mstimberg

from brian2 import *
# parameter dictionary definition
params = {
    'defaultclock.dt' : '0.1*ms',
    'Init_time' : '50000*ms',
    'buffer_time' : '1200*ms',
    'run_time' : '1200*ms',
    'Cm' : '1* uF/cm**2',
    'S' : '20e3 * um**2',
    'gL' : '.05 * mS/cm**2',

mstimberg

from brian2 import *
# import brian2cuda
set_device('cpp_standalone', directory='layers_openmp')
prefs.devices.cpp_standalone.openmp_threads = 4

group1 = NeuronGroup(100, 'dv/dt = 100*Hz : 1', threshold='v>1', reset='v=0')
group1.v = 'rand()'
group2 = NeuronGroup(100, '''dv/dt = -v/tau : 1
                             tau : second ''', threshold='v>1', reset='v=0')
group2.tau = 10*ms

mstimberg

import json
import os
import re
import requests

doi_link = r'(doi: \[.*\]\(https://doi.org/([a-zA-Z0-9/._\-()]+)\))'
unpaywall_api = 'https://api.unpaywall.org/v2/'
email = '[email protected]'  # ← EMAIL
def gather_doi_info(fname):
    """

mstimberg

from brian2 import *
set_device('cpp_standalone')

# Each "input" is one combination of rates across the 5 neurons
n_stimuli = 10
rates = TimedArray(np.random.rand(n_stimuli, 5)*100*Hz, dt=100*ms)
stimulus_length = 100*ms

max_repetitions = 5
input_spikes = NeuronGroup(5, '''

mstimberg

<?xml version="1.0" ?>
<Lems xmlns="http://www.neuroml.org/lems/0.7.3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/lems/0.7.3 https://raw.githubusercontent.com/LEMS/LEMS/development/Schemas/LEMS/LEMS_v0.7.3.xsd">
  <Include file="LEMSUnitsConstants.xml"/>
  <Include file="Simulation.xml"/>
  <Include file="NeuroML2CoreTypes.xml"/>
  <ComponentType extends="baseCell" name="neurongroup">
    <Property dimension="voltage" name="v0"/>
    <EventPort direction="out" name="spike"/>
    <Exposure dimension="voltage" name="v"/>
    <Dynamics>

mstimberg

mstimberg

mstimberg

from brian2 import *

# The following example is very contrived, but writing to a variable that is linked with repeating indices
# might come up in some contexts. It's clearly a cornercase, but one that we should handle.
set_device('cpp_standalone')
prefs.devices.cpp_standalone.openmp_threads = 8  # number of threads
group1 = NeuronGroup(2, 'x : integer')
group2 = NeuronGroup(1000, 'y : integer (linked)')
group2.y = linked_var(group1, 'x', index=np.arange(2).repeat(500))
obj = group2.run_regularly('y += 1')

mstimberg

import numpy as np
import matplotlib.pyplot as plt

scenarios = [('constant', [1., 2., 3., 4., 5., 6., 7., 8., 9., 10.],  # elapsed time
                          [.1, .2, .3, .4, .5, .6, .7, .8, .9, 1.]),  # fraction of simulation completed
             ('varying', [1., 2., 3., 4., 5., 6., 7., 8., 9., 10.],
                         [.1, .175, .3, .375, .5, .575, .7, .775, .9, 1.]),
             ('slow start', [1., 2., 3., 4., 5., 6., 7., 8., 9., 10.],
                            [.05, 0.1, 0.15, 0.2, 0.25, 0.4, 0.55, 0.7, 0.85, 1.0]),
             ('slow end', [1., 2., 3., 4., 5., 6., 7., 8., 9., 10.],

mstimberg