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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Software Carpentry workshope: Particle tracking (2D and 3D) using Ariane data"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Imports"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import netCDF4 as nc\n",
      "import matplotlib.pyplot as plt\n",
      "from mpl_toolkits.mplot3d import Axes3D\n",
      "from matplotlib import animation\n",
      "from salishsea_tools import (nc_tools)\n",
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Download netCDF4? http://netcdf4-python.googlecode.com/svn/trunk/docs/netCDF4-module.html."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Need plt to plot"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Need Axes3D to plot in 3d"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Need animation to produce an animation"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Download salishsea_tools? Is there an easier way to view variables in dataset?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here, I'm using matplotlib inline, assuming that they will have downloaded FFMpegWriter. "
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = nc.Dataset('/ocean/imachuca/MEOPAR/Ariane/results/soft_carpentry/ariane_trajectories_qualitative.nc','r');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Relocate data and adjust directory "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nc_tools.show_variables(data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[u'init_x', u'init_y', u'init_z', u'init_t', u'init_age', u'init_transp', u'final_x', u'final_y', u'final_z', u'final_t', u'final_age', u'final_transp', u'traj_lon', u'traj_lat', u'traj_depth', u'traj_time']\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lon=data.variables['traj_lon']\n",
      "lat=data.variables['traj_lat']\n",
      "dep=data.variables['traj_depth']\n",
      "x=data.variables['init_x']\n",
      "y=data.variables['init_y']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lon.shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "(10, 1)"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It is important to know the shape or length for when you reach the animation part. For example, for our animations, we will have 10 frames."
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Plotting (2D)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots(1,1,figsize=(20,10))\n",
      "ax.scatter(lon[:,:],lat[:,:],color='blue')\n",
      "\n",
      "ax.set_title('2D')\n",
      "ax.set_xlabel('Longitude')\n",
      "ax.set_ylabel('Latitude')\n",
      "\n",
      "ax.set_xlim([-124.6,-123.0])        \n",
      "ax.set_ylim([48.25,48.65])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "(48.25, 48.65)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
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lmHhZAnwLWJu1ZaqbYWKlV3012zDxcjLtV6ieBd6SpXWqk27nhi3A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\nCDhu230AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fbea17fc890>"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Plotting (3D)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(figsize=(20,10))\n",
      "ax = fig.gca(projection='3d')\n",
      "ax.scatter(lon[:,:],lat[:,:],dep[:,0],color='blue')\n",
      "\n",
      "ax.set_title('3D')\n",
      "ax.set_xlabel('Longitude')\n",
      "ax.set_ylabel('Latitude')\n",
      "ax.set_zlabel('Depth')\n",
      "\n",
      "ax.set_xlim([-124.6,-123.0])        \n",
      "ax.set_ylim([48.25,48.65])\n",
      "ax.set_zlim([-100,0])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "(-100, 0)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MelpVUpFjbquiqvF6YzgRxb4YlLU/VlZWtAxq6vU6PvCBD+DFL34xPM/Db//2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\nR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oPbbrsNp512Gj73uc+5mUpfnHDCCXjppZdm/Pnll1+OU045JbR/l3EPCzVM4Dg9qLoJ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\niIiIiIiIiIiIiIiIiIiIiIiIiMgX9V+NAQCdNy2KAwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fbe9b5951d0>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Plotting (3D): Camera Position"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(figsize=(20,10))\n",
      "ax = fig.gca(projection='3d')\n",
      "ax.scatter(lon[:,:],lat[:,:],dep[:,:],color='blue')\n",
      "\n",
      "ax.set_title('3D')\n",
      "ax.set_xlabel('Longitude')\n",
      "ax.set_ylabel('Latitude')\n",
      "ax.set_zlabel('Depth')\n",
      "\n",
      "ax.set_xlim([-124.6,-123.0])        \n",
      "ax.set_ylim([48.25,48.65])\n",
      "ax.set_zlim([-100,0])\n",
      "\n",
      "ax.view_init(elev=0, azim=-90)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MXHDBBfmd3/mdXHnllfmVX/mVTpcFT5m7PgEAALDk1Ov1XHPNNbnmmmty1lln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\nW8dOUd27d9eTTz4pJycnGWO0c+dOeXl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       "text": [
        "<matplotlib.figure.Figure at 0x7fbe9b3e7f10>"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Animation 2D"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Empty map\n",
      "fig, ax = plt.subplots(1,1,figsize=(20,10))\n",
      "\n",
      "ax.set_title('2D')\n",
      "ax.set_xlabel('Longitude')\n",
      "ax.set_ylabel('Latitude')\n",
      "\n",
      "ax.set_xlim([-124.6,-123.0])        \n",
      "ax.set_ylim([48.25,48.65])\n",
      "\n",
      "#Initial image\n",
      "def init():\n",
      "    return [fig, ax]\n",
      "\n",
      "#Animated points\n",
      "def animate(p):\n",
      "    ax.scatter(lon[p,:],lat[p,:],color='blue')\n",
      "\n",
      "#The animation function    \n",
      "anim = animation.FuncAnimation(fig, animate, init_func=init, frames=10)\n",
      "\n",
      "#A line that makes it all work\n",
      "mywriter = animation.FFMpegWriter()\n",
      "\n",
      "#Save in current folder\n",
      "anim.save('Software-Carpentry2D.mp4',writer=mywriter)\n",
      "\n",
      "#Show as a pop-up window\n",
      "#plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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lmHhZAnwLWJu1ZaqbYWKlV3012zDxcjLtV6ieBd6SpXWqk27nhi3A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\nCDhu230AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fbe9b31cf50>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Animation 3D"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Empty map\n",
      "fig = plt.figure(figsize=(20,10))\n",
      "ax = fig.gca(projection='3d')\n",
      "\n",
      "ax.set_title('3D')\n",
      "ax.set_xlabel('Longitude')\n",
      "ax.set_ylabel('Latitude')\n",
      "ax.set_zlabel('Depth')\n",
      "\n",
      "ax.set_xlim([-124.6,-123.0])        \n",
      "ax.set_ylim([48.25,48.65])\n",
      "ax.set_zlim([-100,0])\n",
      "\n",
      "ax.view_init(elev=0, azim=-90)\n",
      "\n",
      "#Initial image\n",
      "def init():\n",
      "    return [fig, ax]\n",
      "\n",
      "#Animated points\n",
      "def animate(p):\n",
      "    ax.scatter(lon[p,:],lat[p,:],dep[p,:],color='blue')\n",
      "\n",
      "#The animation function    \n",
      "anim = animation.FuncAnimation(fig, animate, init_func=init, frames=10)\n",
      "\n",
      "#A line that makes it all work\n",
      "mywriter = animation.FFMpegWriter()\n",
      "\n",
      "#Save in current folder\n",
      "anim.save('Software-Carpentry3D.mp4',writer=mywriter)\n",
      "\n",
      "#Show as a pop-up window\n",
      "#plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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nVa96VV71qlfljDPO6HQ5sGB01AAAALBolGWZm266Kaeddlqe+9zn5rnPfW5O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\nvb310UcfyeFwaPr06WratKkSExO1Zs0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       "text": [
        "<matplotlib.figure.Figure at 0x7fbe9b55a390>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}