"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Text printing\n",
"eqs = []\n",
"eqs.append((r\"$W^{3\\beta}_{\\delta_1 \\rho_1 \\sigma_2} = U^{3\\beta}_{\\delta_1 \\rho_1} + \\frac{1}{8 \\pi 2} \\int^{\\alpha_2}_{\\alpha_2} d \\alpha^\\prime_2 \\left[\\frac{ U^{2\\beta}_{\\delta_1 \\rho_1} - \\alpha^\\prime_2U^{1\\beta}_{\\rho_1 \\sigma_2} }{U^{0\\beta}_{\\rho_1 \\sigma_2}}\\right]$\"))\n",
"eqs.append((r\"$\\frac{d\\rho}{d t} + \\rho \\vec{v}\\cdot\\nabla\\vec{v} = -\\nabla p + \\mu\\nabla^2 \\vec{v} + \\rho \\vec{g}$\"))\n",
"eqs.append((r\"$\\int_{-\\infty}^\\infty e^{-x^2}dx=\\sqrt{\\pi}$\"))\n",
"eqs.append((r\"$E = mc^2 = \\sqrt{{m_0}^2c^4 + p^2c^2}$\"))\n",
"eqs.append((r\"$F_G = G\\frac{m_1m_2}{r^2}$\"))\n",
"\n",
"plt.axes([0.025, 0.025, 0.95, 0.95])\n",
"\n",
"for i in range(24):\n",
" index = np.random.randint(0, len(eqs))\n",
" eq = eqs[index]\n",
" size = np.random.uniform(12, 32)\n",
" x,y = np.random.uniform(0, 1, 2)\n",
" alpha = np.random.uniform(0.25, .75)\n",
" plt.text(x, y, eq, ha='center', va='center', color=\"#11557c\", alpha=alpha,\n",
" transform=plt.gca().transAxes, fontsize=size, clip_on=True)\n",
"plt.xticks(())\n",
"plt.yticks(())\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### matplotlib: imporatnt plotting tutorials\n",
"\n",
"Pyplot - http://matplotlib.org/users/pyplot_tutorial.html
\n",
"Image - http://matplotlib.org/users/image_tutorial.html
\n",
"Text - http://matplotlib.org/users/index_text.html
\n",
"Artist - http://matplotlib.org/users/artists.html
\n",
"Path - http://matplotlib.org/users/path_tutorial.html
\n",
"Transforms - http://matplotlib.org/users/transforms_tutorial.html
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3D Plotting with Mayavi\n",
"\n",
"Important tutorial - http://docs.enthought.com/mayavi/mayavi/mlab.html
\n",
"Installation guide
\n",
"-----------------------
\n",
"i) pip install mayavi
\n",
"ii) pip install PyQt5
\n",
"iii) jupyter nbextension install --py mayavi --user
\n",
"iv) jupyter nbextension enable --py mayavi --user"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"from mayavi import mlab\n",
"# mlab.init_notebook() # for inline"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"# Points\n",
"x, y, z, value = np.random.random((4, 40))\n",
"mlab.points3d(x, y, z, value) \n",
"mlab.show() #use this if inline is disabled"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Lines\n",
"mlab.clf() # Clear the figure\n",
"t = np.linspace(0, 20, 200)\n",
"mlab.plot3d(np.sin(t), np.cos(t), 0.1*t, t)\n",
"mlab.show() #use this if inline is disabled"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Elevation surface\n",
"mlab.clf()\n",
"x, y = np.mgrid[-10:10:100j, -10:10:100j]\n",
"r = np.sqrt(x**2 + y**2)\n",
"z = np.sin(r)/r\n",
"mlab.surf(z, warp_scale='auto')\n",
"mlab.show() #use this if inline is disabled"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Arbitrary regular mesh\n",
"mlab.clf()\n",
"phi, theta = np.mgrid[0:np.pi:11j, 0:2*np.pi:11j]\n",
"x = np.sin(phi) * np.cos(theta)\n",
"y = np.sin(phi) * np.sin(theta)\n",
"z = np.cos(phi)\n",
"mlab.mesh(x, y, z)\n",
"mlab.mesh(x, y, z, representation='wireframe', color=(0, 0, 0))\n",
"mlab.show() #use this if inline is disabled"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# References"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"a) https://www.scipy-lectures.org/intro/matplotlib/index.html
\n",
"b) https://www.scipy-lectures.org/packages/3d_plotting/index.html
\n",
"c) https://github.com/kuleshov/cs228-material/blob/master/tutorials/python/cs228-python-tutorial.ipynb
\n",
"
"
]
}
],
"metadata": {
"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": 2
}