BPL_TEST2_Fedbatch_fmpy_colab.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/janpeter19/BPL_TEST2_Fedbatch/blob/main/BPL_TEST2_Fedbatch_fmpy_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UFcMzs4Y3HwH"
      },
      "source": [
        "# BPL_TEST2_Fedbatch script with FMPy\n",
        "\n",
        "The key library FMPy is installed.\n",
        "\n",
        "After the installation a small application BPL_TEST2_Fedbatch is loaded and run. You can continue with this example if you like."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ID68dwep2zus",
        "outputId": "50496781-84e0-4618-c29b-2752148ca701"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No LSB modules are available.\n",
            "Distributor ID:\tUbuntu\n",
            "Description:\tUbuntu 22.04.2 LTS\n",
            "Release:\t22.04\n",
            "Codename:\tjammy\n"
          ]
        }
      ],
      "source": [
        "!lsb_release -a # Actual VM Ubuntu version used by Google"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pVDcSg-j3SSV",
        "outputId": "c7ca57fb-8be7-43be-8d6c-aa2d34a9d034"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: PYTHONPATH=\n"
          ]
        }
      ],
      "source": [
        "%env PYTHONPATH="
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "04VeBmLU3UFx",
        "outputId": "d2b50962-dfc2-41b2-9aab-a545d6f2819f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-09-11 06:34:50--  https://repo.anaconda.com/miniconda/Miniconda3-py310_23.1.0-1-Linux-x86_64.sh\n",
            "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.130.3, 104.16.131.3, 2606:4700::6810:8303, ...\n",
            "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.130.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 74403966 (71M) [application/x-sh]\n",
            "Saving to: ‘Miniconda3-py310_23.1.0-1-Linux-x86_64.sh’\n",
            "\n",
            "Miniconda3-py310_23 100%[===================>]  70.96M   188MB/s    in 0.4s    \n",
            "\n",
            "2023-09-11 06:34:51 (188 MB/s) - ‘Miniconda3-py310_23.1.0-1-Linux-x86_64.sh’ saved [74403966/74403966]\n",
            "\n",
            "PREFIX=/usr/local\n",
            "Unpacking payload ...\n",
            "                                                                               \n",
            "Installing base environment...\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "\n",
            "Preparing transaction: - \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "Executing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "installation finished.\n"
          ]
        }
      ],
      "source": [
        "!wget https://repo.anaconda.com/miniconda/Miniconda3-py312_24.3.0-0-Linux-x86_64.sh\n",
        "!chmod +x Miniconda3-py312_24.3.0-0-Linux-x86_64.sh\n",
        "!bash ./Miniconda3-py312_24.3.0-0-Linux-x86_64.sh -b -f -p /usr/local\n",
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.12/site-packages/')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5iuP4_vl3WFA",
        "outputId": "af47957c-ee78-470c-efa5-5da7821ed93d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - conda\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    boltons-23.0.0             |  py310h06a4308_0         430 KB\n",
            "    ca-certificates-2023.08.22 |       h06a4308_0         123 KB\n",
            "    certifi-2023.7.22          |  py310h06a4308_0         153 KB\n",
            "    conda-23.7.3               |  py310h06a4308_0         1.0 MB\n",
            "    conda-package-handling-2.2.0|  py310h06a4308_0         268 KB\n",
            "    conda-package-streaming-0.9.0|  py310h06a4308_0          27 KB\n",
            "    cryptography-41.0.2        |  py310h22a60cf_0         1.9 MB\n",
            "    jsonpatch-1.32             |     pyhd3eb1b0_0          15 KB\n",
            "    jsonpointer-2.1            |     pyhd3eb1b0_0           9 KB\n",
            "    libffi-3.4.4               |       h6a678d5_0         142 KB\n",
            "    openssl-3.0.10             |       h7f8727e_2         5.2 MB\n",
            "    packaging-23.1             |  py310h06a4308_0          78 KB\n",
            "    pyopenssl-23.2.0           |  py310h06a4308_0          97 KB\n",
            "    python-3.10.12             |       h955ad1f_0        26.8 MB\n",
            "    requests-2.31.0            |  py310h06a4308_0          97 KB\n",
            "    sqlite-3.41.2              |       h5eee18b_0         1.2 MB\n",
            "    tqdm-4.65.0                |  py310h2f386ee_0         132 KB\n",
            "    tzdata-2023c               |       h04d1e81_0         116 KB\n",
            "    urllib3-1.26.16            |  py310h06a4308_0         201 KB\n",
            "    xz-5.4.2                   |       h5eee18b_0         642 KB\n",
            "    zstandard-0.19.0           |  py310h5eee18b_0         474 KB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:        39.1 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  boltons            pkgs/main/linux-64::boltons-23.0.0-py310h06a4308_0 \n",
            "  jsonpatch          pkgs/main/noarch::jsonpatch-1.32-pyhd3eb1b0_0 \n",
            "  jsonpointer        pkgs/main/noarch::jsonpointer-2.1-pyhd3eb1b0_0 \n",
            "  packaging          pkgs/main/linux-64::packaging-23.1-py310h06a4308_0 \n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  ca-certificates                     2023.01.10-h06a4308_0 --> 2023.08.22-h06a4308_0 \n",
            "  certifi                         2022.12.7-py310h06a4308_0 --> 2023.7.22-py310h06a4308_0 \n",
            "  conda                              23.1.0-py310h06a4308_0 --> 23.7.3-py310h06a4308_0 \n",
            "  conda-package-han~                  2.0.2-py310h06a4308_0 --> 2.2.0-py310h06a4308_0 \n",
            "  conda-package-str~                  0.7.0-py310h06a4308_0 --> 0.9.0-py310h06a4308_0 \n",
            "  cryptography                       38.0.4-py310h9ce1e76_0 --> 41.0.2-py310h22a60cf_0 \n",
            "  libffi                                   3.4.2-h6a678d5_6 --> 3.4.4-h6a678d5_0 \n",
            "  openssl                                 1.1.1s-h7f8727e_0 --> 3.0.10-h7f8727e_2 \n",
            "  pyopenssl          pkgs/main/noarch::pyopenssl-22.0.0-py~ --> pkgs/main/linux-64::pyopenssl-23.2.0-py310h06a4308_0 \n",
            "  python                                  3.10.9-h7a1cb2a_0 --> 3.10.12-h955ad1f_0 \n",
            "  requests                           2.28.1-py310h06a4308_0 --> 2.31.0-py310h06a4308_0 \n",
            "  sqlite                                  3.40.1-h5082296_0 --> 3.41.2-h5eee18b_0 \n",
            "  tqdm                               4.64.1-py310h06a4308_0 --> 4.65.0-py310h2f386ee_0 \n",
            "  tzdata                                   2022g-h04d1e81_0 --> 2023c-h04d1e81_0 \n",
            "  urllib3                           1.26.14-py310h06a4308_0 --> 1.26.16-py310h06a4308_0 \n",
            "  xz                                      5.2.10-h5eee18b_1 --> 5.4.2-h5eee18b_0 \n",
            "  zstandard                          0.18.0-py310h5eee18b_0 --> 0.19.0-py310h5eee18b_0 \n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "tqdm-4.65.0          | 132 KB    | :   0% 0/1 [00:00<?, ?it/s]\n",
            "zstandard-0.19.0     | 474 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n",
            "\n",
            "jsonpointer-2.1      | 9 KB      | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "pyopenssl-23.2.0     | 97 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libffi-3.4.4         | 142 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "ca-certificates-2023 | 123 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "certifi-2023.7.22    | 153 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "requests-2.31.0      | 97 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "urllib3-1.26.16      | 201 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cryptography-41.0.2  | 1.9 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-23.7.3         | 1.0 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "jsonpatch-1.32       | 15 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-package-stream | 27 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "packaging-23.1       | 78 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sqlite-3.41.2        | 1.2 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "xz-5.4.2             | 642 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "tzdata-2023c         | 116 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "boltons-23.0.0       | 430 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "tqdm-4.65.0          | 132 KB    | :  97% 0.9695678546595061/1 [00:00<00:00,  9.16it/s]\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :   0% 0.002330890739852235/1 [00:00<00:43, 43.16s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "zstandard-0.19.0     | 474 KB    | :  27% 0.26999101897550404/1 [00:00<00:00,  2.49it/s]\u001b[A\n",
            "\n",
            "\n",
            "pyopenssl-23.2.0     | 97 KB     | :  66% 0.6601527086649073/1 [00:00<00:00,  6.22it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libffi-3.4.4         | 142 KB    | :  90% 0.9016812966071379/1 [00:00<00:00,  8.66it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "ca-certificates-2023 | 123 KB    | :  13% 0.1305622848399847/1 [00:00<00:00,  1.06it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "certifi-2023.7.22    | 153 KB    | :  10% 0.1045538084541556/1 [00:00<00:01,  1.27s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "urllib3-1.26.16      | 201 KB    | :   8% 0.07944874673287396/1 [00:00<00:01,  1.80s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "requests-2.31.0      | 97 KB     | :  16% 0.1642456868465109/1 [00:00<00:00,  1.07it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cryptography-41.0.2  | 1.9 MB    | :   1% 0.008098446743222297/1 [00:00<00:20, 20.58s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "jsonpatch-1.32       | 15 KB     | : 100% 1.0/1 [00:00<00:00,  5.59it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-23.7.3         | 1.0 MB    | :   2% 0.015454125281794429/1 [00:00<00:11, 11.77s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :   4% 0.04253875600230329/1 [00:00<00:04,  4.26s/it] \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-package-stream | 27 KB     | :  58% 0.5842247896163172/1 [00:00<00:00,  2.78it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "packaging-23.1       | 78 KB     | :  21% 0.20500757016479185/1 [00:00<00:00,  1.05s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sqlite-3.41.2        | 1.2 MB    | :   1% 0.013323043970761513/1 [00:00<00:17, 18.06s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "xz-5.4.2             | 642 KB    | :   2% 0.024932699667797344/1 [00:00<00:09,  9.76s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "boltons-23.0.0       | 430 KB    | :   4% 0.03723027141013289/1 [00:00<00:07,  7.79s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "tzdata-2023c         | 116 KB    | :  14% 0.13846257859509162/1 [00:00<00:01,  2.15s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  11% 0.108969142088092/1 [00:00<00:02,  2.36s/it]  \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "tqdm-4.65.0          | 132 KB    | : 100% 1.0/1 [00:00<00:00,  9.16it/s]               \n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  28% 0.28203777952212045/1 [00:00<00:01,  1.52s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "pyopenssl-23.2.0     | 97 KB     | : 100% 1.0/1 [00:00<00:00,  6.22it/s]               \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libffi-3.4.4         | 142 KB    | : 100% 1.0/1 [00:00<00:00,  8.66it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "ca-certificates-2023 | 123 KB    | : 100% 1.0/1 [00:00<00:00,  1.70it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "ca-certificates-2023 | 123 KB    | : 100% 1.0/1 [00:00<00:00,  1.70it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  38% 0.3758561318011729/1 [00:00<00:00,  1.33s/it] \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "zstandard-0.19.0     | 474 KB    | : 100% 1.0/1 [00:00<00:00,  1.51it/s]                \u001b[A\n",
