{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ``Delay`` Protocol\n",
    "\n",
    "## Introduction\n",
    "\n",
    "Delays are fundamental in neural systems, arising from:\n",
    "- **Axonal conduction delays**: Signal propagation along axons takes time\n",
    "- **Synaptic delays**: Chemical transmission across synapses introduces latency\n",
    "- **Network delays**: Multi-step information processing creates temporal lags\n",
    "\n",
    "BrainState provides three powerful APIs for handling delays:\n",
    "\n",
    "1. **`brainstate.nn.Delay`**: General-purpose delay buffer for any data\n",
    "2. **`brainstate.nn.DelayAccess`**: Named accessor for specific delay entries\n",
    "3. **`brainstate.nn.StateWithDelay`**: Automatic delay tracking for module states\n",
    "\n",
    "### Learning Objectives\n",
    "\n",
    "By the end of this tutorial, you will:\n",
    "\n",
    "- ✅ Understand the two delay buffer methods: rotation vs concatenation\n",
    "- ✅ Use `Delay` to create flexible delay buffers with multiple delay taps\n",
    "- ✅ Access delayed values using `DelayAccess` and named entries\n",
    "- ✅ Leverage `StateWithDelay` for automatic state history tracking\n",
    "- ✅ Implement realistic neural models with synaptic and axonal delays\n",
    "- ✅ Choose between step-based and time-based delay retrieval\n",
    "- ✅ Use linear vs round interpolation for continuous-time delays\n",
    "\n",
    "---\n",
    "\n",
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:07.554591Z",
     "start_time": "2025-10-11T10:28:05.717854Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:45:59.182071Z",
     "iopub.status.busy": "2026-05-30T16:45:59.181803Z",
     "iopub.status.idle": "2026-05-30T16:46:03.685754Z",
     "shell.execute_reply": "2026-05-30T16:46:03.684851Z"
    }
   },
   "outputs": [],
   "source": [
    "import brainstate\n",
    "import brainunit as u\n",
    "import jax.numpy as jnp\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "brainstate.environ.set(dt=0.1 * u.ms)  # 0.1 ms time step"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Part 1: Understanding `brainstate.nn.Delay`\n",
    "\n",
    "### 1.1 What is a Delay Buffer?\n",
    "\n",
    "A delay buffer stores a **rolling history** of values over time. Think of it as a time window looking into the past:\n",
    "\n",
    "```\n",
    "Time:  t-3    t-2    t-1    t (now)\n",
    "       │      │      │      │\n",
    "Data:  [10] → [20] → [30] → [40]\n",
    "       ↑      ↑      ↑      ↑\n",
    "     delay=3 delay=2 delay=1 delay=0\n",
    "```\n",
    "\n",
    "The `Delay` class maintains this history efficiently using two methods:\n",
    "\n",
    "1. **Rotation method** (default): Uses a ring buffer with modulo indexing\n",
    "2. **Concatenation method**: Shifts data by concatenating new values\n",
    "\n",
    "### 1.2 Creating a Basic Delay\n",
    "\n",
    "Let's create a simple delay buffer for a scalar signal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:07.714380Z",
     "start_time": "2025-10-11T10:28:07.560491Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:03.690813Z",
     "iopub.status.busy": "2026-05-30T16:46:03.690184Z",
     "iopub.status.idle": "2026-05-30T16:46:03.900660Z",
     "shell.execute_reply": "2026-05-30T16:46:03.899917Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum delay time: 5. ms\n",
      "Maximum delay length (steps): 51\n",
      "History buffer shape: (51, 1)\n"
     ]
    }
   ],
   "source": [
    "# Create a delay buffer for a scalar value\n",
    "# We need to specify the shape/dtype of data we'll store\n",
    "target_data = jnp.array([0.0])  # Example: scalar in array form\n",
    "\n",
    "# Create delay with 5ms maximum delay\n",
    "delay_buffer = brainstate.nn.Delay(\n",
    "    target_info=target_data,  # Shape/dtype template\n",
    "    time=5.0 * u.ms,          # Maximum delay time\n",
    "    init=0.0,                 # Initial history value\n",
    "    delay_method='rotation'   # Use ring buffer (default)\n",
    ")\n",
    "\n",
    "# Initialize the state\n",
    "delay_buffer.init_state()\n",
    "\n",
    "print(f\"Maximum delay time: {delay_buffer.max_time}\")\n",
    "print(f\"Maximum delay length (steps): {delay_buffer.max_length}\")\n",
    "print(f\"History buffer shape: {delay_buffer.history.value.shape}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 Registering Delay Entries\n",
    "\n",
    "You can register **multiple named entries** for different delay times:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:07.782494Z",
     "start_time": "2025-10-11T10:28:07.717895Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:03.902207Z",
     "iopub.status.busy": "2026-05-30T16:46:03.902064Z",
     "iopub.status.idle": "2026-05-30T16:46:03.986762Z",
     "shell.execute_reply": "2026-05-30T16:46:03.986053Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Registered delay entries:\n",
      "  immediate: (Array(0, dtype=int32),) steps\n",
      "  short: (Array(20, dtype=int32),) steps\n",
      "  medium: (Array(50, dtype=int32),) steps\n",
      "  long: (Array(100, dtype=int32),) steps\n"
     ]
    }
   ],
   "source": [
    "# Create delay buffer with multiple taps\n",
    "delay_buffer = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0]),\n",
    "    time=10.0 * u.ms,  # Support delays up to 10ms\n",
    "    init=0.0\n",
    ")\n",
    "\n",
    "# Register different delay times with names\n",
    "delay_buffer.register_entry('immediate', 0.0 * u.ms)   # No delay\n",
    "delay_buffer.register_entry('short', 2.0 * u.ms)       # 2ms delay\n",
    "delay_buffer.register_entry('medium', 5.0 * u.ms)      # 5ms delay\n",
    "delay_buffer.register_entry('long', 10.0 * u.ms)       # 10ms delay\n",
