fperez/README.md

## README.md

      
    Raw
  

              README.md
            
          
    Polyglot Data Science with IPython & friends

Author: Fernando Pérez.
A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.
This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.
See the companion notebook for data preparation and setup.
Used for a lecture at the Berkeley Institute for Data Science. The lecture video has a live demo of this material.
License: CC-BY.

  
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## polyglot-ds-prep.ipynb

      
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## polyglot-ds.ipynb
{
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  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
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   "source": [
    "# Polyglot Data Science with IPython & friends\n",
    "\n",
    "Author: [Fernando Pérez](http://fperez.org).\n",
    "\n",
    "A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.  \n",
    "\n",
    "This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.\n",
    "\n",
    "See the [companion notebook](polyglot-ds-prep.ipynb) for data preparation and setup.\n",
    "\n",
    "Used for a lecture at the [Berkeley Institute for Data Science](https://bids.berkeley.edu). The [lecture video](https://youtu.be/ZwNCUetnccw) has a live demo of this material.\n",
    "\n",
    "License: [CC-BY](https://creativecommons.org/licenses/by/4.0/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use(\"seaborn\")\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 6)\n",
    "sns.set_context(\"talk\", font_scale=1.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's begin by reading our dataset and having a quick look:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(300, 2)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.094287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.021014</td>\n",
       "      <td>-0.216828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.042028</td>\n",
       "      <td>0.329982</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "0  0.000000  0.094287\n",
       "1  0.021014 -0.216828\n",
       "2  0.042028  0.329982"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('data.csv')\n",
    "print(data.shape)\n",
    "data.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ah, it looks like we have a quantitative dataset with $(x,y)$ pairs - a scatterplot is a decent starting point to get a feel for these data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot.scatter(x='x', y='y');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mmh, what to do?\n",
    "\n",
    "Let's try to build a simple linear model for these data, with some features we'll extract from the data. There's probably:\n",
    "\n",
    "* a linear dependence\n",
    "* something that looks broadly non-linear, let's say quadratic, to keep things simple\n",
    "* and maybe an oscillatorty term: but it looks a bit like a chirp, not a simple sinusoid. Again, simplest non-linear choice: quadratic frequency dependency.\n",
    "\n",
    "In summary, let's try\n",
    "\n",
    "$$\n",
    "y \\sim \\theta_1 x + \\theta_2 x^2 + \\theta_3 \\sin(x^2)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oh boy! Complicated data, Julia to the rescue...\n",
    "\n",
    "Maybe Julia can help us efficiently compute that nasty non-linear feature, $x^2$?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing Julia interpreter. This may take some time...\n"
     ]
    }
   ],
   "source": [
    "%load_ext julia.magic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "jxsq = %julia xsq(x) = x.^2  # Simplest way to define a function in Julia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've defined the function `xsq` in Julia, and in Python we have it available as `jxsq`, which we can call as a normal Python function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = data['x']\n",
    "f2 = jxsq(x)\n",
    "x.shape == f2.shape  # simple sanity check"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# More complicated features, we need performance... \n",
    "## Fortran can help us!\n",
    "\n",
