractors = [a for a in stimlist if variable_categories[0] in a and variable_categories[1][0] in a and easy_em_id in a]
for idx, i in enumerate(distractors):
distractors[idx] = distractors[idx][:-5]+'b.jpg'
targets = top_stimuli # we use identical images for identification
subsequence = hariri(top_stimuli, targets, distractors, forbid_identical_targets=False)
sequence = pd.concat([sequence, subsequence], ignore_index=True)
# Fill out meta-fileds
sequence.ix[(sequence['top face'].map(lambda x: happy_id in x)), 'emotion'] = 'happiness'
sequence.ix[(sequence['top face'].map(lambda x: fearful_id in x)), 'emotion'] = 'fear'
sequence.ix[(sequence['right face'].map(lambda x: easy_em_id in x)), 'emotion intensity'] = 100 # the top face is always C100
sequence.ix[(sequence['right face'].map(lambda x: hard_em_id in x)), 'emotion intensity'] = 40 # the top face is always C100
sequence.ix[(sequence['top face'].map(lambda x: male_id in x)), 'gender'] = 'm'
sequence.ix[(sequence['top face'].map(lambda x: female_id in x)), 'gender'] = 'f'
for scrambling_step in scrambling_steps_id_withprefix:
sequence.ix[(sequence['top face'].map(lambda x: scrambling_step in x)), 'scrambling'] = int(scrambling_step.strip('cell'))
sequence.ix[(sequence['top face'].map(lambda x: scrambling_id not in x)), 'scrambling'] = 0
#make blocks
if make_blocks:
block_number = 0 #start value for iteration
for step in range(0, len(sequence)*block_size, block_size):
sequence.ix[step:step+block_size,'block'] = block_number
block_number +=1
#save raw stimulus list
output_file = output_dir + '.' + sequence_name + '-last_exported_sequence'
save_pd_csv(sequence, output_file)
# BEGIN OUTPUT FILE FORMATTING
if 'christian' in output_format: # 'christian' format (dataframe, versatile, amongst others for faceRT)
output_file = output_dir + sequence_name
save_pd_csv(sequence, output_file)
if 'gabriela1' in output_format: # 'gabriela1' format (for "Presentation")
tamplate_subdir = 'gabriela1/'
header = open(local_dir+templates_dir+tamplate_subdir+'header.txt', 'r').read()
footer = open(local_dir+templates_dir+tamplate_subdir+'footer.txt', 'r').read()
module = Template(open(local_dir+templates_dir+tamplate_subdir+'module.txt', 'r').read())
#~ print module.substitute(name='a', t='a', l='a', r='a', N='a')
for condition_file_id in ['cont_hard', 'cont_easy', 'em_hard', 'em_easy']:
#START REMAP SOME VALUES
sequence.ix[(sequence['correct answer'] == 'right'), 'correct answer'] = 1
sequence.ix[(sequence['correct answer'] == 'left'), 'correct answer'] = 2
#END REMAP SOME VALUES
output_file = output_dir + sequence_name + '_gabriela1_' + condition_file_id
with save_gen(output_file, extension='.txt') as outfile:
outfile.write(header)
if condition_file_id == 'cont_hard':
for idx, trial in sequence[(sequence['scrambling'] == scrambling_steps_id[0])].iterrows():
format_module(outfile, module, trial, idx)
elif condition_file_id == 'cont_easy':
for idx, trial in sequence[(sequence['scrambling'] == scrambling_steps_id[1])].iterrows():
format_module(outfile, module, trial, idx)
elif condition_file_id == 'em_hard':
for idx, trial in sequence[(sequence['scrambling'] == 0) & (sequence['emotion intensity'] == 40)].iterrows():
format_module(outfile, module, trial, idx)
elif condition_file_id == 'em_easy':
for idx, trial in sequence[(sequence['scrambling'] == 0) & (sequence['emotion intensity'] == 100)].iterrows():
format_module(outfile, module, trial, idx)
else: raise InputError('Your condition_file_id values do not correspond to the script\'s expectations.')
outfile.write(footer)
if 'gabriela2' in output_format:
sequence['name'] = sequence['top face']
for pos, le_name in enumerate(sequence['name']):
sequence['name'].ix[pos] = path.splitext(le_name)[0] + ' ;'
sequence.ix[(sequence['correct answer'] == 'right'), 'correct answer'] = 1
sequence.ix[(sequence['correct answer'] == 'left'), 'correct answer'] = 2
sequence = sequence.rename(columns={'top face': 'fname_up', 'left face': 'fname_down_left', 'right face': 'fname_down_right', 'correct answer': 'rating'})
output_file = output_dir + sequence_name + '_gabriela2'
save_pd_tsv(sequence, output_file)
