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# -*- coding: UTF-8 -*-
#
# Authors: Dirk Gütlin <dirk.guetlin@stud.sbg.ac.at>
#
#
# License: BSD (3-clause)
import os.path as op
from collections import namedtuple
import re
import numpy as np
from ..base import BaseRaw
from ..meas_info import create_info
from ..utils import _read_segments_file, _mult_cal_one, warn
from ..constants import FIFF
from ...utils import check_fname, check_version, logger, verbose
from ...annotations import Annotations
FILE_EXTENSIONS = {"Curry 7": {"info": ".dap",
"data": ".dat",
"labels": ".rs3",
"events": ".cef"},
"Curry 8": {"info": ".cdt.dpa",
"data": ".cdt",
"labels": ".cdt.dpa",
"events": ".cdt.cef"}}
CHANTYPES = {"meg": "_MAG1", "eeg": "", "misc": "_OTHERS"}
FIFFV_CHANTYPES = {"meg": FIFF.FIFFV_MEG_CH, "eeg": FIFF.FIFFV_EEG_CH,
"misc": FIFF.FIFFV_MISC_CH}
SI_UNITS = dict(V=FIFF.FIFF_UNIT_V, T=FIFF.FIFF_UNIT_T)
SI_UNIT_SCALE = dict(c=1e-2, m=1e-3, u=1e-6, μ=1e-6, n=1e-9, p=1e-12, f=1e-15)
CurryFileStructure = namedtuple('CurryFileStructure',
'info, data, labels, events')
CurryParameters = namedtuple('CurryParameters',
'n_samples, sfreq, is_ascii, unit_dict')
def _get_curry_version(file_extension):
"""Check out the curry file version."""
return "Curry 8" if "cdt" in file_extension else "Curry 7"
def _get_curry_file_structure(fname, required=[]):
"""Store paths to a CurryFileStructure and check for required files."""
_msg = "The following required files cannot be found: {0}.\nPlease make " \
"sure all required files are located in the same directory as {1}."
# we don't use os.path.splitext to also handle extensions like .cdt.dpa
fname_base, ext = fname.split(".", maxsplit=1)
version = _get_curry_version(ext)
info = fname_base + FILE_EXTENSIONS[version]["info"]
data = fname_base + FILE_EXTENSIONS[version]["data"]
labels = fname_base + FILE_EXTENSIONS[version]["labels"]
events = fname_base + FILE_EXTENSIONS[version]["events"]
my_curry = CurryFileStructure(
info=info if op.isfile(info) else None,
data=data if op.isfile(data) else None,
labels=labels if op.isfile(labels) else None,
events=events if op.isfile(events) else None)
missing = [fname_base + FILE_EXTENSIONS[version][field]
for field in required if getattr(my_curry, field) is None]
if missing:
raise FileNotFoundError(_msg.format(np.unique(missing), fname))
return my_curry
def _read_curry_lines(fname, regex_list):
"""Read through the lines of a curry parameter files and save data.
Parameters
----------
fname : str
Path to a curry file.
regex_list : list of str
A list of strings or regular expressions to search within the file.
Each element `regex` in `regex_list` must be formulated so that
`regex + " START_LIST"` initiates the start and `regex + " END_LIST"`
initiates the end of the elements that should be saved.
Returns
-------
data_dict : dict
A dictionary containing the extracted data. For each element `regex`
in `regex_list` a dictionary key `data_dict[regex]` is created, which
contains a list of the according data.
"""
save_lines = {}
data_dict = {}
for regex in regex_list:
save_lines[regex] = False
data_dict[regex] = []
with open(fname) as fid:
for line in fid:
for regex in regex_list:
if re.match(regex + " END_LIST", line):
save_lines[regex] = False
if save_lines[regex] and line != "\n":
result = line.replace("\n", "")
if "\t" in result:
result = result.split("\t")
data_dict[regex].append(result)
if re.match(regex + " START_LIST", line):
save_lines[regex] = True
return data_dict
def _read_curry_parameters(fname):
"""Extract Curry params from a Curry info file."""
_msg_match = "The sampling frequency and the time steps extracted from " \
"the parameter file do not match."
_msg_invalid = "sfreq must be greater than 0. Got sfreq = {0}"
var_names = ['NumSamples', 'SampleFreqHz',
'DataFormat', 'SampleTimeUsec',
'NUM_SAMPLES', 'SAMPLE_FREQ_HZ',
'DATA_FORMAT', 'SAMPLE_TIME_USEC']
param_dict = dict()
unit_dict = dict()
with open(fname) as fid:
for line in iter(fid):
if any(var_name in line for var_name in var_names):
key, val = line.replace(" ", "").replace("\n", "").split("=")
param_dict[key.lower().replace("_", "")] = val
for type in CHANTYPES:
if "DEVICE_PARAMETERS" + CHANTYPES[type] + " START" in line:
data_unit = next(fid)
unit_dict[type] = data_unit.replace(" ", "") \
.replace("\n", "").split("=")[-1]
n_samples = int(param_dict["numsamples"])
sfreq = float(param_dict["samplefreqhz"])
time_step = float(param_dict["sampletimeusec"]) * 1e-6
is_ascii = param_dict["dataformat"] == "ASCII"
if time_step == 0:
true_sfreq = sfreq
elif sfreq == 0:
true_sfreq = 1 / time_step
elif not np.isclose(sfreq, 1 / time_step):
raise ValueError(_msg_match)
else: # they're equal and != 0
true_sfreq = sfreq
if true_sfreq <= 0:
raise ValueError(_msg_invalid.format(true_sfreq))
return CurryParameters(n_samples, true_sfreq, is_ascii, unit_dict)
def _read_curry_info(info_fname, label_fname):
"""Extract info from curry parameter files."""
