htc/data_exploration/PrecisionAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8e4f7e97-6727-4e75-bef0-6d4c4c3347f4",
   "metadata": {},
   "source": [
    "# Precision Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8585735d-7be1-47e3-9acf-43e3ddf90097",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "import torch\n",
    "\n",
    "from htc.models.image.DatasetImage import DatasetImage\n",
    "from htc.settings import settings\n",
    "from htc.tivita.DataPath import DataPath\n",
    "from htc.utils.Config import Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8850bb0d-9fb2-49e2-a4b5-1ee145496fa8",
   "metadata": {},
   "outputs": [],
   "source": [
    "paths = list(DataPath.iterate(settings.data_dirs.semantic))[:10]\n",
    "dataset_16 = DatasetImage(\n",
    "    paths, train=False, config=Config({\"input/preprocessing\": \"L1\", \"trainer_kwargs/precision\": \"16-mixed\"})\n",
    ")\n",
    "dataset_32 = DatasetImage(paths, train=False, config=Config({\"input/normalization\": \"L1\"}))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddd7fb66-1d9b-42b7-b8f8-373adc2fa927",
   "metadata": {},
   "source": [
    "## Load as fp16 but cast to fp32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "beb9997b-b7c4-4ebf-94bf-dea32960ba01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average absolute difference between reflectance values: 1.6563968756599934e-06\n",
      "Average absolute difference of spectra sums: 0.00016563966346438974\n",
      "Average mean spectra value differences: 3.4010736271739006e-07\n"
     ]
    }
   ],
   "source": [
    "abs_diffs = []\n",
    "spectra_diffs = []\n",
    "mean_spectra_diffs = []\n",
    "for sample_16, sample_32 in zip(dataset_16, dataset_32):\n",
    "    diffs = torch.abs(sample_16[\"features\"].float() - sample_32[\"features\"])\n",
    "    abs_diffs.append(diffs.mean())\n",
    "\n",
    "    spectra_diffs.append(diffs.sum(dim=-1).mean())\n",
    "\n",
    "    sum_16 = sample_16[\"features\"].float().mean(dim=(0, 1))\n",
    "    sum_32 = sample_32[\"features\"].mean(dim=(0, 1))\n",
    "    mean_spectra_diffs.append(torch.abs(sum_16 - sum_32).sum())\n",
    "\n",
    "print(f\"Average absolute difference between reflectance values: {torch.mean(torch.stack(abs_diffs))}\")\n",
    "print(f\"Average absolute difference of spectra sums: {torch.mean(torch.stack(spectra_diffs))}\")\n",
    "print(f\"Average mean spectra value differences: {torch.mean(torch.stack(mean_spectra_diffs))}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cc0ffba-d484-4604-8872-94bf6247e73e",
   "metadata": {},
   "source": [
    "## Load as fp16, use as fp16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e81ffcc1-da8f-4096-8ac3-f880ab18ee40",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average absolute difference between reflectance values: 1.6563968756599934e-06\n",
      "Average absolute difference of spectra sums: 0.00016563966346438974\n",
      "Average mean spectra value differences: 0.9988231658935547\n"
     ]
    }
   ],
   "source": [
    "with torch.autocast(device_type=\"cpu\"):\n",
    "    abs_diffs = []\n",
    "    spectra_diffs = []\n",
    "    mean_spectra_diffs = []\n",
    "    for sample_16, sample_32 in zip(dataset_16, dataset_32):\n",
    "        diffs = torch.abs(sample_16[\"features\"] - sample_32[\"features\"])\n",
    "        abs_diffs.append(diffs.mean())\n",
    "\n",
    "        spectra_diffs.append(diffs.sum(dim=-1).mean())\n",
    "\n",
    "        sum_16 = sample_16[\"features\"].mean(dim=(0, 1))\n",
    "        sum_32 = sample_32[\"features\"].mean(dim=(0, 1))\n",
    "        mean_spectra_diffs.append(torch.abs(sum_16 - sum_32).sum())\n",
    "\n",
    "    print(f\"Average absolute difference between reflectance values: {torch.mean(torch.stack(abs_diffs))}\")\n",
    "    print(f\"Average absolute difference of spectra sums: {torch.mean(torch.stack(spectra_diffs))}\")\n",
    "    print(f\"Average mean spectra value differences: {torch.mean(torch.stack(mean_spectra_diffs))}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb30466f-07f0-438e-9f17-19f592195917",
   "metadata": {},
   "source": [
    "## Visual comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e81e38cf-1c38-47a4-b703-4233aa45289f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.18.2.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "name": "fp16",
         "type": "scatter",
         "y": [
          0.0041148956,