    "\n",
    "delay_buffer.init_state()\n",
    "\n",
    "print(\"Registered delay entries:\")\n",
    "for name, delay_info in delay_buffer._registered_entries.items():\n",
    "    print(f\"  {name}: {delay_info} steps\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 Updating and Accessing Delayed Values\n",
    "\n",
    "Now let's simulate a signal and access its delayed versions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:09.041529Z",
     "start_time": "2025-10-11T10:28:07.788438Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:03.989680Z",
     "iopub.status.busy": "2026-05-30T16:46:03.989416Z",
     "iopub.status.idle": "2026-05-30T16:46:05.720307Z",
     "shell.execute_reply": "2026-05-30T16:46:05.719479Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Delay buffer successfully stores and retrieves delayed values\n"
     ]
    }
   ],
   "source": [
    "# Simulation parameters\n",
    "duration = 50.0 * u.ms\n",
    "dt = brainstate.environ.get_dt()\n",
    "num_steps = int(duration / dt)\n",
    "\n",
    "# Storage for visualization\n",
    "times = []\n",
    "current_values = []\n",
    "delayed_short = []\n",
    "delayed_medium = []\n",
    "delayed_long = []\n",
    "\n",
    "# Simulate a sinusoidal signal\n",
    "for i in range(num_steps):\n",
    "    t = i * dt\n",
    "    brainstate.environ.set(i=i, t=t)\n",
    "    \n",
    "    # Current signal: sin(2π * 50Hz * t)\n",
    "    current = jnp.sin(2 * jnp.pi * 50.0 * (t / u.second)) \n",
    "    current_array = jnp.array([current])\n",
    "    \n",
    "    # Update delay buffer with current value\n",
    "    delay_buffer.update(current_array)\n",
    "    \n",
    "    # Retrieve delayed values\n",
    "    val_immediate = delay_buffer.at('immediate')[0]\n",
    "    val_short = delay_buffer.at('short')[0]\n",
    "    val_medium = delay_buffer.at('medium')[0]\n",
    "    val_long = delay_buffer.at('long')[0]\n",
    "    \n",
    "    # Store for plotting\n",
    "    times.append(float(t / u.ms))\n",
    "    current_values.append(float(val_immediate))\n",
    "    delayed_short.append(float(val_short))\n",
    "    delayed_medium.append(float(val_medium))\n",
    "    delayed_long.append(float(val_long))\n",
    "\n",
    "# Visualize\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(times, current_values, label='Current (0ms delay)', linewidth=2)\n",
    "plt.plot(times, delayed_short, label='Short (2ms delay)', alpha=0.7)\n",
    "plt.plot(times, delayed_medium, label='Medium (5ms delay)', alpha=0.7)\n",
    "plt.plot(times, delayed_long, label='Long (10ms delay)', alpha=0.7)\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Signal Value')\n",
    "plt.title('Delay Buffer: Multiple Delay Taps on 50Hz Sinusoid')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"✅ Delay buffer successfully stores and retrieves delayed values\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.5 Rotation vs Concatenation Methods\n",
    "\n",
    "**Rotation method** (ring buffer):\n",
    "- More memory efficient\n",
    "- Uses modulo indexing: `index = (current_step - delay_step) % max_length`\n",
    "- Default and recommended for most cases\n",
    "\n",
    "**Concatenation method**:\n",
    "- Shifts entire buffer on each update\n",
    "- Easier to understand conceptually\n",
    "- Can be slower for large buffers\n",
    "\n",
    "Let's compare both:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:11.211903Z",
     "start_time": "2025-10-11T10:28:11.071185Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:05.722784Z",
     "iopub.status.busy": "2026-05-30T16:46:05.722514Z",
     "iopub.status.idle": "2026-05-30T16:46:05.877947Z",
     "shell.execute_reply": "2026-05-30T16:46:05.875840Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing rotation vs concatenation methods:\n",
      "\n",
      "Step 0: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 1: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 2: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 3: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 4: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 5: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 6: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 7: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 8: Rotation=0.0, Concat=0.0, Match=True\n",
      "Step 9: Rotation=0.0, Concat=0.0, Match=True\n",
      "\n",
      "✅ Both methods produce identical results\n"
     ]
    }
   ],
   "source": [
    "# Create two delay buffers with different methods\n",
    "delay_rotation = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0]),\n",
    "    time=5.0 * u.ms,\n",
    "    delay_method='rotation'\n",
    ")\n",
    "delay_rotation.register_entry('test', 3.0 * u.ms)\n",
    "delay_rotation.init_state()\n",
    "\n",
    "delay_concat = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0]),\n",
    "    time=5.0 * u.ms,\n",
    "    delay_method='concat'\n",
    ")\n",
    "delay_concat.register_entry('test', 3.0 * u.ms)\n",
    "delay_concat.init_state()\n",
    "\n",
    "# Simulate 10 steps\n",
    "print(\"Comparing rotation vs concatenation methods:\\n\")\n",
    "for i in range(10):\n",
    "    brainstate.environ.set(i=i)\n",
    "    \n",
    "    # Update both with same value\n",
    "    value = jnp.array([float(i)])\n",
    "    delay_rotation.update(value)\n",
    "    delay_concat.update(value)\n",
    "    \n",
    "    # Retrieve delayed values\n",
    "    val_rotation = delay_rotation.at('test')[0]\n",
    "    val_concat = delay_concat.at('test')[0]\n",
    "    \n",
    "    print(f\"Step {i}: Rotation={val_rotation:.1f}, Concat={val_concat:.1f}, Match={jnp.allclose(val_rotation, val_concat)}\")\n",
    "\n",