            "zstandard-0.19.0     | 474 KB    | : 100% 1.0/1 [00:00<00:00,  1.51it/s]\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "certifi-2023.7.22    | 153 KB    | : 100% 1.0/1 [00:00<00:00,  1.61it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "certifi-2023.7.22    | 153 KB    | : 100% 1.0/1 [00:00<00:00,  1.61it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "requests-2.31.0      | 97 KB     | : 100% 1.0/1 [00:00<00:00,  1.42it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "requests-2.31.0      | 97 KB     | : 100% 1.0/1 [00:00<00:00,  1.42it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  47% 0.4708399294501515/1 [00:00<00:00,  1.23s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "jsonpatch-1.32       | 15 KB     | : 100% 1.0/1 [00:00<00:00,  5.59it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-package-stream | 27 KB     | : 100% 1.0/1 [00:00<00:00,  1.14it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-package-stream | 27 KB     | : 100% 1.0/1 [00:00<00:00,  1.14it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "urllib3-1.26.16      | 201 KB    | : 100% 1.0/1 [00:00<00:00,  1.29it/s]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "urllib3-1.26.16      | 201 KB    | : 100% 1.0/1 [00:00<00:00,  1.29it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  56% 0.5611619456194256/1 [00:00<00:00,  1.19s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "packaging-23.1       | 78 KB     | : 100% 1.0/1 [00:00<00:00,  1.18it/s]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "packaging-23.1       | 78 KB     | : 100% 1.0/1 [00:00<00:00,  1.18it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  66% 0.6613902474330717/1 [00:00<00:00,  1.13s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | :  83% 0.8309625487573218/1 [00:01<00:00,  1.12it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cryptography-41.0.2  | 1.9 MB    | : 100% 1.0/1 [00:01<00:00,  1.26s/it]                 \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cryptography-41.0.2  | 1.9 MB    | : 100% 1.0/1 [00:01<00:00,  1.26s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-23.7.3         | 1.0 MB    | : 100% 1.0/1 [00:01<00:00,  1.43s/it]                 \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "conda-23.7.3         | 1.0 MB    | : 100% 1.0/1 [00:01<00:00,  1.43s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "xz-5.4.2             | 642 KB    | : 100% 1.0/1 [00:01<00:00,  1.54s/it]                 \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "xz-5.4.2             | 642 KB    | : 100% 1.0/1 [00:01<00:00,  1.54s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "boltons-23.0.0       | 430 KB    | : 100% 1.0/1 [00:01<00:00,  1.76s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "boltons-23.0.0       | 430 KB    | : 100% 1.0/1 [00:01<00:00,  1.76s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sqlite-3.41.2        | 1.2 MB    | : 100% 1.0/1 [00:01<00:00,  1.83s/it]                 \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sqlite-3.41.2        | 1.2 MB    | : 100% 1.0/1 [00:01<00:00,  1.83s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "tzdata-2023c         | 116 KB    | : 100% 1.0/1 [00:01<00:00,  1.94s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "tzdata-2023c         | 116 KB    | : 100% 1.0/1 [00:01<00:00,  1.94s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | : 100% 1.0/1 [00:03<00:00,  5.71s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.10.12       | 26.8 MB   | : 100% 1.0/1 [00:03<00:00,  5.71s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \n",
            "                                                                        \u001b[A\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "Preparing transaction: / \b\b- \b\bdone\n",
            "Verifying transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "Executing transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n"
          ]
        }
      ],
      "source": [
        "!conda update -n base -c defaults conda --yes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uoBMBSS63Z58",
        "outputId": "5a0672ad-4309-40e3-c243-e81ca4fac72c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "conda 23.7.3\n",
            "Python 3.10.12\n"
          ]
        }
      ],
      "source": [
        "!conda --version\n",
        "!python --version"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RMuJRdfH3dDq",
        "outputId": "782fa968-c086-49fb-f8e0-0e321683e019"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Solving environment: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - fmpy\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    abseil-cpp-20211102.0      |       h27087fc_1         1.1 MB  conda-forge\n",
            "    ansi2html-1.8.0            |  py310hff52083_1          42 KB  conda-forge\n",
            "    arrow-cpp-11.0.0           |       h374c478_2        10.2 MB\n",
            "    attrs-23.1.0               |     pyh71513ae_1          54 KB  conda-forge\n",
            "    aws-c-common-0.6.8         |       h5eee18b_1         177 KB\n",
            "    aws-c-event-stream-0.1.6   |       h6a678d5_6          25 KB\n",
            "    aws-checksums-0.1.11       |       h5eee18b_2          48 KB\n",
            "    aws-sdk-cpp-1.8.185        |       h721c034_1         2.2 MB\n",
            "    blas-1.0                   |              mkl           6 KB\n",
            "    blinker-1.6.2              |     pyhd8ed1ab_0          18 KB  conda-forge\n",
            "    bokeh-2.4.3                |     pyhd8ed1ab_3        13.3 MB  conda-forge\n",
            "    boost-cpp-1.73.0           |      h7f8727e_12          16 KB\n",
            "    bottleneck-1.3.5           |  py310ha9d4c09_0         274 KB\n",
            "    c-ares-1.19.1              |       h5eee18b_0         118 KB\n",
            "    ca-certificates-2023.7.22  |       hbcca054_0         146 KB  conda-forge\n",
            "    certifi-2023.7.22          |     pyhd8ed1ab_0         150 KB  conda-forge\n",
            "    click-8.1.7                |unix_pyh707e725_0          82 KB  conda-forge\n",
            "    cloudpickle-2.2.1          |     pyhd8ed1ab_0          27 KB  conda-forge\n",
            "    conda-23.7.3               |  py310hff52083_0        1006 KB  conda-forge\n",
            "    cycler-0.11.0              |     pyhd8ed1ab_0          10 KB  conda-forge\n",
            "    cytoolz-0.12.0             |  py310h5eee18b_0         370 KB\n",
            "    dash-2.13.0                |     pyhd8ed1ab_0         7.5 MB  conda-forge\n",
            "    dash-bootstrap-components-1.5.0|     pyhd8ed1ab_0         116 KB  conda-forge\n",
            "    dask-2023.9.1              |     pyhd8ed1ab_0           7 KB  conda-forge\n",
            "    dask-core-2023.9.1         |     pyhd8ed1ab_0         836 KB  conda-forge\n",
            "    dbus-1.13.18               |       hb2f20db_0         504 KB\n",
            "    distributed-2023.9.1       |     pyhd8ed1ab_0         768 KB  conda-forge\n",
            "    expat-2.2.10               |       h9c3ff4c_0         164 KB  conda-forge\n",
            "    flask-2.3.3                |     pyhd8ed1ab_0          78 KB  conda-forge\n",
            "    fmpy-0.3.15                |       h13ae965_0          10 KB  conda-forge\n",
            "    fmpy-base-0.3.15           |  py310hff52083_0         5.5 MB  conda-forge\n",
            "    fontconfig-2.14.1          |       hef1e5e3_0         284 KB\n",
            "    freetype-2.10.4            |       h0708190_1         890 KB  conda-forge\n",
            "    fsspec-2023.9.0            |     pyh1a96a4e_0         121 KB  conda-forge\n",
            "    gflags-2.2.2               |    he1b5a44_1004         114 KB  conda-forge\n",
            "    giflib-5.2.1               |       h36c2ea0_2          77 KB  conda-forge\n",
            "    glib-2.69.1                |       he621ea3_2         1.9 MB\n",
            "    glog-0.5.0                 |       h48cff8f_0         104 KB  conda-forge\n",
            "    grpc-cpp-1.48.2            |       he1ff14a_1         4.8 MB\n",
            "    gst-plugins-base-1.14.1    |       h6a678d5_1         2.2 MB\n",
            "    gstreamer-1.14.1           |       h5eee18b_1         1.7 MB\n",
            "    icu-58.2                   |    hf484d3e_1000        22.6 MB  conda-forge\n",
            "    importlib-metadata-6.8.0   |     pyha770c72_0          25 KB  conda-forge\n",
            "    importlib_metadata-6.8.0   |       hd8ed1ab_0           9 KB  conda-forge\n",
            "    importlib_resources-6.0.1  |     pyhd8ed1ab_0          30 KB  conda-forge\n",
            "    intel-openmp-2023.1.0      |   hdb19cb5_46305        17.1 MB\n",
            "    itsdangerous-2.1.2         |     pyhd8ed1ab_0          16 KB  conda-forge\n",
            "    jinja2-3.1.2               |     pyhd8ed1ab_1          99 KB  conda-forge\n",
            "    jpeg-9e                    |       h166bdaf_1         268 KB  conda-forge\n",
            "    jsonschema-4.17.3          |     pyhd8ed1ab_0          69 KB  conda-forge\n",
            "    jupyter_core-5.3.1         |  py310hff52083_0          90 KB  conda-forge\n",
            "    kiwisolver-1.4.4           |  py310h6a678d5_0          76 KB\n",
            "    krb5-1.20.1                |       h143b758_1         1.3 MB\n",
            "    lark-parser-0.12.0         |     pyhd8ed1ab_0          78 KB  conda-forge\n",
            "    lcms2-2.12                 |       h3be6417_0         312 KB\n",
            "    lerc-3.0                   |       h295c915_0         196 KB\n",
            "    libboost-1.73.0            |      h28710b8_12        13.8 MB\n",
            "    libbrotlicommon-1.0.9      |       h166bdaf_7          65 KB  conda-forge\n",
            "    libbrotlidec-1.0.9         |       h166bdaf_7          33 KB  conda-forge\n",
            "    libbrotlienc-1.0.9         |       h166bdaf_7         287 KB  conda-forge\n",
            "    libclang-10.0.1            |default_hb85057a_2        10.8 MB\n",
            "    libcurl-8.2.1              |       h251f7ec_0         399 KB\n",
            "    libdeflate-1.17            |       h5eee18b_0          69 KB\n",
            "    libedit-3.1.20221030       |       h5eee18b_0         181 KB\n",
            "    libev-4.33                 |       h516909a_1         104 KB  conda-forge\n",
            "    libevent-2.1.12            |       hdbd6064_1         453 KB\n",
            "    libllvm10-10.0.1           |       he513fc3_3        26.4 MB  conda-forge\n",
            "    libnghttp2-1.52.0          |       h2d74bed_1         672 KB\n",
            "    libpng-1.6.39              |       h5eee18b_0         304 KB\n",
            "    libpq-12.15                |       hdbd6064_1         2.4 MB\n",
            "    libprotobuf-3.20.3         |       he621ea3_0         2.4 MB\n",
            "    libssh2-1.10.0             |       hdbd6064_2         292 KB\n",
            "    libthrift-0.15.0           |       h1795dd8_2         4.0 MB\n",
            "    libtiff-4.5.1              |       h6a678d5_0         533 KB\n",
            "    libwebp-1.2.4              |       h11a3e52_1          86 KB\n",
            "    libwebp-base-1.2.4         |       h5eee18b_1         376 KB\n",
            "    libxcb-1.15                |       h7f8727e_0         505 KB\n",
            "    libxkbcommon-1.0.1         |       hfa300c1_0         483 KB\n",
            "    libxml2-2.9.14             |       h74e7548_0         718 KB\n",
            "    libxslt-1.1.35             |       h4e12654_0         453 KB\n",
            "    locket-1.0.0               |     pyhd8ed1ab_0           8 KB  conda-forge\n",
            "    lxml-4.9.1                 |  py310h1edc446_0         5.2 MB\n",
            "    lz4-4.3.2                  |  py310h5eee18b_0          35 KB\n",
            "    lz4-c-1.9.4                |       h6a678d5_0         154 KB\n",
            "    markupsafe-2.1.1           |  py310h7f8727e_0          34 KB\n",
            "    matplotlib-base-3.4.3      |  py310h23f4a51_2         7.3 MB  conda-forge\n",
            "    mkl-2023.1.0               |   h213fc3f_46343       171.6 MB\n",
            "    mkl-service-2.4.0          |  py310h5eee18b_1          54 KB\n",
            "    mkl_fft-1.3.6              |  py310h1128e8f_1         207 KB\n",
            "    mkl_random-1.2.2           |  py310h1128e8f_1         284 KB\n",
            "    msgpack-python-1.0.3       |  py310hd09550d_0         218 KB\n",
            "    nbformat-5.9.2             |     pyhd8ed1ab_0          98 KB  conda-forge\n",
            "    nest-asyncio-1.5.6         |     pyhd8ed1ab_0          10 KB  conda-forge\n",
            "    nspr-4.35                  |       h6a678d5_0         244 KB\n",
            "    nss-3.89.1                 |       h6a678d5_0         2.1 MB\n",
            "    numexpr-2.8.4              |  py310h85018f9_1         136 KB\n",
            "    numpy-1.25.2               |  py310h5f9d8c6_0          12 KB\n",
            "    numpy-base-1.25.2          |  py310hb5e798b_0         7.1 MB\n",
            "    orc-1.7.4                  |       hb3bc3d3_1         972 KB\n",
