{ "cells": [ { "cell_type": "code", "execution_count": 92, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from __future__ import division\n", "from numpy import cos, pi\n", "import numpy as np\n", "\n", "def eady_qy_series(N,z):\n", " ''' Galerkin approximatin to Eady's \n", " basic state U = z + 1 \n", " N is the number of baroclinic modes '''\n", "\n", " n = np.arange(N)\n", " Z = np.array( np.matrix(2*n+1).T*np.matrix(z) )\n", "\n", " return 4.*cos(pi*Z).sum(axis=0)" ] }, { "cell_type": "code", "execution_count": 99, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "plt.rcParams.update({'font.size': 25, 'legend.handlelength' : 1.25})\n", "import seaborn as sns\n", "sns.set(style=\"darkgrid\")\n", "sns.set_context(\"notebook\", font_scale=2, rc={\"lines.linewidth\": 4.})\n", "\n", "\n", "z = np.linspace(-1.,0,300) \n", "U_exact = z + 1.\n", "\n", "N = np.arange(200)\n", "Qy_g = np.zeros((z.size,N.size))\n", "\n", "for i in range(N.size):\n", " Qy_g[:,i] = eady_qy_series(N[i],z)" ] }, { "cell_type": "code", "execution_count": 100, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from JSAnimation.IPython_display import display_animation\n", "from matplotlib import animation" ] }, { "cell_type": "code", "execution_count": 101, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "