{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "capital-indiana",
   "metadata": {},
   "source": [
    "PyGeNN Tutorial: Ring of neurons\n",
    "===========================\n",
    "\n",
    "Load some standard libraries and the needed elements of PyGeNN\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "middle-collapse",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from pygenn.genn_model import (GeNNModel, init_connectivity, create_cmlf_class,\n",
    "                               create_custom_sparse_connect_init_snippet_class,\n",
    "                               create_custom_neuron_class)\n",
    "from pygenn.genn_wrapper import NO_DELAY"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "needed-pointer",
   "metadata": {},
   "source": [
    "Create the model class and set the time step\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "boring-stevens",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = GeNNModel(\"float\", \"LIFRing\")\n",
    "model.dT = 0.1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "buried-mission",
   "metadata": {},
   "source": [
    "Define an initialisation code snippet\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "incoming-engine",
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_model = create_custom_sparse_connect_init_snippet_class(\n",
    "    \"ring\",\n",
    "    row_build_code=\n",
    "        \"\"\"\n",
    "        $(addSynapse, ($(id_pre) + 1) % $(num_post));\n",
    "        $(endRow);\n",
    "        \"\"\",\n",
    "    calc_max_row_len_func=create_cmlf_class(\n",
    "        lambda num_pre, num_post, pars: 1)())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "subjective-provincial",
   "metadata": {},
   "source": [
    "Define a custom neuron model\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "animated-volume",
   "metadata": {},
   "outputs": [],
   "source": [
    "adaptive_LIF = create_custom_neuron_class(\n",
    "    \"adaptive_LIF\",\n",
    "    param_names= [\"C_mem\", \"V_reset\", \"V_thresh\", \"V_leak\", \"g_leak\", \"r_scale\", \"g_adapt\", \"V_adapt\", \"tau_adapt\", \"noise_A\"],\n",
    "    var_name_types= [(\"V\", \"scalar\"), (\"a\", \"scalar\")],\n",
    "    sim_code= \"\"\"\n",
    "    $(V)+= (-$(g_leak)*($(V)-$(V_leak)) - $(g_adapt)*$(a)*($(V)-$(V_adapt)) \n",
    "            + $(r_scale)*$(Isyn)+$(noise_A)*$(gennrand_normal))*DT/$(C_mem);\n",
    "    $(a)+= -$(a)*DT/$(tau_adapt);\n",
    "    \"\"\",\n",
    "    threshold_condition_code= \"\"\"\n",
    "    $(V) >= $(V_thresh)\n",
    "    \"\"\",\n",
    "    reset_code= \"\"\"\n",
    "    $(V)= $(V_reset);\n",
    "    $(a)+= 0.3;\n",
    "    \"\"\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "limiting-gateway",
   "metadata": {},
   "source": [
    "Define some neuron parameters and initial variables\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "municipal-bumper",
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 10\n",
    "p = {\"C_mem\": 2.0,\n",
    "             \"V_reset\": -70.0,\n",
    "             \"V_thresh\": -40.0,\n",
    "             \"V_leak\": -60.0,\n",
    "             \"g_leak\": 0.01,\n",
    "             \"r_scale\": 1.0,\n",
    "             \"g_adapt\": 0.005,\n",
    "             \"V_adapt\": -70.0,\n",
    "             \"tau_adapt\": 1000.0,\n",
    "             \"noise_A\": 0.5/np.sqrt(model.dT)\n",
    "             }\n",
    "\n",
    "ini = {\"V\": -60.0,\n",
    "          \"a\": 0.0\n",
    "          }\n",
    "\n",
    "stim_ini = {\"startSpike\": [0], \"endSpike\": [1]}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "express-marks",
   "metadata": {},
   "source": [
    "Define some synaptic parameters and initial values\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "transsexual-elizabeth",
   "metadata": {},
   "outputs": [],
   "source": [
    "s_ini = {\"g\": 0.18}\n",
    "\n",
    "ps_p = {\"tau\": 5.0,  # Decay time constant [ms] \n",
    "        \"E\": 10.0}  # Reversal potential [mV]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adult-warrior",
   "metadata": {},
   "source": [
    "Add a neuron population and stimulus population\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "exclusive-fairy",
   "metadata": {},
   "outputs": [],
   "source": [
    "pop1 = model.add_neuron_population(\"Pop1\", N, adaptive_LIF, p, ini)\n",
    "stim = model.add_neuron_population(\"Stim\", 1, \"SpikeSourceArray\", {}, stim_ini)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "marine-integral",
   "metadata": {},
   "source": [
    "Add a synapse population: \n",
    "---\n",
    "Connect the LIF neurons in a ring with the \"ring\" init snippet\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "armed-gospel",
   "metadata": {},
   "outputs": [],
   "source": [
    "syn1 = model.add_synapse_population(\"Pop1self\", \"SPARSE_GLOBALG\", 10,\n",
    "    pop1, pop1,\n",
    "    \"StaticPulse\", {}, s_ini, {}, {},\n",
    "    \"ExpCond\", ps_p, {},\n",
    "    init_connectivity(ring_model, {}))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "continued-outreach",
   "metadata": {},
   "source": [
    "Add a second synapse population: \n",
    "---\n",
    "Connect the stimuli to the neurons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "charming-blink",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pygenn.genn_groups.SynapseGroup at 0x110f3af40>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.add_synapse_population(\"StimPop1\", \"SPARSE_GLOBALG\", NO_DELAY,\n",
    "    stim, pop1,\n",
    "    \"StaticPulse\", {}, s_ini, {}, {},\n",
    "    \"ExpCond\", ps_p, {},\n",
    "    init_connectivity(\"OneToOne\", {}))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "special-element",
   "metadata": {},
   "source": [
    "Initialize the spike source array\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "tribal-sharp",
   "metadata": {},
   "outputs": [],
   "source": [
    "stim.set_extra_global_param(\"spikeTimes\", [0.0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "incoming-interim",
   "metadata": {},
   "source": [
    "Build the model\n",
    "---\n",
    "This step does the entire code generation and C++/CUDA compilation!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "chubby-incentive",
   "metadata": {},
   "outputs": [],
   "source": [
    "m = model.build()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "outer-legend",
   "metadata": {},
   "source": [
    "Load the model\n",
    "---\n",
    "This step will initialize the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "laughing-carpet",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exotic-remains",
   "metadata": {},
   "source": [
    "Run the model for some time steps\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "dynamic-lincoln",
   "metadata": {},
   "outputs": [],
   "source": [
    "v = np.empty((4000, N))\n",
    "v_view = pop1.vars[\"V\"].view\n",
    "while model.t < 400.0:\n",
    "    model.step_time()\n",
    "    pop1.pull_var_from_device(\"V\")\n",
    "    \n",
    "    v[model.timestep - 1,:]=v_view[:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "protected-responsibility",
   "metadata": {},
   "source": [
    "Plot the results\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "quick-pocket",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axis = plt.subplots()\n",
    "axis.plot(v[:,:])\n",
    "#plt.xlim((0,250))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