            "    pandas-1.5.3               |  py310h1128e8f_0        12.0 MB\n",
            "    partd-1.4.0                |     pyhd8ed1ab_0          20 KB  conda-forge\n",
            "    pathlib-1.0.1              |  py310hff52083_7           5 KB  conda-forge\n",
            "    pcre-8.45                  |       h9c3ff4c_0         253 KB  conda-forge\n",
            "    pillow-9.4.0               |  py310h6a678d5_0         730 KB\n",
            "    pkgutil-resolve-name-1.3.10|     pyhd8ed1ab_0           9 KB  conda-forge\n",
            "    platformdirs-3.10.0        |     pyhd8ed1ab_0          19 KB  conda-forge\n",
            "    plotly-5.16.1              |     pyhd8ed1ab_0         5.7 MB  conda-forge\n",
            "    ply-3.11                   |             py_1          44 KB  conda-forge\n",
            "    psutil-5.9.0               |  py310h5eee18b_0         368 KB\n",
            "    pyarrow-11.0.0             |  py310h468efa6_1         4.2 MB\n",
            "    pyparsing-3.1.1            |     pyhd8ed1ab_0          87 KB  conda-forge\n",
            "    pyqt-5.15.7                |  py310h6a678d5_1         5.1 MB\n",
            "    pyqt5-sip-12.11.0          |  py310h6a678d5_1         277 KB\n",
            "    pyqtgraph-0.13.3           |     pyhd8ed1ab_0         670 KB  conda-forge\n",
            "    pyqtwebengine-5.15.7       |  py310h6a678d5_1         159 KB\n",
            "    pyrsistent-0.18.0          |  py310h7f8727e_0         117 KB\n",
            "    python-dateutil-2.8.2      |     pyhd8ed1ab_0         240 KB  conda-forge\n",
            "    python-fastjsonschema-2.18.0|     pyhd8ed1ab_0         221 KB  conda-forge\n",
            "    python_abi-3.10            |          2_cp310           4 KB  conda-forge\n",
            "    pytz-2023.3.post1          |     pyhd8ed1ab_0         183 KB  conda-forge\n",
            "    pyyaml-6.0                 |  py310h5764c6d_4         178 KB  conda-forge\n",
            "    qt-main-5.15.2             |       h327a75a_7        45.1 MB\n",
            "    qt-webengine-5.15.9        |       hd2b0992_4        47.1 MB\n",
            "    qtwebkit-5.212             |       h4eab89a_4        14.3 MB\n",
            "    re2-2022.04.01             |       h27087fc_0         212 KB  conda-forge\n",
            "    retrying-1.3.3             |             py_2          11 KB  conda-forge\n",
            "    sip-6.6.2                  |  py310h6a678d5_0         692 KB\n",
            "    snappy-1.1.9               |       h295c915_0         636 KB\n",
            "    sortedcontainers-2.4.0     |     pyhd8ed1ab_0          26 KB  conda-forge\n",
            "    tbb-2021.8.0               |       hdb19cb5_0         1.6 MB\n",
            "    tblib-1.7.0                |     pyhd8ed1ab_0          15 KB  conda-forge\n",
            "    tenacity-8.2.3             |     pyhd8ed1ab_0          22 KB  conda-forge\n",
            "    toml-0.10.2                |     pyhd8ed1ab_0          18 KB  conda-forge\n",
            "    tornado-6.1                |  py310h5764c6d_3         657 KB  conda-forge\n",
            "    traitlets-5.9.0            |     pyhd8ed1ab_0          96 KB  conda-forge\n",
            "    typing-extensions-4.7.1    |       hd8ed1ab_0          10 KB  conda-forge\n",
            "    typing_extensions-4.7.1    |     pyha770c72_0          35 KB  conda-forge\n",
            "    utf8proc-2.6.1             |       h27cfd23_0         308 KB\n",
            "    werkzeug-2.3.7             |     pyhd8ed1ab_0         248 KB  conda-forge\n",
            "    yaml-0.2.5                 |       h7f98852_2          87 KB  conda-forge\n",
            "    zict-3.0.0                 |     pyhd8ed1ab_0          35 KB  conda-forge\n",
            "    zipp-3.16.2                |     pyhd8ed1ab_0          18 KB  conda-forge\n",
            "    zstd-1.5.5                 |       hc292b87_0         647 KB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:       502.6 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  abseil-cpp         conda-forge/linux-64::abseil-cpp-20211102.0-h27087fc_1 \n",
            "  ansi2html          conda-forge/linux-64::ansi2html-1.8.0-py310hff52083_1 \n",
            "  arrow-cpp          pkgs/main/linux-64::arrow-cpp-11.0.0-h374c478_2 \n",
            "  attrs              conda-forge/noarch::attrs-23.1.0-pyh71513ae_1 \n",
            "  aws-c-common       pkgs/main/linux-64::aws-c-common-0.6.8-h5eee18b_1 \n",
            "  aws-c-event-stream pkgs/main/linux-64::aws-c-event-stream-0.1.6-h6a678d5_6 \n",
            "  aws-checksums      pkgs/main/linux-64::aws-checksums-0.1.11-h5eee18b_2 \n",
            "  aws-sdk-cpp        pkgs/main/linux-64::aws-sdk-cpp-1.8.185-h721c034_1 \n",
            "  blas               pkgs/main/linux-64::blas-1.0-mkl \n",
            "  blinker            conda-forge/noarch::blinker-1.6.2-pyhd8ed1ab_0 \n",
            "  bokeh              conda-forge/noarch::bokeh-2.4.3-pyhd8ed1ab_3 \n",
            "  boost-cpp          pkgs/main/linux-64::boost-cpp-1.73.0-h7f8727e_12 \n",
            "  bottleneck         pkgs/main/linux-64::bottleneck-1.3.5-py310ha9d4c09_0 \n",
            "  c-ares             pkgs/main/linux-64::c-ares-1.19.1-h5eee18b_0 \n",
            "  click              conda-forge/noarch::click-8.1.7-unix_pyh707e725_0 \n",
            "  cloudpickle        conda-forge/noarch::cloudpickle-2.2.1-pyhd8ed1ab_0 \n",
            "  cycler             conda-forge/noarch::cycler-0.11.0-pyhd8ed1ab_0 \n",
            "  cytoolz            pkgs/main/linux-64::cytoolz-0.12.0-py310h5eee18b_0 \n",
            "  dash               conda-forge/noarch::dash-2.13.0-pyhd8ed1ab_0 \n",
            "  dash-bootstrap-co~ conda-forge/noarch::dash-bootstrap-components-1.5.0-pyhd8ed1ab_0 \n",
            "  dask               conda-forge/noarch::dask-2023.9.1-pyhd8ed1ab_0 \n",
            "  dask-core          conda-forge/noarch::dask-core-2023.9.1-pyhd8ed1ab_0 \n",
            "  dbus               pkgs/main/linux-64::dbus-1.13.18-hb2f20db_0 \n",
            "  distributed        conda-forge/noarch::distributed-2023.9.1-pyhd8ed1ab_0 \n",
            "  expat              conda-forge/linux-64::expat-2.2.10-h9c3ff4c_0 \n",
            "  flask              conda-forge/noarch::flask-2.3.3-pyhd8ed1ab_0 \n",
            "  fmpy               conda-forge/noarch::fmpy-0.3.15-h13ae965_0 \n",
            "  fmpy-base          conda-forge/linux-64::fmpy-base-0.3.15-py310hff52083_0 \n",
            "  fontconfig         pkgs/main/linux-64::fontconfig-2.14.1-hef1e5e3_0 \n",
            "  freetype           conda-forge/linux-64::freetype-2.10.4-h0708190_1 \n",
            "  fsspec             conda-forge/noarch::fsspec-2023.9.0-pyh1a96a4e_0 \n",
            "  gflags             conda-forge/linux-64::gflags-2.2.2-he1b5a44_1004 \n",
            "  giflib             conda-forge/linux-64::giflib-5.2.1-h36c2ea0_2 \n",
            "  glib               pkgs/main/linux-64::glib-2.69.1-he621ea3_2 \n",
            "  glog               conda-forge/linux-64::glog-0.5.0-h48cff8f_0 \n",
            "  grpc-cpp           pkgs/main/linux-64::grpc-cpp-1.48.2-he1ff14a_1 \n",
            "  gst-plugins-base   pkgs/main/linux-64::gst-plugins-base-1.14.1-h6a678d5_1 \n",
            "  gstreamer          pkgs/main/linux-64::gstreamer-1.14.1-h5eee18b_1 \n",
            "  icu                conda-forge/linux-64::icu-58.2-hf484d3e_1000 \n",
            "  importlib-metadata conda-forge/noarch::importlib-metadata-6.8.0-pyha770c72_0 \n",
            "  importlib_metadata conda-forge/noarch::importlib_metadata-6.8.0-hd8ed1ab_0 \n",
            "  importlib_resourc~ conda-forge/noarch::importlib_resources-6.0.1-pyhd8ed1ab_0 \n",
            "  intel-openmp       pkgs/main/linux-64::intel-openmp-2023.1.0-hdb19cb5_46305 \n",
            "  itsdangerous       conda-forge/noarch::itsdangerous-2.1.2-pyhd8ed1ab_0 \n",
            "  jinja2             conda-forge/noarch::jinja2-3.1.2-pyhd8ed1ab_1 \n",
            "  jpeg               conda-forge/linux-64::jpeg-9e-h166bdaf_1 \n",
            "  jsonschema         conda-forge/noarch::jsonschema-4.17.3-pyhd8ed1ab_0 \n",
            "  jupyter_core       conda-forge/linux-64::jupyter_core-5.3.1-py310hff52083_0 \n",
            "  kiwisolver         pkgs/main/linux-64::kiwisolver-1.4.4-py310h6a678d5_0 \n",
            "  krb5               pkgs/main/linux-64::krb5-1.20.1-h143b758_1 \n",
            "  lark-parser        conda-forge/noarch::lark-parser-0.12.0-pyhd8ed1ab_0 \n",
            "  lcms2              pkgs/main/linux-64::lcms2-2.12-h3be6417_0 \n",
            "  lerc               pkgs/main/linux-64::lerc-3.0-h295c915_0 \n",
            "  libboost           pkgs/main/linux-64::libboost-1.73.0-h28710b8_12 \n",
            "  libbrotlicommon    conda-forge/linux-64::libbrotlicommon-1.0.9-h166bdaf_7 \n",
            "  libbrotlidec       conda-forge/linux-64::libbrotlidec-1.0.9-h166bdaf_7 \n",
            "  libbrotlienc       conda-forge/linux-64::libbrotlienc-1.0.9-h166bdaf_7 \n",
            "  libclang           pkgs/main/linux-64::libclang-10.0.1-default_hb85057a_2 \n",
            "  libcurl            pkgs/main/linux-64::libcurl-8.2.1-h251f7ec_0 \n",
            "  libdeflate         pkgs/main/linux-64::libdeflate-1.17-h5eee18b_0 \n",
            "  libedit            pkgs/main/linux-64::libedit-3.1.20221030-h5eee18b_0 \n",
            "  libev              conda-forge/linux-64::libev-4.33-h516909a_1 \n",
            "  libevent           pkgs/main/linux-64::libevent-2.1.12-hdbd6064_1 \n",
            "  libllvm10          conda-forge/linux-64::libllvm10-10.0.1-he513fc3_3 \n",
            "  libnghttp2         pkgs/main/linux-64::libnghttp2-1.52.0-h2d74bed_1 \n",
            "  libpng             pkgs/main/linux-64::libpng-1.6.39-h5eee18b_0 \n",
            "  libpq              pkgs/main/linux-64::libpq-12.15-hdbd6064_1 \n",
            "  libprotobuf        pkgs/main/linux-64::libprotobuf-3.20.3-he621ea3_0 \n",
            "  libssh2            pkgs/main/linux-64::libssh2-1.10.0-hdbd6064_2 \n",
            "  libthrift          pkgs/main/linux-64::libthrift-0.15.0-h1795dd8_2 \n",
            "  libtiff            pkgs/main/linux-64::libtiff-4.5.1-h6a678d5_0 \n",
            "  libwebp            pkgs/main/linux-64::libwebp-1.2.4-h11a3e52_1 \n",
            "  libwebp-base       pkgs/main/linux-64::libwebp-base-1.2.4-h5eee18b_1 \n",
            "  libxcb             pkgs/main/linux-64::libxcb-1.15-h7f8727e_0 \n",
            "  libxkbcommon       pkgs/main/linux-64::libxkbcommon-1.0.1-hfa300c1_0 \n",
            "  libxml2            pkgs/main/linux-64::libxml2-2.9.14-h74e7548_0 \n",
            "  libxslt            pkgs/main/linux-64::libxslt-1.1.35-h4e12654_0 \n",
            "  locket             conda-forge/noarch::locket-1.0.0-pyhd8ed1ab_0 \n",
            "  lxml               pkgs/main/linux-64::lxml-4.9.1-py310h1edc446_0 \n",
            "  lz4                pkgs/main/linux-64::lz4-4.3.2-py310h5eee18b_0 \n",
            "  lz4-c              pkgs/main/linux-64::lz4-c-1.9.4-h6a678d5_0 \n",
            "  markupsafe         pkgs/main/linux-64::markupsafe-2.1.1-py310h7f8727e_0 \n",
            "  matplotlib-base    conda-forge/linux-64::matplotlib-base-3.4.3-py310h23f4a51_2 \n",
            "  mkl                pkgs/main/linux-64::mkl-2023.1.0-h213fc3f_46343 \n",
            "  mkl-service        pkgs/main/linux-64::mkl-service-2.4.0-py310h5eee18b_1 \n",
            "  mkl_fft            pkgs/main/linux-64::mkl_fft-1.3.6-py310h1128e8f_1 \n",
            "  mkl_random         pkgs/main/linux-64::mkl_random-1.2.2-py310h1128e8f_1 \n",
            "  msgpack-python     pkgs/main/linux-64::msgpack-python-1.0.3-py310hd09550d_0 \n",
            "  nbformat           conda-forge/noarch::nbformat-5.9.2-pyhd8ed1ab_0 \n",
            "  nest-asyncio       conda-forge/noarch::nest-asyncio-1.5.6-pyhd8ed1ab_0 \n",
            "  nspr               pkgs/main/linux-64::nspr-4.35-h6a678d5_0 \n",
            "  nss                pkgs/main/linux-64::nss-3.89.1-h6a678d5_0 \n",
            "  numexpr            pkgs/main/linux-64::numexpr-2.8.4-py310h85018f9_1 \n",
            "  numpy              pkgs/main/linux-64::numpy-1.25.2-py310h5f9d8c6_0 \n",
            "  numpy-base         pkgs/main/linux-64::numpy-base-1.25.2-py310hb5e798b_0 \n",
            "  orc                pkgs/main/linux-64::orc-1.7.4-hb3bc3d3_1 \n",
            "  pandas             pkgs/main/linux-64::pandas-1.5.3-py310h1128e8f_0 \n",
            "  partd              conda-forge/noarch::partd-1.4.0-pyhd8ed1ab_0 \n",
            "  pathlib            conda-forge/linux-64::pathlib-1.0.1-py310hff52083_7 \n",
            "  pcre               conda-forge/linux-64::pcre-8.45-h9c3ff4c_0 \n",
            "  pillow             pkgs/main/linux-64::pillow-9.4.0-py310h6a678d5_0 \n",