    "Let's use this oldie but goodie to assist in the task of estimating our next non-linear feature, $\\sin(x^2)$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/fperez/.local/lib/python3.6/site-packages/fortranmagic.py:147: UserWarning: get_ipython_cache_dir has moved to the IPython.paths module since IPython 4.0.\n",
      "  self._lib_dir = os.path.join(get_ipython_cache_dir(), 'fortran')\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "$.getScript(\"https://raw.github.com/marijnh/CodeMirror/master/mode/fortran/fortran.js\", function () {\n",
       "IPython.config.cell_magic_highlight['magic_fortran'] = {'reg':[/^%%fortran/]};});\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%load_ext fortranmagic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%fortran\n",
    "subroutine sinx2(x, y, n)\n",
    "    real, intent(in), dimension(n) :: x\n",
    "    real, intent(out), dimension(n) :: y\n",
    "    !intent(hide) :: n\n",
    "    y = sin(x**2)\n",
    "end subroutine sinx2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, `sinx2` can be used as a plain Python function too:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f3 = sinx2(x)\n",
    "f3.shape == x.shape  # same sanity check"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistical modeling? Maybe R can do that??\n",
    "\n",
    "We now have our data `y` and our features $x$, $f_2 = x^2$ and $f_3 = \\sin(x^2)$.  This is a classic linear modeling problem, and R is awesome at fitting those!\n",
    "\n",
    "Let's put our features together in a nice design matrix and load up R:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300, 3)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.column_stack([x, f2, f3])\n",
    "A.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "y = data['y']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In R, this can be written as a linear model `lm(y ~ 0 + A)`.\n",
    "\n",
    "Note that we'll ask for the fit coefficients `fitc` to keep moving forward:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = y ~ 0 + A)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-0.7186 -0.1182  0.0090  0.1275  0.5450 \n",
       "\n",
       "Coefficients:\n",
       "    Estimate Std. Error t value Pr(>|t|)    \n",
       "A1  1.000707   0.012517   79.95   <2e-16 ***\n",
       "A2 -0.199631   0.002566  -77.81   <2e-16 ***\n",
       "A3  1.015147   0.016646   60.98   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.1958 on 297 degrees of freedom\n",
       "Multiple R-squared:  0.9741,\tAdjusted R-squared:  0.9739 \n",
       "F-statistic:  3730 on 3 and 297 DF,  p-value: < 2.2e-16\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -i y,A -o fitc\n",
    "\n",
    "ylm = lm(y ~ 0 + A)\n",
    "fitc = coef(ylm)\n",
    "print(summary(ylm))\n",
    "par(mfrow=c(2,2))\n",
    "plot(ylm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Back to Python to look at the results!\n",
    "\n",
    "R gave us our fit coefficient vector `fitc`, we can now proceed using it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <span>FloatVector with 3 elements.</span>\n",
       "    <table>\n",
       "      <tbody>\n",
       "      <tr>\n",
       "      \n",
       "      <td>\n",
       "        1.000707\n",
       "      </td>\n",
       "      \n",
       "      <td>\n",
       "        -0.199631\n",
       "      </td>\n",
       "      \n",
       "      <td>\n",
       "        1.015147\n",
       "      </td>\n",
       "      \n",
       "      </tr>\n",
       "      </tbody>\n",
       "    </table>\n",
       "    "
      ],
      "text/plain": [
       "R object with classes: ('numeric',) mapped to:\n",
       "<FloatVector - Python:0x1a35448e48 / R:0x7fcc7291b498>\n",
       "[1.000707, -0.199631, 1.015147]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fitc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We construct our fitted model and visualize our results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "yfit = A @ fitc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, 'o', label='data')\n",
    "plt.plot(x, yfit, label='fit', color='orange', lw=4)\n",
    "plt.title('Julia, Python and R working in Jupyter')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Polyglot Data Science FTW!!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Bonus\n",
    "\n",
    "## Cython, the happy child of C and Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    return x**2-x\n",
    "\n",