    "print(\"\\n✅ Both methods produce identical results\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Part 2: Time-based vs Step-based Retrieval\n",
    "\n",
    "### 2.1 Step-based Retrieval\n",
    "\n",
    "When you know the exact delay in **integer time steps**, use `retrieve_at_step()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:11.237763Z",
     "start_time": "2025-10-11T10:28:11.215026Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:05.880214Z",
     "iopub.status.busy": "2026-05-30T16:46:05.879965Z",
     "iopub.status.idle": "2026-05-30T16:46:05.896133Z",
     "shell.execute_reply": "2026-05-30T16:46:05.895204Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step-based retrieval at step 19:\n",
      "  0 steps back (current):  190.0 (expected: 190)\n",
      "  5 steps back:            140.0 (expected: 140)\n",
      "  10 steps back:           90.0 (expected: 90)\n"
     ]
    }
   ],
   "source": [
    "delay_buffer = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0]),\n",
    "    time=10.0 * u.ms,\n",
    ")\n",
    "delay_buffer.init_state()\n",
    "\n",
    "# Populate buffer\n",
    "for i in range(20):\n",
    "    brainstate.environ.set(i=i)\n",
    "    delay_buffer.update(jnp.array([float(i * 10)]))\n",
    "\n",
    "# Retrieve by step (integer delay)\n",
    "brainstate.environ.set(i=19)  # At step 19\n",
    "current = delay_buffer.retrieve_at_step(0)      # 0 steps back\n",
    "delayed_5 = delay_buffer.retrieve_at_step(5)    # 5 steps back\n",
    "delayed_10 = delay_buffer.retrieve_at_step(10)  # 10 steps back\n",
    "\n",
    "print(\"Step-based retrieval at step 19:\")\n",
    "print(f\"  0 steps back (current):  {current[0]:.1f} (expected: {19*10})\")\n",
    "print(f\"  5 steps back:            {delayed_5[0]:.1f} (expected: {(19-5)*10})\")\n",
    "print(f\"  10 steps back:           {delayed_10[0]:.1f} (expected: {(19-10)*10})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Time-based Retrieval\n",
    "\n",
    "When delays are specified in **continuous time**, use `retrieve_at_time()`. This supports interpolation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:11.414429Z",
     "start_time": "2025-10-11T10:28:11.238430Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:05.898143Z",
     "iopub.status.busy": "2026-05-30T16:46:05.897895Z",
     "iopub.status.idle": "2026-05-30T16:46:06.160880Z",
     "shell.execute_reply": "2026-05-30T16:46:06.160159Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time-based retrieval at t=9.9ms, delay=2.5ms:\n",
      "  Linear interpolation: 74.00 (between steps 74 and 75)\n",
      "  Round interpolation:  74.00 (rounds to nearest step)\n",
      "  Expected exact value: 74 (25 steps back from step 99)\n"
     ]
    }
   ],
   "source": [
    "# Create delay with linear interpolation\n",
    "delay_linear = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0]),\n",
    "    time=5.0 * u.ms,\n",
    "    interp_method='linear_interp'  # Linear interpolation\n",
    ")\n",
    "delay_linear.init_state()\n",
    "\n",
    "# Create delay with round interpolation\n",
    "delay_round = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0]),\n",
    "    time=5.0 * u.ms,\n",
    "    interp_method='round'  # Round to nearest step\n",
    ")\n",
    "delay_round.init_state()\n",
    "\n",
    "# Populate both buffers\n",
    "for i in range(100):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    brainstate.environ.set(i=i, t=t)\n",
    "    value = jnp.array([float(i)])\n",
    "    delay_linear.update(value)\n",
    "    delay_round.update(value)\n",
    "\n",
    "# Retrieve at non-integer delay times\n",
    "t_current = 99 * brainstate.environ.get_dt()\n",
    "brainstate.environ.set(i=99, t=t_current)\n",
    "\n",
    "delay_time = 2.5 * u.ms  # 2.5ms = 25 steps (non-integer at 0.1ms resolution)\n",
    "target_time = t_current - delay_time\n",
    "\n",
    "val_linear = delay_linear.retrieve_at_time(target_time)[0]\n",
    "val_round = delay_round.retrieve_at_time(target_time)[0]\n",
    "\n",
    "print(f\"Time-based retrieval at t={float(t_current / u.ms):.1f}ms, delay={float(delay_time / u.ms)}ms:\")\n",
    "print(f\"  Linear interpolation: {val_linear:.2f} (between steps 74 and 75)\")\n",
    "print(f\"  Round interpolation:  {val_round:.2f} (rounds to nearest step)\")\n",
    "print(f\"  Expected exact value: {99 - 25} (25 steps back from step 99)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Interpolation Comparison\n",
    "\n",
    "Let's visualize the difference between linear and round interpolation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:12.194330Z",
     "start_time": "2025-10-11T10:28:11.424944Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:06.163231Z",
     "iopub.status.busy": "2026-05-30T16:46:06.162969Z",
     "iopub.status.idle": "2026-05-30T16:46:07.353538Z",
     "shell.execute_reply": "2026-05-30T16:46:07.352508Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Linear interpolation provides smooth continuous values\n",
      "✅ Round interpolation snaps to nearest discrete time step\n"
     ]
    }
   ],
   "source": [
    "# Create delays with different interpolation\n",
    "delay_linear = brainstate.nn.Delay(jnp.array([0.0]), time=10.0 * u.ms, interp_method='linear_interp')\n",
    "delay_round = brainstate.nn.Delay(jnp.array([0.0]), time=10.0 * u.ms, interp_method='round')\n",
    "delay_linear.init_state()\n",
    "delay_round.init_state()\n",
    "\n",
    "# Populate with ramp signal\n",
    "for i in range(200):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    brainstate.environ.set(i=i, t=t)\n",
    "    value = jnp.array([float(i)])\n",
    "    delay_linear.update(value)\n",
    "    delay_round.update(value)\n",
    "\n",
    "# Test various delay times (non-integer steps)\n",
