Training Results.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Training Log</h1>\n",
    "The training_log.csv is be appended after each generation to show evolution while training is in progress.\n",
    "<br>Below will show the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from IPython.display import clear_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "variable=Top Fitness<br>Generation=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "Top Fitness",
         "line": {
          "color": "#636efa",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Top Fitness",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          1,
          2,
          3,
          4,
          5,
          6,
          7,
          8,
          9,
          10,
          11,
          12,
          13,
          14,
          15,
          16,
          17,
          18,
          19,
          20,
          21,
          22,
          23,
          24,
          25,
          26,
          27,
          28,
          29,
          30,
          31,
          32,
          33,
          34,
          35,
          36,
          37,
          38,
          39,
          40,
          41,
          42,
          43,
          44,
          45,
          46,
          47,
          48,
          49,
          50,
          51,
          52,
          53,
          54,
          55,
          56,
          57,
          58,
          59,
          60,
          61,
          62,
          63,
          64,
          65,
          66,
          67,
          68,
          69,
          70,
          71,
          72,
          73,
          74
         ],
         "xaxis": "x",
         "y": [
          14,
          22,
          24,
          24,
          23,
          22,
          18,
          18,
          16,
          18,
          16,
          22,
          16,
          20,
          19,
          21,
          24,
          28,
          23,
          26,
          26,
          18,
          26,
          26,
          26,
          31,
          30,
          29,
          26,
          28,
          26,
          28,
          28,
          26,
          28,
          28,
          28,
          29,
          33,
          31,
          27,
          31,
          34,
          34,
          80,
          143,
          83,
          201,
          142,
          83,
          503,
          82,
          82,
          97,
          143,
          194,
          289,
          213,
          142,
          481,
          132,
          142,
          290,
          615,
          479,
          392,
          501,
          502,
          897,
          502,
          898,
          1500,
          1500,
          1500
         ],
         "yaxis": "y"
        },
        {
         "hovertemplate": "variable=Mean Fitness<br>Generation=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "Mean Fitness",
         "line": {
          "color": "#EF553B",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Mean Fitness",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          1,
          2,
          3,
          4,
          5,
          6,
          7,
          8,
          9,
          10,
          11,
          12,
          13,
          14,
          15,
          16,
          17,
          18,
          19,
          20,
          21,
          22,
          23,
          24,
          25,
          26,
          27,
          28,
          29,
          30,
          31,
          32,
          33,
          34,
          35,
          36,
          37,
          38,
          39,
          40,
          41,
          42,
          43,
          44,
          45,
          46,
          47,
          48,
          49,
          50,
          51,
          52,
          53,
          54,
          55,
          56,
          57,
          58,
          59,
          60,
          61,
          62,
          63,
          64,
          65,
          66,
          67,
          68,
          69,
          70,
          71,
          72,
          73,
          74
         ],
         "xaxis": "x",
         "y": [
          1.09765625,
          1.3125,
          1.6484375,
          1.6640625,
          1.99609375,
          1.84375,
          1.95703125,
          1.77734375,
          1.5859375,
          1.90625,
          2.078125,
          1.9609375,
          1.92578125,
          1.95703125,
          1.97265625,
          2.3671875,
          2.06640625,
          2.703125,
          2.703125,
          2.7265625,
          2.48828125,
          2.45703125,
          2.859375,
          2.765625,
          3.03515625,
          3.3046875,
          3.30859375,
          2.6640625,
          2.8359375,
          3.05859375,
          3.34375,
          2.9453125,
          3.140625,
          3.3984375,
          3.171875,
          3.63671875,
          3.14453125,
          4.58203125,
          3.25390625,
          3.875,
          3.50390625,
          3.62109375,
          2.60546875,
          4.09375,
          4.6640625,
          6,
          7.92578125,
          7.9609375,
          10.8984375,
          9.80078125,
          12.03125,