    "def integrate_f(a, b, N):\n",
    "    s = 0; dx = (b-a)/N\n",
    "    for i in range(N):\n",
    "        s += f(a+i*dx)\n",
    "    return s * dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       "<p><span style=\"border-bottom: solid 1px grey;\">Generated by Cython 0.28.2</span></p>\n",
       "<p>\n",
       "    <span style=\"background-color: #FFFF00\">Yellow lines</span> hint at Python interaction.<br />\n",
       "    Click on a line that starts with a \"<code>+</code>\" to see the C code that Cython generated for it.\n",
       "</p>\n",
       "<div class=\"cython\"><pre class=\"cython line score-0\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">01</span>: <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">fcy</span><span class=\"p\">(</span><span class=\"n\">double</span> <span class=\"n\">x</span><span class=\"p\">)</span> <span class=\"k\">except</span><span class=\"o\">?</span> <span class=\"o\">-</span><span class=\"mf\">2</span><span class=\"p\">:</span></pre>\n",
       "<pre class='cython code score-0 '>static double __pyx_f_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_fcy(double __pyx_v_x) {\n",
       "  double __pyx_r;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"fcy\", 0);\n",
       "/* … */\n",
       "  /* function exit code */\n",
       "  __pyx_L0:;\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return __pyx_r;\n",
       "}\n",
       "</pre><pre class=\"cython line score-0\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">02</span>:     <span class=\"k\">return</span> <span class=\"n\">x</span><span class=\"o\">**</span><span class=\"mf\">2</span><span class=\"o\">-</span><span class=\"n\">x</span></pre>\n",
       "<pre class='cython code score-0 '>  __pyx_r = (pow(__pyx_v_x, 2.0) - __pyx_v_x);\n",
       "  goto __pyx_L0;\n",
       "</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">03</span>: </pre>\n",
       "<pre class=\"cython line score-71\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">04</span>: <span class=\"k\">def</span> <span class=\"nf\">integrate_fcy</span><span class=\"p\">(</span><span class=\"n\">double</span> <span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">double</span> <span class=\"n\">b</span><span class=\"p\">,</span> <span class=\"nb\">int</span> <span class=\"n\">N</span><span class=\"p\">):</span></pre>\n",
       "<pre class='cython code score-71 '>/* Python wrapper */\n",
       "static PyObject *__pyx_pw_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/\n",
       "static PyMethodDef __pyx_mdef_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy = {\"integrate_fcy\", (PyCFunction)__pyx_pw_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy, METH_VARARGS|METH_KEYWORDS, 0};\n",
       "static PyObject *__pyx_pw_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n",
       "  double __pyx_v_a;\n",
       "  double __pyx_v_b;\n",
       "  int __pyx_v_N;\n",
       "  PyObject *__pyx_r = 0;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"integrate_fcy (wrapper)\", 0);\n",
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       "    static PyObject **__pyx_pyargnames[] = {&amp;__pyx_n_s_a,&amp;__pyx_n_s_b,&amp;__pyx_n_s_N,0};\n",
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       "    if (unlikely(__pyx_kwds)) {\n",
       "      Py_ssize_t kw_args;\n",
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       "      switch (pos_args) {\n",
       "        case  3: values[2] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 2);\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  2: values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  1: values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  0: break;\n",
       "        default: goto __pyx_L5_argtuple_error;\n",
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       "      kw_args = <span class='py_c_api'>PyDict_Size</span>(__pyx_kwds);\n",
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       "        if (likely((values[0] = <span class='pyx_c_api'>__Pyx_PyDict_GetItemStr</span>(__pyx_kwds, __pyx_n_s_a)) != 0)) kw_args--;\n",
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       "        if (likely((values[1] = <span class='pyx_c_api'>__Pyx_PyDict_GetItemStr</span>(__pyx_kwds, __pyx_n_s_b)) != 0)) kw_args--;\n",
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       "          <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"integrate_fcy\", 1, 3, 3, 1); <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "        }\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  2:\n",
       "        if (likely((values[2] = <span class='pyx_c_api'>__Pyx_PyDict_GetItemStr</span>(__pyx_kwds, __pyx_n_s_N)) != 0)) kw_args--;\n",
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       "      values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n",
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       "      values[2] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 2);\n",
       "    }\n",
       "    __pyx_v_a = __pyx_<span class='py_c_api'>PyFloat_AsDouble</span>(values[0]); if (unlikely((__pyx_v_a == (double)-1) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "    __pyx_v_b = __pyx_<span class='py_c_api'>PyFloat_AsDouble</span>(values[1]); if (unlikely((__pyx_v_b == (double)-1) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "    __pyx_v_N = <span class='pyx_c_api'>__Pyx_PyInt_As_int</span>(values[2]); if (unlikely((__pyx_v_N == (int)-1) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "  }\n",
       "  goto __pyx_L4_argument_unpacking_done;\n",
       "  __pyx_L5_argtuple_error:;\n",
       "  <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"integrate_fcy\", 1, 3, 3, <span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args)); <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "  __pyx_L3_error:;\n",
       "  <span class='pyx_c_api'>__Pyx_AddTraceback</span>(\"_cython_magic_e533f0119deb0c87f04cae3c0c2176c0.integrate_fcy\", __pyx_clineno, __pyx_lineno, __pyx_filename);\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return NULL;\n",
       "  __pyx_L4_argument_unpacking_done:;\n",
       "  __pyx_r = __pyx_pf_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_integrate_fcy(__pyx_self, __pyx_v_a, __pyx_v_b, __pyx_v_N);\n",
       "\n",
       "  /* function exit code */\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return __pyx_r;\n",
       "}\n",
       "\n",
       "static PyObject *__pyx_pf_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_integrate_fcy(CYTHON_UNUSED PyObject *__pyx_self, double __pyx_v_a, double __pyx_v_b, int __pyx_v_N) {\n",
       "  int __pyx_v_i;\n",
       "  double __pyx_v_s;\n",
       "  double __pyx_v_dx;\n",
       "  PyObject *__pyx_r = NULL;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"integrate_fcy\", 0);\n",
       "/* … */\n",
       "  /* function exit code */\n",
       "  __pyx_L1_error:;\n",
       "  <span class='pyx_macro_api'>__Pyx_XDECREF</span>(__pyx_t_5);\n",
       "  <span class='pyx_c_api'>__Pyx_AddTraceback</span>(\"_cython_magic_e533f0119deb0c87f04cae3c0c2176c0.integrate_fcy\", __pyx_clineno, __pyx_lineno, __pyx_filename);\n",
       "  __pyx_r = NULL;\n",
       "  __pyx_L0:;\n",
       "  <span class='refnanny'>__Pyx_XGIVEREF</span>(__pyx_r);\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return __pyx_r;\n",
       "}\n",
       "/* … */\n",
       "  __pyx_tuple_ = <span class='py_c_api'>PyTuple_Pack</span>(6, __pyx_n_s_a, __pyx_n_s_b, __pyx_n_s_N, __pyx_n_s_i, __pyx_n_s_s, __pyx_n_s_dx);<span class='error_goto'> if (unlikely(!__pyx_tuple_)) __PYX_ERR(0, 4, __pyx_L1_error)</span>\n",
       "  <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_tuple_);\n",
       "  <span class='refnanny'>__Pyx_GIVEREF</span>(__pyx_tuple_);\n",
       "/* … */\n",
       "  __pyx_t_1 = PyCFunction_NewEx(&amp;__pyx_mdef_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy, NULL, __pyx_n_s_cython_magic_e533f0119deb0c87f0);<span class='error_goto'> if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 4, __pyx_L1_error)</span>\n",
       "  <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_1);\n",
       "  if (<span class='py_c_api'>PyDict_SetItem</span>(__pyx_d, __pyx_n_s_integrate_fcy, __pyx_t_1) &lt; 0) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L1_error)</span>\n",
       "  <span class='pyx_macro_api'>__Pyx_DECREF</span>(__pyx_t_1); __pyx_t_1 = 0;\n",
       "</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">05</span>:     <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">i</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">06</span>:     <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">s</span><span class=\"p\">,</span> <span class=\"nf\">dx</span></pre>\n",
       "<pre class=\"cython line score-5\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">07</span>:     <span class=\"n\">s</span> <span class=\"o\">=</span> <span class=\"mf\">0</span><span class=\"p\">;</span> <span class=\"n\">dx</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">b</span><span class=\"o\">-</span><span class=\"n\">a</span><span class=\"p\">)</span><span class=\"o\">/</span><span class=\"n\">N</span></pre>\n",
       "<pre class='cython code score-5 '>  __pyx_v_s = 0.0;\n",
       "  __pyx_t_1 = (__pyx_v_b - __pyx_v_a);\n",
       "  if (unlikely(__pyx_v_N == 0)) {\n",
       "    <span class='py_c_api'>PyErr_SetString</span>(PyExc_ZeroDivisionError, \"float division\");\n",
       "    <span class='error_goto'>__PYX_ERR(0, 7, __pyx_L1_error)</span>\n",
       "  }\n",
       "  __pyx_v_dx = (__pyx_t_1 / ((double)__pyx_v_N));\n",
       "</pre><pre class=\"cython line score-0\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">08</span>:     <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">N</span><span class=\"p\">):</span></pre>\n",
       "<pre class='cython code score-0 '>  __pyx_t_2 = __pyx_v_N;\n",
       "  __pyx_t_3 = __pyx_t_2;\n",
       "  for (__pyx_t_4 = 0; __pyx_t_4 &lt; __pyx_t_3; __pyx_t_4+=1) {\n",
       "    __pyx_v_i = __pyx_t_4;\n",
       "</pre><pre class=\"cython line score-5\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">09</span>:         <span class=\"n\">s</span> <span class=\"o\">+=</span> <span class=\"n\">fcy</span><span class=\"p\">(</span><span class=\"n\">a</span><span class=\"o\">+</span><span class=\"n\">i</span><span class=\"o\">*</span><span class=\"n\">dx</span><span class=\"p\">)</span></pre>\n",
       "<pre class='cython code score-5 '>    __pyx_t_1 = __pyx_f_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_fcy((__pyx_v_a + (__pyx_v_i * __pyx_v_dx))); if (unlikely(__pyx_t_1 == ((double)-2.0) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 9, __pyx_L1_error)</span>\n",
       "    __pyx_v_s = (__pyx_v_s + __pyx_t_1);\n",
       "  }\n",
       "</pre><pre class=\"cython line score-6\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">10</span>:     <span class=\"k\">return</span> <span class=\"n\">s</span> <span class=\"o\">*</span> <span class=\"n\">dx</span></pre>\n",
       "<pre class='cython code score-6 '>  <span class='pyx_macro_api'>__Pyx_XDECREF</span>(__pyx_r);\n",
       "  __pyx_t_5 = <span class='py_c_api'>PyFloat_FromDouble</span>((__pyx_v_s * __pyx_v_dx));<span class='error_goto'> if (unlikely(!__pyx_t_5)) __PYX_ERR(0, 10, __pyx_L1_error)</span>\n",
       "  <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_5);\n",
       "  __pyx_r = __pyx_t_5;\n",
       "  __pyx_t_5 = 0;\n",
       "  goto __pyx_L0;\n",
       "</pre></div></body></html>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%cython -a\n",
    "cdef double fcy(double x) except? -2:\n",
    "    return x**2-x\n",
    "\n",
    "def integrate_fcy(double a, double b, int N):\n",
    "    cdef int i\n",
    "    cdef double s, dx\n",
    "    s = 0; dx = (b-a)/N\n",
    "    for i in range(N):\n",
    "        s += fcy(a+i*dx)\n",
    "    return s * dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "21.8 µs ± 2.87 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
      "195 ns ± 0.482 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "tpy = %timeit -o -n 1000 integrate_f(0, 1, 100)\n",
    "tcy = %timeit -o -n 1000 integrate_fcy(0, 1, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100.78896158720855"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpy.best/tcy.best"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Julia interoperability is pretty neat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "%julia @pyimport numpy as np\n",
    "%julia @pyimport matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a39d48e80>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%julia\n",
    "# Note how we mix numpy and julia:\n",
    "t = linspace(0,2*pi,1000); # use the julia linspace\n",
    "s = sin(3*t + 4*np.cos(2*t)); # use the numpy cosine and julia sine\n",
    "fig = plt.gcf()\n",
    "plt.plot(t, s, color=\"red\", linewidth=2.0, linestyle=\"--\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = %julia fig\n",