          0.003618038,
          0.0037185887,
          0.0034904361,
          0.0032028132,
          0.0030216211,
          0.0028724922,
          0.0029119495,
          0.0029562814,
          0.0029773694,
          0.0030081521,
          0.003063786,
          0.0030948666,
          0.0030373167,
          0.0029613606,
          0.0029350964,
          0.0030556628,
          0.0034611893,
          0.0040175766,
          0.0046815667,
          0.00532212,
          0.0059367474,
          0.006451241,
          0.006874791,
          0.007191477,
          0.0075075817,
          0.007764147,
          0.007947509,
          0.00813567,
          0.008342323,
          0.008507725,
          0.008660538,
          0.008813748,
          0.00898953,
          0.009222074,
          0.009460616,
          0.009737253,
          0.010008195,
          0.010284158,
          0.010533151,
          0.010722318,
          0.010871179,
          0.010997125,
          0.011086261,
          0.011147358,
          0.011191836,
          0.011174886,
          0.011111685,
          0.01103304,
          0.010865345,
          0.010719061,
          0.010607166,
          0.010570151,
          0.010636296,
          0.010769088,
          0.010875439,
          0.0109826885,
          0.0110802185,
          0.01114651,
          0.011209655,
          0.011271042,
          0.011326942,
          0.011374962,
          0.011429587,
          0.0114706345,
          0.011521678,
          0.011577403,
          0.011675176,
          0.011818049,
          0.011962968,
          0.012108961,
          0.012262591,
          0.012446558,
          0.012614421,
          0.012786757,
          0.012971903,
          0.013138885,
          0.013323858,
          0.0135204075,
          0.013756765,
          0.013975388,
          0.014179889,
          0.014391564,
          0.014588257,
          0.014761117,
          0.014905758,
          0.015031075,
          0.0152442325,
          0.015415975,
          0.015501267,
          0.015582056,
          0.015696963,
          0.015524241,
          0.01544014,
          0.015589858,
          0.015640706,
          0.01560781,
          0.015555533,
          0.015684588,
          0.015807036
         ]
        },
        {
         "name": "fp32",
         "type": "scatter",
         "y": [
          0.004114895,
          0.0036180352,
          0.0037185892,
          0.0034904361,
          0.0032028123,
          0.0030216186,
          0.0028724938,
          0.0029119493,
          0.0029562798,
          0.0029773668,
          0.0030081535,
          0.0030637868,
          0.0030948666,
          0.0030373149,
          0.0029613606,
          0.0029350996,
          0.003055664,
          0.0034611877,
          0.004017574,
          0.004681564,
          0.0053221188,
          0.0059367456,
          0.0064512393,
          0.006874786,
          0.007191479,
          0.0075075817,
          0.007764145,
          0.007947513,
          0.00813567,
          0.008342321,
          0.00850773,
          0.008660535,
          0.008813746,
          0.00898953,
          0.009222073,
          0.009460614,
          0.009737246,
          0.010008197,
          0.010284157,
          0.010533151,
          0.010722315,
          0.010871174,
          0.010997131,
          0.011086265,
          0.011147366,
          0.011191844,
          0.011174882,
          0.011111691,
          0.011033038,
          0.010865345,
          0.010719073,
          0.010607161,
          0.010570149,
          0.0106362915,
          0.010769089,
          0.010875434,
          0.010982695,
          0.011080225,
          0.01114651,
          0.011209654,
          0.011271041,
          0.011326943,
          0.011374963,
          0.011429587,
          0.011470645,
          0.011521673,
          0.0115774,
          0.011675179,
          0.011818056,
          0.011962969,
          0.012108965,
          0.012262586,
          0.012446555,
          0.01261442,
          0.01278676,
          0.0129719125,
          0.013138885,
          0.013323857,
          0.013520411,
          0.01375676,
          0.013975385,
          0.014179891,
          0.014391566,
          0.01458827,
          0.014761115,
          0.014905758,
          0.015031079,
          0.015244228,
          0.015415972,
          0.015501288,
          0.0155820595,
