{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "Ce premier code permet de visualiser 2 choses :\n",
        "*   le déplacement d'une onde interne à une profondeur donnée, où chaque courbe correspond à la courbe précédente au temps t+dt avec dt = 50s\n",
        "*   à un temps donné, des ondes internes à différentes profondeurs\n",
        "\n"
      ],
      "metadata": {
        "id": "ZXZhbLNTIvn9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "\n",
        "l=1\n",
        "m=1\n",
        "Um=1\n",
        "N=0.007\n",
        "w=np.sqrt(N**2*(l**2)/(l**2+m**2))\n",
        "\n",
        "\n",
        "x=np.arange(0,10,0.1)\n",
        "z=np.arange(0,10,0.1)\n",
        "\n",
        "def u(temps):\n",
        "    u=np.zeros((len(x),len(z)))\n",
        "    for i in range(len(x)):\n",
        "        for j in range(len(z)):\n",
        "            u[i,j]=-l/(l**2+m**2)*m*Um*np.cos(l*x[i]+m*z[j]-w*temps)\n",
        "    return u\n",
        "\n",
        "\n",
        "\n",
        "plt.figure(1)\n",
        "for i in range(5):\n",
        "    p=i*50\n",
        "    plt.plot(x,u(p)[:,0])\n",
        "plt.title('Déplacement d une onde interne à une profondeur fixe')\n",
        "\n",
        "\n",
        "\n",
        "plt.figure(2)\n",
        "for i in range(10):\n",
        "    p=i*10\n",
        "    plt.plot(x,u(0)[:,p]+2*z[p])\n",
        "plt.title('Ondes internes à différentes profondeur')\n",
        "\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "-SyE3m-8GqO4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "L'objectif de ce code est de tracer un profil de densité linéaire pour une tranche d'océan de la surface jusqu'à la profondeur z=1000m"
      ],
      "metadata": {
        "id": "-u5Cf838JpLF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "\n",
        "def profil(z):\n",
        "    rho=1029+0.021*z\n",
        "    return rho\n",
        "\n",
        "plt.figure\n",
        "plt.axis([0, 1050, 1052.5, 1027.5])\n",
        "plt.plot(z,profil(z))\n",
        "plt.xlabel('Profondeur')\n",
        "plt.ylabel('Densité')\n",
        "plt.title('Profil de densité en fonction de la profondeur')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "659pRZccHXYi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Ce code permet de visualiser le déplacement l'onde au cours du temps. Pour changer la profondeur à laquelle on souhaite la visualiser, il suffit de choisir le paramètre z (entre 0 et 1000 m). La vitesse tracée est sinusoïdale selon les équations décrites dans le h5p. Afin d'accentuer les différences de vitesses entre les deux animations du h5p, le pas de temps a été modifié entre les deux animations. Cela accentue la différence de vitesse qui était déjà existente pour un pas de temps similaire."
      ],
      "metadata": {
        "id": "etb1IuKvX0QE"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BnZo1TzeGnET"
      },
      "outputs": [],
      "source": [
        "import matplotlib.animation as animation\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from IPython import display\n",
        "\n",
        "\n",
        "rho_init=1050\n",
        "l=2\n",
        "k=2\n",
        "Um=1\n",
        "alpha=0.21\n",
        "dt=1\n",
        "\n",
        "x=np.arange(0,10,0.1)\n",
        "z=np.arange(0,1000,10)\n",
        "\n",
        "def N(alt):\n",
        "    N=np.sqrt((9.81/(rho_init-alpha*alt))*alpha)\n",
        "    return N\n",
        "\n",
        "\n",
        "\n",
        "def u(t):\n",
        "    u=np.zeros((len(x),len(z)))\n",
        "    for i in range(len(x)):\n",
        "        for j in range(len(z)):\n",
        "            w=np.sqrt((N(z[j]))**2*l**2/(l**2+k**2))\n",
        "            u[i,j]=-l/(l**2)*k*Um*np.cos(l*x[i]+k*z[j]-w*t)\n",
        "    return u\n",
        "\n",
        "\n",
        "\n",
        "fig = plt.figure() # initialise la figure\n",
        "line, = plt.plot([], [])\n",
        "plt.xlim(0, 10)\n",
        "plt.ylim(-5,5)\n",
        "\n",
        "\n",
        "\n",
        "def init():\n",
        "    line.set_data([], [])\n",
        "    return line,\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "def animate(i):\n",
        "    z=1000 #on choisit ici la profondeur en m à laquelle on souhaite visualiser l'onde\n",
        "    t = i * dt\n",
        "    y = Um*np.cos(l*x+k*z-(np.sqrt(N(z)**2*l**2/(l**2+k**2))*t))\n",
        "    line.set_data(x,y)\n",
        "    return line,\n",
        "\n",
        "anim= animation.FuncAnimation(fig, animate, init_func=init, frames=1000,interval=0.5, blit=True, repeat=False)\n",
        "\n",
        "\n",
        "plt.show()"
      ]
    }
  ]
}