/usr/lib/python2.7/dist-packages/neo/io/micromedio.py is in python-neo 0.3.3-2.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 | # -*- coding: utf-8 -*-
"""
Class for reading/writing data from micromed (.trc).
Inspired by the Matlab code for EEGLAB from Rami K. Niazy.
Completed with matlab Guillaume BECQ code.
Supported : Read
Author: sgarcia
"""
import datetime
import os
import struct
# file no longer exists in Python3
try:
file
except NameError:
import io
file = io.BufferedReader
import numpy as np
import quantities as pq
from neo.io.baseio import BaseIO
from neo.core import Segment, AnalogSignal, EpochArray, EventArray
from neo.io.tools import create_many_to_one_relationship
class struct_file(file):
def read_f(self, fmt):
return struct.unpack(fmt , self.read(struct.calcsize(fmt)))
class MicromedIO(BaseIO):
"""
Class for reading data from micromed (.trc).
Usage:
>>> from neo import io
>>> r = io.MicromedIO(filename='File_micromed_1.TRC')
>>> seg = r.read_segment(lazy=False, cascade=True)
>>> print seg.analogsignals # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
[<AnalogSignal(array([ -1.77246094e+02, -2.24707031e+02, -2.66015625e+02,
...
"""
is_readable = True
is_writable = False
supported_objects = [ Segment , AnalogSignal , EventArray, EpochArray ]
readable_objects = [Segment]
writeable_objects = [ ]
has_header = False
is_streameable = False
read_params = { Segment : [ ] }
write_params = None
name = None
extensions = [ 'TRC' ]
mode = 'file'
def __init__(self , filename = None) :
"""
This class read a micromed TRC file.
Arguments:
filename : the filename to read
"""
BaseIO.__init__(self)
self.filename = filename
def read_segment(self, cascade = True, lazy = False,):
"""
Arguments:
"""
f = struct_file(self.filename, 'rb')
#Name
f.seek(64,0)
surname = f.read(22)
while surname[-1] == ' ' :
if len(surname) == 0 :break
surname = surname[:-1]
firstname = f.read(20)
while firstname[-1] == ' ' :
if len(firstname) == 0 :break
firstname = firstname[:-1]
#Date
f.seek(128,0)
day, month, year, hour, minute, sec = f.read_f('bbbbbb')
rec_datetime = datetime.datetime(year+1900 , month , day, hour, minute, sec)
f.seek(138,0)
Data_Start_Offset , Num_Chan , Multiplexer , Rate_Min , Bytes = f.read_f('IHHHH')
#~ print Num_Chan, Bytes
#header version
f.seek(175,0)
header_version, = f.read_f('b')
assert header_version == 4
seg = Segment( name = firstname+' '+surname,
file_origin = os.path.basename(self.filename),
)
seg.annotate(surname = surname)
seg.annotate(firstname = firstname)
seg.annotate(rec_datetime = rec_datetime)
if not cascade:
return seg
# area
f.seek(176,0)
zone_names = ['ORDER', 'LABCOD', 'NOTE', 'FLAGS', 'TRONCA', 'IMPED_B', 'IMPED_E', 'MONTAGE',
'COMPRESS', 'AVERAGE', 'HISTORY', 'DVIDEO', 'EVENT A', 'EVENT B', 'TRIGGER']
zones = { }
for zname in zone_names:
zname2, pos, length = f.read_f('8sII')
zones[zname] = zname2, pos, length
#~ print zname2, pos, length
# reading raw data
if not lazy:
f.seek(Data_Start_Offset,0)
rawdata = np.fromstring(f.read() , dtype = 'u'+str(Bytes))
rawdata = rawdata.reshape(( rawdata.size/Num_Chan , Num_Chan))
# Reading Code Info
zname2, pos, length = zones['ORDER']
f.seek(pos,0)
code = np.fromfile(f, dtype='u2', count=Num_Chan)
units = {-1: pq.nano*pq.V, 0:pq.uV, 1:pq.mV, 2:1, 100: pq.percent, 101:pq.dimensionless, 102:pq.dimensionless}
for c in range(Num_Chan):
zname2, pos, length = zones['LABCOD']
f.seek(pos+code[c]*128+2,0)
label = f.read(6).strip("\x00")
ground = f.read(6).strip("\x00")
logical_min , logical_max, logical_ground, physical_min, physical_max = f.read_f('iiiii')
k, = f.read_f('h')
if k in units.keys() :
unit = units[k]
else :
unit = pq.uV
f.seek(8,1)
sampling_rate, = f.read_f('H') * pq.Hz
sampling_rate *= Rate_Min
if lazy:
signal = [ ]*unit
else:
factor = float(physical_max - physical_min) / float(logical_max-logical_min+1)
signal = ( rawdata[:,c].astype('f') - logical_ground )* factor*unit
anaSig = AnalogSignal(signal, sampling_rate=sampling_rate,
name=label, channel_index=c)
if lazy:
anaSig.lazy_shape = None
anaSig.annotate(ground = ground)
seg.analogsignals.append( anaSig )
sampling_rate = np.mean([ anaSig.sampling_rate for anaSig in seg.analogsignals ])*pq.Hz
# Read trigger and notes
for zname, label_dtype in [ ('TRIGGER', 'u2'), ('NOTE', 'S40') ]:
zname2, pos, length = zones[zname]
f.seek(pos,0)
triggers = np.fromstring(f.read(length) , dtype = [('pos','u4'), ('label', label_dtype)] , )
ea = EventArray(name =zname[0]+zname[1:].lower())
if not lazy:
keep = (triggers['pos']>=triggers['pos'][0]) & (triggers['pos']<rawdata.shape[0]) & (triggers['pos']!=0)
triggers = triggers[keep]
ea.labels = triggers['label'].astype('S')
ea.times = (triggers['pos']/sampling_rate).rescale('s')
else:
ea.lazy_shape = triggers.size
seg.eventarrays.append(ea)
# Read Event A and B
# Not so well tested
for zname in ['EVENT A', 'EVENT B']:
zname2, pos, length = zones[zname]
f.seek(pos,0)
epochs = np.fromstring(f.read(length) ,
dtype = [('label','u4'),('start','u4'),('stop','u4'),] )
ep = EpochArray(name =zname[0]+zname[1:].lower())
if not lazy:
keep = (epochs['start']>0) & (epochs['start']<rawdata.shape[0]) & (epochs['stop']<rawdata.shape[0])
epochs = epochs[keep]
ep.labels = epochs['label'].astype('S')
ep.times = (epochs['start']/sampling_rate).rescale('s')
ep.durations = ((epochs['stop'] - epochs['start'])/sampling_rate).rescale('s')
else:
ep.lazy_shape = triggers.size
seg.epocharrays.append(ep)
create_many_to_one_relationship(seg)
return seg
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