          0.015696965,
          0.015524248,
          0.015440145,
          0.015589844,
          0.015640697,
          0.0156077985,
          0.015555525,
          0.015684586,
          0.01580704
         ]
        }
       ],
       "layout": {
        "autosize": true,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "fillpattern": {
             "fillmode": "overlay",
             "size": 10,
             "solidity": 0.2
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Image median spectrum",
         "x": 0.5
        },
        "xaxis": {
         "autorange": true,
         "range": [
          0,
          99
         ]
        },
        "yaxis": {
         "autorange": true,
         "range": [
          0.002153906211111111,
          0.01652562598888889
         ],
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "text/html": [
       "<div>                            <div id=\"cd072cd8-be6f-4f62-ac4c-09c28206e7e3\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"cd072cd8-be6f-4f62-ac4c-09c28206e7e3\")) {                    Plotly.newPlot(                        \"cd072cd8-be6f-4f62-ac4c-09c28206e7e3\",                        [{\"name\":\"fp16\",\"y\":[0.0041148956,0.003618038,0.0037185887,0.0034904361,0.0032028132,0.0030216211,0.0028724922,0.0029119495,0.0029562814,0.0029773694,0.0030081521,0.003063786,0.0030948666,0.0030373167,0.0029613606,0.0029350964,0.0030556628,0.0034611893,0.0040175766,0.0046815667,0.00532212,0.0059367474,0.006451241,0.006874791,0.007191477,0.0075075817,0.007764147,0.007947509,0.00813567,0.008342323,0.008507725,0.008660538,0.008813748,0.00898953,0.009222074,0.009460616,0.009737253,0.010008195,0.010284158,0.010533151,0.010722318,0.010871179,0.010997125,0.011086261,0.011147358,0.011191836,0.011174886,0.011111685,0.01103304,0.010865345,0.010719061,0.010607166,0.010570151,0.010636296,0.010769088,0.010875439,0.0109826885,0.0110802185,0.01114651,0.011209655,0.011271042,0.011326942,0.011374962,0.011429587,0.0114706345,0.011521678,0.011577403,0.011675176,0.011818049,0.011962968,0.012108961,0.012262591,0.012446558,0.012614421,0.012786757,0.012971903,0.013138885,0.013323858,0.0135204075,0.013756765,0.013975388,0.014179889,0.014391564,0.014588257,0.014761117,0.014905758,0.015031075,0.0152442325,0.015415975,0.015501267,0.015582056,0.015696963,0.015524241,0.01544014,0.015589858,0.015640706,0.01560781,0.015555533,0.015684588,0.015807036],\"type\":\"scatter\"},{\"name\":\"fp32\",\"y\":[0.004114895,0.0036180352,0.0037185892,0.0034904361,0.0032028123,0.0030216186,0.0028724938,0.0029119493,0.0029562798,0.0029773668,0.0030081535,0.0030637868,0.0030948666,0.0030373149,0.0029613606,0.0029350996,0.003055664,0.0034611877,0.004017574,0.004681564,0.0053221188,0.0059367456,0.0064512393,0.006874786,0.007191479,0.0075075817,0.007764145,0.007947513,0.00813567,0.008342321,0.00850773,0.008660535,0.008813746,0.00898953,0.009222073,0.009460614,0.009737246,0.010008197,0.010284157,0.010533151,0.010722315,0.010871174,0.010997131,0.011086265,0.011147366,0.011191844,0.011174882,0.011111691,0.011033038,0.010865345,0.010719073,0.010607161,0.010570149,0.0106362915,0.010769089,0.010875434,0.010982695,0.011080225,0.01114651,0.011209654,0.011271041,0.011326943,0.011374963,0.011429587,0.011470645,0.011521673,0.0115774,0.011675179,0.011818056,0.011962969,0.012108965,0.012262586,0.012446555,0.01261442,0.01278676,0.0129719125,0.013138885,0.013323857,0.013520411,0.01375676,0.013975385,0.014179891,0.014391566,0.01458827,0.014761115,0.014905758,0.015031079,0.015244228,0.015415972,0.015501288,0.0155820595,0.015696965,0.015524248,0.015440145,0.015589844,0.015640697,0.0156077985,0.015555525,0.015684586,0.01580704],\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"title\":{\"x\":0.5,\"text\":\"Image median spectrum\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('cd072cd8-be6f-4f62-ac4c-09c28206e7e3');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_16 = dataset_16[2]\n",
    "sample_32 = dataset_32[2]\n",
    "s_16 = sample_16[\"features\"].float().reshape(-1, 100).mean(dim=0)\n",
    "s_32 = sample_32[\"features\"].reshape(-1, 100).mean(dim=0)\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(y=s_16, name=\"fp16\"))\n",
    "fig.add_trace(go.Scatter(y=s_32, name=\"fp32\"))\n",
    "fig.update_layout(title_x=0.5, title_text=\"Image median spectrum\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b1b1ec6e-283e-4da6-9166-475a17aa741f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "name": "fp16",
