mstimberg

mstimberg

import time
import numpy as np
import theano
import theano.tensor as tt

# constants
N = 1000000
freq = 1000.
tau = 20*0.001
dt = 0.1*0.001

mstimberg

# Tested with Brian 2.1.3.1 

from brian2 import *

G = NeuronGroup(2, '''drate/dt = amplitude*sin(2*pi*100*Hz*t)/(10*ms) : Hz
                      rate_delayed : Hz                  
                      amplitude : Hz
                      buffer_pointer : integer (shared)
                      delay_steps : integer''', method='euler')
G.amplitude = [50, 100] * Hz

mstimberg

mstimberg

from brian2 import *

# A little script to get an overview over the new error messages for unit
# errors in Brian 2 (in the form of a table that can be pasted into github)

if __name__ == '__main__':

    @check_units(x=volt, y=1, result=amp)
    def myfunc(x, y):
        if y == 0:

mstimberg

from brian2 import *
from brian2.devices.cpp_standalone import CPPStandaloneCodeObject

# The following code works only for numpy runtime or C++ standalone

set_device('cpp_standalone')
prefs.codegen.cpp.headers += ['"run.h"']  # This is necessary to use brian_end()
#prefs.codegen.target = 'numpy'

# Simple model, the neurons will increasingly spike

mstimberg

'''
Record the spikes at a synapse with Brian 2. Note that you cannot use
SpikeMonitor for this task, as it is only meant to record from a NeuronGroup
(or another SpikeSource such as PoissonGroup).
'''
from brian2 import *
# The record_spikes function only works with the numpy target
prefs.codegen.target = 'numpy'

synapse_spikes = []

mstimberg

def print_schedule(network=None):
    if network is None:
        network = magic_network
        network._update_magic_objects(level=1)
    network._sort_objects()

    print('Available slots (also "before_..." and "after_..."):\n%s\n' % network.schedule)

    print('Slot                Order               Name')
    prev_slot = None

mstimberg

mstimberg

from brian2 import *
# Does also work in standalone mode, enable with:
# set_device('cpp_standalone')

N = 10
G = NeuronGroup(N,
                '''
                dv/dt = -v / (10*ms) + 1*mV*ms**-0.5*xi : volt
                v_max  : volt
                ''')