{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from IPython.display import Image\n", "import pandas as pd\n", "from matplotlib import cm\n", "%matplotlib inline\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Lecture 26:\n", "\n", "- Learn about 3D plots of points and surfaces\n", "- Show some examples with subduction zone Earthquakes and isotopic systems\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3D Plotting with Python\n", "\n", "Contour plots are really just a way to visualize something that is inherently 3D on a 2D surface. Think about our topographic map - the contour intervals are elevations and our brains can reconstruct the 3D world by looking at the contours on the map. But with computers we can visualize the 3D world in a more realistic manner. There are many 3D plotting packages that apply many different approaches to plot in 3D. For example, **mplot3d**, is a 3D toolkit of **matplotlib** that uses the same logic as for \"regular\" **matplotlib**. For more on this module, see:\n", "\n", "http://matplotlib.sourceforge.net/mpl_toolkits/mplot3d/index.html\n", "\n", "\n", " But for more 3D horsepower, there is a module called **mlab**, which is part of the **mayavi** package. See: \n", " \n", " \n", " http://github.enthought.com/mayavi/mayavi/mlab.html\n", "\n", "\n", " And then there is **Mayavi** itself, which comes with the Canopy Python Edition. This was way beyond what I know, but if you are curious, check out this website:\n", " \n", " http://github.enthought.com/mayavi/mayavi/examples.html\n", " \n", "\n", "### 3D Plotting in Jupyter Notebooks\n", "Until now, we have used **%matplotlib inline** to plot our matplotlib figures within the jupyter notebook. In order to plot a 3D figure within the jupyter notebook and allow interaction with a 3D plot, we must use this alternative: **%matplotlib notebook**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plotting points in 3D\n", "\n", "Remember this plot from Lecture 18?" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Image(filename='Figures/earthquakes_depth.png')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We used color to represent the depth of each earthquake . You can see that there are increasingly deep earthquakes as you move away from subduction zones- sort of. \n", "\n", "It would be more instructive to view the depth of the earthquakes as points in a 3D plot. So, let's read-in the data, filter for a lat/lon box from 35$^{\\circ}$S to 20$^{\\circ}$N and 170$^{\\circ}$-190$^{\\circ}$E (the Marianas trench), and plot the data in 3D.\n", "\n", "To begin, let's filter the data by the desired bounds and make an array of longitudes,x, an array of latitudes,y,and an array of depths,z. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# read in the data from the Lecture 18 as a Pandas DataFrame: \n", "eq_data=pd.read_csv('Datasets/EarthquakeLocations/last5Years.csv',skiprows=1)\n", "\n", "# define some boundaries for our box\n", "lat_min,lon_min,lat_max,lon_max=-35,175,-15,190\n", "\n", "# use Pandas filtering to fish out lat/lon in this range\n", "box=eq_data[(eq_data.longitude.values%360=lon_min)] \n", "box=box[(box.latitude.values=lat_min)] \n", "\n", "# and export them to NumPy arrays\n", "x=box.longitude.values%360\n", "y=box.latitude.values\n", "z=-box.depth.values\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can use the **Axes3D** class from the **mplot3d**, which is another tool in the **matplotlib** toolkit (**mpl_toolkits**). [Remember that is where we got Basemap.] \n", "\n", "We will import the **Axes3D** module. \n", "\n", "But before we can use it, we have to make the notebook ready for 3D plots. One somewhat annoying thing about using the 3D options in a Jupyter notebook is that there are two different **magic** commands that are used. You are already familiar with the **%matplotlib inline** command that allows us to plot \"regular\" matplotlib plots in the notebook. But now we need a NEW one: **%matplotlib notebook** strictly for plotting 3D objects. The trouble comes when you try to do both in one notebook, because you have to always use the magic correct command before you can see your figure. So we import the Axes3D module and call the magic command:\n", "\n", "%matplotlib notebook" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# import the module\n", "from mpl_toolkits.mplot3d import Axes3D\n", "%matplotlib notebook\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The trick to using **Axes3D** is to first make a figure object using **plt.figure( )** (called **fig** below) and then use the figure method **fig.add_subplot( )** to make an **Axis** instance (here called **ax**). Finally we set the keyword **projection** of the **add_sublot** call to '3d'. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
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');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