         "type": "scatter",
         "y": [
          0.0053977966,
          0.0065956116,
          0.0058403015,
          0.0044021606,
          0.005455017,
          0.004825592,
          0.005367279,
          0.005619049,
          0.005012512,
          0.005302429,
          0.0054473877,
          0.0056915283,
          0.005554199,
          0.005493164,
          0.00554657,
          0.005760193,
          0.0058631897,
          0.0063972473,
          0.0071258545,
          0.007980347,
          0.008682251,
          0.00932312,
          0.009880066,
          0.010070801,
          0.010513306,
          0.010810852,
          0.01096344,
          0.010887146,
          0.010902405,
          0.011306763,
          0.011512756,
          0.011192322,
          0.011077881,
          0.01134491,
          0.0113220215,
          0.011802673,
          0.011932373,
          0.012039185,
          0.012451172,
          0.012451172,
          0.012466431,
          0.012374878,
          0.012489319,
          0.012573242,
          0.012588501,
          0.012207031,
          0.012413025,
          0.012397766,
          0.012252808,
          0.012062073,
          0.011886597,
          0.011627197,
          0.011749268,
          0.011978149,
          0.011947632,
          0.012039185,
          0.011894226,
          0.012077332,
          0.012046814,
          0.012138367,
          0.012161255,
          0.012023926,
          0.012008667,
          0.012214661,
          0.01197052,
          0.012184143,
          0.0118637085,
          0.0116119385,
          0.0115356445,
          0.01158905,
          0.011383057,
          0.011512756,
          0.011314392,
          0.011604309,
          0.011367798,
          0.011604309,
          0.011062622,
          0.010955811,
          0.011306763,
          0.010734558,
          0.010848999,
          0.010971069,
          0.011039734,
          0.010398865,
          0.010437012,
          0.010414124,
          0.010505676,
          0.010261536,
          0.010017395,
          0.0090789795,
          0.0096206665,
          0.009429932,
          0.009216309,
          0.008888245,
          0.007972717,
          0.008583069,
          0.008148193,
          0.007144928,
          0.008262634,
          0.008369446
         ]
        },
        {
         "name": "fp32",
         "type": "scatter",
         "y": [
          0.00539673,
          0.0065954677,
          0.0058398633,
          0.004402478,
          0.005453697,
          0.004824771,
          0.005367884,
          0.005618643,
          0.005011311,
          0.005301554,
          0.0054489584,
          0.0056912815,
          0.0055557373,
          0.0054936046,
          0.005547623,
          0.005758984,
          0.0058636004,
          0.00639589,
          0.0071263164,
          0.007982104,
          0.00868441,
          0.009322106,
          0.009881936,
          0.010067347,
          0.010514475,
          0.010808443,
          0.010966727,
          0.0108906375,
          0.010904984,
          0.01130352,
          0.011509086,
          0.011190399,
          0.01107883,
          0.01134484,
          0.011322909,
          0.011805343,
          0.011935204,
          0.012038812,
          0.012452648,
          0.012454443,
          0.012466888,
          0.012377435,
          0.012492192,
          0.012573446,
          0.012589676,
          0.01220977,
          0.012416058,
          0.01239625,
          0.012256508,
          0.012064522,
          0.011889923,
          0.011625433,
          0.011746742,
          0.011976165,
          0.011945025,
          0.012041974,
          0.011897032,
          0.012079354,
          0.012043721,
          0.012136724,
          0.012160989,
          0.012022857,
          0.01200491,
          0.012211193,
          0.0119712595,
          0.01218372,
          0.011866957,
          0.01161462,
          0.011533251,
          0.0115920305,
          0.011382677,
          0.011513124,
          0.01131208,
          0.011606392,
          0.011370186,
          0.0116045885,
          0.011060543,
          0.010952283,
          0.0113039,
          0.010736198,
          0.010849821,
          0.010972585,
          0.011038912,
          0.010400158,
          0.0104368245,
          0.010414942,
          0.010507317,
          0.010263165,