            "  pkgutil-resolve-n~ conda-forge/noarch::pkgutil-resolve-name-1.3.10-pyhd8ed1ab_0 \n",
            "  platformdirs       conda-forge/noarch::platformdirs-3.10.0-pyhd8ed1ab_0 \n",
            "  plotly             conda-forge/noarch::plotly-5.16.1-pyhd8ed1ab_0 \n",
            "  ply                conda-forge/noarch::ply-3.11-py_1 \n",
            "  psutil             pkgs/main/linux-64::psutil-5.9.0-py310h5eee18b_0 \n",
            "  pyarrow            pkgs/main/linux-64::pyarrow-11.0.0-py310h468efa6_1 \n",
            "  pyparsing          conda-forge/noarch::pyparsing-3.1.1-pyhd8ed1ab_0 \n",
            "  pyqt               pkgs/main/linux-64::pyqt-5.15.7-py310h6a678d5_1 \n",
            "  pyqt5-sip          pkgs/main/linux-64::pyqt5-sip-12.11.0-py310h6a678d5_1 \n",
            "  pyqtgraph          conda-forge/noarch::pyqtgraph-0.13.3-pyhd8ed1ab_0 \n",
            "  pyqtwebengine      pkgs/main/linux-64::pyqtwebengine-5.15.7-py310h6a678d5_1 \n",
            "  pyrsistent         pkgs/main/linux-64::pyrsistent-0.18.0-py310h7f8727e_0 \n",
            "  python-dateutil    conda-forge/noarch::python-dateutil-2.8.2-pyhd8ed1ab_0 \n",
            "  python-fastjsonsc~ conda-forge/noarch::python-fastjsonschema-2.18.0-pyhd8ed1ab_0 \n",
            "  python_abi         conda-forge/linux-64::python_abi-3.10-2_cp310 \n",
            "  pytz               conda-forge/noarch::pytz-2023.3.post1-pyhd8ed1ab_0 \n",
            "  pyyaml             conda-forge/linux-64::pyyaml-6.0-py310h5764c6d_4 \n",
            "  qt-main            pkgs/main/linux-64::qt-main-5.15.2-h327a75a_7 \n",
            "  qt-webengine       pkgs/main/linux-64::qt-webengine-5.15.9-hd2b0992_4 \n",
            "  qtwebkit           pkgs/main/linux-64::qtwebkit-5.212-h4eab89a_4 \n",
            "  re2                conda-forge/linux-64::re2-2022.04.01-h27087fc_0 \n",
            "  retrying           conda-forge/noarch::retrying-1.3.3-py_2 \n",
            "  sip                pkgs/main/linux-64::sip-6.6.2-py310h6a678d5_0 \n",
            "  snappy             pkgs/main/linux-64::snappy-1.1.9-h295c915_0 \n",
            "  sortedcontainers   conda-forge/noarch::sortedcontainers-2.4.0-pyhd8ed1ab_0 \n",
            "  tbb                pkgs/main/linux-64::tbb-2021.8.0-hdb19cb5_0 \n",
            "  tblib              conda-forge/noarch::tblib-1.7.0-pyhd8ed1ab_0 \n",
            "  tenacity           conda-forge/noarch::tenacity-8.2.3-pyhd8ed1ab_0 \n",
            "  toml               conda-forge/noarch::toml-0.10.2-pyhd8ed1ab_0 \n",
            "  tornado            conda-forge/linux-64::tornado-6.1-py310h5764c6d_3 \n",
            "  traitlets          conda-forge/noarch::traitlets-5.9.0-pyhd8ed1ab_0 \n",
            "  typing-extensions  conda-forge/noarch::typing-extensions-4.7.1-hd8ed1ab_0 \n",
            "  typing_extensions  conda-forge/noarch::typing_extensions-4.7.1-pyha770c72_0 \n",
            "  utf8proc           pkgs/main/linux-64::utf8proc-2.6.1-h27cfd23_0 \n",
            "  werkzeug           conda-forge/noarch::werkzeug-2.3.7-pyhd8ed1ab_0 \n",
            "  yaml               conda-forge/linux-64::yaml-0.2.5-h7f98852_2 \n",
            "  zict               conda-forge/noarch::zict-3.0.0-pyhd8ed1ab_0 \n",
            "  zipp               conda-forge/noarch::zipp-3.16.2-pyhd8ed1ab_0 \n",
            "  zstd               pkgs/main/linux-64::zstd-1.5.5-hc292b87_0 \n",
            "\n",
            "The following packages will be SUPERSEDED by a higher-priority channel:\n",
            "\n",
            "  ca-certificates    pkgs/main::ca-certificates-2023.08.22~ --> conda-forge::ca-certificates-2023.7.22-hbcca054_0 \n",
            "  certifi            pkgs/main/linux-64::certifi-2023.7.22~ --> conda-forge/noarch::certifi-2023.7.22-pyhd8ed1ab_0 \n",
            "  conda              pkgs/main::conda-23.7.3-py310h06a4308~ --> conda-forge::conda-23.7.3-py310hff52083_0 \n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "python_abi-3.10      | 4 KB      | :   0% 0/1 [00:00<?, ?it/s]\n",
            "gst-plugins-base-1.1 | 2.2 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n",
            "\n",
            "tbb-2021.8.0         | 1.6 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "cloudpickle-2.2.1    | 27 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "retrying-1.3.3       | 11 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "python-fastjsonschem | 221 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "dash-bootstrap-compo | 116 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "jpeg-9e              | 268 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "kiwisolver-1.4.4     | 76 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libprotobuf-3.20.3   | 2.4 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "typing_extensions-4. | 35 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cycler-0.11.0        | 10 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "glog-0.5.0           | 104 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "partd-1.4.0          | 20 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sip-6.6.2            | 692 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "gst-plugins-base-1.1 | 2.2 MB    | :   1% 0.007263006939842141/1 [00:00<00:38, 39.18s/it]\u001b[A\n",
            "\n",
            "tbb-2021.8.0         | 1.6 MB    | :   1% 0.009480285473244695/1 [00:00<00:33, 34.23s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "python_abi-3.10      | 4 KB      | : 100% 1.0/1 [00:00<00:00,  2.76it/s]\n",
            "\n",
            "\n",
            "\n",
            "retrying-1.3.3       | 11 KB     | : 100% 1.0/1 [00:00<00:00,  2.81it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "python-fastjsonschem | 221 KB    | :   7% 0.0725315200453322/1 [00:00<00:04,  5.16s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "cloudpickle-2.2.1    | 27 KB     | : 100% 1.0/1 [00:00<00:00,  1.80it/s]               \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "python_abi-3.10      | 4 KB      | : 100% 1.0/1 [00:00<00:00,  2.76it/s]\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "kiwisolver-1.4.4     | 76 KB     | :  21% 0.2098172551128869/1 [00:00<00:01,  1.96s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "dash-bootstrap-compo | 116 KB    | :  14% 0.13836669200236468/1 [00:00<00:02,  3.04s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "tbb-2021.8.0         | 1.6 MB    | :  92% 0.9195876909047354/1 [00:00<00:00,  2.76it/s]  \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | :   0% 0.0027393810944917607/1 [00:00<02:39, 160.14s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libprotobuf-3.20.3   | 2.4 MB    | :   1% 0.006631979385165641/1 [00:00<01:07, 67.53s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "retrying-1.3.3       | 11 KB     | : 100% 1.0/1 [00:00<00:00,  2.81it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "typing_extensions-4. | 35 KB     | :  45% 0.451088901737287/1 [00:00<00:00,  1.07s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libprotobuf-3.20.3   | 2.4 MB    | :  42% 0.4178147012654354/1 [00:00<00:00,  1.00it/s]  \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | :  24% 0.24106553631527494/1 [00:00<00:01,  1.75s/it]   \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | :  49% 0.4930885970085169/1 [00:00<00:00,  1.06it/s] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | :  74% 0.7368935144182837/1 [00:00<00:00,  1.41it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cycler-0.11.0        | 10 KB     | : 100% 1.0/1 [00:00<00:00,  1.18it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | :  96% 0.9642621452610998/1 [00:00<00:00,  1.63it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "python-fastjsonschem | 221 KB    | : 100% 1.0/1 [00:00<00:00,  1.28it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "python-fastjsonschem | 221 KB    | : 100% 1.0/1 [00:00<00:00,  1.28it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :   0% 0.0009111874734858015/1 [00:00<16:12, 973.84s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :   0% 0.0006924013097812081/1 [00:00<21:21, 1282.10s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "partd-1.4.0          | 20 KB     | :  80% 0.8010560797926954/1 [00:00<00:00,  1.16s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :   0% 0.0011306395165963997/1 [00:00<13:59, 840.75s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "kiwisolver-1.4.4     | 76 KB     | : 100% 1.0/1 [00:00<00:00,  1.11it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "kiwisolver-1.4.4     | 76 KB     | : 100% 1.0/1 [00:00<00:00,  1.11it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :   8% 0.07653974777280732/1 [00:00<00:08,  9.49s/it]   \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :   5% 0.04777569037490336/1 [00:00<00:14, 15.36s/it]    \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "glog-0.5.0           | 104 KB    | :  15% 0.1532833740305182/1 [00:01<00:05,  6.65s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  10% 0.09723499842729037/1 [00:01<00:07,  8.02s/it]   \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  15% 0.15307949554561465/1 [00:01<00:03,  4.68s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  11% 0.10939940694543088/1 [00:01<00:05,  6.50s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  20% 0.19673127588777353/1 [00:01<00:03,  3.85s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  23% 0.2323528057388794/1 [00:01<00:02,  3.14s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  16% 0.16479151172792753/1 [00:01<00:03,  4.37s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  29% 0.2894437162486783/1 [00:01<00:01,  2.64s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  22% 0.2215684191299866/1 [00:01<00:02,  3.33s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  32% 0.3161820532995731/1 [00:01<00:01,  2.43s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sip-6.6.2            | 692 KB    | :   2% 0.023125923646623917/1 [00:01<00:56, 57.52s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "dash-bootstrap-compo | 116 KB    | : 100% 1.0/1 [00:01<00:00,  1.28s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "dash-bootstrap-compo | 116 KB    | : 100% 1.0/1 [00:01<00:00,  1.28s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  37% 0.36971912192702266/1 [00:01<00:01,  2.16s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  29% 0.2908085501081074/1 [00:01<00:01,  2.69s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  41% 0.4054784257011817/1 [00:01<00:01,  1.99s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  46% 0.46017028325473464/1 [00:01<00:00,  1.81s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  35% 0.3517398653688537/1 [00:01<00:01,  2.35s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  48% 0.4847517358944464/1 [00:01<00:00,  1.76s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  58% 0.5834099905637422/1 [00:01<00:00,  1.45s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "gst-plugins-base-1.1 | 2.2 MB    | : 100% 1.0/1 [00:01<00:00,  1.54s/it]                 \u001b[A\n",