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');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig=plt.figure(2,(7,7)) # let's make a new one.\n", "ax = fig.add_subplot(111, projection='3d') # so we can do this. \n", "\n", "\n", "ax.scatter(x,y,z,c='r',marker='o')\n", "ax.set_xlabel('Longitude')\n", "ax.set_ylabel('Latitude')\n", "ax.set_zlabel('Depth (km)');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try twirling the figure around! Can you see the slab? \n", "\n", "You can imagine other enhancements, for example setting the size of the points to be proportional to the size of the earthquake." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3D contour type plots\n", "\n", "In Lecture 19, we learned how to make 2D color contour plots, but 3D is much more fun, so let's try to make a 3D version of something geophysical, namely the gravity anomaly of a buried sphere. \n", "\n", "Let's choose a sphere with a radius $R$ of 2 m (whose volume is ${{4\\pi}\\over{3}}R^3$), that is buried $z=$ 3 m deep. The sphere's density ($\\Delta \\rho$) is 500 kg/m$^3$, which is, for this purpose, much higher than the surrounding material. Oh and we'll need the universal gravitational constant $G$, which is 6.67x 10$^{-11}$ Nm$^2$/kg$^2$.\n", "\n", "The formula for gravitational attraction of such a body is: \n", "\n", "$$g= {{4\\pi}\\over{3}} R^3 {{G \\Delta \\rho}\\over{(h^2+z^2})},$$\n", "\n", "where $h$ is the horizontal distance from the mass.\n", "\n", "The units (from dimensional analysis remembering that Newtons are kg $\\cdot$ m $\\cdot$ s$^2$) are m $\\cdot$ s$^{-2}$. 1 Gal (for Galileo) = 1 cm $\\cdot$s$^{-2}$, so to convert $g$ to the units of microgals, we multiply the above by 10$^{8}$. \n", "\n", "We can write our equation as a lambda function." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "gravity= lambda G,R,drho,h,z : (1e8*G*4.*np.pi*R**3.*drho)/(3.*(h**2+z**2)) # gravitational attraction. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And set up the arrays the same way as we did in the previous lectures as a color contour on a 2D surface. \n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "from matplotlib import tri" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "x=np.arange(-6.,6.,0.1) # range of x values\n", "y=np.arange(-6,6.,0.1) # range of y values\n", "X,Y=np.meshgrid(x,y) # make a meshgrid" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To get the gravity array $g$, we need $z,G,R$ and $\\Delta \\rho$ and $h$ the horizontal distance from ground zero of the buried sphere, which is given by good old Pythagorous as: \n", "\n", "$$ h=\\sqrt {x^2 + y^2}. $$ \n", "\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# define the other parameters\n", "z=3.\n", "G=6.67e-11 # grav constant in Nm^2/kg^2 (SI)\n", "R=2. # radius in meters\n", "drho=500 # density contrast in kg/m^3\n", "\n", "h=np.sqrt(X**2+Y**2) # get the horizontal distance from ground zero for x,y\n", "# and make the g array\n", "g=gravity(G,R,drho,h,z) # multipy by a million to get the units reasonable for the plots." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We want to make the plot of the gravitational attraction first using our old friend from the Lecture 19, **plt.pcolormesh( )**. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# put this back to 'normal' for use in the notebook using the correct Jupyter magic command \n", "%matplotlib inline \n", "plt.figure(3)\n", "plt.pcolormesh(x,y,g,cmap=cm.jet,shading='gouraud')\n", "plt.axis('equal')\n", "plt.axis('off');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Well that IS pretty. But now we want to do this in 3D." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3D Surfaces\n", "\n", "There are a few ways to plot this in 3D: wireframes and surfaces. Let's start with a wireframe plot. For this we need to use matplotlib **Axes3D**. \n", "\n", "#### Wireframes\n", "There is an **Axes3D** method called **plot_wireframe( )** which will do the trick. It is in many ways similar to the **pcolormesh( )**, but instead of using color to represent values, it uses a 3D projection. \n", "Let's try the **plot_wireframe( )** function on our gravity data. \n", "\n", " In the following plot, we create an **Axes3D** instance called **ax** from the **figure** object, **fig**. By setting $projection='3d'$, we get a 3D projection. \n", "\n", "Remember that because we were just plotting in 2D (%matplotlib inline), we have to call the 3D version (%matplotlib notebook). \n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('');\n", " button.click(method_name, toolbar_event);\n", " button.mouseover(tooltip, toolbar_mouse_event);\n", " nav_element.append(button);\n", " }\n", "\n", " // Add the status bar.