    "t_now = 199 * brainstate.environ.get_dt()\n",
    "brainstate.environ.set(i=199, t=t_now)\n",
    "\n",
    "delay_times_ms = jnp.linspace(0.0, 10.0, 101)  # 0 to 10ms\n",
    "linear_vals = []\n",
    "round_vals = []\n",
    "\n",
    "for delay_ms in delay_times_ms:\n",
    "    delay_time = delay_ms * u.ms\n",
    "    target_time = t_now - delay_time\n",
    "    \n",
    "    val_linear = delay_linear.retrieve_at_time(target_time)[0]\n",
    "    val_round = delay_round.retrieve_at_time(target_time)[0]\n",
    "    \n",
    "    linear_vals.append(float(val_linear))\n",
    "    round_vals.append(float(val_round))\n",
    "\n",
    "plt.figure(figsize=(12, 5))\n",
    "plt.plot(delay_times_ms, linear_vals, label='Linear Interpolation', linewidth=2)\n",
    "plt.plot(delay_times_ms, round_vals, label='Round Interpolation', linewidth=2, alpha=0.7, linestyle='--')\n",
    "plt.xlabel('Delay Time (ms)')\n",
    "plt.ylabel('Retrieved Value')\n",
    "plt.title('Linear vs Round Interpolation in Time-based Delay Retrieval')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"✅ Linear interpolation provides smooth continuous values\")\n",
    "print(\"✅ Round interpolation snaps to nearest discrete time step\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Part 3: `brainstate.nn.DelayAccess`\n",
    "\n",
    "### 3.1 What is DelayAccess?\n",
    "\n",
    "`DelayAccess` creates a **reusable accessor** for a specific delay entry. It's useful when:\n",
    "- You need to pass delay accessors to other modules\n",
    "- You want to encapsulate delay configuration\n",
    "- Building modular neural network components\n",
    "\n",
    "### 3.2 Creating and Using DelayAccess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:12.365347Z",
     "start_time": "2025-10-11T10:28:12.203264Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:07.361545Z",
     "iopub.status.busy": "2026-05-30T16:46:07.361264Z",
     "iopub.status.idle": "2026-05-30T16:46:07.564023Z",
     "shell.execute_reply": "2026-05-30T16:46:07.563128Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DelayAccess retrieval at step 199:\n",
      "  2ms delay (20 steps): [179. 358. 537.]\n",
      "  5ms delay (50 steps): [149. 298. 447.]\n",
      "  Expected 2ms: [179, 358, 537]\n",
      "  Expected 5ms: [149, 298, 447]\n"
     ]
    }
   ],
   "source": [
    "# Create a delay buffer\n",
    "delay_buffer = brainstate.nn.Delay(\n",
    "    target_info=jnp.array([0.0, 0.0, 0.0]),  # 3D vector\n",
    "    time=10.0 * u.ms,\n",
    ")\n",
    "delay_buffer.init_state()\n",
    "\n",
    "# Create DelayAccess objects for different delays\n",
    "# Method 1: Using .access() method\n",
    "accessor_2ms = delay_buffer.access('entry_2ms', 2.0 * u.ms)\n",
    "accessor_5ms = delay_buffer.access('entry_5ms', 5.0 * u.ms)\n",
    "\n",
    "# Simulate signal\n",
    "for i in range(200):\n",
    "    brainstate.environ.set(i=i)\n",
    "    \n",
    "    # Update with [i, i*2, i*3]\n",
    "    value = jnp.array([float(i), float(i*2), float(i*3)])\n",
    "    delay_buffer.update(value)\n",
    "\n",
    "# Access delayed values by calling the DelayAccess objects\n",
    "delayed_2ms = accessor_2ms()  # call the accessor to retrieve\n",
    "delayed_5ms = accessor_5ms()\n",
    "\n",
    "print(\"DelayAccess retrieval at step 199:\")\n",
    "print(f\"  2ms delay (20 steps): {delayed_2ms}\")\n",
    "print(f\"  5ms delay (50 steps): {delayed_5ms}\")\n",
    "print(f\"  Expected 2ms: [{199-20}, {(199-20)*2}, {(199-20)*3}]\")\n",
    "print(f\"  Expected 5ms: [{199-50}, {(199-50)*2}, {(199-50)*3}]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Using DelayAccess in Modules\n",
    "\n",
    "DelayAccess is particularly useful when building modular components:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:12.565497Z",
     "start_time": "2025-10-11T10:28:12.371359Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:07.566433Z",
     "iopub.status.busy": "2026-05-30T16:46:07.566172Z",
     "iopub.status.idle": "2026-05-30T16:46:07.830596Z",
     "shell.execute_reply": "2026-05-30T16:46:07.829587Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing DelayedConnection module:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step  0: Input=  0.0, Output=  0.0\n",
      "Step 10: Input= 10.0, Output=  0.0\n",
      "Step 20: Input= 20.0, Output=  0.0\n",
      "Step 30: Input= 30.0, Output=  0.0\n",
      "Step 40: Input= 40.0, Output=  5.0\n",
      "\n",
      "✅ DelayAccess enables modular delay handling in custom modules\n"
     ]
    }
   ],
   "source": [
    "class DelayedConnection(brainstate.nn.Module):\n",
    "    \"\"\"A module that applies delayed weighted connection.\"\"\"\n",
    "    \n",
    "    def __init__(self, size, weight, delay_time):\n",
    "        super().__init__()\n",
    "        self.weight = weight\n",
    "        \n",
    "        # Create delay buffer and accessor\n",
    "        self.delay_buffer = brainstate.nn.Delay(\n",
    "            target_info=jnp.zeros(size),\n",
    "            time=delay_time * 2,  # Buffer size\n",
    "        )\n",
    "        self.delay_access = self.delay_buffer.access('conn', delay_time)\n",
    "    \n",
    "    def update(self, current_input):\n",
    "        # Store current input\n",
    "        self.delay_buffer.update(current_input)\n",
    "        \n",
    "        # Get delayed input\n",
    "        delayed_input = self.delay_access()\n",
    "        \n",
    "        # Apply weight to delayed input\n",
    "        return self.weight * delayed_input\n",
    "\n",
    "# Create delayed connection\n",
    "conn = DelayedConnection(size=5, weight=0.5, delay_time=3.0 * u.ms)\n",
    "conn.delay_buffer.init_state()\n",
    "\n",
    "# Simulate\n",
