# -*- coding: utf-8 -*-
#_____________________________________________________________________________
#
# Copyright (c) 2012 Berlin Institute of Technology
# All rights reserved.
#
# Developed by: Philipp Meier <pmeier82@gmail.com>
# Neural Information Processing Group (NI)
# School for Electrical Engineering and Computer Science
# Berlin Institute of Technology
# MAR 5-6, Marchstr. 23, 10587 Berlin, Germany
# http://www.ni.tu-berlin.de/
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# deal with the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
# sell copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimers.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimers in the documentation
# and/or other materials provided with the distribution.
# * Neither the names of Neural Information Processing Group (NI), Berlin
# Institute of Technology, nor the names of its contributors may be used to
# endorse or promote products derived from this Software without specific
# prior written permission.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# WITH THE SOFTWARE.
#_____________________________________________________________________________
#
# Acknowledgements:
# Philipp Meier <pmeier82@gmail.com>
#_____________________________________________________________________________
#
"""datafile implementation for wri file format"""
__docformat__ = 'restructuredtext'
__all__ = ['WriFile', '_WRI_H']
##---IMPORTS
import scipy as sp
from .datafile import DataFile, DataFileError
from ..funcs_general import dict_list_to_ndarray
##---CONSTANTS
VERBOSE = False
##---CLASSES
class _WRI_H(object):
"""WRI header struct"""
def __init__(self, fp):
"""
:type fp: file
:param fp: open file at seek(0)
"""
# version
self.srate = fp.readline().strip('\r\n').split()
if self.srate[0] != 'Sampling':
raise DataFileError('expected "Sampling:" in first row!"')
self.srate = int(self.srate[1][10:])
if VERBOSE:
print self.srate
print "header done."
[docs]class WriFile(DataFile):
"""WRI file format - Chen Sorter"""
## constructor
def __init__(self, filename=None, dtype=sp.float32):
# members
self.header = None
self.data = None
self.npdata = None
# super
super(WriFile, self).__init__(filename=filename, dtype=dtype)
## implementation
def _initialize_file(self, filename, **kwargs):
# open file
self.fp = open(filename, 'r')
# read header info
self.header = _WRI_H(self.fp)
self.data = {}
# read data
current_unit = None
line = self.fp.readline().strip('\r\n')
while line:
if line.isdigit():
# we found a spike for the current unit.
# Current unit should not be None at this point
self.data[current_unit].append(int(line))
else:
# This is a subheader indicating a new unit
current_unit = line[5]
self.data[current_unit] = []
line = self.fp.readline().strip('\r\n')
# Convert the lists to numpyarrays for the spike train alignment
# function
self.npdata = dict_list_to_ndarray(self.data)
if VERBOSE:
print "found_units: "
print self.data.keys()
def _close(self):
self.fp.close()
def _closed(self):
return self.fp.closed
def _filename(self):
return self.fp.name
def _get_data(self, **kwargs):
""" Returns the wri content as a dictionary of numpy arrays
:rtype: dict
:returns: mapping unit id to spike train
"""
return self.npdata
if __name__ == '__main__':
w = WriFile('C:\\\\SVN\\\\Datenanalyse\\\\Alle\\\write_test000.wri')
print w.get_data()