            "gst-plugins-base-1.1 | 2.2 MB    | : 100% 1.0/1 [00:01<00:00,  1.54s/it]\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  41% 0.4064395688415692/1 [00:01<00:01,  2.24s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  56% 0.5612914836672538/1 [00:01<00:00,  1.63s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  69% 0.6942126631901894/1 [00:01<00:00,  1.30s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  47% 0.47360249589034636/1 [00:01<00:01,  1.98s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  64% 0.6350976690196036/1 [00:01<00:00,  1.61s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  82% 0.8163217309826005/1 [00:01<00:00,  1.16s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  53% 0.5338414098413115/1 [00:01<00:00,  1.97s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  73% 0.7289499787886412/1 [00:01<00:00,  1.49s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | :  91% 0.9146873689264873/1 [00:01<00:00,  1.14s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  59% 0.5899259159335893/1 [00:01<00:00,  1.96s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  81% 0.8136904138228207/1 [00:01<00:00,  1.39s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "tbb-2021.8.0         | 1.6 MB    | : 100% 1.0/1 [00:02<00:00,  2.76it/s]               \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  65% 0.6494724285747732/1 [00:02<00:00,  1.89s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  89% 0.8902301615956281/1 [00:02<00:00,  1.41s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "typing_extensions-4. | 35 KB     | : 100% 1.0/1 [00:02<00:00,  2.25s/it]              \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "typing_extensions-4. | 35 KB     | : 100% 1.0/1 [00:02<00:00,  2.25s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  72% 0.7180201582431128/1 [00:02<00:00,  1.78s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | :  98% 0.9795265339972367/1 [00:02<00:00,  1.36s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "jpeg-9e              | 268 KB    | : 100% 1.0/1 [00:02<00:00,  2.13s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "jpeg-9e              | 268 KB    | : 100% 1.0/1 [00:02<00:00,  2.13s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  81% 0.8087247298244511/1 [00:02<00:00,  1.58s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cycler-0.11.0        | 10 KB     | : 100% 1.0/1 [00:02<00:00,  1.18it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  87% 0.8731180516341034/1 [00:02<00:00,  2.05s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  93% 0.9278177551068189/1 [00:02<00:00,  2.05s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | :  98% 0.9804402546501907/1 [00:02<00:00,  2.03s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libprotobuf-3.20.3   | 2.4 MB    | : 100% 1.0/1 [00:03<00:00,  3.27s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libprotobuf-3.20.3   | 2.4 MB    | : 100% 1.0/1 [00:03<00:00,  3.27s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "partd-1.4.0          | 20 KB     | : 100% 1.0/1 [00:03<00:00,  3.93s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "partd-1.4.0          | 20 KB     | : 100% 1.0/1 [00:03<00:00,  3.93s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "glog-0.5.0           | 104 KB    | : 100% 1.0/1 [00:03<00:00,  3.42s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "glog-0.5.0           | 104 KB    | : 100% 1.0/1 [00:03<00:00,  3.42s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sip-6.6.2            | 692 KB    | : 100% 1.0/1 [00:04<00:00,  3.94s/it]                 \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "sip-6.6.2            | 692 KB    | : 100% 1.0/1 [00:04<00:00,  3.94s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "plotly-5.16.1        | 5.7 MB    | : 100% 1.0/1 [00:19<00:00,  1.63it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "intel-openmp-2023.1. | 17.1 MB   | : 100% 1.0/1 [00:21<00:00,  1.36s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libboost-1.73.0      | 13.8 MB   | : 100% 1.0/1 [00:22<00:00,  1.14s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 22.6 MB   | : 100% 1.0/1 [00:32<00:00,  2.03s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \n",
            "                                                                        \u001b[A\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "Preparing transaction: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "Verifying transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "Executing transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n"
          ]
        }
      ],
      "source": [
        "!conda install -c conda-forge fmpy --yes # Install the key package"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#!conda install matplotlib --yes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EfPDDPvUPiBP",
        "outputId": "a89e5344-de29-4df6-ceea-2a29d6386969"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "Solving environment: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - matplotlib\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    brotli-1.0.9               |       he6710b0_2         375 KB\n",
            "    contourpy-1.0.5            |  py310hdb19cb5_0         204 KB\n",
            "    fonttools-4.25.0           |     pyhd3eb1b0_0         632 KB\n",
            "    matplotlib-3.7.1           |  py310h06a4308_1           8 KB\n",
            "    matplotlib-base-3.7.1      |  py310h1128e8f_1         6.7 MB\n",
            "    munkres-1.1.4              |             py_0          13 KB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:         7.9 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  brotli             pkgs/main/linux-64::brotli-1.0.9-he6710b0_2 \n",
            "  contourpy          pkgs/main/linux-64::contourpy-1.0.5-py310hdb19cb5_0 \n",
            "  fonttools          pkgs/main/noarch::fonttools-4.25.0-pyhd3eb1b0_0 \n",
            "  matplotlib         pkgs/main/linux-64::matplotlib-3.7.1-py310h06a4308_1 \n",
            "  munkres            pkgs/main/noarch::munkres-1.1.4-py_0 \n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  ca-certificates    conda-forge::ca-certificates-2023.7.2~ --> pkgs/main::ca-certificates-2023.08.22-h06a4308_0 \n",
            "  matplotlib-base    conda-forge::matplotlib-base-3.4.3-py~ --> pkgs/main::matplotlib-base-3.7.1-py310h1128e8f_1 \n",
            "\n",
            "The following packages will be SUPERSEDED by a higher-priority channel:\n",
            "\n",
            "  certifi            conda-forge/noarch::certifi-2023.7.22~ --> pkgs/main/linux-64::certifi-2023.7.22-py310h06a4308_0 \n",
            "  conda              conda-forge::conda-23.7.3-py310hff520~ --> pkgs/main::conda-23.7.3-py310h06a4308_0 \n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "contourpy-1.0.5      | 204 KB    | :   0% 0/1 [00:00<?, ?it/s]\n",
            "fonttools-4.25.0     | 632 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n",
            "\n",
            "brotli-1.0.9         | 375 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "matplotlib-3.7.1     | 8 KB      | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "matplotlib-base-3.7. | 6.7 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "munkres-1.1.4        | 13 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "contourpy-1.0.5      | 204 KB    | :   8% 0.0782994341642453/1 [00:00<00:04,  4.86s/it]\n",
            "\n",
            "\n",
            "\n",
            "matplotlib-base-3.7. | 6.7 MB    | :   0% 0.002337417250949647/1 [00:00<02:45, 165.50s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "brotli-1.0.9         | 375 KB    | :   4% 0.042610296794865124/1 [00:00<00:08,  9.18s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "matplotlib-3.7.1     | 8 KB      | : 100% 1.0/1 [00:00<00:00,  2.52it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "munkres-1.1.4        | 13 KB     | : 100% 1.0/1 [00:00<00:00,  2.36it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "matplotlib-3.7.1     | 8 KB      | : 100% 1.0/1 [00:00<00:00,  2.52it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "contourpy-1.0.5      | 204 KB    | : 100% 1.0/1 [00:00<00:00,  2.49it/s]\n",
            "\n",
            "brotli-1.0.9         | 375 KB    | : 100% 1.0/1 [00:00<00:00,  2.17it/s]                 \u001b[A\u001b[A\n",
            "\n",
            "brotli-1.0.9         | 375 KB    | : 100% 1.0/1 [00:00<00:00,  2.17it/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "matplotlib-base-3.7. | 6.7 MB    | :  83% 0.8297831240871247/1 [00:00<00:00,  2.00it/s] \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "munkres-1.1.4        | 13 KB     | : 100% 1.0/1 [00:00<00:00,  2.36it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "fonttools-4.25.0     | 632 KB    | : 100% 1.0/1 [00:00<00:00,  1.45it/s]                \u001b[A\n",
            "fonttools-4.25.0     | 632 KB    | : 100% 1.0/1 [00:00<00:00,  1.45it/s]\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \n",
            "                                                                        \u001b[A\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "Preparing transaction: / \b\b- \b\bdone\n",
            "Verifying transaction: | \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Executing transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#!conda install scipy --yes"
      ],
      "metadata": {
        "id": "RmT9vSpZPvnU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#!conda install xlrd --yes"
      ],
      "metadata": {
        "id": "-Z2W0-K0P0D2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#!conda install openpyxl --yes"
      ],
      "metadata": {
        "id": "hh1XE5MZP0PR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UTETJm3l6heL"
      },
      "source": [
        "# BPL_TEST2_Fedbatch setup\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mxILgQ103nZ6"
      },
      "source": [
        "Now specific installation and the run simulations. Start with connecting to Github. Then upload the two files:\n",
        "\n",
        "* FMU - BPL_TEST2_Fedbatch_linux_om_me.fmu\n",
        "* Setup-file - BPL_TEST2_Fedbatch_fmpy_explore.py"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RfWPh1B63yBF",
        "outputId": "ec187836-08ed-4e9a-c25d-0d03fb49a34a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Cloning into 'BPL_TEST2_Fedbatch'...\n"
          ]
        }
      ],
      "source": [
        "%%bash\n",
        "git clone https://github.com/janpeter19/BPL_TEST2_Fedbatch"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i6uOVB44300a",
        "outputId": "4a8f5843-47f8-4d71-aaa2-865da08601c4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/BPL_TEST2_Fedbatch/BPL_TEST2_Fedbatch\n"
          ]
        }
      ],
      "source": [
        "%cd BPL_TEST2_Fedbatch"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "b-y82jZY33cO",
        "outputId": "92c46feb-a4a2-40f5-ce42-6d43966b01ba"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Linux - run FMU pre-comiled OpenModelica 1.21.0\n",
            "\n",
            "Model for bioreactor has been setup. Key commands:\n",
            " - par()       - change of parameters and initial values\n",
            " - init()      - change initial values only\n",
            " - simu()      - simulate and plot\n",
            " - newplot()   - make a new plot\n",
            " - show()      - show plot from previous simulation\n",
            " - disp()      - display parameters and initial values from the last simulation\n",
            " - describe()  - describe culture, broth, parameters, variables with values/units\n",
            "\n",
            "Note that both disp() and describe() takes values from the last simulation\n",
            "and the command process_diagram() brings up the main configuration\n",
            "\n",
            "Brief information about a command by help(), eg help(simu)\n",
            "Key system information is listed with the command system_info()\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 984.252x787.402 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "run -i BPL_TEST2_Fedbatch_fmpy_explore.py"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HUFhuE-H4RCw"
      },
      "outputs": [],
      "source": [
        "%matplotlib inline\n",
        "plt.rcParams['figure.figsize'] = [25/2.54, 20/2.54]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cMO4OlAgJIlb"
      },
      "outputs": [],
      "source": [
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dx9oMnP0RJkM"
      },
      "source": [
        "## BPL_TEST2_Fedbatch - demo\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Y3NHWIj4TZ6",
        "outputId": "308b6814-98ec-4dc1-e034-e05df239efc4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Simplified text book model - only substrate S and cell concentration X\n",
            "\n"
          ]
        }
      ],
      "source": [
        "describe('culture'); print(); #describe('liquidphase')                                  # Pump schedule parameter\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "process_diagram()"
      ],
      "metadata": {
        "id": "Ibb01P6g_jOc",