\n", " var status_bar = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ " # make the notebook ready for interactive 3D plots again\n", "%matplotlib notebook \n", "fig=plt.figure(4,(8,5)) # make a figure object\n", "ax=fig.add_subplot(111,projection='3d') # get a 3d plot object\n", "surf=ax.plot_surface(X,Y,g,cmap=cm.jet) # use plot_surface to do the plot using a color map\n", "ax.set_xlabel('X') # and label the axes\n", "ax.set_ylabel('Y')\n", "ax.set_zlabel('Z')\n", "bar=fig.colorbar(surf) # put on the color bar\n", "bar.set_label('Gravity in $\\mu$gal'); #label the color bar" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "OR - we can plot the data as a 3D color contour plot. For this, we can use **ax.contour( )**. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "scrolled": true }, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('');\n", " button.click(method_name, toolbar_event);\n", " button.mouseover(tooltip, toolbar_mouse_event);\n", " nav_element.append(button);\n", " }\n", "\n", " // Add the status bar.\n", " var status_bar = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ " # make the notebook ready for interactive 3D plots again\n", "%matplotlib notebook \n", "fig=plt.figure(4,(8,5)) # make a figure object\n", "ax=fig.add_subplot(111,projection='3d') # get a 3d plot object\n", "surf=ax.contour3D(X,Y,g,cmap=cm.jet) # use plot_surface to do the plot using a color map\n", "ax.set_xlabel('X') # and label the axes\n", "ax.set_ylabel('Y')\n", "ax.set_zlabel('Z')\n", "bar=fig.colorbar(surf) # put on the color bar\n", "bar.set_label('Gravity in $\\mu$gal'); #label the color bar" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can even make a wedding cake setting the **extend3d** keyword of the **ax.contour( )** function to **True**. " ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('');\n", " button.click(method_name, toolbar_event);\n", " button.mouseover(tooltip, toolbar_mouse_event);\n", " nav_element.append(button);\n", " }\n", "\n", " // Add the status bar.\n", " var status_bar = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib notebook \n", "fig=plt.figure(6,(8,5)) # make a figure object\n", "ax=fig.add_subplot(111,projection='3d') # give it the powers of an Axes3D object\n", "surf=ax.plot_surface(X,Y,g,alpha=0.3) \n", "cset=ax.contour(X,Y,g,zdir='z',offset=1,cmap=cm.jet)\n", "cset=ax.contour(X,Y,g,zdir='x',offset=-7,cmap=cm.jet)\n", "cset=ax.contour(X,Y,g,zdir='y',offset=7,cmap=cm.jet)\n", "ax.set_xlabel('X') # and label the axes\n", "ax.set_ylabel('Y')\n", "ax.set_zlabel('Z');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotting vectors\n", "\n", "Before we leave the gravity anomaly problem, consider one more way to plot the data. Gravity data are inherently vectors, so we could plot them as arrows. This can be done using the **plt.quiver( )** method.\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on function quiver in module matplotlib.pyplot:\n", "\n", "quiver(*args, **kw)\n", " Plot a 2-D field of arrows.\n", " \n", " Call signatures::\n", " \n", " quiver(U, V, **kw)\n", " quiver(U, V, C, **kw)\n", " quiver(X, Y, U, V, **kw)\n", " quiver(X, Y, U, V, C, **kw)\n", " \n", " *U* and *V* are the arrow data, *X* and *Y* set the location of the\n", " arrows, and *C* sets the color of the arrows. These arguments may be 1-D or\n", " 2-D arrays or sequences.\n", " \n", " If *X* and *Y* are absent, they will be generated as a uniform grid.\n", " If *U* and *V* are 2-D arrays and *X* and *Y* are 1-D, and if ``len(X)`` and\n", " ``len(Y)`` match the column and row dimensions of *U*, then *X* and *Y* will be\n", " expanded with :func:`numpy.meshgrid`.\n", " \n", " The default settings auto-scales the length of the arrows to a reasonable size.\n", " To change this behavior see the *scale* and *scale_units* kwargs.\n", " \n", " The defaults give a slightly swept-back arrow; to make the head a\n", " triangle, make *headaxislength* the same as *headlength*. To make the\n", " arrow more pointed, reduce *headwidth* or increase *headlength* and\n", " *headaxislength*. To make the head smaller relative to the shaft,\n", " scale down all the head parameters. You will probably do best to leave\n", " minshaft alone.\n", " \n", " *linewidths* and *edgecolors* can be used to customize the arrow\n", " outlines.\n", " \n", " Parameters\n", " ----------\n", " X : 1D or 2D array, sequence, optional\n", " The x coordinates of the arrow locations\n", " Y : 1D or 2D array, sequence, optional\n", " The y coordinates of the arrow locations\n", " U : 1D or 2D array or masked array, sequence\n", " The x components of the arrow vectors\n", " V : 1D or 2D array or masked array, sequence\n", " The y components of the arrow vectors\n", " C : 1D or 2D array, sequence, optional\n", " The arrow colors\n", " units : [ 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y' | 'xy' ]\n", " The arrow dimensions (except for *length*) are measured in multiples of\n", " this unit.