NEST与NESTML安装与使用指南

安装最新版本的cmake (需要sudo权限)

参考资料: https://graspingtech.com/upgrade-cmake/

sudo apt install build-essential libssl-dev
wget https://github.com/Kitware/CMake/releases/download/v3.22.0/cmake-3.22.0.tar.gz
tar -zxvf cmake-3.22.0.tar.gz
cd cmake-3.22.0
./bootstrap
make 
sudo make install

安装NEST-v3.1

参考资料: https://nest-simulator.readthedocs.io/en/stable/installation/linux_install.html

警告: 通过pip或conda直接安装NEST v2.20.1 可能会产生该报错问题。

  • 新建conda环境. 
      conda create -n nestml python=3.9 -y
  • 安装依赖环境. 
      conda activate nestml
  conda install -y numpy cython matplotlib ipython scipy
  conda install -y pytest pytest-xdist pytest-timeout
  pip install junitparser
  • 下载最新版的NEST安装包 
      wget -O nest-simulator-3.1.tar.gz https://codeload.github.com/nest/nest-simulator/tar.gz/refs/tags/v3.1
  • 解压tar压缩包 
      tar -xzvf nest-simulator-3.1.tar.gz

  • 创建编译目录

      mkdir nest-simulator-3.1-build

  • 切换到编译目录

      cd nest-simulator-3.1-build

  • 配置NEST。可能需要额外cmake配置选项(see CMake Options for NEST).

      cmake ../nest-simulator-3.1/

  • 编译NEST并安装:

      make
  make install
  make installcheck

    make installcheck命令会检查安装是否成功。如果安装成功，会显示如下信息:

      [100%] Built target installcheck

安装最新的NEST::ml开发版本

参考资料: https://nestml.readthedocs.io/en/latest/installation.html

从GitHub下载最新的开发版本。

git clone https://github.com/nest/nestml

安装到当前Python环境。

cd nestml
python setup.py install --user

注意: antlr4-python3-runtime==4.10可能引起报错，推荐版本：4.9.3。

测试安装 (可选)

安装完成后，可通过下面命令检验是否安装成功。

python setup.py test

注意：tests.docstring_comment_test可能会失败报错，但并不影响正常使用。

安装测试*.nestml模块

参考资料: https://nestml.readthedocs.io/en/latest/tutorials/izhikevich/nestml_izhikevich_tutorial.html

import nest
from pynestml.frontend.pynestml_frontend import to_nest, install_nest

NEST_SIMULATOR_INSTALL_LOCATION = nest.ll_api.sli_func("statusdict/prefix ::")

to_nest(input_path="izhikevich_solution.nestml", # replace with path of your own nestml file
        target_path="~/tmp/nestml-component",
        logging_level="ERROR")

install_nest("~/tmp/nestml-component", NEST_SIMULATOR_INSTALL_LOCATION)

nest.Install("nestmlmodule")

使用NEST编写模型并运行

import numpy as np
import matplotlib.pyplt as plt
import nest

nest.set_verbosity("M_WARNING")
nest.ResetKernel()

neuron = nest.Create("izhikevich_tutorial") # replace with name of your own model
voltmeter = nest.Create("voltmeter")

voltmeter.set({"record_from": ["v", "u"]})
nest.Connect(voltmeter, neuron)

cgs = nest.Create('dc_generator')
cgs.set({"amplitude": 25.})
nest.Connect(cgs, neuron)

sr = nest.Create("spike_recorder")
nest.Connect(neuron, sr)

nest.Simulate(250.)

spike_times = nest.GetStatus(sr, keys='events')[0]['times']

fig, ax = plt.subplots(nrows=2)
ax[0].plot(voltmeter.get("events")["times"], voltmeter.get("events")["v"])
ax[1].plot(voltmeter.get("events")["times"], voltmeter.get("events")["u"])
ax[0].scatter(spike_times, 30 * np.ones_like(spike_times), marker="d", c="orange", alpha=.8, zorder=99)
for _ax in ax:
    _ax.grid(True)
ax[0].set_ylabel("v [mV]")
ax[1].set_ylabel("u")
ax[-1].set_xlabel("Time [ms]")
fig.savefig('test.png')
fig.show()

代码输出结果如下: