{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PySeison - Tutorial 5: Drifter class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. PySeidon-dvt - Drifter object initialisation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly to the \"ADCP class\" and the \"TideGauge class\", the \"Drifter class\" is a measurement-based object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1. Package importation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As any other library in *Python-dvt*, PySeidon has to be first imported before to be used. Here we will use an alternative *import* statement compared to the one previoulsy presented:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from pyseidon_dvt import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*** Star *** here means *all*. Usually this form of statements would import the entire library. In the case of *PySeidon-dvt*, this statement will import the following object classes: FVCOM, Station, Validation, ADCP, Tidegauge and Drifter. Only the TideGauge class will be tackle in this tutorial. However note should note that the architecture design and functioning between each classes are very similar. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2. Object definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Python* is by definition an [**object oriented language**](http://www.tutorialspoint.com/python/python_classes_objects.htm)...and so is *matlab*. *PySeidon-dvt* is based on this notion of object, so let us define our first \"Drifter\" object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Exercise 1: ***\n",
    "- Unravel Drifter documentation with Ipython ***shortcuts***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Answer: ***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Drifter?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to the documentation, in order to define a Drifter object, the only required input is a ***filename**. This string input represents path to a file (e.g. *testAdcp=Drifter('./path_to_matlab_file/filename')* and whose file must be a matlab file (i.e. *.mat).\n",
    "\n",
    "**Note** that, at the current stage, the package only handle a certain type of file and data format. A template for the TideGauge file/data format is provided in the package under *data4tutorial*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Exercise 2: ***\n",
    "- define a drifter object named *drift* from the following template: **./data4tutorial/drifter_GP_01aug2013.mat**\n",
    "- Tip: adapt the file's path to your local machine. \n",
    "\n",
    "***Answer: ***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "drift = Drifter('./data4tutorial/drifter_GP_01aug2013.mat')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3. Object attributes, functions, methods & special methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The TideGauge object possesses 3 attributes and 2 methods. They would appear by typing ***tg. Tab*** for instance.\n",
    "\n",
    "An *attribute* is a quantity intrinsic to its *object*. A *method* is an intrinsic *function* which changes an *attribute* of its object. Contrarily a *function* will generate its own *output*:"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "object.method(inputs)\n",
    "output = object.function(inputs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Station attributes are:\n",
    "- ***History***: history metadata that keeps track of the object changes\n",
    "- ***Data***: gathers the raw/unchanged data of the specified *.mat file\n",
    "- ***Variables***: gathers the hydrodynamics related data. Note that methods will generate new fields in this attribute\n",
    "\n",
    "The Station methods & functions are:\n",
    "- ***Plots***: gathers plotting methods for use with 2D and 3D variables\n",
    "- ***dump_profile_data***: dumps profile data (x,y) in a *.csv file."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. PySeidon-dvt - Hands-on (10 seconds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Exercise 3: ***\n",
    "- Plot drifter's trajectorie\n",
    "\n",
    "***Answer: ***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_base.py:1057: UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal\n",
      "  if aspect == 'normal':\n",
      "/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_base.py:1062: UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal\n",
      "  elif aspect in ('equal', 'auto'):\n",
      "/usr/local/lib/python2.7/dist-packages/matplotlib/figure.py:387: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
      "  \"matplotlib is currently using a non-GUI backend, \"\n"
     ]
    },
    {
     "data": {
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8f5cAkkxXn1t7Fwr8vDrHvlpWV/LhGsDNbC3h7ONngD8Cnt+qUNu82cy+seRx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\n0pCCg4g09P8BPkqo5MT3bXcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x602e550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drift.Plots.trajectories()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More to come in next version of Pyseidon..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Bug patrol & steering committee"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1. Bug report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As beta tester, your first assignement is to report bugs...yet not everything is a bug. The first thing to check before to report a bug is to verify that your version of *PySeidon-dvt* is up-to-date. The best way to keep up with the package evolution is to [***git***](http://git-scm.com/) to ***clone*** the repository, use ***pull*** to update it and ***re-install*** it if needed. \n",
    "\n",
    "The second thing to check before to report a bug is to verify that the bug is ***reproducible***. When running into a bug, double check that your inputs fit the description of the documentation then turn the ***debug flag on*** (e.g. *output = tidegaugeobject.function(inputs, debug=True)*) and submit the command again. If the error re-occurs then report it (i.e. copy entire error message + command and send it to package administrator)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2. Suggestions & critics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your second role as beta-tester is to submit suggestions and critics to the developpers regarding the functioning and functionality of the package. Beta testing phase is the best opportunity to steer a project towards the applications you would like to be tackled..."
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Raw Cell Format",
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}