Split scipy and matplotlib notebooks

matplotlib-tutorial.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Matplotlib](images/matplotlib_logo-s.png)\n",
+    "\n",
+    "# Matplotlib"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's take a quick look at the *matplotlib* essentials.\n",
+    "\n",
+    "First let's import the neccesary modules and tell the notebook to generate the figures inline:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `inline` is important for the notebook, so that plots are displayed\n",
+    "in the notebook and not in a new window.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use (note that you have to use `show` explicitly if you don't use `%matplotlib inline`):\n",
+    "\n",
+    "```\n",
+    "   plt.plot(x,y)  # line plot\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "And now let's go with some examples."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Basic matplotlib visualization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* **1D plotting**:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.linspace(0, 4.*np.pi, 100)\n",
+    "y = np.sin(x)\n",
+    "plt.plot(x, y)  # line plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.plot(x, y, 'o')  # dot plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.plot(x, y)\n",
+    "plt.plot(x, y, 'o')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* **2D arrays** (such as images):\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image = np.random.rand(30, 30)\n",
+    "plt.imshow(image, cmap=plt.cm.hot)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercise: Simple visualizations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* Plot some simple arrays / functions.\n",
+    "\n",
+    "* Try using the `gray` colormap.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1D plot"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A tangent between 0 and 4$\\pi$.\n",
+    "\n",
+    "$$y = \\tan(x), \\; x\\in[0., 4\\pi]$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.linspace( 0., 4.*np.pi, num=200 )\n",
+    "y = np.tan(x)\n",
+    "\n",
+    "plt.plot(x, y)\n",
+    "\n",
+    "plt.xlabel(r'$x$')        #using LaTeX syntax\n",
+    "plt.ylabel(r'$\\tan(x)$')\n",
+    "plt.grid(True)\n",
+    "#plt.savefig('tan.png')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1D polar plot "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "$\\theta(\\rho) = 2\\pi \\rho, \\; \\rho \\in [0, 2]$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r = np.arange(0, 2., 0.01)\n",
+    "theta = 2 * np.pi * r\n",
+    "\n",
+    "plt.polar(theta, r, color='r', linewidth=3)\n",
+    "plt.grid(True)\n",
+    "\n",
+    "plt.title(\"A line plot on a polar axis\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercise"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot the function \n",
+    "\n",
+    "$$y = \\frac{\\sin(x)}{x}, \\; x\\in[0.1, 6\\pi]$$\n",
+    "\n",
+    "and try to \n",
+    "\n",
+    "* set the figure *legend*\n",
+    "* change the *line style*\n",
+    "\n",
+    "hint: checkout the [matplotlib examples](http://matplotlib.org/examples/index.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %load files/sol_sinc.py"
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Raw Cell Format",
+  "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": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

scipy-tutorial.ipynb

 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "![Matplotlib](images/matplotlib_logo-s.png)\n",
-    "\n",
-    "# Matplotlib"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's take a quick look at the matplotlib essentials.\n",
-    "\n",
-    "First let's import the neccesary modules:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
-   "source": [
-    "And now let's go with some examples."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 1D plot"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A tangent between 0 and 4$\\pi$.\n",
-    "\n",
-    "$$y = \\tan(x), \\; x\\in[0., 4\\pi]$$"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "x = np.linspace( 0., 4.*np.pi, num=200 )\n",
-    "y = np.tan(x)\n",
-    "\n",
-    "plt.plot(x, y)\n",
-    "\n",
-    "plt.xlabel(r'$x$')        #using LaTeX syntax\n",
-    "plt.ylabel(r'$\\tan(x)$')\n",
-    "plt.grid(True)\n",
-    "#plt.savefig('tan.png')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 1D polar plot "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "$\\theta(\\rho) = 2\\pi \\rho, \\; \\rho \\in [0, 2]$"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "r = np.arange(0, 2., 0.01)\n",
-    "theta = 2 * np.pi * r\n",
-    "\n",
-    "plt.polar(theta, r, color='r', linewidth=3)\n",
-    "plt.grid(True)\n",
-    "\n",
-    "plt.title(\"A line plot on a polar axis\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exercise"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Plot the function \n",
-    "\n",
-    "$$y = \\frac{\\sin(x)}{x}, \\; x\\in[0.1, 6\\pi]$$\n",
-    "\n",
-    "and try to \n",
-    "\n",
-    "* set the figure *legend*\n",
-    "* change the *line style*\n",
-    "\n",
-    "hint: checkout the [matplotlib examples](http://matplotlib.org/examples/index.html)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "# %load files/sol_sinc.py"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},