/usr/share/pyshared/neo/io/micromedio.py is in python-neo 0.2.0-1.
This file is owned by root:root, with mode 0o644.
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"""
Class for reading/writing data from micromed (.trc).
Inspired by the Matlab code for EEGLAB from Rami K. Niazy.
Supported : Read
Author: sgarcia
"""
from .baseio import BaseIO
from ..core import *
from .tools import create_many_to_one_relationship
import numpy as np
import quantities as pq
import os
import struct
import datetime
# file no longer exists in Python3
try:
file
except NameError:
import io
file = io.BufferedReader
class struct_file(file):
def read_f(self, format):
return struct.unpack(format , self.read(struct.calcsize(format)))
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 ]
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]
name = f.read(20)
while name[-1] == ' ' :
if len(name) == 0 :break
name = name[:-1]
#Date
f.seek(128,0)
day, month, year = f.read_f('bbb')
rec_date = datetime.date(year+1900 , month , day)
#header
f.seek(175,0)
header_version, = f.read_f('b')
assert header_version == 4
f.seek(138,0)
Data_Start_Offset , Num_Chan , Multiplexer , Rate_Min , Bytes = f.read_f('IHHHH')
f.seek(176+8,0)
Code_Area , Code_Area_Length, = f.read_f('II')
f.seek(192+8,0)
Electrode_Area , Electrode_Area_Length = f.read_f('II')
f.seek(400+8,0)
Trigger_Area , Tigger_Area_Length=f.read_f('II')
seg = Segment( name = name,
file_origin = os.path.basename(self.filename),
)
seg.annotate(surname = surname)
seg.annotate(rec_date = rec_date)
if not cascade:
return seg
# 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
f.seek(Code_Area,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):
f.seek(Electrode_Area+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)
if lazy:
#TODO
anaSig.lazy_shape = None
anaSig.annotate(channel_index = c)
anaSig.annotate(ground = ground)
seg.analogsignals.append( anaSig )
sampling_rate = np.mean([ anaSig.sampling_rate for anaSig in seg.analogsignals ])*pq.Hz
# Read trigger
f.seek(Trigger_Area,0)
ea = EventArray()
if not lazy:
labels = [ ]
times = [ ]
first_trig = 0
for i in range(0,Tigger_Area_Length/6) :
pos , label = f.read_f('IH')
if i == 0:
first_trig = pos
if ( pos > first_trig ) and (pos < rawdata.shape[0]) :
labels.append(str(label))
times.append(pos/sampling_rate)
ea.labels = np.array(labels)
ea.times = times*pq.s
else:
ea.lazy_shape = Tigger_Area_Length/6
seg.eventarrays.append(ea)
create_many_to_one_relationship(seg)
return seg
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