/usr/lib/python2.7/dist-packages/neo/io/asciispiketrainio.py is in python-neo 0.3.3-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | # -*- coding: utf-8 -*-
"""
Classe for reading/writing SpikeTrains in a text file.
It is the simple case where different spiketrains are written line by line.
Supported : Read/Write
Author: sgarcia
"""
import os
import numpy as np
import quantities as pq
from neo.io.baseio import BaseIO
from neo.core import Segment, SpikeTrain
from neo.io.tools import create_many_to_one_relationship
class AsciiSpikeTrainIO(BaseIO):
"""
Classe for reading/writing SpikeTrain in a text file.
Each Spiketrain is a line.
Usage:
>>> from neo import io
>>> r = io.AsciiSpikeTrainIO( filename = 'File_ascii_spiketrain_1.txt')
>>> seg = r.read_segment(lazy = False, cascade = True,)
>>> print seg.spiketrains # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
[<SpikeTrain(array([ 3.89981604, 4.73258781, 0.608428 , 4.60246277, 1.23805797,
...
"""
is_readable = True
is_writable = True
supported_objects = [Segment , SpikeTrain]
readable_objects = [Segment]
writeable_objects = [Segment]
has_header = False
is_streameable = False
read_params = {
Segment : [
('delimiter' , {'value' : '\t', 'possible' : ['\t' , ' ' , ',' , ';'] }) ,
('t_start' , { 'value' : 0., } ),
]
}
write_params = {
Segment : [
('delimiter' , {'value' : '\t', 'possible' : ['\t' , ' ' , ',' , ';'] }) ,
]
}
name = None
extensions = [ 'txt' ]
mode = 'file'
def __init__(self , filename = None) :
"""
This class read/write SpikeTrains in a text file.
Each row is a spiketrain.
**Arguments**
filename : the filename to read/write
"""
BaseIO.__init__(self)
self.filename = filename
def read_segment(self,
lazy = False,
cascade = True,
delimiter = '\t',
t_start = 0.*pq.s,
unit = pq.s,
):
"""
Arguments:
delimiter : columns delimiter in file '\t' or one space or two space or ',' or ';'
t_start : time start of all spiketrain 0 by default
unit : unit of spike times, can be a str or directly a Quantities
"""
unit = pq.Quantity(1, unit)
seg = Segment(file_origin = os.path.basename(self.filename))
if not cascade:
return seg
f = open(self.filename, 'Ur')
for i,line in enumerate(f) :
alldata = line[:-1].split(delimiter)
if alldata[-1] == '': alldata = alldata[:-1]
if alldata[0] == '': alldata = alldata[1:]
if lazy:
spike_times = [ ]
t_stop = t_start
else:
spike_times = np.array(alldata).astype('f')
t_stop = spike_times.max()*unit
sptr = SpikeTrain(spike_times*unit, t_start=t_start, t_stop=t_stop)
if lazy:
sptr.lazy_shape = len(alldata)
sptr.annotate(channel_index = i)
seg.spiketrains.append(sptr)
f.close()
create_many_to_one_relationship(seg)
return seg
def write_segment(self, segment,
delimiter = '\t',
):
"""
Write SpikeTrain of a Segment in a txt file.
Each row is a spiketrain.
Arguments:
segment : the segment to write. Only analog signals will be written.
delimiter : columns delimiter in file '\t' or one space or two space or ',' or ';'
information of t_start is lost
"""
f = open(self.filename, 'w')
for s,sptr in enumerate(segment.spiketrains) :
for ts in sptr :
f.write('%f%s'% (ts , delimiter) )
f.write('\n')
f.close()
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