    "print(\"Testing DelayedConnection module:\\n\")\n",
    "for i in range(50):\n",
    "    brainstate.environ.set(i=i)\n",
    "    \n",
    "    # Input: [i, i, i, i, i]\n",
    "    input_signal = jnp.ones(5) * i\n",
    "    output = conn.update(input_signal)\n",
    "    \n",
    "    if i % 10 == 0:\n",
    "        print(f\"Step {i:2d}: Input={float(input_signal[0]):5.1f}, Output={float(output[0]):5.1f}\")\n",
    "\n",
    "print(\"\\n✅ DelayAccess enables modular delay handling in custom modules\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Part 4: `brainstate.nn.StateWithDelay`\n",
    "\n",
    "### 4.1 What is StateWithDelay?\n",
    "\n",
    "`StateWithDelay` is a **specialized delay** that automatically tracks a `State` variable in a module:\n",
    "\n",
    "- Automatically bound to a module's state (e.g., membrane potential `V`)\n",
    "- Updates history buffer after each simulation step\n",
    "- Commonly created via `prefetch_delay()` helper\n",
    "- Ideal for delayed feedback and recurrent connections\n",
    "\n",
    "### 4.2 Using StateWithDelay via `prefetch_delay()`\n",
    "\n",
    "The easiest way to use `StateWithDelay` is through the Dynamics `prefetch_delay()` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:53.495505Z",
     "start_time": "2025-10-11T10:28:50.079065Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:07.832604Z",
     "iopub.status.busy": "2026-05-30T16:46:07.832411Z",
     "iopub.status.idle": "2026-05-30T16:46:11.377015Z",
     "shell.execute_reply": "2026-05-30T16:46:11.376131Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ StateWithDelay automatically tracks module states for delayed feedback\n"
     ]
    }
   ],
   "source": [
    "class LIFWithDelayedFeedback(brainstate.nn.Dynamics):\n",
    "    \"\"\"LIF neuron with delayed self-feedback.\"\"\"\n",
    "    \n",
    "    def __init__(self, size, feedback_delay=5.0 * u.ms, feedback_strength=0.3):\n",
    "        super().__init__(in_size=size)\n",
    "        \n",
    "        # Neuron parameters\n",
    "        self.tau = 10.0 * u.ms\n",
    "        self.V_rest = -65.0 * u.mV\n",
    "        self.V_th = -50.0 * u.mV\n",
    "        self.V_reset = -65.0 * u.mV\n",
    "        self.R = 1.0 * u.ohm\n",
    "        self.feedback_strength = feedback_strength\n",
    "        \n",
    "        # States\n",
    "        self.V = brainstate.State(jnp.ones(size) * self.V_rest)\n",
    "        self.spike = brainstate.State(jnp.zeros(size, dtype=bool))\n",
    "        \n",
    "        # Create StateWithDelay for V using prefetch_delay()\n",
    "        # This automatically creates a StateWithDelay and registers it\n",
    "        self.V_delayed = self.prefetch_delay('V', feedback_delay)\n",
    "    \n",
    "    def update(self, I):\n",
    "        # Get delayed voltage for feedback\n",
    "        V_delayed = self.V_delayed()  # Call to retrieve delayed value\n",
    "        \n",
    "        # Add delayed feedback to input current\n",
    "        feedback_current = (V_delayed - self.V_rest) * self.feedback_strength / self.R\n",
    "        I_total = I + feedback_current\n",
    "        \n",
    "        # Update voltage (exponential Euler)\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "        V_inf = self.V_rest + I_total * self.R\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "        \n",
    "        # Spike detection and reset\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "        \n",
    "        return self.spike.value\n",
    "\n",
    "# Create neuron with delayed feedback\n",
    "neuron = LIFWithDelayedFeedback(size=1, feedback_delay=3.0 * u.ms, feedback_strength=0.4)\n",
    "brainstate.nn.init_all_states(neuron)\n",
    "\n",
    "# Simulate\n",
    "duration = 100.0 * u.ms\n",
    "num_steps = int(duration / brainstate.environ.get_dt())\n",
    "\n",
    "times = []\n",
    "voltages = []\n",
    "spikes = []\n",
    "\n",
    "for i in range(num_steps):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    brainstate.environ.set(i=i, t=t)\n",
    "    \n",
    "    # Constant input current\n",
    "    I_input = 1.5 * u.nA * jnp.ones(1)\n",
    "    \n",
    "    spike_output = neuron.update(I_input)\n",
    "    \n",
    "    times.append(float(t / u.ms))\n",
    "    voltages.append(float(neuron.V.value[0] / u.mV))\n",
    "    spikes.append(float(spike_output[0]))\n",
    "\n",
    "# Visualize\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 6), sharex=True)\n",
    "\n",
    "# Voltage trace\n",
    "ax1.plot(times, voltages, linewidth=1.5)\n",
    "ax1.axhline(y=-50.0, color='r', linestyle='--', alpha=0.5, label='Threshold')\n",
    "ax1.set_ylabel('Membrane Potential (mV)')\n",
    "ax1.set_title('LIF Neuron with Delayed Self-Feedback (3ms delay)')\n",
    "ax1.legend()\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Spike raster\n",
    "spike_times = [times[i] for i in range(len(spikes)) if spikes[i] > 0.5]\n",
    "ax2.eventplot([spike_times], lineoffsets=0.5, linelengths=0.8, colors='red')\n",
    "ax2.set_ylabel('Spikes')\n",
    "ax2.set_xlabel('Time (ms)')\n",
    "ax2.set_ylim([0, 1])\n",
    "ax2.set_yticks([])\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"✅ StateWithDelay automatically tracks module states for delayed feedback\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 Direct StateWithDelay Creation\n",
    "\n",
    "You can also create `StateWithDelay` explicitly (advanced usage):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:28:56.977529Z",
     "start_time": "2025-10-11T10:28:56.818741Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:11.379370Z",
     "iopub.status.busy": "2026-05-30T16:46:11.379194Z",
     "iopub.status.idle": "2026-05-30T16:46:11.601182Z",