          0.010014301,
          0.009080624,
          0.009619826,
          0.009428479,
          0.009219758,
          0.0088844905,
          0.007975631,
          0.008581391,
          0.008151512,
          0.007145152,
          0.008259836,
          0.008373054
         ]
        }
       ],
       "layout": {
        "autosize": true,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "fillpattern": {
             "fillmode": "overlay",
             "size": 10,
             "solidity": 0.2
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Example spectrum",
         "x": 0.5
        },
        "xaxis": {
         "autorange": true,
         "range": [
          0,
          99
         ]
        },
        "yaxis": {
         "autorange": true,
         "range": [
          0.003947298633333333,
          0.013044537966666665
         ],
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "text/html": [
       "<div>                            <div id=\"5594aa6b-342f-4d0a-ba5e-4842fab428f7\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"5594aa6b-342f-4d0a-ba5e-4842fab428f7\")) {                    Plotly.newPlot(                        \"5594aa6b-342f-4d0a-ba5e-4842fab428f7\",                        [{\"name\":\"fp16\",\"y\":[0.0053977966,0.0065956116,0.0058403015,0.0044021606,0.005455017,0.004825592,0.005367279,0.005619049,0.005012512,0.005302429,0.0054473877,0.0056915283,0.005554199,0.005493164,0.00554657,0.005760193,0.0058631897,0.0063972473,0.0071258545,0.007980347,0.008682251,0.00932312,0.009880066,0.010070801,0.010513306,0.010810852,0.01096344,0.010887146,0.010902405,0.011306763,0.011512756,0.011192322,0.011077881,0.01134491,0.0113220215,0.011802673,0.011932373,0.012039185,0.012451172,0.012451172,0.012466431,0.012374878,0.012489319,0.012573242,0.012588501,0.012207031,0.012413025,0.012397766,0.012252808,0.012062073,0.011886597,0.011627197,0.011749268,0.011978149,0.011947632,0.012039185,0.011894226,0.012077332,0.012046814,0.012138367,0.012161255,0.012023926,0.012008667,0.012214661,0.01197052,0.012184143,0.0118637085,0.0116119385,0.0115356445,0.01158905,0.011383057,0.011512756,0.011314392,0.011604309,0.011367798,0.011604309,0.011062622,0.010955811,0.011306763,0.010734558,0.010848999,0.010971069,0.011039734,0.010398865,0.010437012,0.010414124,0.010505676,0.010261536,0.010017395,0.0090789795,0.0096206665,0.009429932,0.009216309,0.008888245,0.007972717,0.008583069,0.008148193,0.007144928,0.008262634,0.008369446],\"type\":\"scatter\"},{\"name\":\"fp32\",\"y\":[0.00539673,0.0065954677,0.0058398633,0.004402478,0.005453697,0.004824771,0.005367884,0.005618643,0.005011311,0.005301554,0.0054489584,0.0056912815,0.0055557373,0.0054936046,0.005547623,0.005758984,0.0058636004,0.00639589,0.0071263164,0.007982104,0.00868441,0.009322106,0.009881936,0.010067347,0.010514475,0.010808443,0.010966727,0.0108906375,0.010904984,0.01130352,0.011509086,0.011190399,0.01107883,0.01134484,0.011322909,0.011805343,0.011935204,0.012038812,0.012452648,0.012454443,0.012466888,0.012377435,0.012492192,0.012573446,0.012589676,0.01220977,0.012416058,0.01239625,0.012256508,0.012064522,0.011889923,0.011625433,0.011746742,0.011976165,0.011945025,0.012041974,0.011897032,0.012079354,0.012043721,0.012136724,0.012160989,0.012022857,0.01200491,0.012211193,0.0119712595,0.01218372,0.011866957,0.01161462,0.011533251,0.0115920305,0.011382677,0.011513124,0.01131208,0.011606392,0.011370186,0.0116045885,0.011060543,0.010952283,0.0113039,0.010736198,0.010849821,0.010972585,0.011038912,0.010400158,0.0104368245,0.010414942,0.010507317,0.010263165,0.010014301,0.009080624,0.009619826,0.009428479,0.009219758,0.0088844905,0.007975631,0.008581391,0.008151512,0.007145152,0.008259836,0.008373054],\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"title\":{\"x\":0.5,\"text\":\"Example spectrum\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('5594aa6b-342f-4d0a-ba5e-4842fab428f7');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_16 = dataset_16[2]\n",
    "sample_32 = dataset_32[2]\n",
    "s_16 = sample_16[\"features\"][100, 200, :]\n",
    "s_32 = sample_32[\"features\"][100, 200, :]\n",
    "fig = go.Figure()\n",
    "# We need to cast float16 to float32 so that plotly can understand the dtype\n",
    "fig.add_trace(go.Scatter(y=s_16.float(), name=\"fp16\"))\n",
    "fig.add_trace(go.Scatter(y=s_32, name=\"fp32\"))\n",
    "fig.update_layout(title_x=0.5, title_text=\"Example spectrum\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}