curry_params = _read_curry_parameters(info_fname)
# read labels from label files
labels = _read_curry_lines(label_fname,
["LABELS" + CHANTYPES[key] for key in
["meg", "eeg", "misc"]])
sensors = _read_curry_lines(label_fname,
["SENSORS" + CHANTYPES[key] for key in
["meg", "eeg", "misc"]])
all_chans = list()
for key in ["meg", "eeg", "misc"]:
for ind, chan in enumerate(labels["LABELS" + CHANTYPES[key]]):
ch = {"ch_name": chan,
"unit": curry_params.unit_dict[key],
"kind": FIFFV_CHANTYPES[key]}
if key in ("meg", "eeg"):
loc = sensors["SENSORS" + CHANTYPES[key]][ind]
ch["loc"] = np.array(loc, dtype=float)
all_chans.append(ch)
ch_names = [chan["ch_name"] for chan in all_chans]
info = create_info(ch_names, curry_params.sfreq)
for ind, ch_dict in enumerate(info["chs"]):
ch_dict["kind"] = all_chans[ind]["kind"]
ch_dict['unit'] = SI_UNITS[all_chans[ind]['unit'][1]]
ch_dict['cal'] = SI_UNIT_SCALE[all_chans[ind]['unit'][0]]
if ch_dict["kind"] in (FIFF.FIFFV_MEG_CH,
FIFF.FIFFV_EEG_CH):
ch_dict["loc"] = all_chans[ind]["loc"]
return info, curry_params.n_samples, curry_params.is_ascii
def _read_events_curry(fname):
"""Read events from Curry event files.
Parameters
----------
fname : str
Path to a curry event file with extensions .cef, .ceo,
.cdt.cef, or .cdt.ceo
Returns
-------
events : ndarray, shape (n_events, 3)
The array of events.
"""
check_fname(fname, 'curry event', ('.cef', '.cdt.cef'),
endings_err=('.cef', '.cdt.cef'))
events_dict = _read_curry_lines(fname, ["NUMBER_LIST"])
# The first 3 column seem to contain the event information
curry_events = np.array(events_dict["NUMBER_LIST"], dtype=int)[:, 0:3]
return curry_events
def _read_annotations_curry(fname, sfreq='auto'):
r"""Read events from Curry event files.
Parameters
----------
fname : str
The filename.
sfreq : float | 'auto'
The sampling frequency in the file. If set to 'auto' then the
``sfreq`` is taken from the respective info file of the same name with
according file extension (\*.dap for Curry 7; \*.cdt.dpa for Curry8).
So data.cef looks in data.dap and data.cdt.cef looks in data.cdt.dpa.
Returns
-------
annot : instance of Annotations | None
The annotations.
"""
required = ["events", "info"] if sfreq == 'auto' else ["events"]
curry_paths = _get_curry_file_structure(fname, required)
events = _read_events_curry(curry_paths.events)
if sfreq == 'auto':
sfreq = _read_curry_parameters(curry_paths.info).sfreq
onset = events[:, 0] / sfreq
duration = np.zeros(events.shape[0])
description = events[:, 2]
return Annotations(onset, duration, description)
@verbose
def read_raw_curry(fname, preload=False, verbose=None):
"""Read raw data from Curry files.
Parameters
----------
fname : str
Path to a curry file with extensions .dat, .dap, .rs3, .cdt, cdt.dpa,
.cdt.cef or .cef.
%(preload)s
%(verbose)s
Returns
-------
raw : instance of RawCurry
A Raw object containing Curry data.
"""
return RawCurry(fname, preload, verbose)
class RawCurry(BaseRaw):
"""Raw object from Curry file.
Parameters
----------
fname : str
Path to a curry file with extensions .dat, .dap, .rs3, .cdt, cdt.dpa,
.cdt.cef or .cef.
%(preload)s
%(verbose)s
See Also
--------
mne.io.Raw : Documentation of attribute and methods.
"""
@verbose
def __init__(self, fname, preload=False, verbose=None):
curry_paths = _get_curry_file_structure(fname, required=["info",
"data",
"labels"])
data_fname = op.abspath(curry_paths.data)
info, n_samples, is_ascii = _read_curry_info(curry_paths.info,
curry_paths.labels)
last_samps = [n_samples - 1]
self._is_ascii = is_ascii
super(RawCurry, self).__init__(
info, preload, filenames=[data_fname], last_samps=last_samps,
orig_format='int', verbose=verbose)
if curry_paths.events is not None:
logger.info('Event file found. Extracting Annotations from'
' %s...' % curry_paths.events)
annots = _read_annotations_curry(curry_paths.events,
sfreq=self.info["sfreq"])
self.set_annotations(annots)
else:
logger.info('Event file not found. No Annotations set.')
def _read_segment_file(self, data, idx, fi, start, stop, cals, mult):
"""Read a chunk of raw data."""
if self._is_ascii:
ch_idx = range(0, len(self.ch_names))
if check_version("numpy", "1.16.0"):
block = np.loadtxt(self.filenames[0],
skiprows=start,
usecols=ch_idx[idx],
max_rows=stop - start).T
else:
warn("Data reading might take longer for ASCII files. Update "
"numpy to version 1.16.0 or greater for more efficient "
"data reading.")
block = np.loadtxt(self.filenames[0],
skiprows=start,
usecols=ch_idx[idx]).T
block = block[:, :stop - start]
data_view = data[:, :block.shape[1]]
_mult_cal_one(data_view, block, idx, cals, mult)
else:
_read_segments_file(self, data, idx, fi, start, stop, cals,
mult, dtype="<f4")
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