     "shell.execute_reply": "2026-05-30T16:46:11.600442Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Manual StateWithDelay creation:\n",
      "\n",
      "Step   0: Current V=[0. 0. 0.], Delayed V=[0. 0. 0.]\n",
      "Step  20: Current V=[12.094189 24.188377 36.282566], Delayed V=[0. 0. 0.]\n",
      "Step  40: Current V=[31.133022 62.266045 93.39906 ], Delayed V=[0. 0. 0.]\n",
      "Step  60: Current V=[ 51.016167 102.03233  153.0485  ], Delayed V=[ 4.1381054  8.276211  12.414316 ]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step  80: Current V=[ 71.00195 142.0039  213.00584], Delayed V=[21.381517 42.763035 64.14455 ]\n",
      "\n",
      "✅ StateWithDelay can be created explicitly for fine-grained control\n"
     ]
    }
   ],
   "source": [
    "class SimpleNeuron(brainstate.nn.Dynamics):\n",
    "    \"\"\"Simple neuron for demonstration.\"\"\"\n",
    "    \n",
    "    def __init__(self, size):\n",
    "        super().__init__(in_size=size)\n",
    "        self.V = brainstate.State(jnp.zeros(size))\n",
    "    \n",
    "    def update(self, x):\n",
    "        self.V.value = self.V.value * 0.9 + x\n",
    "        return self.V.value\n",
    "\n",
    "# Create neuron\n",
    "neuron = SimpleNeuron(size=3)\n",
    "neuron.init_state()\n",
    "\n",
    "# Manually create StateWithDelay for neuron.V\n",
    "state_delay = brainstate.nn.StateWithDelay(\n",
    "    target=neuron,          # The module owning the state\n",
    "    item='V',               # Name of the state attribute\n",
    "    delay_method='rotation'\n",
    ")\n",
    "\n",
    "# Register a delay time\n",
    "state_delay.register_entry('V_5ms', 5.0 * u.ms)\n",
    "\n",
    "# Initialize\n",
    "state_delay.init_state()\n",
    "\n",
    "# Simulate\n",
    "print(\"Manual StateWithDelay creation:\\n\")\n",
    "for i in range(100):\n",
    "    brainstate.environ.set(i=i)\n",
    "    \n",
    "    # Update neuron\n",
    "    neuron.update(jnp.array([1.0, 2.0, 3.0]) * (i / 10.0))\n",
    "    \n",
    "    # Update delay buffer (must be done manually in this case)\n",
    "    state_delay.update()\n",
    "    \n",
    "    if i % 20 == 0:\n",
    "        current_V = neuron.V.value\n",
    "        delayed_V = state_delay.at('V_5ms')\n",
    "        print(f\"Step {i:3d}: Current V={current_V}, Delayed V={delayed_V}\")\n",
    "\n",
    "print(\"\\n✅ StateWithDelay can be created explicitly for fine-grained control\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Part 5: Practical Example - Synaptic Transmission with Delays\n",
    "\n",
    "Let's build a realistic synapse model with axonal and dendritic delays:\n",
    "\n",
    "### 5.1 Delayed Synaptic Connection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:31:02.524571Z",
     "start_time": "2025-10-11T10:30:56.766790Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:11.602855Z",
     "iopub.status.busy": "2026-05-30T16:46:11.602692Z",
     "iopub.status.idle": "2026-05-30T16:46:14.298576Z",
     "shell.execute_reply": "2026-05-30T16:46:14.297662Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "✅ Delayed synaptic transmission: presynaptic spikes appear at postsynaptic neuron after 5ms delay\n",
      "   First pre spike: ~13.8ms\n",
      "   First syn current rise: ~18.8ms (5ms delay)\n"
     ]
    }
   ],
   "source": [
    "class SimpleLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"Simple LIF neuron.\"\"\"\n",
    "    \n",
    "    def __init__(self, size, tau=10.0 * u.ms, V_rest=-65.0 * u.mV,\n",
    "                 V_th=-50.0 * u.mV, V_reset=-65.0 * u.mV, R=1.0 * u.ohm):\n",
    "        super().__init__(in_size=size)\n",
    "        \n",
    "        self.tau = tau\n",
    "        self.V_rest = V_rest\n",
    "        self.V_th = V_th\n",
    "        self.V_reset = V_reset\n",
    "        self.R = R\n",
    "        \n",
    "        self.V = brainstate.State(jnp.ones(size) * V_rest)\n",
    "        self.spike = brainstate.State(jnp.zeros(size, dtype=bool))\n",
    "    \n",
    "    def update(self, I):\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "        \n",
    "        V_inf = self.V_rest + I * self.R\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "        \n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "        \n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "class DelayedSynapse(brainstate.nn.Dynamics):\n",
    "    \"\"\"Synapse with conduction delay.\"\"\"\n",
    "    \n",
    "    def __init__(self, pre_size, post_size, weight_matrix, \n",
    "                 axonal_delay=2.0 * u.ms, tau_syn=5.0 * u.ms):\n",
    "        super().__init__(in_size=pre_size)\n",
    "        \n",
    "        self.weight = weight_matrix\n",
    "        self.tau_syn = tau_syn\n",
    "        \n",
    "        # Synaptic current state\n",
    "        self.I_syn = brainstate.State(jnp.zeros(post_size) * u.mA)\n",
    "        \n",
    "        # Create delay buffer for presynaptic spikes\n",
    "        self.spike_delay = brainstate.nn.Delay(\n",
    "            target_info=jnp.zeros(pre_size, dtype=bool),\n",
    "            time=axonal_delay * 2,\n",
    "            init=False\n",
    "        )\n",
    "        self.spike_delay.register_entry('axonal', axonal_delay)\n",
    "    \n",
    "    def update(self, pre_spike):\n",
    "        # Store presynaptic spikes\n",
    "        self.spike_delay.update(pre_spike)\n",
    "        \n",
    "        # Retrieve delayed spikes\n",
    "        delayed_spike = self.spike_delay.at('axonal')\n",
    "        \n",
    "        # Synaptic current injection\n",
    "        I_input = self.weight @ delayed_spike.astype(jnp.float32)\n",
    "        \n",
    "        # Synaptic current decay\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau_syn)\n",