        "outputId": "c536b663-e4ab-4d98-ace2-d58149dfc00a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No processDiagram.png file in the FMU, but try the file on disk.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 984.252x787.402 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAw4AAAE2CAYAAADI9MWkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABn60lEQVR4nO3dd5wkZZ0/8M9Tnbunpyfn2Z3NObNLXFhyFEQEJZ3IqRhQ786fnqce3hlQFO9Q8BRMqKiIIAgsCwosS9wFll025zg7Oc907qr6/TGxZ7q7qtP0dPfn/XrBzFQ99dTTtV1Vz7eeUEJVVRVEREREREQxSJkuABERERERTX0MHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTQwciIiIiIhIEwMHIiIiIiLSxMCBiIiIiIg0MXAgIiIiIiJNORs4eDwetLW1ZboYOaO5uRmBQCDTxcgJXq+X380U4ncztTweD1577bVMFyNntLe3w+12Z7oYOSEUCqGpqQmqqma6KDmho6OD380UyafvZs4GDkRERERElDoMHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTQwciIiIiIhIEwMHIiIiIiLSxMCBiIiIiIg0MXAgIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiIiIk0MHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTQwciIiIiIhIEwMHIiIiIiLSxMCBiIiIiIg0MXAgIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiLKCioAGdv+th7fffoQ3jjugay5SQi97c14/nfP4tuv9SGkqlAnoaSUmxg4EBEREWUNFR1Hj2Hr0V4092uGDQBUKKEQ3H1udHqUnAwaVCWEkLsZT/7xbbzSIsMr5+KnnBoYOBARERHlLAlWhxPzVs7HhTMsuVnxU2WEvK145vH38FqbDJ+eeIoSYsx0AYiIiIgoTqoMj9uNtrYQ/CFAGI1wFjpQbBGAEBCqAp/bgz53AANBFfbp07DSaZ4YOKgqZDkE74AXPd4QgoqAwWSC02mFw2yA2SBG0qlqAG0tXkiFNkjBAAKBEPwyIBmNcBQ6UGIRg+Xq96HPF0RAVqEKA8wWMwqdVhSYBvNSQwH0uwPw+EPwhxQoEDAYjXAU2FFskyCEwFBKKLKMoD+AnoEAvEEFkCSYLVYUFphhMyoIeH3o6upHX48bHkVGb0c3jp0yottshL3AikKnBXYJUFUVatCPzl4fvEEFCiQYzWbY7WYU2owwipEDgsDAADr9EgwGAYuQMeAJIqAIGMxWVJRaYRECQow/kPmBgQMRERFRllE9XXjnpZPY2tmOLc0yTJU1uOqG8/HF012wQAXgx+5Nb+Avf9+Np47LgMGMuTfcjMevL4VpTKVXVfzoa2vBxme24BdvNeOUx4DS6Q248gOn4Yol5ZhfZIQkAEAB/IfxrS9shOOms1HceAR7D7Rgf7cCa2UNLr3pCnx1lQXKQAdeemozntrajH0dQYRsLsxYOBsf/dBpuLphsMVD6TqJZzfswcvvt+BAuxf9shGuqipceNU5+MK55XAaVAghoKoKvD2dOLBtN379/EG8c8KDoN2FOUuW4p+unYc1Ff048uZO3PuLndgZUhAIKnj3J7/HswIQxgqsu/o03HTtQpzjUAFFRs/Bnbj3kfex+cQABiQ7qufMwrqzF+Cmc6tRbRoNVo699Dzu3uVEUZEFS6yd2LC5GYf6BYrmrMF9X1uFBVYDLBn4N58KGDgQERERZZm+3QdxZMlyXHndmbij1I1Dr27BXfc9j5r7bsD1FQJWyYqVV1yClVecjy+dPIG//vx5rJ+Qi4Le4414/e+b8e13CvDPX7gZV1cG8M6T/8BDj25GX98K3HhxAxaE1ZL9ePWZ3TjrqjX4xLWXYLEzBE93H46oAlD7sf6nT+AnfXNxzQevwJ0zbTC1N2Lz63txz/8EUPPD87HaAqgeL9SyaTj/g0vwmXonSgxeNO3chv/66d9gqroNn5ljhMsEBNuO4c1XduJ/13eh4tJ1eOhfq1Ac7MbmTW0wqCF4bNVYfXE1/nzhOvi79+Kzn9qMGf91O+6cb0KRCcBQKAAliEDXQXz7+69i78qL8J8fr0WNrxGbXt6Hjeu7cEy5GD++uAjS6BaQ249gS1sNjKcvwzfvuQqzTF7s2dWHYqPIze5eOjFwICIiIsoyonYeLjl7Dq5bU4FyEUBdsYKr33oWz27pxVWXu2CxSIOV4FjjhJUBnGxqxzuHFcy9bC0+sawMZqGi+qY12P/Dt3HiWDu2Hq/FgrmmMRvJKDvzDNx4Zh2WV5lhFEBRYSGqFQXKiV14eJsL19x1Oj44qwB1FgHUWlDkVLD7++/h2X3nYtVSCYZpC/GROgACQ92SQqguXoVr/v4nvL6/D76GYhQagzi8pxHvHnJDWnMm7r5hDqoMAoAT195cDyENdWkSkT+iGNOXSPb70bVtH14MzsJ/37oQpxcb4RBFcAUCMLx6CI++dRiHLliFuWMjB5Rg+co5uO4Ds7CoQEDAghVrXBCSQJ72UgLAwIGIiIgo61jLXCh3WlFskCDBBLOtGLMqVbzc3IegXAgV0K7gyl4MDPjQ5TFhel0RLAYBQMDoLEZ9kcAJvw+dvX7IMMEwspEZs6YXo8hhgnGoEi2EgKrI8JxqxzF/K3577x/xuEkaHDegKggFg+jrB07vCQEwA4EevPf6HmzcfgrbG93o9AYRkmX0dMio9oQgqyqgutHR40Wv34z6GZUoM0pDXaYEpLge+asIhUJobe1DqGw2ZjokWCQBSRhQUuxAdaEFwWN9aFIwGDgMkYqKUFHqxDTH8H4BgyGfQ4ZBDByIiIiIsoxklGCUBAwCg4/chQFmIxCS45hyVVWgqApkRcBkNIwGGpIBJoMYHDitjM/NALvNAMOEJ+8q1EAIIUs1rrthCRa7zCgYk0BIBpTPNEISMg6/8Q6eeNePUFEtLryiBNUOAQQHsPFPm7BXVaCqg4OZZVmBogqYTAYkVWdXATmkAEYDzCP5CBgMEgwGCaqsIDRuE2EywWwywMpYIQwDByIiIqIsE3T74AnI8KmAAwpU2YuufqBwtgUGoaO1AQAkE8wmI2wmGd19PihwDG4X9KLXq0ItMMJmMYbnJSRIEiLMKiRgcDngEkFUzZ6BsxscqDaPS6SqANw4tLsRpzALq+bPwqWnlaParkL2NGP3n4G9I9mZYLeZYDHIaOl2w6e64Ij2ocTQf1ChKBO7LkmShIICCzDgQXcIUCyDab2+AAZ8QUh2CwrH5y0NtqTk83iGSHg8iIiIiLJMsKMTR1t6cLTbhwG3G22nmrG724a505yDrQV6SDa4Ch2oLlJw8uApHOsNwOfzoeVoMw73STA7HagpMemrLEoSTNXVWOLoxe7dbTjS6kG3OwC3x4uurl4cO9aFthCgqiH0e0IwFjhRXlKAcrsEEfSju7EZ+7oHWxsAAMKKinInqgqBrsMnsa1pAH2+ILxeL9qae9HpCcI7lFYAEAYT7MYQurt98AUVhBQViqpChYDBZERpXRnK3e1471g/Ot0BDPT34dipHhzpllFYW4xqtizowhYHIiIioiwj+lrx/u6TKLEqWFHgwfGtB7HTMg1fWuyA1SiAoA89AwEM+P3o7HCjJ6AgMNCPxlYjjJIJsizDZHWgsqoMy2bZsGHLTjwx34x1JQHsevkADqAUZ0wvwcJKfVVFISQYKmfig6u24cdv7MDfQ7PQNcOJUuFHZ1svDh4JYPEtZ+OiQjvqa50QJ7txqrEDh8pCcHh7sOeNI9gXBFwjGZpQO7MaS1t68NYLB/DwP6y4aVUpChU3jux1o+yMWZhX70KtAYAwQDI7MaNSxau7T2BvZTn6nVYUFlrhclpgM5vgnDsT60r/gX+8cADVaytQ7m/F1h2t2OW2Y+lZdYP5kCYGDkRERERZRDIaUbxoJurkThzdsBd/bFZgqa7Hhz99Pq4sEzAKAfnw+3josd348zudGBje8NDjuPwZQFjn4PbPLMS1Kwswp64ep19mwr+GtuDB3zyFhz0GVMyYgQ9ccxquWFyG2WFTsQ6ONzBKER7PCwGgAJfcfhXEU2/hiTffwPef9MMrWVBcUY6lS+fjMouAgBmrrzwbJ598F+s3/B3PPi7BWeLCjCVzce3cVrxhHH25mqmsHqvPdaDEtRu/fHYL/uO5AQRsLsxbthwfUyXYhoshDDBYavCRjy7CjkdewZdf8cGjlmPdNafh5g8twtoCM8zFs/ClLwzgBw+/hx/fNwC3wY6aObNxwUULcMtaF8bGDUKSYDJIkT9nnhOqquoeQ5NNPB4PBgYGUFFRkemi5ITm5maUlpbCbDZnuihZz+v1or+/n9/NFOF3M7U8Hg+2bt2KtWvXZrooOaG9vR12ux0OhyPTRcl6oVAIbW1tqK6uDptqM/+oiFlzGz42GtW7zs5O2Gw2OOz22IOph9/iPJSfGrZq4r9D7Grl0PSpeqqeQkBofVYMBxmx0unZ59g3QY/PS/st0fn03WSLAxEREVHW0K7IDibTWYEVOt9LMJSfVlo9FWf9lWudn1VHutTvMz9xcDQREREREWli4EBERERERJrYVYmIiIiI0iYUCqGvrw99fX0jy0pKSmC322E0siqaTfivRURERERp4/P5sG3bNrz77rsjyy644ALMnz8fTqczgyWjeDFwICIiIppCmpqaoChKWvfR3d0Ni8UCu92e1v0AQFtbG/74xz/i17/+9ciyu+66CwBQXV2d9v2nmyzL6OzshKIoqKmpgSTl7kgABg5EREREU8g555yD3t7etE7tqSgKhBCTMn2ooijwer1hy+69917cf//9OVPJVhQFsiyjsbExp1tRGDgQERERTTEvvPACVq1albb8Ozo6Bt/jMAnvGGlubsY999yDn/zkJyPLvvWtb+GGG25AXV1d2vefbqFQCI2NjVixYkWmi5J2DByIiIiIpph0twYM55+pF5Zlev+plAufQa/caB8iIiIiIqK0YuBARERERESaGDgQEREREZEmBg5ERERERKSJgQMREREREWli4EBERERERJoYOBARERERkSYGDkREREREpImBAxERERERaWLgQEREREREmhg4EBERERGRJgYORERERESkyZjpAhAR5TcVSigEf0CGP6RAUQEIAxwFFpgFIMRklUFGICij1x2EPH6dLCOkAKqQYDZI6S+TqgKQMdAfgGq2wGqWYJQEJuVQEBFRVAwciIgySVXQunMb/vLiXjy9rQMn+iUYnTPwrQc/iA8VYNIqy337d2L9K4fw04Ml+NS15rB1XYeP4L0WBZ7Ccly0rBQFaS+NCoQO4a5Pb0D3Bz6MO9ZV4/Rq3q6IiDKNV2Iiokzyn8BTz+zBZm8pVnzoTHxncSHsJgvq7JMXNMSmovPwQbz0fggd1UacOSmBAxERTUUMHIiIMkhx96PTa0BxfQ1WrZyBVdMkCAhIU2gEmjr0P1XNdEmIiCiTGDgQEU0yVQ4huHcz7njkONz+AZxodCPY+C727t+Lv1pMMDtq8Ikvr8W5tsFWB7m/HTt2HMPr7zdhZ4sXHsmOhoXz8LEr56LBJmAaCjKUgAc9zU14/pUDeO1wD3phQ/3cObhi7QwsrXWg2AgAKlRFRvveHfj180ewv1uFvboOC519GPCPRgaq2o8NDz2HJ44H0drWhVa3iuC+NtyxezPMkgRD1RJ853OLMM0kwRjoxeEDjdiy/RTeb+xDa38IsDkxb9kCfPDceswoNMEmAUp/F1p278bX1odwzfVlOLLxIPZ1BIGiKqw6bRYuOK0Wcx1R2lnUEPrb27Dz9ffxi71WfOT2tbiw0gCTNDXaZYiI8gEDByKiySYEDK5ynL4M8A20INgjw1NcihlzKjHfZYTRUowKw2DQoPo6sXnTTvx9ZxeO+Y0oqyhGlRpA43vb8Eu7E5+/oBJVNgMMoQE0HT2BF1/ciw0nVNTUlaFC8qN53x78DQLeM6bjvFkFsMpB+DuO45End+JtXzFmV9tgkTtx5Gg3jnWqUEZaOkyomT0Na1whNO4PYFuLArezAquXlcAhBAxFLhRIg1Pzqb4BtLb143iXAnNRIWaUSBAhH46/8x7+ZDDh+jWVWFhuhhQKwtfVjq07O6DWGnD6tHqsrujBvv3N2LpNgmwrQMOaIpgnHDAZ/S1t2LH1AP6ytQ+ORTMw3SGBMQMR0eRi4EBENMmEkCBVzcBHr6xHqGM3Wvd70DV9Gs5ZtwhX1EgQkgF28+DT//6TR/Di26dwUJRi9opZuHSBC8VyH979+xt4cONBXLCiBE6LBHNXB/bvOooXdvbDtmYFrjm7GlViAO+/sgV/3XsSW0udmF3nQIPiR+veffjbzhBW37wI1y5wwNzViDfe6MXeox4oRcOlNGP+GcvQICs4YO5Cv5DRWTULH75yBsoFIAwmOA0CkgBUgxlFFWVYvKwMJZUOlNpNEJ5uvPm3jfjTO6ewpMGJ6WVmOAEAKqD40Gcow1nnzMR0Qy/ekd/Akwc7sHVvJ647rQhVYQGBAndHG3aeOoyXd3Wjt2ombrtwNuY7BcTkTDlFRERDGDgQEU02ISBMZhSZzFD8JliMEsxmM+wFNpS4hh75qyoABSe3HcTOXhtmnDsXH7p4FpY7BFS5DLPNLfjLfxzCey0rML/YBNPJFuw/1IVThdPxnx9ainVFAkAFZpk7sOPBI2ht7ML+3lrUmHw4sOMkmosX4IaLGrDMZoBFLYSxrw+tp47iH/JwESVYHXZYoaDQZoTFBJjMFhS57CgZV18XjjLMnetE7YAP3e4gfCEZstmJhdMLENzYgaY+H7oVDAUOAsLgwOq1c7Gw1ACzVIHls0vwXmMXtrb3oUUBqgzDOasIuXux/70mnDrRgwOGOtx49TKcV8lbFxFRJvDqS0Q0ValeHDjaA3fBHFS6rKhQ/OgdAKAqQEkJGgy9ONkchHuGH/72fjT2KbDWVGCeYSgdALhcKLcE0N3vQVNnAIFSD442+2CaXo05ZgGTACCsqCx1Ynq1FVJj3IWEIvvQeuQY3tpyAM9sb8PRLh+8IQVqMIDekBHuoIyR4RNCgjA6MaPKMNJiYLOaYJEA2ReEZ9wA7PadW/GnrgFIlTOw5sJ5uLzeNEVmmyIiyj8MHIiIpiw/+r0qfAe34cFd2/CLB8ZWmVXIIYFV3iBCIQneQAgDra04vGM9Ln4lPJ0iC0w7owEL/EEoShAeH2CvNcOE4SlfBSxmI+xWE+KezEkF+vZux2PPHsQzJyxYfvF5+NyyEpRZBALvvYzPPWEYNyOTgBAGGMfuaCiAUKEiPG5Q0HTSj+nTbAj5u7Bn8x78fdVaXF0uJunFeERENBYDByKiqUpY4LRJcC1ehctXz8AHFjrHVewF7EVFKLcHsNdiQlFNFRasWIl7rqqccHE32+0oLDBB6jOjwAr4/DKUkbUqgiEZgYCM+GdcDWD/3hYcCzoxe+0K3HXNdBQNFbJtlwpJJDOHq4R5l12Iz15QANP+XXj8H0fwf4+UY+W/LEQdJuut2kRENIyBAxHRlGXDwllFsLwXgB9GWKpKMM0wdr2AkAQkYUV1uRN1xRa81eVFqKIE80zjshISJEmFz2fH7Ho7AgfacVKehbkGwIQgOnvcaGr3Qo5QCqMkIKkqFFlGUMW4N9MpCIYUqAYzLDYz7JKAgArAh+17OuD2l40JUOIl4CiwwGovxdIVM+FzD2D/hnfwP6/V4d5znRh84wUREU2WKfSKISIiGiEACAn1qxdipb0bh9/Zhd8+dwCvH2jDvsOnsPnt3fj179/GxlY/ukMCJQ01WDCnGHVte3H/n3Zi4/527D/ShLe37sNjf30PT29twl6vgMVmxbzTZmJ6+wH85e1OtLr9aD92GO/sacbmU6GIBSkqdsCpetFx/BRe3tuJk+19aOryI6iqUGFGTaUTxaoHrUdO4Y0WP4JBLw5veQdP7AugP5DcW+OEEBBCgq2sGgsWz8a1s4J46+l38Eo3IPONdEREk0p3i0Nvb286y5FyoVAIiqJkXbmnKlVV4Xa74fV6M12UrBcKhSDLMr+bKZLt302l34dAKIRgwAvvQB96e8c9Q7cX48zl5ZD39+Lojj34y34jDGJo0IBUiIr+fgxY/DDAhKr6clywpB+vHDuEJ9uOwziSzoH5RYWY1t+HAXMIxopaXLO8HW+/9g5+vscCq+pHf2cAVqcRkhqECnPY91N1udBQ1YWDe5vwwtNu7LQbYCiehtuurEOFUcBaVYb5tV60HzmKx//Si81OCarPg6q6Alj6FAS9bgz09aLPPYABbxCqGoKvvw996uBNyO32wx8MQQ764O7rRa9RBUIehBQVIb8b7oE+9NslmJ0FWLasEjWPH8ajL07H9AvKUGoSU/oJmCzL8Pl8CIUiBWUUD3UoUOzr68twSdJPURQMDAyk9T4RCoXg9Xon5bvZ39+PQCAQtszn86G/vz8n7oXD301VVdHf3w9FSbydNZNcLpdmGt2BQ7YdBEVRoKqq/nKrARzfcxxHVRfqqlyYWWaZ0jejTNB1LFUf2pu7cbzJh2BVDc6os7ArwTjDF5hsO6emsmw+lorJhUXLGuAucaHWqkBRxp0xRicWrpwLW3E7dh3pxpFOP9yKAQ6nHdOnV2GmQ8CiKlAkC0qqq3HueVbYdzRjR5Mb/bIBdocdVdWlmFdTgHKDAgUChsJKXHHJfODtNhwf8EEtLMKsBS7Mm6/gcJ8VBfCGHVNjaSWWLhMQ1jbsavPCHZARCsoIyTJkIcFWWYOVK0yw2FqxvcWHjl4TKurqcfmSEkhlKuaXWVCgKlAMZtiqanDZ2QpqJQWqDCgCkApLMHe+GVLIiVJVgaKogFqA5WfNg6feihKzCllRYbQ7UL94Hq5rFtgZCkCWZciShKl+kVEUJau/o1PF8DHMl2M5Gd+buOpJSRiuk41flivnxvBnUFUVsiznxGeKRnfgUFxcnM5ypJzH48HAwIC+cqsqgF688OpW/E5ejKsvLsOKOcUcADKGz+eD0+mE2Tzxna5h5Dbs2dyIv61vQd8l03HpkmJImPL39Unl9XrR39+fdefUVKX7uzlVFRfj5lsXaKYpq5mO1WdrZ1daUYXp8xbgOo10JaVl+Nzyics9Hg+2bt064ftZXFaNxafFKGJZFeYvXzJhv2eeE5YKJbX1uOes8RsX40OLJ5QQt39h7sT9lFbg5k9NXD5Vtbe3w263w+FwZLooWS8UCqGtrQ1FRUU5//I/SZJQWFiY1vtER0cHbDbbpHw3vV4vLBZL2DK73Q6Xy5UT98JQKIS+vj5IkoSioiI4nc5MFylt+FCdiIiIiIg05eVD9fHNZYMLI6aE1ti7sKce6vg5yKOk15EOYni2kOF+c1ob6M17dP7ziMchStphsbeZOMPJSL+/GPnGynP4+GqXNTxvzfSCs7EQERERxSM/AwdfDw7tPoQn1u/E+n19GLAU47yrVqJmQEbIOi6tIqNj91b8z5924s3j/eiHFaV1dTjjjHn48IVzsDxsHEkAx7fuxIbXD+KFne041icDVjvqptXj+lsvxLUzzSg0A1C8aD1xChv/vhvP7W7FwTY3PMKK6obpOP/CpbhseRWWlY2dS1HG0ddfwwPPHsC7pwIIFpRj0ZwynFfvxc+e6MUtP7gJn6gXMAsAqh/NB4/hjdf24Il3m7CvMwhjcQXOu2wt7riwGg2FJox06FBC8Lcdxc8f3oz1ezrR6pNgLihATcN0nH3GAnz8klpUjP14/h5se+sg/vHmEWw60IMmtwprcTFWnLEKd14/D7PtBow0RKoh+Pva8PeHX8L9LzehKWTFjJWrcOsVc3D+/CKUDE0pqaoqvCf34Vd/2YYX93bi1ABgKi7DohXzcNPVy3BB1WDC/jeew6ef8gAmP4yKF0e6LJi2ehn+ybUf9zzVBH/1Qnz69jW4aE4RaiwAlCD83a146onN+MOWJpwYABxl1VizdgmuOmsG1k235ueXn4iIiChB+Vd3Uvrx/hvv46mXDmOTrxRX3LQGS21ubH55C5476kX3jNEn1WrAB/fxHfj3/92M43WL8ZFbKlAp+nBw1wm8t/Ft3N0YwHc/sxhzhur4nn1b8au/HcYepQjzLlqAj9dZILwDOH6kCR29MuThsTKyDwMDHpwacGD5ujX4QIkVDtWHk7v3Y+Nzm9HaugjXXbEA5xQLqIoC95438I3f7EbP9Pm48royTDcNoPlIIx57rgPdISdkdaTAOPT6Fjz2ylG80mnDvLPPwkemmeE5eQiPPfs87g1dik+srcZp1WZIahCevlY88dCL+GNnHW68cRVmFQDBgT40dqhQ3B70K0DF8Jzxch+e/8NWPLE3gL7iCpz1gaVYXGaE0t+Nd94+if3uOai1DQcOKgK9vTjx1jb8dels3Hb7fPTv24Un39mGvzrNUM02fGiOBUIOItiyF1///iZsszXggksW4KPFKjxNzXh/z05872c+FHzlLKy2A1AUBPp7EJw2A6sbzDit5Sh+v/EN3LdsOb7wyUo8+6fdePX9Wah32VFVI6Pz5An85Teb8JtThbj8qgtwe7GCroOH8PrWbfh9ay/6r1+Na2vDJsQnIiIiohjyLnCQ205h54E27A0UYsm603Dj2SUokkKYbe3FwYf60D8yEF6Bz+vBrrf2YZuvCp+8bhmumGZHoQhieZkZpW8cwp8PHMTfj87HnLkGACo6T7bhRJ8Z5UvrceG6OTitQIKQQ1ixYBqCBRYUDDciGAtQPX0Grr22FkanFQ6LAUZVhnu6hL5HduLgqQ7sOOHDWUUWqLIXb2/ah/2GenziskVYN9OJMimA1goblJYO7N8/+tmUruN49b1T2OVxYc6ZS3DHuirU2CXI80phaXsWv9x+FLtmF2B6ZSkqEUTA141dB70oPncxrlxdhXIroASD8PhUyJIJ5WNGwHgOH8WGXQMIzlyIi86cg8tnF6DIIqAGa7F4th8OlwF2gZE+SbLBApTU48bL52NpkQHyLBO6T72GN9u6caTZDXm2CQh4se3l7Xi9rxQfvmkVLp9diGorEOorQkPJfjQ/dRBP7ViOVWfYBjOVXJgxuwZnr3HAfmAAL27pQ+H8uVi7UkbnKzvxQs8AetxB+Lu6cXzHATx7VMKqD5+FfzqzDCUWFYE5hSiQtuOVEy14+b12XFZbBVtav21EREREuSPPAgcVnrZOnOoIwGevwvKlVWgoMQKqCteS6VhQtA9Nw0dElRHwDWD/gW54q9Zg3bwS1FklmARQNKcSC5pbUby9FduPeSDPHXyDqdFkhAH96O3uR2NLPxpqnKgocqCuaHB0/UifeskEsykIB/rw7tajaOzxwxdSoci92NPaj/YiL2p7AlBhgir34f29fRB1a3DajGLMKLPCKhTYAxVYM8uJX44JHDynmrG/JYhgUT1WLK/DgiorDFCBQivOXlyCh//aiZOdHrT7S1BpERDCAItJhbujC8faCmCsdKLMWYCaYgMMYvSYASpajrbgsLcAy2fVYM3CcsxwSYOfR7WhtARQhj/fUOBgsFhQXF+L06YVohCAcFZjTpkJb3f60D/gQ0CVIfy9eG97B7y1Z+GCheWYU2SCTQLUAhXBgR7MsxzC2wd6IZ9hgwpAmG0odjlQXVkAY1cBig1GlFS6UFIoo7pQIOgPwB8Ioq+7D0cOt6PZXImPn16LmWUSJCEAZw2WNBzB/qZ2vHekE+1KFaZxegAiIiIiXfIucHD3eNDvk2B0OlBbbhypzIuCYtS5jLCN9F4JIRT0oqVLhqm+BLUmjFSmDQU2OIsdKEUITe1eqCgEALjq67B0ugfvdbZi86YAOqsLUV1WiNqKYiyYXYYyi4BRElB8A2g53ohX3jiIV08GoA4N5lVVP1oGAvAWKPAHQlChQpX7capdRcHiYpSYDYPjGCDBajGjqtIJE/pHPl1/ey+6PCG4zQNoP3EcL3aNfvJQuwyf24vu/gB6fQCsRlhsJVi9qhpbDx3B868OoL68EFWlBaiqKEJdlQszSiwwCgBQ0NbuhtdchupSG6qc0mgQNDR4eXz922gywlXmhGMkoQUOqwQjZIRCCkKQIYX6cbQ5BDHdjyM7DqHTPJxvCD1tveiHjNa2foTUqqEDL8FoEDAaBCSjAWYhwWwSgDDAZBSQgwpkJYQBtw8tHW4EUYqug4fw98MYGWje2TiAdncQHsWNDgUMHIiIiIh0yrPAAQiFZMiKgMFggGXs+GMYYTMLGNSRKYegqAr8QcBoMcCIMS0GQoIkSTBJKgJBeSQH+6yF+PClJtRsO4E3DjThtX0H0eNVIEqn4/ZPrsM1s2xwmQFvWxN2bNmJX21yY/bFa3D7mZWodhhgkFvx9O+24HW3CkUFABVQZfiDgNlsCJuzSEgCBpMh7B8wEAhBlj04eeAQnm05iZfGThukqgjZCmA3G2BQAQgTrAVluOSGs9H37C68duAY/rHdi76AAYV103Dm2YvxiQtqUW0GAGXwc5qMMBskhB22iAQkIWAySuEzFw0fWqhDgVIIXr+C4LE9+Pkf90MSo8dYBaAKJyptAvL4DIZ+F2I4bhEQ0tBMSqqCkKLA7/PD130Cf/p9a9gxUlUVqsGFmnKD9sxWRERERDQizwIHAavNDLMJUOQQfAEVsIjBCqQahDegQDYMVSeFBINkRIEN8A/44VUBuzpYUVVlGcFACB5ZwGEfU40WZtQtWoQbFi3C9UoI/oEe7H1vB+558B3c9+R0nPbpuXAUG9DW1IkDJ92Qpy/Cv964CAsNQ/l6u2AWAnJotLyQLCi0A163H7KiDNaohQpZVuD3BOAf8+kcDgvMljIsO3MGPviBOVgZ/q4VAINvm3XaByvgwmCEtaIBt9zegFugwN3Wgrc3bcXjb5zExhcVVC+oxSemD21nN0Py+TDgD8GjqFCloTAmbLrVOKY4FRIkyYLiAgMqT1uHe68sR5Fl/PYCktUBuwDcevOFARaTCYVFThTOXojvfG4haiaMgTbAbLaglGOjKQ1kWYbP58t0MRLm9Xrh8/ngdus/67KR3W7P+ZeIERGlWt4FDsXVxah0tWJPdx8OnZKhzhuqPQ60YX9rCAOlw0nNsFhdWDDNjOD7x7HVvQDnFaqwAgi0dqP1RCeOSjacObNo6CCOe+eDMMDiLMWSs07Hja+9h6919aM3pCAIAxRZhawKGGxmFEij72nwHGzEgU43mtVSzAQAGCAZy7B0lgFP7m/EEU8NKotMcEJBX78buw+2I4TRNz4Wz6rC9MIu7PUG0OV3YsaMSG0DozfK8HcdCNjLq3HuubPR0edH8w4P2noUYLoBgAFz5pSheHsbdh3uxsKZFZhRbxx9Yq+qkCHGjIvQ809hgslSjtMXmPH4sR6gZDZqXUZMiHWAOG/uBpQUF2DedBekjV04ZS/BWaVR3lzNOgOlwY4dO3D++ednuhgJU1UVsizDaMzd24PRaER7e3umi0FElHVy984QhVQ3A6vmtuLYay147untOO3jS7HK2osNv3sbr3f50Tvy5nMBW0EBzrh4Eea+sRXf+3Eh2i6sQS16sPvdA3hljweGmUvxkcVGDA8g3rv+BTzZaoOptAyLah0oMQXRdXgffr5dRe1VdaixGmGFhMqqIsyqtCC4ZT9+v3UG/m1VAbxH9uDnjx3Ae41u+OtHRl5AMhbg0qsW4lc/eB/3/8GEk2dUYbaxB0d3H8Zj74fCxhZI1Qtw5Zo29Lx6CH/8RTeaz5uL82bYYfQO4OTxZrxzwo5zLp2LsxaVoVIeQE/zYfzwwZMoO2MmFtc54ZL7sf/d3Xhxpxve0llYOX0098IlC3H9rrfw2ObNeKixGYfOnI7VVSbIvR146