simple_model_plots37.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "testIKColabpy37.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/opensim-org/conda-opensim/blob/jupyter_01/simple_model_plots37.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hXS4NEKMp29Q",
        "outputId": "ada50457-90d6-476b-e89f-e85a548d9558"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "⏬ Downloading https://github.com/jaimergp/miniforge/releases/latest/download/Mambaforge-colab-Linux-x86_64.sh...\n",
            "📦 Installing...\n",
            "📌 Adjusting configuration...\n",
            "🩹 Patching environment...\n",
            "⏲ Done in 0:00:47\n",
            "🔁 Restarting kernel...\n"
          ]
        }
      ],
      "source": [
        "#!conda --version\n",
        "#If !conda --version returns no results, install conda with uncommenting the next three lines:\n",
        "!pip install -q condacolab\n",
        "import condacolab\n",
        "condacolab.install()\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!conda install -c opensim-org opensim\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Soa2ui-nq_4n",
        "outputId": "ddec67a5-2db1-44e4-88aa-abf657192a11"
      },
      "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\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\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\bdone\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - opensim\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    ca-certificates-2022.6.15  |       ha878542_0         149 KB  conda-forge\n",
            "    certifi-2022.6.15          |   py37h89c1867_0         155 KB  conda-forge\n",
            "    conda-4.13.0               |   py37h89c1867_1         989 KB  conda-forge\n",
            "    libblas-3.9.0              |5_h92ddd45_netlib         202 KB  conda-forge\n",
            "    libcblas-3.9.0             |5_h92ddd45_netlib          54 KB  conda-forge\n",
            "    libgfortran-3.0.0          |                1         281 KB  conda-forge\n",
            "    libgfortran-ng-12.1.0      |      h69a702a_16          23 KB  conda-forge\n",
            "    libgfortran5-12.1.0        |      hdcd56e2_16         1.8 MB  conda-forge\n",
            "    liblapack-3.9.0            |5_h92ddd45_netlib         3.0 MB  conda-forge\n",
            "    numpy-1.20.3               |   py37h038b26d_1         5.7 MB  conda-forge\n",
            "    openblas-0.3.3             |       ha44fe06_1        13.7 MB  conda-forge\n",
            "    opensim-4.4                |        py37np120        68.7 MB  opensim-org\n",
            "    python_abi-3.7             |          2_cp37m           4 KB  conda-forge\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:        94.6 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  libblas            conda-forge/linux-64::libblas-3.9.0-5_h92ddd45_netlib\n",
            "  libcblas           conda-forge/linux-64::libcblas-3.9.0-5_h92ddd45_netlib\n",
            "  libgfortran        conda-forge/linux-64::libgfortran-3.0.0-1\n",
            "  libgfortran-ng     conda-forge/linux-64::libgfortran-ng-12.1.0-h69a702a_16\n",
            "  libgfortran5       conda-forge/linux-64::libgfortran5-12.1.0-hdcd56e2_16\n",
            "  liblapack          conda-forge/linux-64::liblapack-3.9.0-5_h92ddd45_netlib\n",
            "  numpy              conda-forge/linux-64::numpy-1.20.3-py37h038b26d_1\n",
            "  openblas           conda-forge/linux-64::openblas-0.3.3-ha44fe06_1\n",
            "  opensim            opensim-org/linux-64::opensim-4.4-py37np120\n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  ca-certificates                      2020.12.5-ha878542_0 --> 2022.6.15-ha878542_0\n",
            "  certifi                          2020.12.5-py37h89c1867_1 --> 2022.6.15-py37h89c1867_0\n",
            "  conda                                4.9.2-py37h89c1867_0 --> 4.13.0-py37h89c1867_1\n",
            "  python_abi                                    3.7-1_cp37m --> 3.7-2_cp37m\n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "certifi-2022.6.15    | 155 KB    | : 100% 1.0/1 [00:00<00:00, 10.85it/s]\n",
            "numpy-1.20.3         | 5.7 MB    | : 100% 1.0/1 [00:01<00:00,  1.62s/it]\n",
            "python_abi-3.7       | 4 KB      | : 100% 1.0/1 [00:00<00:00, 32.44it/s]\n",
            "liblapack-3.9.0      | 3.0 MB    | : 100% 1.0/1 [00:00<00:00,  1.45it/s]\n",
            "libgfortran-ng-12.1. | 23 KB     | : 100% 1.0/1 [00:00<00:00, 25.94it/s]\n",
            "libgfortran5-12.1.0  | 1.8 MB    | : 100% 1.0/1 [00:00<00:00,  2.29it/s]\n",
            "libcblas-3.9.0       | 54 KB     | : 100% 1.0/1 [00:00<00:00, 24.01it/s]\n",
            "ca-certificates-2022 | 149 KB    | : 100% 1.0/1 [00:00<00:00, 20.91it/s]\n",
            "openblas-0.3.3       | 13.7 MB   | : 100% 1.0/1 [00:04<00:00,  4.12s/it]\n",
            "libblas-3.9.0        | 202 KB    | : 100% 1.0/1 [00:00<00:00, 15.31it/s]\n",
            "libgfortran-3.0.0    | 281 KB    | : 100% 1.0/1 [00:00<00:00, 11.47it/s]\n",
            "opensim-4.4          | 68.7 MB   | : 100% 1.0/1 [00:22<00:00, 22.48s/it]\n",
            "conda-4.13.0         | 989 KB    | : 100% 1.0/1 [00:00<00:00,  1.94it/s]\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\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\bdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "DiP6nrXnsxlV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The following line/cell imports opensim module and if successful shows the current version and build date (**should be 4.4**)\n"
      ],
      "metadata": {
        "id": "TDQ7EpBxZpco"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import opensim as osim\n",
        "osim.GetVersionAndDate()"
      ],
      "metadata": {
        "id": "Q-kqxhn_ZbEP",
        "outputId": "8afa13fd-08d4-41ed-cb4b-d9e7ab8a4b2a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'version 4.4, build date 23:28:47 Jul 25 2022'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import opensim as osim\n",
        "pendulum = osim.ModelFactory_createPendulum()\n",
        "s = pendulum.initSystem()\n",
        "manager = osim.Manager(pendulum)\n",
        "manager.initialize(s)\n",
        "s = manager.integrate(2.0)\n",
        "statesTable = manager.getStatesTable()"
      ],
      "metadata": {
        "id": "yQ6TqM6cr-3N"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "times = statesTable.getIndependentColumn()\n",
        "positions = statesTable.getDependentColumn('/jointset/j0/q0/value')\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "jvsig7YesJgD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Data for plotting time against swinging pendulum\n",
        "plt.plot(times, positions.to_numpy())\n"
      ],
      "metadata": {
        "id": "QPFC-ebbNVJH",
        "outputId": "ab9e038b-9376-4fe2-a9a0-eb2505f80f15",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fb9bbe3d750>]"
            ]
          },
          "metadata": {},
          "execution_count": 37
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}