Examples

Introduction

A set of examples in neo/examples/ illustrates the use of Neo classes.

# -*- coding: utf-8 -*-
"""
This is an example for reading files with neo.io
"""

import urllib

import neo

url_repo = 'https://web.gin.g-node.org/NeuralEnsemble/ephy_testing_data/raw/master/'

# Plexon files
distantfile = url_repo + 'plexon/File_plexon_3.plx'
localfile = './File_plexon_3.plx'
urllib.request.urlretrieve(distantfile, localfile)

# create a reader
reader = neo.io.PlexonIO(filename='File_plexon_3.plx')
# read the blocks
blks = reader.read(lazy=False)
print(blks)
# access to segments
for blk in blks:
    for seg in blk.segments:
        print(seg)
        for asig in seg.analogsignals:
            print(asig)
        for st in seg.spiketrains:
            print(st)

# CED Spike2 files
distantfile = url_repo + 'spike2/File_spike2_1.smr'
localfile = './File_spike2_1.smr'
urllib.request.urlretrieve(distantfile, localfile)

# create a reader
reader = neo.io.Spike2IO(filename='File_spike2_1.smr')
# read the block
bl = reader.read(lazy=False)[0]
print(bl)
# access to segments
for seg in bl.segments:
    print(seg)
    for asig in seg.analogsignals:
        print(asig)
    for st in seg.spiketrains:
        print(st)

# -*- coding: utf-8 -*-
"""
This is an example for reading files with neo.rawio
compare with read_files_neo_io.py
"""

import urllib
from neo.rawio import PlexonRawIO

url_repo = 'https://web.gin.g-node.org/NeuralEnsemble/ephy_testing_data/raw/master/'

# Get Plexon files
distantfile = url_repo + 'plexon/File_plexon_3.plx'
localfile = './File_plexon_3.plx'
urllib.request.urlretrieve(distantfile, localfile)

# create a reader
reader = PlexonRawIO(filename='File_plexon_3.plx')
reader.parse_header()
print(reader)
print(reader.header)

# Read signal chunks
channel_indexes = None  # could be channel_indexes = [0]
raw_sigs = reader.get_analogsignal_chunk(block_index=0, seg_index=0, i_start=1024, i_stop=2048,
                                         channel_indexes=channel_indexes)
float_sigs = reader.rescale_signal_raw_to_float(raw_sigs, dtype='float64')
sampling_rate = reader.get_signal_sampling_rate()
t_start = reader.get_signal_t_start(block_index=0, seg_index=0)
units = reader.header['signal_channels'][0]['units']
print(raw_sigs.shape, raw_sigs.dtype)
print(float_sigs.shape, float_sigs.dtype)
print(sampling_rate, t_start, units)

# Count unit and spike per units
nb_unit = reader.unit_channels_count()
print('nb_unit', nb_unit)
for unit_index in range(nb_unit):
    nb_spike = reader.spike_count(block_index=0, seg_index=0, unit_index=unit_index)
    print('unit_index', unit_index, 'nb_spike', nb_spike)

# Read spike times
spike_timestamps = reader.get_spike_timestamps(block_index=0, seg_index=0, unit_index=0,
                                               t_start=0., t_stop=10.)
print(spike_timestamps.shape, spike_timestamps.dtype, spike_timestamps[:5])
spike_times = reader.rescale_spike_timestamp(spike_timestamps, dtype='float64')
print(spike_times.shape, spike_times.dtype, spike_times[:5])

# Read spike waveforms
raw_waveforms = reader.get_spike_raw_waveforms(block_index=0, seg_index=0, unit_index=0,
                                               t_start=0., t_stop=10.)
print(raw_waveforms.shape, raw_waveforms.dtype, raw_waveforms[0, 0, :4])
float_waveforms = reader.rescale_waveforms_to_float(raw_waveforms, dtype='float32', unit_index=0)
print(float_waveforms.shape, float_waveforms.dtype, float_waveforms[0, 0, :4])

# Read event timestamps and times (take anotehr file)
distantfile = url_repo + 'plexon/File_plexon_2.plx'
localfile = './File_plexon_2.plx'
urllib.request.urlretrieve(distantfile, localfile)

# Count event per channel
reader = PlexonRawIO(filename='File_plexon_2.plx')
reader.parse_header()
nb_event_channel = reader.event_channels_count()
print('nb_event_channel', nb_event_channel)
for chan_index in range(nb_event_channel):
    nb_event = reader.event_count(block_index=0, seg_index=0, event_channel_index=chan_index)
    print('chan_index', chan_index, 'nb_event', nb_event)

ev_timestamps, ev_durations, ev_labels = reader.get_event_timestamps(block_index=0, seg_index=0,
                                                                     event_channel_index=0,
                                                                     t_start=None, t_stop=None)
print(ev_timestamps, ev_durations, ev_labels)
ev_times = reader.rescale_event_timestamp(ev_timestamps, dtype='float64')
print(ev_times)

# -*- coding: utf-8 -*-
"""
This is an example for plotting a Neo object with matplotlib.
"""

import urllib

import numpy as np
import quantities as pq
from matplotlib import pyplot

import neo

distantfile = 'https://web.gin.g-node.org/NeuralEnsemble/ephy_testing_data/raw/master/plexon/File_plexon_3.plx'
localfile = './File_plexon_3.plx'

urllib.request.urlretrieve(distantfile, localfile)

# reader = neo.io.NeuroExplorerIO(filename='File_neuroexplorer_2.nex')
reader = neo.io.PlexonIO(filename='File_plexon_3.plx')

bl = reader.read(lazy=False)[0]
for seg in bl.segments:
    print("SEG: " + str(seg.file_origin))
    fig = pyplot.figure()
    ax1 = fig.add_subplot(2, 1, 1)
    ax2 = fig.add_subplot(2, 1, 2)
    ax1.set_title(seg.file_origin)
    ax1.set_ylabel('arbitrary units')
    mint = 0 * pq.s
    maxt = np.inf * pq.s
    for i, asig in enumerate(seg.analogsignals):
        times = asig.times.rescale('s').magnitude
        asig = asig.magnitude
        ax1.plot(times, asig)

    trains = [st.rescale('s').magnitude for st in seg.spiketrains]
    colors = pyplot.cm.jet(np.linspace(0, 1, len(seg.spiketrains)))
    ax2.eventplot(trains, colors=colors)

pyplot.show()