    "fig.suptitle(\"Adding a title!\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## And you can really use Fortran as an interactive language"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%fortran\n",
    "subroutine f1(x, y, n)\n",
    "    real, intent(in), dimension(n) :: x\n",
    "    real, intent(out), dimension(n) :: y\n",
    "    !intent(hide) :: n\n",
    "    y = sin(x**2) - cos(x)\n",
    "end subroutine f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = np.linspace(0,2* np.pi, 1000)\n",
    "plt.plot(f1(t));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Bash, Perl, Ruby, etc..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/fperez\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "echo $HOME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feb"
     ]
    }
   ],
   "source": [
    "%%perl\n",
    "@months = (\"Jan\", \"Feb\", \"Mar\");\n",
    "print($months[1])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
	x	y
	0.0	0.09428703274649862
	0.02101399768287487	-0.21682787079387694
	0.04202799536574974	0.32998247004803666
	0.06304199304862461	0.0036910376779959175
	0.08405599073149948	-0.0544094870632954
	0.10506998841437436	0.29133411420559346
	0.12608398609724922	0.310718736500297
	0.1470979837801241	0.03710184794855739
	0.16811198146299897	0.19385680449502704
	0.18912597914587384	-0.23080372945059743
	0.21013997682874871	0.4754598194444005
	0.2311539745116236	0.47226348579069954
	0.25216797219449844	0.4936609017425528
	0.2731819698773733	-0.07143553645414097
	0.2941959675602482	0.2965134877139408
	0.31520996524312306	0.39495610271631554
	0.33622396292599793	0.5075112614675588
	0.3572379606088728	0.5168053860493421
	0.3782519582917477	0.7564556008394825
	0.39926595597462256	0.216741161143698
	0.42027995365749743	0.520141808615399
	0.4412939513403723	0.46466381308230564
	0.4623079490232472	0.6703516636116772
	0.48332194670612205	0.7787710470956681
	0.5043359443889969	0.9687162726597178
	0.5253499420718718	0.6487924421695102
	0.5463639397547466	0.9158718710835747
	0.5673779374376215	0.4559752998461058
	0.5883919351204964	0.821859705782694
	0.6094059328033713	1.1098222426034332
	0.6304199304862461	0.8584153034108905
	0.651433928169121	1.0457914750281228
	0.6724479258519959	1.2284594600580687
	0.6934619235348707	1.2690396077874566
	0.7144759212177456	1.2737166912460058
	0.7354899189006204	1.1178291771613955
	0.7565039165834954	1.2085523305960715
	0.7775179142663702	1.160430948324203
	0.7985319119492451	1.4346476634879184
	0.8195459096321199	1.7856896638059545
	0.8405599073149949	1.363698304252134
	0.8615739049978697	1.2758144742466853
	0.8825879026807446	1.436564698288517
	0.9036019003636194	1.054058214396473
	0.9246158980464944	1.5577062715745673
	0.9456298957293692	1.3670737307877898
	0.9666438934122441	1.5566477333034936
	0.9876578910951189	1.6241865931574329
	1.0086718887779937	1.8070252562351916
	1.0296858864608687	1.7331681488676631
	1.0506998841437436	1.891108813605713
	1.0717138818266183	1.4650168717924723
	1.0927278795094932	1.5033905033420423
	1.1137418771923682	1.7913946882131335
	1.134755874875243	1.7277602211222844
	1.1557698725581178	1.8322012987848455
	1.1767838702409927	1.9533801227508665
	1.1977978679238677	1.894507174191391
	1.2188118656067426	2.0312237287401396
	1.2398258632896173	2.2409586168192526
	1.2608398609724922	1.74787016968533
	1.2818538586553672	1.9365386844626173
	1.302867856338242	2.016956985811513
	1.3238818540211168	1.915157228352737
	1.3448958517039917	2.1617305993411757
	1.3659098493868667	1.4695044990462909
	1.3869238470697414	2.346755263624674
	1.4079378447526163	1.6994786100038657
	1.4289518424354912	1.9540142243834207
	1.4499658401183662	2.0324245533593643
	1.4709798378012409	1.7104125016036007
	1.4919938354841158	1.932092715157879
	1.5130078331669907	1.9488771044291837
	1.5340218308498657	1.8772836619419955
	1.5550358285327404	1.5481368188707556
	1.5760498262156153	2.092098081216662
	1.5970638238984902	1.689508668821579
	1.6180778215813651	1.363753243257729
	1.6390918192642399	1.6675992701153861
	1.6601058169471148	1.4929715328232587
	1.6811198146299897	1.518989678972056
	1.7021338123128644	0.6518879009250004
	1.7231478099957394	1.5650234771609497
	1.7441618076786143	1.2655960185446726
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