    "        self.I_syn.value = self.I_syn.value * alpha + I_input\n",
    "        \n",
    "        return self.I_syn.value\n",
    "\n",
    "\n",
    "# Create network: pre -> synapse -> post\n",
    "pre_neuron = SimpleLIF(size=1)\n",
    "post_neuron = SimpleLIF(size=1)\n",
    "\n",
    "# Synaptic weight\n",
    "weight = jnp.array([[2.0]]) * u.mA  # Strong connection\n",
    "\n",
    "synapse = DelayedSynapse(\n",
    "    pre_size=1, \n",
    "    post_size=1, \n",
    "    weight_matrix=weight,\n",
    "    axonal_delay=5.0 * u.ms,  # 5ms axonal delay\n",
    "    tau_syn=3.0 * u.ms\n",
    ")\n",
    "\n",
    "# Initialize\n",
    "pre_neuron.init_state()\n",
    "post_neuron.init_state()\n",
    "synapse.spike_delay.init_state()\n",
    "\n",
    "# Simulate\n",
    "duration = 100.0 * u.ms\n",
    "num_steps = int(duration / brainstate.environ.get_dt())\n",
    "\n",
    "times = []\n",
    "pre_voltages = []\n",
    "post_voltages = []\n",
    "syn_currents = []\n",
    "pre_spikes = []\n",
    "post_spikes = []\n",
    "\n",
    "for i in range(num_steps):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    brainstate.environ.set(i=i, t=t)\n",
    "    \n",
    "    # Strong input to presynaptic neuron\n",
    "    I_pre = 20. * u.mA * jnp.ones(1)\n",
    "    \n",
    "    # Update presynaptic neuron\n",
    "    pre_spike = pre_neuron.update(I_pre)\n",
    "    \n",
    "    # Update synapse with delayed transmission\n",
    "    I_syn = synapse.update(pre_spike)\n",
    "    \n",
    "    # Update postsynaptic neuron\n",
    "    post_spike = post_neuron.update(I_syn)\n",
    "    \n",
    "    # Record\n",
    "    times.append(float(t / u.ms))\n",
    "    pre_voltages.append(float(pre_neuron.V.value[0] / u.mV))\n",
    "    post_voltages.append(float(post_neuron.V.value[0] / u.mV))\n",
    "    syn_currents.append(float(I_syn[0] / u.nA))\n",
    "    pre_spikes.append(float(pre_spike[0]))\n",
    "    post_spikes.append(float(post_spike[0]))\n",
    "\n",
    "# Visualize\n",
    "fig, axes = plt.subplots(4, 1, figsize=(14, 10), sharex=True)\n",
    "\n",
    "# Presynaptic voltage\n",
    "axes[0].plot(times, pre_voltages, 'b', linewidth=1.5)\n",
    "axes[0].axhline(y=-50.0, color='r', linestyle='--', alpha=0.5)\n",
    "axes[0].set_ylabel('Pre V (mV)')\n",
    "axes[0].set_title('Synaptic Transmission with 5ms Axonal Delay')\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# Presynaptic spikes\n",
    "pre_spike_times = [times[i] for i in range(len(pre_spikes)) if pre_spikes[i] > 0.5]\n",
    "axes[1].eventplot([pre_spike_times], lineoffsets=0.5, linelengths=0.8, colors='blue')\n",
    "axes[1].set_ylabel('Pre Spikes')\n",
    "axes[1].set_ylim([0, 1])\n",
    "axes[1].set_yticks([])\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "# Synaptic current\n",
    "axes[2].plot(times, syn_currents, 'g', linewidth=1.5)\n",
    "axes[2].set_ylabel('Syn Current (nA)')\n",
    "axes[2].grid(True, alpha=0.3)\n",
    "\n",
    "# Postsynaptic voltage\n",
    "axes[3].plot(times, post_voltages, 'r', linewidth=1.5)\n",
    "axes[3].axhline(y=-50.0, color='r', linestyle='--', alpha=0.5)\n",
    "axes[3].set_ylabel('Post V (mV)')\n",
    "axes[3].set_xlabel('Time (ms)')\n",
    "axes[3].grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n✅ Delayed synaptic transmission: presynaptic spikes appear at postsynaptic neuron after 5ms delay\")\n",
    "if len(pre_spike_times) > 0:\n",
    "    print(f\"   First pre spike: ~{pre_spike_times[0]:.1f}ms\")\n",
    "    print(f\"   First syn current rise: ~{pre_spike_times[0] + 5.0:.1f}ms (5ms delay)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Part 6: Advanced - Heterogeneous Delays\n",
    "\n",
    "### 6.1 Vector Delays\n",
    "\n",
    "BrainState supports **heterogeneous delays** where each element can have a different delay time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T10:31:08.054155Z",
     "start_time": "2025-10-11T10:31:07.686924Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:46:14.300379Z",
     "iopub.status.busy": "2026-05-30T16:46:14.300128Z",
     "iopub.status.idle": "2026-05-30T16:46:14.805010Z",
     "shell.execute_reply": "2026-05-30T16:46:14.804115Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Heterogeneous delays at step 199:\n",
      "  Delays: [2ms, 5ms, 8ms] = [20 50 80] steps\n",
      "  Retrieved values: [  179.  1490. 11900.]\n",
      "  Expected values:  [  179  1490 11900]\n",
      "  Match: True\n",
      "\n",
      "✅ Vector delays enable different delay times for each element\n"
     ]
    }
   ],
   "source": [
    "# Create delay buffer for 3 neurons\n",
    "delay_buffer = brainstate.nn.Delay(\n",
    "    target_info=jnp.zeros(3),\n",
    "    time=10.0 * u.ms,\n",
    ")\n",
    "\n",
    "# Register heterogeneous delays: different delay for each neuron\n",
    "# Delays: [2ms, 5ms, 8ms]\n",
    "delay_times = jnp.array([2.0, 5.0, 8.0]) * u.ms\n",
    "neuron_indices = jnp.array([0, 1, 2])  # Which neuron\n",
    "\n",
    "delay_buffer.register_entry('heterogeneous', delay_times, neuron_indices)\n",
    "delay_buffer.init_state()\n",
    "\n",
    "# Simulate\n",
    "for i in range(200):\n",
    "    brainstate.environ.set(i=i)\n",
    "    \n",
    "    # Update with [i, i*10, i*100]\n",
    "    values = jnp.array([float(i), float(i*10), float(i*100)])\n",
    "    delay_buffer.update(values)\n",
    "\n",
    "# Retrieve heterogeneous delays\n",
    "delayed_values = delay_buffer.at('heterogeneous')\n",
    "\n",
    "expected_delays_steps = jnp.array([20, 50, 80])  # in steps (0.1ms each)\n",
    "expected_values = jnp.array([\n",
    "    199 - 20,\n",
    "    (199 - 50) * 10,\n",
    "    (199 - 80) * 100\n",
    "])\n",
    "\n",
    "print(\"Heterogeneous delays at step 199:\")\n",
