# Source code for spynnaker.spike_checker

# Copyright (c) 2017-2019 The University of Manchester
#
# This program is free software: you can redistribute it and/or modify
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

import numpy

[docs]def synfire_spike_checker(spikes, nNeurons):
"""
:param spikes: The spike data to check.
:type spikes: ~numpy.ndarray or list(~numpy.ndarray)
:param int nNeurons: The number of neurons.
:raises Exception: If there is a problem with the data
"""
if isinstance(spikes, numpy.ndarray):
sorted_spikes = spikes[spikes[:, 1].argsort()]
print(len(sorted_spikes))
num = 0
for row in sorted_spikes:
if num != round(row[0]):
numpy.savetxt("spikes.csv", sorted_spikes, fmt=['%d', '%d'],
delimiter=',')
raise Exception("Unexpected spike at time " + str(row[1]))
num += 1
if num >= nNeurons:
num = 0
else:
for single in spikes:
synfire_spike_checker(single, nNeurons)

[docs]def synfire_multiple_lines_spike_checker(
spikes, nNeurons, lines, wrap_around=True):
"""
Checks that there are the expected number of spike lines

:param spikes: The spikes
:type spikes: ~numpy.ndarray or list(~numpy.ndarray)
:param int nNeurons: The number of neurons.
:param int lines: Expected number of lines
:param bool wrap_around:
If True the lines will wrap around when reaching the last neuron.
:raises Exception: If there is a problem with the data
"""
sorted_spikes = spikes[spikes[:, 1].argsort()]
nums = [0] * lines
used = [False] * lines
for row in sorted_spikes:
node = round(row[0])
found = False
for i in range(lines):
if nums[i] == node:
found = True
nums[i] += 1
if nums[i] >= nNeurons and wrap_around:
nums[i] = 0
used[i] = True
break
numpy.savetxt("sorted_spikes.csv", sorted_spikes, fmt=['%d', '%d'],
delimiter=',')
raise Exception("Unexpected spike at time " + str(row[1]))
if False in used:
numpy.savetxt("sorted_spikes.csv", sorted_spikes, fmt=['%d', '%d'],
delimiter=',')
print(used)
raise Exception("Expected " + str(lines) + " spike lines")

if __name__ == '__main__':