          11.0234375,
          9.3984375,
          10.9765625,
          8.5625,
          9.79296875,
          13.69921875,
          16.6796875,
          11.98046875,
          15.8515625,
          13.12109375,
          11.484375,
          14.1875,
          18.33203125,
          23.6171875,
          23.45703125,
          21.3125,
          19.9453125,
          37.48046875,
          26.19140625,
          21,
          126.0234375,
          76.3125,
          82.44921875
         ],
         "yaxis": "y"
        },
        {
         "hovertemplate": "variable=Run Time (s)<br>Generation=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "Run Time (s)",
         "line": {
          "color": "#00cc96",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Run Time (s)",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          1,
          2,
          3,
          4,
          5,
          6,
          7,
          8,
          9,
          10,
          11,
          12,
          13,
          14,
          15,
          16,
          17,
          18,
          19,
          20,
          21,
          22,
          23,
          24,
          25,
          26,
          27,
          28,
          29,
          30,
          31,
          32,
          33,
          34,
          35,
          36,
          37,
          38,
          39,
          40,
          41,
          42,
          43,
          44,
          45,
          46,
          47,
          48,
          49,
          50,
          51,
          52,
          53,
          54,
          55,
          56,
          57,
          58,
          59,
          60,
          61,
          62,
          63,
          64,
          65,
          66,
          67,
          68,
          69,
          70,
          71,
          72,
          73,
          74
         ],
         "xaxis": "x",
         "y": [
          11.42256999,
          12.75161791,
          13.70251894,
          13.68866825,
          13.63654947,
          13.57151628,
          15.63606024,
          13.36351919,
          14.81751657,
          14.87651873,
          13.95608664,
          15.45400095,
          14.25603628,
          14.94606686,
          16.4975462,
          15.18551874,
          14.78999829,
          18.74463916,
          16.15903354,
          16.46903539,
          15.81304598,
          17.37425709,
          16.30562401,
          15.98851562,
          18.16561151,
          21.76152515,
          22.07800913,
          17.39635634,
          18.28551531,
          19.77678943,
          19.75081682,
          17.8400619,
          18.2965486,
          18.68503404,
          18.04927468,
          21.46303153,
          20.76198673,
          21.23952484,
          20.67363262,
          22.04603601,
          17.92903423,
          19.50097299,
          17.28703856,
          24.51503372,
          26.76234984,
          31.00803161,
          48.30430365,
          44.53907013,
          54.46888971,
          44.99619532,
          60.37901545,
          59.74814820000001,
          50.87220979,
          61.15191364,
          48.03426361,
          56.52764988,
          82.80792904,
          92.08536482,
          66.69095993,
          85.7017262,
          74.88170576,
          63.35742307,
          75.56854463,
          112.9893639,
          116.9930608,
          134.46534630000002,
          117.7960577,
          90.50857806,
          171.7755411,
          123.46794990000001,
          110.227772,
          224.0609307,
          210.71856499999998,
          250.63889980000002
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "legend": {
         "title": {
          "text": "variable"
         },
         "tracegroupgap": 0
        },
        "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": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "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": "Training Log"
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "Generation"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "value"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_csv('./logs/training_log.csv')\n",
    "fig = px.line(df, y=['Top Fitness', 'Mean Fitness', 'Run Time (s)'], x='Generation', title='Training Log')\n",
    "clear_output()\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Comments</h1>\n",
    "<br>Generation 45, the agent was able to clear the first screen.  This marks a explosion in evolution rate\n",
    "<br>Agent reached a perfect game by generation 72"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Seaborn Output for github rendering</h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_csv('./logs/training_log.csv')\n",
    "sns.set_style(\"whitegrid\")\n",
    "fig = sns.lineplot(data=df)\n",
    "plt.xlabel(\"Generation\")\n",
    "plt.title(\"Training Log\")\n",
    "plt.show(fig)"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "b3ba2566441a7c06988d0923437866b63cedc61552a5af99d1f4fb67d367b25f"
  },
  "kernelspec": {
   "display_name": "Python 3.8.5 64-bit ('base': conda)",
   "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": "3.8.5"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}