YU2LL7zYlxcZkax/iYHmK0FOP/6M7DiG2/g3//Hg6vOqsOichPMIS/aW7pw+FgHvKsux11nRwonorNVVWLumgW4+p1X8L3/egYt1yzA8goTFLcbrU2tONhrQqhyNr5xVbWObldE8SsqKsLevXszXYyEeDwebN++HWeddVami5IWzc3NWLNmTaaLQUSUlfIucBAGJ5aftRTGAgee3LQH37lrG4ImO2YtmoMz6wewdWR+TgFhtqFw7mp8707gwRcO4g+/3QUfjLAXlWLeWQtwxbp5mG8ZnYO0qKoItiON2LrnCF4eCMITAiyOAky/6CJ84qpKVDoMEELAXt+A1ecJfMq/E0/+5jFc/RsjXKWlWHbaYpyu7sOxkbhBAJBQuORs/PctKn77+j489oc9EAVFmFVbiA+cL+GXG3wwm4aTWzDv3DX4WPlxzHr7CDa98gY2PR2EaraipKwEcxfWo6rIhgIBQBhhsjoxs8SLl15+Cxv6AwjACHuhC7OWL8ZVZ87FWueYKMDkwuU3n4/yrcfw6vtN2PjUUfwtAFgKCjBj3iLMskuwSiOHQs+/BGAwwTptKb7zZQMefekw3nruCJ7xKlCNZhS6nJjWUIOL641xNwwIox0VDbPxyTvNKHthN155+hU85ZEhma0oKi3CtNnTcHpDwYQB3USpIoSAzZadk/2qqgqz2Zy15dditVq1ExERUUR5FzhAGGAtLsOCFTYUVtejpT+EkGREUZkL9nPqcJ3RhdpyJyQM3vwNVgfmnbYcn62aiS5PCCFIMFltKClxorbCCsvoiGmUzpmPa4qnYe1AAJ6AjJAiYLCYUVxajNklJliGxgUIkw0V06bj0qtdmHumF25ZwGyzobLKDsyvg1s1w1I6XAZAWAuw9OzV+OysAfR4FSgmM+whN7wHdyBkLkBVoYAkAAgJFocLMxfMhquiEiu6fej3y4DBCKvNiuLiQlSVWGEDICQzrK4qXPrBs7C0zw9PQIYMCWarFUXFTlSWFcAeNgZAQkFZJdac5ULD/NnoGAjCKwMGkwlFJcWYaR+a8Um4MH/Vcnyqzo/Q0HEcZMayS8/Hl7xm2ItdcAwdXxitqJ8/Dx8prMIF/X54gipUyQCLxYwCpx01lYOFsC1aja+UCLgqClFtNAAN8/HZf6uBeZYBAiqWXXU5viG7UFvhgCQkCIsNFQ0NuPpqF1Z2eeEJqhAGAyxWC5yFDpSV2Bg4EBEREcUh/wIHAMJgRkGxGfOKizEvbE3x+JQQQsDqKsFiV0msHAEAFlcxZrmKMUuzABLMNgeqpjtQNX3cuoqi8L9VAKF+HGkOwlxcgtnVBhhCXrQdbcM7x9womD0T823AyPxFwgBrgRO1BU7Ujs87jASj2Y76mXbUa5V3ZBMTisodKCovxdyoiSworaxAaeW4xcKAioZpqBi/WAgY7U7MnO0cGtcRmam0CqtLxyxwlWD5quF/E4GKmTPC8xYSDBYb6hpsqGvQ+FxEREREpCkvA4esE+rFti1H0OO0wW4dDBw62rqxf8CJtec1oMEw8joFIiIiIqK0YOCQDSQTrKFe7H7vOE4NBBEyWFBcVYUVa1fglvPLYAYnCCIiIiKi9GLgMNUJAViqccOnr8ENmS4LEREREeUtjg8lIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiIiIk0MHIiIiIiISBOnYyUiIiKaQlRVRUtLC06cOJG2fXR3d8NqtcJms6VtH8Pa2trQ398ftqynpwdNTU1QFCXt+083WZbR3NycE59FCwMHIiIioinEPTCAW27+KIyG9FXTVFUBICBE+l8hqygKvD5/2LL/+dEP8dP7fwxJyoXOLyoURcHAwECmC5J2DByIiIiIppACqwGP/vscrJxVkOmipERzdwA//OtJ3L++aWTZf91Qg+vPLkNtqSWDJUsdf1BF7cc3Z7oYaZfzgUNfXx8WL16c6WJkvVAoBIPBMClPJjLh7bffRlVVVaaLQUREBIjB/1J1z1WHsox3XaJ5jhcxnQAgBCBE3PtPtMyJ5jE+bcS/hZpkibJDzgcOqqqir68PGzduhMlkynRxslZ7ezuKiopy7hiqqop169ZBVfPjhCciouyTbEU51raR10Xb4+hyESPl8B1VT5mjp4n+qVP9CFOrvOOXa/2dy3I+cBi2aNEimM3mTBcjazU3N6O0tDTnjmE+DGQiIqLsNloxjfSsGxGWJVuV1VuFjpxSpLUMemjvX0T5PdX7yTW5MCKFiIiIKA8N9WmKU6ra2CPnM3mV6fH7VzXaDlSNT661fqL8ChoABg5EREREWSK5zj/AYOVYDP0WHzXsZ9TwQJ28oGFil6GJ+1bH/DZ+/fgjMLieXZdjYeBARERElONGn8WLkd+ip4q0PHy7qOHBJD2Ej39gtr5uVvnYihAPBg5EREREOS7Ws/hYqcYv1/c8fnKf2qd6b9r55W+rBAMHIiIioqySiup7Yk/W9W01uWMcRITRDsmYmN/EFKncXzZh4EBERESUVaZS9T39olXLo3dDmuwZnXLlSGtj4EBEREREGaGnW5DWcO/E9xt/pyQ1jm1zEQMHIiIioqwysdIaTzU2vVXe+CY11X5WHz7T0cS8R9fHSjV+6fgh3ioibx+pLUNjeHhOY+BARERElFUizRCkVV1Xo/w+PpUac722SJOiJmtsp6Tog7pjzaAUfenoOq3tiYEDERERUVaJ/Exfq7I7tloc/X0FIsGXyo1Sx/1MYNNoW6vAZFfqtVox8g0DByIiIqIskppn+lptFLHWxloX6z0RGkTEXzUWphdbIcIxcCAiIiLKQyNV4YhxgFbHnsnAp/xTDQMHIiIiIiLSxMCBiIiIKA+NPM+P2ICQaFelVGL3oKmGgQMRERFRFolvwtPoucSulifaVSndg6MnFwdHh2PgQERERJRFIg+O1j8d62DgEbnyn4rpWMN/JrBptK0FMNkVeA6ODsfAgYiIiCgr6JnNKFoafVXgVMzYlLqq/dR7yq9G/GvqlTNdjJkuABERERHpoadSr51m53EP/EEFaorqu3aLhEXTHHGUYFT0tg+gsSOA5u5AMkUbIUnAqlnOcfuNtffo5Zu4bfT3YuQaBg5JkGUZvb29KCkpyXRRiIiIiHS54Z49ONLqhaykJr9lDQ5s/d9VCW0bq9r+fxua8IO/nkysUOPYLRJ6/3Q2hBj7lumxrTT63jad712X2FUpCYcOHcLixYszXQwiIiLKK/qebufHM/BUiNSmEI/8OdIMHJKgKAr6+voyXQwiIiLKK/qedmfumXh2V6S15pua+Pnyp/WBXZUStH79enz84x+Hx+PB/PnzsX37dlit1kwXi4iIiGgC7d78iTva5sN1398ddb0vqODgKW/Yst++1IJ/bO+GzRz9Gfaek56UlTEe2scpfwKF8Rg4JMjr9aK9vR3AYJclNVUjjIiIiIhSbLQ3f+rrKwNeGa/s7Im6XlEBfzB8QMWhZh+Ot/shxaiD+wIpGoQRReRgKp0hVvZj4JCA9evX4+GHHx75W5Zl3HXXXfjqV7+K0tLSzBWMiIiIcpieSm3sNKmYbnU8RQV6PXJc2/iCCnzBlBclLhNHNqhpOT65hGMc4vTqq6/iV7/6FdavXx+2/Kc//Sl6e3szVCoiIiLKP8m+rI3Gij9oyL9jzxaHOP3kJz/Bs88+O2G51+vF7t27UVpaCpfLlYGSERERUW6LPjlo7GXpZTVLmFtji7o+KKto7wmgoz80sqy62IwihxEmY/TyNncH0N6b4WaJmPKvdYKBQ5wkSYLdbgcw2EXJ7XajsLAQAHDrrbfi0UcfxWWXXZbJIhIRERGNSHev/bk1Nrx978qo65u7A7j3yZP46XNNI8v+5epafPisctSWWqJu941HjuLepxpTWtZh8RyT8Wkj/Z0vGDjE6bHHHhv5ff/+/Tj//PPR1NQUYwsiIiKizEn3c3EBwGiIvhejhAmDoCVJwGAQQ9tFrsZLsUZOJymenLXaefKp3YFjHIiIiIgoZdSR/2s/ix9MISYsS/dT/NHZpaLtSWt9fmKLAxEREdEUlY5uRi9+eylCipqyOrE54jiFxF9SN7zsy9fW445LqxMtVnieAhBidG+jA6Ejl3N0fqXYnyPfJm9l4EBEREQ0RaWjUhprXEEqpKrMxQVGFBfoqarGrr5rV+4njlrQO8NSPgUNAAMHIqIUU+H19OK//uvrmS5IQkLBIFpaWvHSS89nuihp0d8/AL/fn+liEOk0sco7vCRSZTh/X2gmhj5l5M86uiTaMGcR5e+J8uFoxsLAgYgopVTIshtH9/0+0wVJytF9mS5Beni9MgMHyiLRKsHDT8TVsKWRK7TjK8XxmKxt4ssj0trIR2B8yujDmgdTRuu2pKfFIj8wcCAiSjGH3Yhf/yT61IS6b6sxEqYij3SYEk/jYhTiVLMXT23YOKnFIUq92P3zY28znr5n9cnvJ5roYUCkNLFKOzG1/rLESik0cxwbxOU2zqpERDTJdN/KYiSMuCrSfUvEXh1r+ch6nfdDVR3//E7fDlJ+u8145EKUfuqY/5ITu4qtP/9ES6LnWf7YQc3a28RTjde8/kXZX36ECRMxcCAimiyx7vK670IREob3Voial4iyMuYtWNVeHzmfBJ70TSiaGr484ueKdeDy9dZOuSbaMwEBdehpePqk5pl9IqJV2aHr1NZ7XLTSiSj7y9fnEwwciIgmS6Qxd8N142SaIfS08sfaXmN3Mcs2tkUjWreqhO+w40KdiPnoLBxRFoteuY01kDc1AUX636cQjb4m1+jPYvSd/7rShSXJ7wcSDByIiNJNjfGnCPuR6l1NyHyw0SP6jU+jt1NMkdJpjXnQE9OIRA5O6qaoJ5oCUjXWINJZocZcr71ndcz/o6+PRs8ni5WDiHJFi/+6pY77LfJe09/GM7UxcCAiSrd0PPiO0u1Ja1eDzyejp9Lo7RS2ez20goZUBkzjgxC2N1B+UWP8NSzSWTG2IpxIpTj6fEYxOhtFELvtIdbaRPcQ/vfoZ9caBp3P1xbOqkRENMlSctNJw51rbEVeTwCSrFR+hHy+kRMNSnSUUewJSxMVfz7aA56TpdWrc+zfU2KGuCmILQ5ERGmQzIweY8cCJ9MkHu+2Kb1JJlHwmGOhNbJOzSwzRPkl8nUo0c5HiZ2DWud9augveXzXw/y56jBwICJKg2TGBYx96p9MZT6jT8uS2LlWq4fWcGg+JaR8lEzVNfycGe5gpN2lMdH1sbZJ7/mbrrbU/LnqMHAgIsoCeioFufjMK18/N1G8Eq266hsOnfhZlplzmFeFdGHgQESUZpN1C0tdxSH12yeaRs9nSnZWFqJslIoXwOnfNvJZFqs703AKPbMyRQ9VouQ/8oqXWNPUhiWNnokGNWbS/LuyMHAgIkozPW8xHb45TUyXghuTRhbJNrLrrdxrfZLUNPZHmFlG6yV2RFlIIDVd83RPlxxx22ivldSTe+w0g9eMaHM0Dw9e1s4/8Q5XY1JFTZp/V5a8n1VJlf0IvXcvrrrjKbgdVkiSBAEJzplrsPLaL+CbV9fCkOlCElFWGj9LUaxZOoZvThPXj5kYMM5pPjIxK4jmZ9TYVm/a6CLMLJN/93aiKEbP0Ei/DT7DHw0HhOaVa1AqTzG914GEp3rmdElJyfvAAaoK1dOKY30zccsXPoT5ZQWwCwGTsxxlDUVskiGihGlN/adlwv0tzgzEhF/CM1fT8K6Dkfxi3JxHVo1LE89c7JP1fgiiqUXPt3timtElE0OF8McaAsNvMxgNICb3bIr/00XKI0YqkdgVIvZW+dNliYEDAEBAOGZi1fmX4Oz6YrgYLRDRFJDW27VG0JB05TzGypgBjQ6JzIvCYIJyQ6T5jyK2s8VcEi3F2O4/escOTfZ5FUcHownGtqfo+Vv/fvV0xswNDBwAACpU70ns2vw6lCMFcAgLHCWVqJ09E7V23mrisXv3bjQ1NaUl79WrV6OoqCgteRNNplTcbIfzSCqvSBsP3fuERqaa+4zV3yADtQ1eySkXjX/XcWzhJ16k0zDe8yS155XeC0M8nznc+KBA6+/wffIqAjBwGKF0vIZHfnQYDrMRRqkUM06/BB/64h2otXOEQzx++tOf4plnnkFJSUnK8/7d737HwIFyQmqa4gdT6hkcGFdBUnVv1Ns5OV334zR1xSKaXKl8zBAu2jP5wR9iTJcefWVIvKSj3aT0pR5/1Ru/Z73ljufzjVufx3EEAwcAgICh/iZ8/y9fYVelJAQCAUiShFtvvRV33313potDlLViPxOMnDJVYu0xkXtlMl2aEqcCIqmQimiKSKRj3qjwmYf0nBFizI/4Hk8kfr7Ft2WkEGjimA3tfGON4cjMdSs7sIpMKXPxxRfjzDPPxHe/+91MF4VoSorWA1aNmkbE3jD2qglptKYij9ZzSbNjgBr2I4yIkC5a/qkTHnoR5at4JhxIJo90nWd631URbVyTnm0i5a9nxILmdTVH6W5xaG5uTmc5Uk5VB/8pe3p6oCgKWlpaYDKZJiaU/Qh1uiGHVHS3taLV5INH55nW3t4OWZaz7tgkQlVVdHZ2xkzj9/vR09ODlpaWSSpV8lRVhaIoaGtrm9R9Atl3Tk1Ver6bk6mjoyPqumiXFqGVRs9A4xgiP38bEyaISOsnLov6FC7G9lEzi74opaLl39zcDKE1kCMFVFVFb28v+vr60r6vfJFN95hEKYqinUjFUHciINkzKdkzQaiq9sCoqKI/30+mXFott1odpLS2H72uhq9vbW3BwMBAvMWdEqqrqzXT6A4cysrKkirMZPP5fPB4PCgtLYUkSSgtLYXZbJ6YUPYhWGSDZLChsKQEpWXFKNT5Te3q6oLBYMi6Y5OIjo4OFBUVwWiM/pUxm81wOp1ZdTxUVYUkSSgpKZm0cvv9frjd7rSMA8lHHR0dcLlckR8MZMCEcTgR7jlp7R6bxsxzqXW+rKxsUgKH7u5uWK1W2Gy2tO8r18myjK6urqy6xyRKEsMdQqL13x/+Ee1Z+8Rt4hqpEO91JKlzKTOPD4Y7YiXbHWz8+tLSUhQUOPUVLQvpDhymyk1Zr2AwCCHESEXXZDJF/AyqQYJh8W340T1GrKwqgtNkgknnd3hs3vnAYDBE/axf+MIX8LGPfQznnntuVh2P4ac6RqNx0sodCoUghMiq4zTVTea/n5bh68LI7Wiyn7LrvudHSTFuY828svSlCiaTaVICByFEzGsn6Tf872U0Gifl3y6jxIRfovw92uIw/l0N47fRMxpipJPOyPGdzBM4nn0lc+EZu05v+KBnf4OMxsj1zVyR92MchGSAVLEKV12+DDUOM8w5fi1Kl6effhqrVq1CQ0NDpotCNCVk8lKSyADmaBsn0v0o2vp86wtMlH6jnW1S11lJs/NkmsTVxKFxPRnf4jL29+jdjiJdpVRdZcufymPeBw5EROnASvJE+XNrJZoKEr0KaU3jkMGrm5rIWxxiBUKRhkVTLAwciIjSYDJvPwnfxodf9pbu/aQoIwZjRPHQd2ZPPK9E2Bp1wvIMVK7HRAtJ7z1sFriEO3XmLb7HgZKiqipCoVCW9zk1IBRSEAzKkCQBg4HxNGWXhM+8ODcUQGq6PCe4fbZeYYjSYXTI87BIT9MjnzVBWdEZiesL14UQMBpijSlIjKyoUJTUPTIwGSX9s8BRRAwcKCmyLKOyshKHDh1CcXFxpouTAIH+/k9i8eLfQggJ3/vehfjMZ1ZnulBEUxfvtkRTgvbIhqgTMGPZF7aitSeYsrIsme7AK3cv01WOeHz3sRP48TOnEt5+LLtFwolfnZ7FDzmnBgYOlDRVVSGEyOKTUWDz5k+gqsqJe+99Ew0N92HRonKsX39zpgtGNAkme9qjKTrNEqXV8DtzgsHEK6uhUAiBQAB+vz+FJZs62trasGLFCjidTpxqasc13+2GxShw83mV+NbNDWNSJvZ+97Dhwirg9smQU/Q0f8AXiqssevmCCvo8kfKOX0hOX2+Ckx0+nPcf76PPG8KiRYsgSRIeeOABXHXVVWnbZ6YwcCAC4HJZUVxsw2c/uxrXX78IjY19OO+83wAAXnrpYzAa2X2JclVyN/b4qwbx7y/R6gdDlKlBlmXs2LEDDz74ILZs2ZJUXsFgMGenugyFQujq6kJPTw9sJoF7b5uJBfV2vL63D59/6BDu/9TsoZRRphBVEdf7FFSoKRs3FJRVdPRHDwq7BkLwBcJfaufxyegeCMJqjn5/9QbklJVRUYEBn4wCq2Hcg87hIxn/FeMPm1rxy7+3oNRpxJ+/shAX37UDjz76KOx2Ox5++GGcOnUKd9xxR4o+wdTAwIES1tPTg69//eu4//77YbfbM12clKitLURtbSGmTXPhU59aBVUFvvjFDUM/T8e8ebn/4iGaXBmt3EbZeTxlSmgmdZ070HqzqxYGDZknyzLeeustPProo3j66afR3Nyc6SJNeYqiQJIMmFNrw7IZBXj3UD8ON3vHpBge1htp7uTMXFFOdfrxhYcORV3vDSjYd9IdtuzJzR1491A/bBZD1O12HEvdG5hDsopfv9iKz15RDVPYeIxIg76jvXgvfHlbTxAhWcWt51diaYMDBklgyZIlcDqduO666/Dmm2/i/vvvx+c///mUfY5MY+BACfN6vXj00Udx//33Q5Jy64l8SYkNN9+8FKqqYvfuNsiyig0bDuGVV45h9uwSXHjhzEwXkfJA2p+0R0kUaXEir1uKml7nh4q/M4a+9TQ5ZFnG22+/jT//+c949tlnGTQkaGG9Ayfn+vH7ja249fxKJH5mpE+PW8Zjr7fHtc32o25sP+rWTpgiiqrizb29+PRl1UD0WGXI+CBhYnDx4vZuBGUVt19UhWtOL4M/GN6isnbtWrz77rvYuHEjAweifCGEwPe+dxEA4KtffRHvv9+CxYsrYLOZIMtKQjMwBQJ+eDweFBWlt5+uwSBw+ul1ad0HJSbS7SiSlDxpVwE1jikMR8o2rg4yYXut9ZGTpQRfxZQdDh48iN/97ndYv349Tp48meniZK0z5xdCCOBj9+0fChyi0T+rEsU2eORiH7s/bGrDzCorbruoKmqa2tpaVFdXY+vWrVi1alWKS5kZDBwoIYFAAF1dXaisrMziQdHx+f73L0J/vx9//vNuXHnlH2CzmVBQYI47H1VVoCgKDIb0nX6yrMDjCaKp6Ut58+8zJUW5b0/qv8iYoCGuJ/VxvhE6WnI9PYfTUr0ZlymrUJPvRz/6EZ5++mm0tbVluihZTO84hFhtfun/9gsAZlP0fajq4NSq8piH8kZJQJJiD8sIyeHbJMusc7xiPCMeYqW58sorYbPZ8P/+3//Dxo0bde17qmPgQAnZsmULPvnJT2Lfvn2ZLsqkkIeuXN///uv42c/exZIllXj11Y8nlJfX60V/fz8qKipSWcQwhw51Ye3aX6ctf9Jpij0AFBr7T9dYAs31iY9N1L3T4exp8rz11lvo7OzMdDGynNZz79F0ia1LjUK7ARctiz4luzegYH+TB4ebfSPLFtbbUVdmgS3G4Oidx9040OSNuj4ekhBYMbMAUpJdJePx0EMP4bXXXsuZoAFg4ECky9KlP0NTUz++850L0NHxlUwXh7JVugYspOLRmF6pbj7Q229Lb94x0rDFgSg9Giqs+NOXF0Rd39wVwA+fPIkH1jeNLLv1/Ap8+Oxy1JZaom739d8fxQ+fbExJGU1GgX+9plZnarZRRsPAgeL2m9/8Bhs2bMCbb76Z6aKkVW+vDytXPggAeOaZm1BR4YDDYYKk93EFUSpMVkCgV6oHGMSTfqodC6JJ8IdNrXjyrQ689YPliCd6VqHqbq9IBSlGnyMp0jirofc/xdouHV1t9eWpneYnn5qFX7zQgk/cvx+//Py8Ces///nPo6ysDL/5zW8SKOXUxcCB4nLPPffA4/Hg29/+NkpKSjJdnLT4xz8O45573oDVasSjj34YADB7dgnMZs1pGIgyLlXPyfQ2LCSzPz7To3Xr1qG+vl5XWkVR4Pf7YbPZ0lyqzPB6vfjb3/42+HsghDt/fghOmwFnzCvEd26ZgRKn3vdXiKH/j55dk3muJbyvDFwQok26qofTZsSN51Zg484eXHLXDigq4PaF8IEPfABGoxE33XQTLrnkErhcrtQXPIMYOJBuP/rRj2CxWHDFFVdg3ryJ0XW2e+CBt3HoUBeKi624+eYlMJsNWL1ab7MmUTgV2mMK0iGu3UUrXxzljjmb0ph81LHpkzguDDZyx8qVK3Hrrbdi0aJFutLLsozu7m6UleXm+3SCwSAuvfRSAMB/fOVLuGxlEaZXWDG/zo75dZHflTR23I72KIfws8dilJCiF0fDYhodpyASPUsjXDBNBgGrKTXTvacmn/AyVpeYce4iFwIhBSFZxZYDffjIRz4Cq9WKdevWoa4u92Y2ZOBAujz11FPo6urC9ddfjzVr1mS6OCn32GO70d7ugaqqmDWrBLfcsjTTRaIsJ0b+l0ax7s/J1LB1TN+qa73GdK0x84gyjSyDhtwxc+ZMrFy5EsuXL9eVPhQKoa2tDdXV1Tk7W9w555wDALj7W9/AVWtKsWqWc2RdPO9K0Tr9rz+7HH3eUBIlDRc+TiGxf5tIHatWz3HiE5dEn+40HpFmVIp0PGMfu7EpBn/WlVlw24VV8AcV/Ptvj+KWW26B0+mMmkO2Y+BAutx999149tlnsWzZskwXJeUMhlY88cQu3H//B7B8eWouUESTIsLdbeSml2Q33rR2VRrTChF1Wx3BC1E+SWY40Pj3Enzr5oa49h3PeZ7oM4tILbRXri7FVatLk8oXY0Z7jG9gSayrkt7ZHHJTbr3ul1JOVVV0dnbC5XLBYMjFPv4q7Pa/4rHHrmLQQGkRrSdAoj0EtLZLuG+xnnzUieuTuXVO2DaBgxJ1E869Sjkj1pdZ1bF+uPuQ3rwnLhNR10w08Zqg82SMcEEQsVZrGu0gGe16JcLSJR6Y5NMFhy0OFJWqqggEApgzZw7efPNNzJw5M9NFIso60W5Eum9Qet7QnGzHf73b6mlimOTpWCMGHyLOMhBNabFOPL2dCuO5EsXuqBO/JPpM6pbMMOckB3rFFVZlP7Y4UFTNzc2YNm0a2tracm5WAKKskZqZA+MW9RYo9K3XTei42YaNrNbKL879E2UFfrFj0zf6Q+tqk2zbQz5g4EARvfXWW7jhhhuwY8eOHO2iRDQJptgDKP03zfgGR8eTb6ScNA9TIvdwNeafRFlCharr26vdXSl6/onTt21yVwitEmrnrj8ciO+6lp9XFXZVogmefPJJ/OMf/8B9992HysrKTBeHKHvprPBO1rznyc6UlGhnCS1pebYn4usFRTQ1RX4bw8RzMfJw6MjrouUfaVut0unZKrkrT1gJw3Yy9o9Ye4/c1Sv2C/K0X54nJnz6/MAWB5qgqakJjY2NOO200zJdFKKcpzWjakxRNkzHLUzP0IZoUl1p1/v8ksEC5RYR4bex4mkz1Lef9G+VzE7EhP+PF6utIXZgEGkOJt0Fy2kMHCjMm2++CY/HgwsuuCDTRSHKaqmovCc65E7vdqm8LcY7jDHW/pOdOSp/buGUvyKdJan55ifbMSpd+4993Yi8NLGRDsNpxrdQaKXPDwwcaMSBAwfw+OOPw2az4V/+5V8yXRyirJbMfB4T0iR4T4qZt5q5CnZc87xwrAJRBOk7e/XPQZCGszHGdUmo0dYnO61cxL3pWKJ/bS5h4EAAgN7eXnzuc5/DueeeizvvvDPTxSHKSQnfZsd18Y0334jrNfJMVLxDNFWN9cNjFYbXR+rJnWy5iPJR8ueEjokN4i1HlOuSOrwu4vrIoUR08VXy1Rh/ae8r93BwdJ5T1cGv/JIlS/Dcc89h8eLFGS4RUe5KxTOpuAcnq4DQ2HEqn5VFevtrrP0IjfVjlyfy2YcT5M/zQCJ90nU9SlUeWtcGrREKqRJ7EHr+XVsYOOS5YDCI2tpa7Nu3DyUlJZkuDhGlWjpGJk/WHTtZU6ksRCk2eCrGGhCttwtPgl19VMR+UhCWkHIFuyoRgsEgjEYjhNZjSSJKC3XCLwlsm4LEaoTfJqyPcJmInq3O0sXZ1yruw8R6C2Up7dnKxJj/IqdQNfJRE42wxfD/kp3OIL4TNN7TOdr7FlI5eUQ+YeCQx9rb2/HRj34UTz31FBwOR6aLQ5RTEpqxKIH7d1ybaEzfqjXZo67BzDrXxJVMxPwz+fyJpqjkvrrqSB7xNRLGO69RsidYHNsnUJuPNu2q1gDvRGe1y3XsqpSnDh06hEceeQQXXHABzjvvPLY2EE1B6ZgrJFK+sQYcx3rHhJ73OmTiyhJtEDWvcpRfEv3G6x9tNOnnlYh9TRpKEtXEl76Ff5ZIL34T4z5lvl9LGDjkmS1btuDkyZPo6OiAx+PhDEpEU1iiN6ekhiGMG0wdLS+hkUBrfTrFPYiaKGuNVpeTO9WivYU5dq6pPa/i+QQT0wqN9YNpRMR1o0uiXT1ip3D7ZDzzTieCIQV/e+opWG02nH766aivr9fxWbILA4ccpygK9u3bN/L3n/70J2zZsgVr1qzBj3/84wyWjCi3Rb39hd2zErvVp3V8so6gYWSFnuKnscae70/+iPRW8PXnE+33yTjb4sk/mQtP5JmREgmROvqCaOsNoKMvhJ88cwr+kIKf3H8/DAYDPv3pT+Oyyy5DZWWlRlmzCwOHHOT3+xEIBAAAgUAAl1566ci0qw888ADuu+++DJaOKM+JqH8klkXCtCsCUbv7TOyxkBEMGiivjcxqBETvyZ8qGrmrOuZ9jr6xdv5JiZy/VpdNre0B4PcbW/G9x09gbq0dG7+7DDW3bcZLL70Ep9OJz3zmMzh27Bi+/OUvw263J/UJphIOjs4BqqqG/fd///d/qK+vR319PRYsWIATJ06gsbERjY2N+OAHP5jp4hJRnNIzOC/+AYmaW6hhP4gonUaieI1ZD5KiM5OYQcPkXhHUCbuLb7IHvSmHH8iuW1KE17+/fML6n/3sZygsLMQtt9yie0/ZgC0OWc7v92PatGlhyz772c+ipaUFADjomWiKSPSZWrK33Hh6FUXNQ2NAohiXLp6ByXrKF89s9NCZlig7aH2rY6zX6BKpdxKEWOujCd8u9tYThyNHzk/v9WG42jO6fOKQaL15xyrRHT89iGnlFvzh3+bn1cMSBg5Z6Be/+AUeeOABAIDJZMKWLVvC1rtcLlit1kwUjYiiiOfGNPZGpnXL1dvdKFW9n2Ot05qLJeK6oY+QijEbYenU2AEPUfZI1bc4/HoR5Tn60A8BiOHqtr6qtf7rVjg9w7rHrp3YxWj8ksG/R5dHCxrGp4uDKhCUB98QYTJG77xz++23o6GhAZdddhmef/75+PYxRTFwyBK33nor/H4/AGD58uX4wQ9+AAAwGAyYPn06WxaIpphknqDrOptVJNGnWEfWk5VPij7ChH1FCBry6akg5QrtRwfaqeKpzosISWNVu2On0nctie8iEHloc6R5j7SuwEk8VtG5ycaNG/Hqq6/ia1/7Wvz7mKIYOCRBVVUMDAzg29/+dtr3tWzZspHfzzjjDJxzzjlp3ycRJS4VT9AT3kEKstbzngatIkzm44xkujoQZa/Ufqv1tEmMXZvWGd7ipK87Y3inJa2/k3X06FEcP34c5557bsryzDQGDkkKhULYv39/2vfzy1/+kt2PiPJQtBtzrLEBqRgvoJVnPPtMpUQDGgYNlIsSHrcUZdvIIyGi7yW14wbioe9KMPG6FX7VnPiyN32fSAWwanYB+r0ythzow+lzC+Msf/Zi4JAEIQSKiorwyCOPZLooRKShtXUAvb1+2GxG1Ne7JmWfkXvexmd8v/3xPQli3fxHkkfYLl56WxeSGoStY39TqZWDKPsM9+sPHzw89gwefeae+NQKyZyHeq4D2l24RFhnpPCViQx+Gh9gAHdeWYuHX2rBr/7RgpICIwIhFYqi4vDhQ7DbHQAG36VVW1sb786mNAYORJQX7r77NTz88HacdloNnn76RgghYLMZ0zo+aHzO+scu6MxQ7/6FdtapMvKML46dje9xnFLso0R5If62xMhdkkSE5ZPbrqCvNTPKvnVMtpBYkSfuTwVw24VVmFZuxflf3wEVwIBfxmWXXT5yX7nzzjtx//33J7LDKYuBAxHljUBAxssvH4HTeTeKimxob/8yJAlpn1wgrttrlISpuEWn6/YfsV+0iJUmcrnSUg2ZxKCJaDKFP5lP7Nud3BTGQseYAD1nXqzQIEr+Q60GE/YfPZZIsGxDqSK0Ugy3ylywtAiNvzkD/qCCmts24+DBg3A6nZr5Ziu+AI6I8oyAqgLd3V44nXejqupevPtuU5r3GK+J8/+ks9KbroAkJWnUmH/qxqCBco0Y8190sc+YwYq51vZq1Gy0A5bEz7yY06QO9cEc6XQV42OKqCvHdyQd/6c6mirqx8i/KwtbHIgob3m9Ifj9Mq677s8oKrLi+usX4RvfyPDsF7GmWY3dOq+VTFdeU86YMiZU5Gz5nERx0nfeR/7yX/7fO9HZF0xZWebW2vDIvy1IcOvobZE/XX8Kv325NdFihbGaJWy6e1mUFuZIzQm8cETCwIGI8pqiqDhxoheNjX0YGAhg27ZmlJc78POfX5V85kmPhh6XRZRaQrxjKSLFJvEGH6mYrjXeDfUM04z0Poex64hyw3BLwdhOgvo75Rxr9eFEuw9yik6KideT+F4eN7zV+LTN3QHsOO5OQQkBu2W4k83YYeHjp2PVvg6mesrWbMPAgYgIgwHEkSPdOHq0G0VFNtTWOmGxGPG5z62Gw2FOLNMU3FvS0UKeiq5FWjfXhIunsWEyHSPy91ZPuWR0XqTxoocOkZaFFBWykpoyhcZFIKPli+esm5hWUSfmnajRfMYGW+H71HdtzO8rCQMHIqIxhsc/3HXXRtjtJtTUOFFaasOiRRWYNi0107impPdMcqMaJ9A3k0nk9YkWIZW9iPQcjq7uADa92QlVVfH888/joosugslkSlEJiCZH9O947Kfn6TTgl/Hant6o6zv7g2jqCoQtO9rqxTsH+nDUFf3BTGOHP2VljESrhSG/Q4TIGDgQEUXh8QRx661/hc1mwn/+57n4yEcWw2o1oqYmuRkzEptjRDsTvRUFPekSaVGIt6KSyptyrLzaO/1wu2Xs2teH7913AKFQCF/96lfxyCOPYO7cubBYLCksCdHki9QKMZmV3lMdftz54MGo60OyivZxYyr++mYHXny/ByZD9JK29gSirkuF8fNCCXXkf4h4RVMjvQYivwZSMXCgKSMQCEBRBttNJUmC2Zxg9xCiFPN6g/ja117CN7/5Cs46qx7PP38LAMBiMSQ/lWuE1x4kmmPU7cbd1yb7Fqf7thpt8Lcafby4Fn9AwTe/vw9PPdeMs9aU4PnHzsTs1Ruxfft2zJ8/H3/4wx+wYsUKGAyGxHZANClin0X6Rjakjy+oYvcJT1zbtPQE0dKTugHaiYk1KDrCsROROoTlT9AAcDpWmkKuuOIKuFwuuFwuXHVVCgamEqVYMChj06ZjsNu/g+rqeyGnou9tlAHOKZVk5no3jz43SnIZRBrIrdclH34D684uw6ldl+Ivv14dtm7fvn340pe+hD//+c9x5EiUCQmcxGp+VWgTpfuhRnxb5Cy2ONCUoqoqgsEgNm3ahKVLl2LHjh2ZLhLlHe2ndKoK9PT4UFz8fTidFjz55Edw+ul1k1O8mAVDzKJHW605nkHnE//wdGNyTbBc0ehNu/icl/DwAyuxbLErrGUoFArh8stH3+769a9/Hd/+9rfR0NAQRyn0CQQCMBgMedmicfToUciynOli5KzwF8BFMIn1WwHAqPEVl5XBwc7DDBIgaZRx/DbpoGs8VxJdQ3MNAweakgKBAPbt24fFixejoKAAGzZsQHFxcaaLRXlB/61gYCAAjyeIG298HMXFNlx77QJceaUjjWWDvlcwx7lac7yDzkMiwrpc6e8bldTNN8bxcHtkWMwGmIzhjeuqquK1114b+TsQGOxHfeLEiWRKErl4qpr2N5NPVV6vN9NFyHlT5Zs1t9aGv/z7wqjr3T4ZWw8PYPuRgZFlaxe5MKfahgJb9IjjvqdP4dcvtqS0rOG0p1YVQ+nGH+2YL6jLYQwckqCqKnp6enDbbbdluihp5/V6YbVa03oD3LNnT9jTqWAwiN27d8NkMuHjH/84fvCDH2Du3Llp2z/li9Re7BVFxdGjPTh+vBe9vX68+qoFPt+lUKGMjrFLpRTkN7ZYsYqYgtdQxM4zFccnwe09non9sUOhUJKFIZosY9+TAKRuWoTEWE0SFtYPPzSZuJ9gSEFtqQVnLxidma662AyXfWJgPzaPssJ0z3qmbxaqseFFxIcjefSWGAYOSTIYDJg+fXqmi5F2/f39sNvtaW1ut1qtEZcLIbBhwwZ89atfTdu+KZ/onWQ0zlyFwMmTvWg82Y/i4j4IFEzZh1F6h/Wlo/gi6h9EpE+sqRSSaJJMI5NRQk2JBTUlkWYwixT8TH5Zo7UsAHpKNjaIy20MHJJQUFCAK6+8Ev/93/+d6aKkXXNzM0pLS9M609Ebb7yBxsbGkZmVjMbBr+fll18OAOyqFCdZVvHKK8cyXYy06+rqQmHhwMj3JZrGxj4omp1l479ZGQwCQggsWlSBhoYi9PcfxeGDbwG4OPIGqXrlcox0KX7FQ0bkZyeA/GEwGFBdXQ2bzZbpomQZrbdDR5lGNAKDlLpXmRkMkarWsdo2Iwc/49/KLAnAqDUQQqfRfNIRXOVH0AAwcEhKXV0dHn300UwXIyc5HA40NDRAkiQ88cQTeTmwMBlGo4SKCgc+//kNmS5K2gWDQRiNRs1udM3N/QgGY70mNb6q6vDuZs8uhdEo4ctfPgs337wU27ZtxbXXfCdqzhPnAB+fsd4CJJ5FooOkx6eLMdt5HLlFloqqQk2VFd09Abg9ITjsvN1NFUIINDQ04IorrkBVVVWmi5NF1NEfImwJxPAidcIvEVWXmGEypi40byiP1GMg/vbM8aFMeaEJc2tTE1zazINdorRHNQweu/iuk2xxIJp0RqMRZrMZZrMZ5557Lp577rlMFylrNTQUYdeuz2a6GJNCb2vYF7+4AQ89tBU+X6R+7PEHDaWldgDApk23obKyIHb6KL/HI7FquHazu57l43Mb/5wwetN9rFJMXDn6a/gWiYYgbzx3Li689g186p+m48NX1457KkqZIIRASUkJfvvb32LVqlVRu6hSJCLsx7hfxyzQ/p6//J1lKSpTNPrP4VgV9C9eXYcvXh17xrrEHlyMb9sYa+IIholr8xcDB5oyNmzI/afjNFXpuxWYTAbYbEaUlNhw5MgX01ymcAmOvJgCZdDfwiIiLUxivwDw4l/Pwme+/D527OnDd78efdYXSj9JklBWVoZnnnkGp512Wt7ONpUfxp/D0f+to40tSK7xVWvr1HXTyjcMHLKaCkUOYP8zD+Lw/E/ivBlWOC3hfQiVkBdb7joX/zv9Udxz/XQ0lJim7MnCmwhNVXa7CUajhI9+dDF+8IOLIYRI2/c16b794zKYkJ/Orgwp2v2kbz8hIyHwP99egof/dBwzVv595KV9kjTYbWHGjBlp7WcfCoUgSdLI/vJZdXU1vvGNb2DlypVpPYfyUTrOZr2zr6Vm/+FbJ9v9cbLHSOVHJ6VBDByymgpV8eHg+ofwouFWrKy1jAscACGZMetD/4k7CipQ5uA4AaJ4FBQMdn/62c+uwtKllSgpscHl0te1ItEbV8RtImSmApGnexUx/xyzIHrp4ir7uMTRhj/qlbKbvRjdv91mwA3X1GLtGWVo6/Djyhvfxttvvw0hBCwWS1orsN3d3bDZbHnfJUcIAaPRiOrqas2JDCh+6fgGx9PFMvpYp7G03gQ5+gbJRFoRYs01lW75FALz7M1SqqcN3Ydex8NPb8c7m49iv/t/8ON3baheeC7WrFyM0xsEvK3v44lHXsXeQzuAK1dhYY0dBRYJav8hHNqxGX986jCchW402+ZgjnICx/pqcdpVF2PNimkodTfiyObn8eTrJ+GFCq91Nj50ywexpL4ELlM+nSKUbyRJwGIxQgjgwQc/AEkSuPDCGSgvj+/FbrEe6sf99C7OU05XhT3Bsk0QI7G+ykT6jN1vWakFZaUWnGr2QgiB5cuXT8oT7/b2dtjtdjgcaX4xIFGGaZ9NGimSOB1jD2dOND+KhIFDthIGSCYbnE4nbEYJJlsBnE4HnHYLLEYJQgDCYIG9wA7/4dew67gbnuBgY5rqa0fH8V14+ZWTuOT6Amz9y7MIXrEK7p0vY8ecOSgpFfC3bcbfXj6MYHE5XCYZ3v2v4oXNS+Gw2LCs1g42ulN2m3hbMBgkGAwC1dUFuPHGJRBC4KMfXQwpBVMBxnsT0jOTR6wxkLr2pbFtsl0Txg+kTuWNOJG8WBGg3KDnm5z0s/8kSxM79+hr4y9R+HVGxBzyPJhe33peK6Jj4JClhK0URQsuxe2zz4Tr9R9CvuwTuO3SYtQVjlbpHdVrcN2nF6P68IPYP76XkrEA9uoVuOaOlWh56JuovfYzmBv4Z7zn7cWRPbvgO/ISntxTh6/ddSlmWIPY1foCfv3WPiybXYfFNXakaFplogwZ/QIPz7SzaFE56uoKMW9eGb73vYtSupvxXYrS2YUp46KUKZNBA1G2SmzIsPZ4gcTOIb1nX+w0qWyJnJiHnk5VY0V8JEMxMHDIVwYjDE4XnEYnXIVFKHYZ4SyUoMghtB9vg7z7PZw6dRK//8FOAIC/T4E6ywsJIQQBpPsl8ETpNtxLpaGhGAaDwH/8x1p89KOLU7uT8Y/dI6xKShrvcfHefsevSHSMhJZEPzKrA5SNhO7XOUZ/lp66LjwTc9Kfa/iW2tvFU+bRtPFft+IPy6IWIU8wcMgR6pifur/4YrBBTpIkCAkQkoCqqFBVwFo+B4tu+gYe/coSmAC0tLSgtLQUJpOJd2DKekIAxcWDM+ls3vwJlJXZ07Qj/asSmec8VWnimT0lXpr5idR9PqLcM9z9Rjtd9DSxzm7tK8/Y96vE14ln/HDlifuK3W1peP96X9kWD/3dqaKVOqxcIn8iB3ZVz2oCgAS7w4Cerj6E5FhvxdXLgNLp01E3rQzdz/wef2+WAQChngPYtq8Vbd3+FOyDKDPMZgMKCy2YObME7e1fQXv7V1Bamr6pOOMR66aXfOeA2GnS2VCf7rIT5bqRyqlG3VSN+sdoTvqWha+Lp50gdt7xdiwa3r92O0L81wc9ex73uxq+RKT1yjl1scUhy0mSFWfefBt+/s1b8c+PO1F21j/huivOx2V17dj39P24+7lTaN/ThEP2z+CO9S4svuZzuGKFEc4YeRprTsfypYW4q+tnuO/aM/FdgwG+kANnfOLb+OfLS1Fekk+nCOWKu+++EN/85joAgy0OqRj0rBeflk8SHmjKZRrfbRH1D9Km4+LBYwqAgUP2k0woOuNO/OihmxASBhid5SgtdsFhdmLBtV/B99YFIPs88Es2WE0G2IurUFwgwTh3Ln603IhKqwOfeviHsFQ4YbnlB5gjlcJS4EKhaTnOu/2/MPsDboQg0NHZg7q5C1BTZuG5Q1nJ4TAjUzNixnvOpLPrUDoyDcsu2jsnUre76Jnq7PZElAtS3T0nlVKzJ325JDcDXIyBaBQRA4esJiAEYHDWYt7i2nHrzHBWzcaCqmjbFmJeyeBvdYvnDv5SPQeFI+sdcFXPhqt68K/m5maUljpgNvMlckS6Dd2TUjEdayqpIrX70HrSmZbPw/s85SU9A4GjXXGEjjR610+GyOMi4h1orb9Tkj7hex/+i2MciIgoWSLsRzJZJCTarSzT1QEtydyCp/pnI0oX7fNmbIrIZ4qqsV6v5K9bY2eTGv/Jkj3Lk6vkTwwawpfmOgYORESZlIYHVWETOOrIf6o8K9M78SRR/hqe32jiWav9DD7Sk/vYKRKjjvsZ36bD7SkRg5iUXKzi7+AVeef5eaVi4EBENAmi3u903HtGbsPRMhm3PN5BkppJ1Ii/TvxbZ/niKYc6dvN4Kg1TJRoiStrEsy76PEJqjL/GG3yaHynNaNVf1ZNRhHzH/owt7Bwfs0nErROqq0/8jPF8HP3v0sgPDByIiCZBwrccVcdtON33sxg387BWDb0POuPctRj7hxbe4ynnaE9rGm2d9mkgIrZMivC1aT2fYg9NTsUTgIlhVnwfhxeTsRg4EBFNZdkwVfhUKtdUKgtR0pJsxgt/nh9dMk82Eqrc690mnqcFNBkYOBARpUsy7eNJb5ftN9P4y5/tn5hIP6Hz+66/u1BcwvoWaQ20jiRt87rpLkF4ulgdtmgsTsdKRJRi/QMhXPGRtzJdDIrAF5AzXQSiOESvYOuvekebhlXP1K6J73z8XuPZT3KTwcb7bgb9g8ljjS7JF3kTOHz1q1+FJLGBJVFutxs2my0nj6GiKJkuAuWQurp6fP/7/5vpYiQsEAji5MkTmDVrVqaLkhYqgI/eku+3fsoGDzzbhHKXKdPFIJ1kJT9aKHI+cDCbzbjlllsQCAQyXZSs5vP5IITIycDh5ptvhs1my3QxKEeUl1fgk5/6bKaLkTCPx4OtW7di7dq1mS4KUd66/oYb4XYPwJ/Gffh8PhgNRhhNOV8VTDtFUeHzeXHLP9lhMuV2sJfz3xabzYYHHngg08XIeoNvji6F2WzOdFGIiIhy2j33pr/VsqOjAzabDQ6HI+37ynWhUAhtbW2orq6GELndoqk7cAgGg+ksR8qFQiHIspx15Z6qZFlGKBTK+RNiMvC7mVqKovC7mUKhUAhA9l3zp6rhayePZ/JkWR453yl5/G6mTq58N/W0lghVjfpKoTCbNm1KukBERERERDT1nHfeeZppdAcO2TaA1Ov1wu12o6ysLNNFyQmtra0oLS2F0ZjzvdvSzufzob+/H+Xl5ZkuSk5obW1FSUlJzvcrnSxerxfvvfcezj777EwXJSd0dnbCZrPBbrdnuihZT5ZltLe3o6qqKtNFyQn8bqZOrnw39Yxj1V0LzLZBscPdFrKt3FMdj2fyhBA5O9A8U3g8U4fXztTj9zM1hh9gDl9DKTm8F6VOPn03+W0hIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiIiIk0MHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTQwciIiIiIhIEwMHIiIiIiLSxMCBiIiIiIg0MXAgIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiIiIk0MHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTQwciIiIiIhIEwMHIiIiIiLSxMCBiIiIiIg0MXAgIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiIiIk0MHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTQwciIiIiIhIEwMHIiIiIiLSxMCBiIiIiIg0MXAgIiIiIiJNDByIiIiIiEgTAwciIiIiItLEwIGIiIiIiDQxcCAiIiIiIk0MHIiIiIiISBMDByIiIiIi0sTAgYiIiIiINDFwICIiIiIiTUJVVTXThSAiIiIioqmNLQ5ERERERKSJgQMREREREWli4EBERERERJoYOBARERERkSYGDkREREREpImBAxERERERaWLgQEREREREmhg4EBERERGRJgYORERERESk6f8Dx1J1/dNbdLgAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "id": "UeMOu19LJT6b",
        "outputId": "7e1a7c77-7d9c-455e-ee98-9b1bc688da52"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 984.252x787.402 with 4 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Simulation with default values of the process\n",
        "newplot(plotType='TimeSeries')\n",
        "simu(20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mtWJ3rfbJaVN",
        "outputId": "c3e0f25d-4e62-40cd-9c46-8d322bbf59f3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "bioreactor.V_0 : V_0 : 1.0\n",
            "bioreactor.m_0[1] : VX_0 : 1.0\n",
            "bioreactor.m_0[2] : VS_0 : 10.0\n",
            "bioreactor.culture.Y : Y : 0.5\n",
            "bioreactor.culture.qSmax : qSmax : 1.0\n",
            "bioreactor.culture.Ks : Ks : 0.1\n",
            "feedtank.c_in[2] : feedtank.S_in : 300.0\n",
            "feedtank.V_0 : feedtank.V_0 : 10.0\n",
            "dosagescheme.mu_feed : mu_feed : 0.1\n",
            "dosagescheme.t_start : t_start : 3.0\n",
            "dosagescheme.F_start : F_start : 0.001\n",
            "dosagescheme.F_max : F_max : 0.3\n"
          ]
        }
      ],
      "source": [
        "disp(mode='long')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 532
        },
        "id": "0Bj8zdIMJiHr",
        "outputId": "94b02688-0190-4d8a-e362-6284cc85f1d7"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 984.252x787.402 with 4 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# A more typical feed scheme for the culture at hand\n",
        "newplot(plotType='TimeSeries')\n",
        "par(t_startExp=4, F_startExp=0.008, mu_feed=0.2, F_max=0.1)\n",
        "simu(20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IOLRVcsFJ5NX",
        "outputId": "7d585ea6-1954-480c-cf83-c01f8fd40274"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Y : 0.5\n",
            "qSmax : 1.0\n",
            "Ks : 0.1\n"
          ]
        }
      ],
      "source": [
        "disp('culture')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yjcgKrvpJ96A",
        "outputId": "77124cf6-a7d9-44b7-e409-7d02b732be16"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cell specific growth rate variable : 0.12 [ 1/h ]\n"
          ]
        }
      ],
      "source": [
        "describe('mu')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sLF6NdXvKBY4",
        "outputId": "f020d520-e8df-4e0e-879a-a93621ae9500"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['bioreactor', 'bioreactor.culture', 'dosagescheme', 'feedtank']\n"
          ]
        }
      ],
      "source": [
        "describe('parts')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cZKKtkydKHH-",
        "outputId": "3eec471f-8e5e-40f5-8b43-b780f35d524d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "MSL: 3.2.3 - used components: RealInput, RealOutput\n"
          ]
        }
      ],
      "source": [
        "describe('MSL')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D7lCWmdiKNLm",
        "outputId": "0cde4a93-f9cb-4e4c-f81c-fa3754885376"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "System information\n",
            " -OS: Linux\n",
            " -Python: 3.10.12\n",
            " -Scipy: not installed in the notebook\n",
            " -FMPy: 0.3.15\n",
            " -FMU by: OpenModelica Compiler OpenModelica 1.21.0\n",
            " -FMI: 2.0\n",
            " -Type: ME\n",
            " -Name: BPL_TEST2.Fedbatch\n",
            " -Generated: 2023-04-20T12:24:29Z\n",
            " -MSL: 3.2.3\n",
            " -Description: Bioprocess Library version 2.1.1\n",
            " -Interaction: FMU-explore for FMPy version 0.9.8\n"
          ]
        }
      ],
      "source": [
        "system_info()"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "jsjfegdU-lSS"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "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": "3.8.16"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}