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    "# How to create an LGST-only report\n",
    "This example shows how you can create a HTML report from just the results of running *linear GST* (LGST).  This can be useful when you want to get a rough estimate of your gates quickly, as LGST is takes substantially less data and computation time compared with long-sequence GST.  This example is modeled after Tutorial 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Only 92 sequences are required!\n"
     ]
    }
   ],
   "source": [
    "#Import the pygsti module (always do this) and the standard XYI model\n",
    "import pygsti\n",
    "from pygsti.modelpacks import smq1Q_XYI\n",
    "\n",
    "#Get experiment design (for now, just max_max_length=1 GST sequences)\n",
    "exp_design = smq1Q_XYI.get_gst_experiment_design(max_max_length=1)\n",
    "pygsti.io.write_empty_protocol_data(exp_design, \"example_files/lgst_only_example\", clobber_ok=True)\n",
    "print(\"Only %d sequences are required!\" % len(exp_design.all_circuits_needing_data))\n",
    "\n",
    "#Simulate taking the data (here you'd really fill in dataset.txt with actual data)\n",
    "mdl_datagen = smq1Q_XYI.target_model().depolarize(op_noise=0.1, spam_noise=0.001)\n",
    "pygsti.io.fill_in_empty_dataset_with_fake_data(mdl_datagen, \"example_files/lgst_only_example/data/dataset.txt\",\n",
    "                                               nSamples=1000, seed=2020)\n",
    "\n",
    "#load in the data\n",
    "data = pygsti.io.load_data_from_dir(\"example_files/lgst_only_example\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--- LGST ---\n",
      "  Singular values of I_tilde (truncating to first 4 of 6) = \n",
      "  4.243739384333438\n",
      "  1.174085597747583\n",
      "  0.9927915010167846\n",
      "  0.9182042113995429\n",
      "  0.0731735967798496\n",
      "  0.032353259963406746\n",
      "  \n",
      "  Singular values of target I_tilde (truncating to first 4 of 6) = \n",
      "  4.242640687119284\n",
      "  1.4142135623730956\n",
      "  1.4142135623730954\n",
      "  1.4142135623730951\n",
      "  2.5394445830714747e-16\n",
      "  1.118988490269554e-16\n",
      "  \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "WARNING: Treating result as *converged* after maximum iterations (100) were exceeded.\n"
     ]
    }
   ],
   "source": [
    "#Run LGST and create a report\n",
    "# You can also eliminate gauge optimization step by setting gaugeOptParams=False\n",
    "results = pygsti.protocols.LGST().run(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running idle tomography\n",
      "Computing switchable properties\n",
      "Found standard clifford compilation from smq1Q_XYI\n"
     ]
    }
   ],
   "source": [
    "pygsti.report.construct_standard_report(\n",
    "    results, title=\"LGST-only Example Report\", verbosity=2\n",
    ").write_html('example_files/LGSTonlyReport', verbosity=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Click to open the file [example_files/LGSTonlyReport/main.html](example_files/LGSTonlyReport/main.html) in your browser to view the report."
   ]
  }
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