{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Readout IQ blob classification\n",
    "\n",
    "Feed a dense cloud of single-shot IQ values to the VLM. The model recognizes\n",
    "under-separated blobs, leakage to `|2⟩`, and skewed populations — all things\n",
    "that degrade readout fidelity. We also sketch a cheap linear threshold for\n",
    "reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "rng = np.random.default_rng(7)\n",
    "n = 4000\n",
    "ground = rng.normal(loc=(-0.9, 0.1), scale=(0.35, 0.35), size=(n//2, 2))\n",
    "excited = rng.normal(loc=(+0.8, 0.4), scale=(0.40, 0.40), size=(n//2, 2))\n",
    "iq = np.vstack([ground, excited])\n",
    "np.save('readout_iq.npy', iq)\n",
    "iq.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qcal.data import from_npy\n",
    "\n",
    "payload = from_npy('readout_iq.npy', experiment_type='readout_iq')\n",
    "payload.image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qcal.analyzer import analyze_payload\n",
    "\n",
    "result = analyze_payload(payload, backend='auto')\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once the VLM returns a `recommended_parameters.readout_threshold`, wire it into\n",
    "your control stack's classifier. Below: a crude linear threshold along the I-axis\n",
    "for reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "thresh = result.parsed.get('recommended_parameters', {}).get('readout_threshold', 0.0)\n",
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "ax.scatter(iq[:, 0], iq[:, 1], s=3, alpha=0.4)\n",
    "ax.axvline(thresh, color='r', linewidth=1.0, label=f'threshold = {thresh}')\n",
    "ax.set_xlabel('I'); ax.set_ylabel('Q'); ax.legend(); ax.grid(alpha=0.3)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
  "language_info": {"name": "python", "version": "3.11"}
 },
 "nbformat": 4,
 "nbformat_minor": 5
}