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 "cells": [
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   "cell_type": "markdown",
   "id": "c1ac0e4b-d065-41af-97ec-b73bbc7dad7d",
   "metadata": {},
   "source": [
    "# Hyperparameters\n",
    "\n",
    "This example simulates the alignment of a KB mirror endstation (with four degrees of freedom)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a1798fa-b251-409e-9d2d-097240372b03",
   "metadata": {},
   "outputs": [],
   "source": [
    "from blop.utils import prepare_re_env\n",
    "\n",
    "%run -i $prepare_re_env.__file__ --db-type=temp\n",
    "bec.disable_plots()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ca926ab-5859-49f3-a96a-73c401cc18e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from blop.sim import Beamline\n",
    "\n",
    "beamline = Beamline(name=\"bl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28ee6cfc-428a-4472-b503-bb072f939866",
   "metadata": {},
   "outputs": [],
   "source": [
    "from blop import DOF, Objective, Agent\n",
    "from blop.digestion import beam_stats_digestion\n",
    "\n",
    "dofs = [\n",
    "    DOF(description=\"KBV downstream\", device=beamline.kbv_dsv, search_domain=(-5.0, 5.0)),\n",
    "    DOF(description=\"KBV upstream\", device=beamline.kbv_usv, search_domain=(-5.0, 5.0)),\n",
    "    DOF(description=\"KBH downstream\", device=beamline.kbh_dsh, search_domain=(-5.0, 5.0)),\n",
    "    DOF(description=\"KBH upstream\", device=beamline.kbh_ush, search_domain=(-5.0, 5.0)),\n",
    "]\n",
    "\n",
    "objectives = [\n",
    "    Objective(name=\"bl_det_sum\", target=\"max\", transform=\"log\", trust_domain=(200, np.inf)),\n",
    "    Objective(name=\"bl_det_wid_x\", target=\"min\", transform=\"log\", latent_groups=[(\"bl_kbh_dsh\", \"bl_kbh_ush\")]),\n",
    "    Objective(name=\"bl_det_wid_y\", target=\"min\", transform=\"log\", latent_groups=[(\"bl_kbv_dsv\", \"bl_kbv_usv\")]),\n",
    "]\n",
    "\n",
    "agent = Agent(\n",
    "    dofs=dofs,\n",
    "    objectives=objectives,\n",
    "    detectors=[beamline.det],\n",
    "    digestion=beam_stats_digestion,\n",
    "    digestion_kwargs={\"image_key\": \"bl_det_image\"},\n",
    "    verbose=True,\n",
    "    db=db,\n",
    "    tolerate_acquisition_errors=False,\n",
    "    enforce_all_objectives_valid=True,\n",
    "    train_every=3,\n",
    ")\n",
    "\n",
    "(uid,) = RE(agent.learn(\"qr\", n=32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "491636be-1e04-45a2-a622-dc21e192d208",
   "metadata": {},
   "outputs": [],
   "source": [
    "RE(agent.learn(\"qei\", n=4, iterations=4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6434fc9-682a-45fa-b100-465dfda3aff1",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.imshow(agent.best.bl_det_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef89c0cd-65be-4d1f-ab6d-c8a4ce251d7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "agent.plot_objectives(axes=(2, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb56db05-0fe5-46a5-8435-383f1e34f55d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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