Retrospective attention gates discrete conscious access to past sensory stimuli

readme.md

Authors

1. Louis Thibault (corresponding author)
2. Ronald van den Berg
3. Patrick Cavanagh
4. Claire Sergent

Laboratoire Psychologie de la Perception, UMR 8242

Manuscript

• Read on PlosOne: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148504
• DOI: https://doi.org/10.1371/journal.pone.0148504

Description of Data

subnum	congruent	cuepos	normalizedResp	response	rt	soa	targetorientation	targetpos
int	bool	int	float	float	float	float	float	int
subject number	1 if cuepos == targetpos	1 if cue left, 2 if cue right, -1 if no cue	response error (degrees)	absolute response (degrees)	response time (s)	SOA (s)	Orientation of target Gabor (degrees)	1 if target left, 2 if target right

format_data_for_distribution.py

#!/usr/bin/env python3

"""
Convert experimental data from .mat files under raw/ into a single CSV.
"""

import csv
import os.path as osp
from glob import glob
from itertools import chain

from scipy.io import loadmat

HDR = [
    'subnum',
    'congruent',
    'cuepos',
    'normalizedResp',
    'response',
    'rt',
    'soa',
    'targetorientation',
    'targetpos'
]


def get_subnum_from_path(path):
    return int(osp.split(path)[0][-2:])


def load_matfile(path):
    """Load a .mat file into a dictionary, squeezing numpy arrays and storing
    structs as arrays rather than record types.
    """
    d = loadmat(path, struct_as_record=False, squeeze_me=True)
    return {k: v for k, v in d.items() if not k.startswith('__')}


def to_tabular(md, subnum):
    """Covert matdict to tuple generator representing tabular data

    md : dict
        matdict output from `load_matfile`

    subnum : int
        Subject number

    return : generator
        Produces tuples, representing rows
    """
    for row in zip(*(md[k] for k in sorted(md))):
        yield (subnum,) + row


def to_csv(path, it):
    """Convert output of `to_tabular` to a tab-delimited file
    Iterators passed via *it are appended in order to a single file.

    path : str
        Path to output file

    it : iterable of tuples
        Tuples produced represent rows
    """
    with open(path, 'wt') as f:
        writer = csv.writer(f, delimiter='\t')
        writer.writerow(HDR)
        for r in chain(*it):
            writer.writerow(r)


def main(src, dst):
    """Aggregate all .mat files matching the glob expression `S??_?_main.mat`,
    existing in a directory matching the glob expression `S??` and compile into
    a tab-delimited output file, `dst`.
    """
    paths = sorted(glob(osp.join(src, 'S??/data.mat')))
    mds = map(load_matfile, paths)
    rowiters = map(to_tabular, mds, map(get_subnum_from_path, paths))
    to_csv(dst, rowiters)

if __name__ == '__main__':
    from sys import argv
    _, src, dst, *_ = argv
    main(src, dst)

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