/usr/lib/python2.7/dist-packages/neo/io/asciisignalio.py is in python-neo 0.3.3-2.
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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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 | # -*- coding: utf-8 -*-
"""
Class for reading/writing analog signals in a text file.
Each columns represents a AnalogSignal. All AnalogSignal have the same sampling rate.
Covers many case when part of a file can be viewed as a CSV format.
Supported : Read/Write
Author: sgarcia
"""
import csv
import os
import numpy as np
import quantities as pq
from neo.io.baseio import BaseIO
from neo.core import AnalogSignal, Segment
from neo.io.tools import create_many_to_one_relationship
class AsciiSignalIO(BaseIO):
"""
Class for reading signal in generic ascii format.
Columns respresents signal. They share all the same sampling rate.
The sampling rate is externally known or the first columns could hold the time
vector.
Usage:
>>> from neo import io
>>> r = io.AsciiSignalIO(filename='File_asciisignal_2.txt')
>>> seg = r.read_segment(lazy=False, cascade=True)
>>> print seg.analogsignals
[<AnalogSignal(array([ 39.0625 , 0. , 0. , ..., -26.85546875 ...
"""
is_readable = True
is_writable = True
supported_objects = [ Segment , AnalogSignal]
readable_objects = [ Segment]
writeable_objects = [Segment]
has_header = False
is_streameable = False
read_params = {
Segment : [
('delimiter' , {'value' : '\t', 'possible' : ['\t' , ' ' , ',' , ';'] }) ,
('usecols' , { 'value' : None , 'type' : int } ),
('skiprows' , { 'value' :0 } ),
('timecolumn' , { 'value' : None, 'type' : int } ) ,
('unit' , { 'value' : 'V', } ),
('sampling_rate' , { 'value' : 1000., } ),
('t_start' , { 'value' : 0., } ),
('method' , { 'value' : 'homemade', 'possible' : ['genfromtxt' , 'csv' , 'homemade' ] }) ,
]
}
write_params = {
Segment : [
('delimiter' , {'value' : '\t', 'possible' : ['\t' , ' ' , ',' , ';'] }) ,
('writetimecolumn' , { 'value' : True, } ) ,
]
}
name = None
extensions = [ 'txt' , 'asc', ]
mode = 'file'
def __init__(self , filename = None) :
"""
This class read/write AnalogSignal in a text file.
Each signal is a column.
One of the column can be the time vector
Arguments:
filename : the filename to read/write
"""
BaseIO.__init__(self)
self.filename = filename
def read_segment(self,
lazy = False,
cascade = True,
delimiter = '\t',
usecols = None,
skiprows =0,
timecolumn = None,
sampling_rate = 1.*pq.Hz,
t_start = 0.*pq.s,
unit = pq.V,
method = 'genfromtxt',
):
"""
Arguments:
delimiter : columns delimiter in file '\t' or one space or two space or ',' or ';'
usecols : if None take all columns otherwise a list for selected columns
skiprows : skip n first lines in case they contains header informations
timecolumn : None or a valid int that point the time vector
samplerate : the samplerate of signals if timecolumn is not None this is not take in account
t_start : time of the first sample
unit : unit of AnalogSignal can be a str or directly a Quantities
method : 'genfromtxt' or 'csv' or 'homemade'
in case of bugs you can try one of this methods
'genfromtxt' use numpy.genfromtxt
'csv' use cvs module
'homemade' use a intuitive more robust but slow method
"""
seg = Segment(file_origin = os.path.basename(self.filename))
if not cascade:
return seg
if type(sampling_rate) == float or type(sampling_rate)==int:
# if not quantitities Hz by default
sampling_rate = sampling_rate*pq.Hz
if type(t_start) == float or type(t_start)==int:
# if not quantitities s by default
t_start = t_start*pq.s
unit = pq.Quantity(1, unit)
#loadtxt
if method == 'genfromtxt' :
sig = np.genfromtxt(self.filename,
delimiter = delimiter,
usecols = usecols ,
skiprows = skiprows,
dtype = 'f')
if len(sig.shape) ==1:
sig = sig[:, np.newaxis]
elif method == 'csv' :
tab = [l for l in csv.reader( file(self.filename,'rU') , delimiter = delimiter ) ]
tab = tab[skiprows:]
sig = np.array( tab , dtype = 'f')
elif method == 'homemade' :
fid = open(self.filename,'rU')
for l in range(skiprows):
fid.readline()
tab = [ ]
for line in fid.readlines():
line = line.replace('\r','')
line = line.replace('\n','')
l = line.split(delimiter)
while '' in l :
l.remove('')
tab.append(l)
sig = np.array( tab , dtype = 'f')
if timecolumn is not None:
sampling_rate = 1./np.mean(np.diff(sig[:,timecolumn])) * pq.Hz
t_start = sig[0,timecolumn] * pq.s
for i in range(sig.shape[1]) :
if timecolumn == i : continue
if usecols is not None and i not in usecols: continue
if lazy:
signal = [ ]*unit
else:
signal = sig[:,i]*unit
anaSig = AnalogSignal(signal, sampling_rate=sampling_rate,
t_start=t_start, channel_index=i,
name='Column %d'%i)
if lazy:
anaSig.lazy_shape = sig.shape
seg.analogsignals.append( anaSig )
create_many_to_one_relationship(seg)
return seg
def write_segment(self, segment,
delimiter = '\t',
skiprows =0,
writetimecolumn = True,
):
"""
Write a segment and AnalogSignal in a text file.
**Arguments**
delimiter : columns delimiter in file '\t' or one space or two space or ',' or ';'
writetimecolumn : True or Flase write time vector as first column
"""
if skiprows:
raise NotImplementedError('skiprows values other than 0 are not ' +
'supported')
l = [ ]
if writetimecolumn is not None:
l.append(segment.analogsignals[0].times[:, np.newaxis])
for anaSig in segment.analogsignals:
l.append(anaSig.magnitude[:, np.newaxis])
sigs = np.concatenate(l, axis=1)
#print sigs.shape
np.savetxt(self.filename , sigs , delimiter = delimiter)
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