    "print(f\"  Delays: [2ms, 5ms, 8ms] = {expected_delays_steps} steps\")\n",
    "print(f\"  Retrieved values: {delayed_values}\")\n",
    "print(f\"  Expected values:  {expected_values}\")\n",
    "print(f\"  Match: {jnp.allclose(delayed_values, expected_values)}\")\n",
    "\n",
    "print(\"\\n✅ Vector delays enable different delay times for each element\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Summary\n",
    "\n",
    "### Key Concepts\n",
    "\n",
    "1. **`brainstate.nn.Delay`**: General-purpose delay buffer\n",
    "   - Stores rolling history of values\n",
    "   - Supports rotation (ring buffer) or concatenation methods\n",
    "   - Multiple named delay entries via `register_entry()`\n",
    "   - Step-based (`retrieve_at_step`) or time-based (`retrieve_at_time`) retrieval\n",
    "   - Linear or round interpolation for continuous-time queries\n",
    "\n",
    "2. **`brainstate.nn.DelayAccess`**: Named accessor for delay entries\n",
    "   - Created via `delay.access(entry, delay_time)`\n",
    "   - Encapsulates delay configuration\n",
    "   - Useful for modular design\n",
    "   - Call `.update()` to retrieve delayed value\n",
    "\n",
    "3. **`brainstate.nn.StateWithDelay`**: Automatic state tracking\n",
    "   - Bound to a module's `State` variable\n",
    "   - Created via `prefetch_delay(state_name, delay_time)`\n",
    "   - Automatically updates after each step\n",
    "   - Ideal for delayed feedback and recurrent connections\n",
    "   - Call as function `()` to retrieve delayed state\n",
    "\n",
    "### API Comparison Table\n",
    "\n",
    "| Feature | `Delay` | `DelayAccess` | `StateWithDelay` |\n",
    "|---------|---------|---------------|------------------|\n",
    "| **Use Case** | General data buffering | Named accessors | Module state tracking |\n",
    "| **Creation** | Manual instantiation | Via `delay.access()` | Via `prefetch_delay()` |\n",
    "| **Updates** | Manual `update(value)` | Inherits from Delay | Automatic after step |\n",
    "| **Retrieval** | `at(entry)` or `retrieve_at_*` | `.update()` | Call as function `()` |\n",
    "| **Multiple delays** | ✅ Multiple entries | ✅ One per accessor | ✅ Multiple registrations |\n",
    "| **Interpolation** | ✅ Linear or round | ✅ Via underlying Delay | ✅ Via underlying Delay |\n",
    "\n",
    "### Best Practices\n",
    "\n",
    "1. **Choose the right tool**:\n",
    "   - Use `Delay` for general data buffering (synaptic inputs, external signals)\n",
    "   - Use `DelayAccess` when passing delay accessors to other modules\n",
    "   - Use `StateWithDelay` (via `prefetch_delay()`) for module state feedback\n",
    "\n",
    "2. **Delay method selection**:\n",
    "   - Default to `rotation` (ring buffer) for efficiency\n",
    "   - Use `concat` only if you need sequential buffer structure\n",
    "\n",
    "3. **Interpolation**:\n",
    "   - Use `linear_interp` for smooth continuous-time delays\n",
    "   - Use `round` for discrete time steps\n",
    "\n",
    "4. **Buffer sizing**:\n",
    "   - Set `time` parameter larger than maximum expected delay\n",
    "   - Buffer size = `ceil(max_delay / dt) + 1` steps\n",
    "\n",
    "5. **Initialization**:\n",
    "   - Always call `.init_state()` before simulation\n",
    "   - Provide meaningful `init` values for t < 0 history\n",
    "\n",
    "### Common Patterns\n",
    "\n",
    "**Pattern 1: Delayed synaptic connection**\n",
    "```python\n",
    "# In synapse __init__:\n",
    "self.spike_delay = brainstate.nn.Delay(jnp.zeros(pre_size), time=delay_time)\n",
    "self.spike_delay.register_entry('syn', delay_time)\n",
    "\n",
    "# In synapse update:\n",
    "self.spike_delay.update(pre_spike)\n",
    "delayed_spike = self.spike_delay.at('syn')\n",
    "```\n",
    "\n",
    "**Pattern 2: Delayed feedback**\n",
    "```python\n",
    "# In neuron __init__:\n",
    "self.V_delayed = self.prefetch_delay('V', feedback_delay)\n",
    "\n",
    "# In neuron update:\n",
    "V_past = self.V_delayed()\n",
    "feedback = compute_feedback(V_past)\n",
    "```\n",
    "\n",
    "**Pattern 3: Multiple delay taps**\n",
    "```python\n",
    "delay = brainstate.nn.Delay(data, time=max_delay)\n",
    "delay.register_entry('short', 2.0 * u.ms)\n",
    "delay.register_entry('medium', 5.0 * u.ms)\n",
    "delay.register_entry('long', 10.0 * u.ms)\n",
    "```\n",
    "\n",
    "---\n",
    "\n",
    "## Exercise\n",
    "\n",
    "**Challenge**: Implement a network of 3 LIF neurons with the following connections:\n",
    "- Neuron 0 → Neuron 1 (2ms delay, weight=1.0)\n",
    "- Neuron 1 → Neuron 2 (5ms delay, weight=1.5)\n",
    "- Neuron 2 → Neuron 0 (3ms delay, weight=-0.5, inhibitory)\n",
    "\n",
    "Use `brainstate.nn.Delay` for the synaptic connections and simulate for 200ms.\n",
    "\n",
    "**Hints**:\n",
    "1. Create 3 `SimpleLIF` neurons\n",
    "2. Create 3 `DelayedSynapse` objects for the connections\n",
    "3. Drive Neuron 0 with external input\n",
    "4. Plot voltage traces of all 3 neurons\n",
    "5. Observe the sequential activation with delays\n",
    "\n",
    "---\n",
    "\n",
    "## What's Next?\n",
    "\n",
    "- **Tutorial 7: Collective Operations** - Learn about communication patterns in neural populations\n",
    "- **Advanced Delays** - Explore plastic delays and state-dependent delays\n",
    "- **Network Architecture** - Build large-scale networks with distributed delays\n",
    "\n",
    "---\n",
    "\n",
    "**Congratulations!** You now understand BrainState's powerful delay mechanisms for modeling realistic neural dynamics. 🎉"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Ecosystem-py",
   "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": "3.13.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
