calculate.ipynb

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  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "tkkUieoCALe8"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MK59mBJuNhF_"
      },
      "source": [
        "def times100(start_speed,end_speed,number_frames):\n",
        "  speeds = np.logspace(start=np.log(start_speed),stop=np.log(end_speed),num=number_frames,base=np.e) # assumes inputs in ms\n",
        "  std_speeds = np.ceil((speeds-1.0) / 100.0).astype(int) * 100 # round to nearest 100 ms\n",
        "  return std_speeds"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EYwx6GhIVNwp"
      },
      "source": [
        " num_frames = 240"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m3PxU80NLRw0"
      },
      "source": [
        "shutters = times100(100,180000,num_frames)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yy7X2PzGZErJ",
        "outputId": "f06157f0-a7ad-476f-85b7-543df014963e"
      },
      "source": [
        "pauses = times100(120000,1000,num_frames-1)\n",
        "print(\"Total time paused =\", round(np.sum(pauses)/60000,1), \"minutes\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total time paused = 99.8 minutes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P0zX0FPtz4nW",
        "outputId": "c056e453-6a92-4fe6-dc38-a7c463ca5152"
      },
      "source": [
        "total_hrs = (np.sum(shutters) + np.sum(pauses)) / 1000 / 3600\n",
        "print(\"Total capture period =\", int(np.floor(total_hrs)), \"Hrs, \", int((total_hrs - np.floor(total_hrs) ) * 60),\"Mins\")\n",
        "# print(\"Start sequence\", np.round(60 * np.cumsum(shutters)[0] / 1000 / 3600) , \"mins before sunset\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total capture period = 3 Hrs,  17 Mins\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Bj_Hb1CGZNSB",
        "outputId": "7271806a-479b-4a10-c5b7-26d9f939c5fc"
      },
      "source": [
        "rec_time = np.sum(shutters) / 3600000\n",
        "print(\"Total light gathering time =\", int(np.floor(rec_time)), \"Hrs, \", int((rec_time - np.floor(rec_time) ) * 60),\"Mins\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total light gathering time = 1 Hrs,  37 Mins\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X_2sm16_sgl3",
        "outputId": "631d6db6-d206-410e-b6b5-a8f1ca9c325d"
      },
      "source": [
        "print(\"Video playback length @ 30p =\", round(num_frames/30,1), \"seconds\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Video playback length @ 30p = 8.0 seconds\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KCraGKN-NTb-",
        "outputId": "fd24b536-c770-4c1a-fc19-a09af068150f"
      },
      "source": [
        "shutters"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "QbJgNq1yaNTV",
        "outputId": "23fe8da5-564e-435e-9a9a-ff655a026b90"
      },
      "source": [
        "pauses"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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          "metadata": {
            "tags": []
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          "execution_count": 10
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    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "-1bAh8JtbWm9",
        "outputId": "32eb7676-e7e4-4ea7-8d96-84f2db135cdb"
      },
      "source": [
        "frames_start_mins = [0] + [(np.cumsum(shutters)[x] + np.cumsum(pauses)[x]) / 60000 for x in range(len(pauses))]\n",
        "\n",
        "plt.step(frames_start_mins,shutters/60000,where='post')\n",
        "plt.title(\"Capture sequence\")\n",
        "plt.xlabel(\"Elapsed minutes\")\n",
        "plt.ylabel(\"Exposure minutes\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "sCYoYrTyeL7O",
        "outputId": "3128ba4f-e499-4fef-fd9b-616a005c0187"
      },
      "source": [
        "plt.plot(frames_start_mins, np.arange(1,num_frames+1))\n",
        "plt.title(\"Frame number vs. real elapsed minutes\")\n",
        "plt.xlabel(\"Elapsed minutes\")\n",
        "plt.ylabel(\"Frame number\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "MVEgMUU0QKNZ",
        "outputId": "aa018d36-76b0-4856-c548-92b2806dbb26"
      },
      "source": [
        "interval_minutes = np.diff(frames_start_mins)*60\n",
        "\n",
        "plt.plot(frames_start_mins[:-1],60/interval_minutes)\n",
        "plt.title(\"Frame capture rate\")\n",
        "plt.xlabel(\"Elapsed minutes\")\n",
        "plt.ylabel(\"Frames per minute\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "HSAmFTSB3l12",
        "outputId": "a3674952-4e85-42a1-9ce4-5c45772f7bbf"
      },
      "source": [
        "plt.plot(np.arange(1,num_frames),interval_minutes)\n",
        "plt.title(\"Playback apparent speed multiplier by frame number\")\n",
        "plt.xlabel(\"Frame number\")\n",
        "plt.ylabel(\"Multiple of real passage of time\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "18dsFz-LTlvC"
      },
      "source": [
        "df = pd.DataFrame(zip(frames_start_mins[:-1],60/interval_minutes),columns=[\"StartFrameMinute\",\"CaptureRatePerMinute\"])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6x-dhWuK8dcS",
        "outputId": "82cdfc76-9e42-45df-bbc9-8ed3b374e0c3"
      },
      "source": [
        "print(\"Peak capture rate is\",round(df[\"StartFrameMinute\"][df.idxmax(axis=0)[\"CaptureRatePerMinute\"]]),\"minutes into recording.\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Peak capture rate is 96 minutes into recording.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wkXYUupN81Tb",
        "outputId": "88fa3f83-087b-484c-d0ef-8efe1ba352d0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "len(pauses)==len(shutters)-1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2FTcWOPgc90w"
      },
      "source": [],
      "execution_count": null,
      "outputs": []
    }
  ]
}