\n", " \n", " 'width' or 'height': the width or height of the axis\n", " \n", " 'dots' or 'inches': pixels or inches, based on the figure dpi\n", " \n", " 'x', 'y', or 'xy': respectively *X*, *Y*, or :math:`\\sqrt{X^2 + Y^2}`\n", " in data units\n", " \n", " The arrows scale differently depending on the units. For\n", " 'x' or 'y', the arrows get larger as one zooms in; for other\n", " units, the arrow size is independent of the zoom state. For\n", " 'width or 'height', the arrow size increases with the width and\n", " height of the axes, respectively, when the window is resized;\n", " for 'dots' or 'inches', resizing does not change the arrows.\n", " angles : [ 'uv' | 'xy' ], array, optional\n", " Method for determining the angle of the arrows. Default is 'uv'.\n", " \n", " 'uv': the arrow axis aspect ratio is 1 so that\n", " if *U*==*V* the orientation of the arrow on the plot is 45 degrees\n", " counter-clockwise from the horizontal axis (positive to the right).\n", " \n", " 'xy': arrows point from (x,y) to (x+u, y+v).\n", " Use this for plotting a gradient field, for example.\n", " \n", " Alternatively, arbitrary angles may be specified as an array\n", " of values in degrees, counter-clockwise from the horizontal axis.\n", " \n", " Note: inverting a data axis will correspondingly invert the\n", " arrows only with ``angles='xy'``.\n", " scale : None, float, optional\n", " Number of data units per arrow length unit, e.g., m/s per plot width; a\n", " smaller scale parameter makes the arrow longer. Default is *None*.\n", " \n", " If *None*, a simple autoscaling algorithm is used, based on the average\n", " vector length and the number of vectors. The arrow length unit is given by\n", " the *scale_units* parameter\n", " scale_units : [ 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y' | 'xy' ], None, optional\n", " If the *scale* kwarg is *None*, the arrow length unit. Default is *None*.\n", " \n", " e.g. *scale_units* is 'inches', *scale* is 2.0, and\n", " ``(u,v) = (1,0)``, then the vector will be 0.5 inches long.\n", " \n", " If *scale_units* is 'width'/'height', then the vector will be half the\n", " width/height of the axes.\n", " \n", " If *scale_units* is 'x' then the vector will be 0.5 x-axis\n", " units. To plot vectors in the x-y plane, with u and v having\n", " the same units as x and y, use\n", " ``angles='xy', scale_units='xy', scale=1``.\n", " width : scalar, optional\n", " Shaft width in arrow units; default depends on choice of units,\n", " above, and number of vectors; a typical starting value is about\n", " 0.005 times the width of the plot.\n", " headwidth : scalar, optional\n", " Head width as multiple of shaft width, default is 3\n", " headlength : scalar, optional\n", " Head length as multiple of shaft width, default is 5\n", " headaxislength : scalar, optional\n", " Head length at shaft intersection, default is 4.5\n", " minshaft : scalar, optional\n", " Length below which arrow scales, in units of head length. Do not\n", " set this to less than 1, or small arrows will look terrible!\n", " Default is 1\n", " minlength : scalar, optional\n", " Minimum length as a multiple of shaft width; if an arrow length\n", " is less than this, plot a dot (hexagon) of this diameter instead.\n", " Default is 1.\n", " pivot : [ 'tail' | 'mid' | 'middle' | 'tip' ], optional\n", " The part of the arrow that is at the grid point; the arrow rotates\n", " about this point, hence the name *pivot*.\n", " color : [ color | color sequence ], optional\n", " This is a synonym for the\n", " :class:`~matplotlib.collections.PolyCollection` facecolor kwarg.\n", " If *C* has been set, *color* has no effect.\n", " \n", " Notes\n", " -----\n", " Additional :class:`~matplotlib.collections.PolyCollection`\n", " keyword arguments:\n", " \n", " agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array \n", " alpha: float or None \n", " animated: bool \n", " antialiased or antialiaseds: Boolean or sequence of booleans \n", " array: ndarray\n", " capstyle: unknown\n", " clim: a length 2 sequence of floats; may be overridden in methods that have ``vmin`` and ``vmax`` kwargs. \n", " clip_box: a `.Bbox` instance \n", " clip_on: bool \n", " clip_path: [(`~matplotlib.path.Path`, `.Transform`) | `.Patch` | None] \n", " cmap: a colormap or registered colormap name \n", " color: matplotlib color arg or sequence of rgba tuples\n", " contains: a callable function \n", " edgecolor or edgecolors: matplotlib color spec or sequence of specs \n", " facecolor or facecolors: matplotlib color spec or sequence of specs \n", " figure: a `.Figure` instance \n", " gid: an id string \n", " hatch: [ '/' | '\\\\' | '|' | '-' | '+' | 'x' | 'o' | 'O' | '.' | '*' ] \n", " joinstyle: unknown\n", " label: object \n", " linestyle or dashes or linestyles: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) | ``'-'`` | ``'--'`` | ``'-.'`` | ``':'`` | ``'None'`` | ``' '`` | ``''``]\n", " linewidth or linewidths or lw: float or sequence of floats \n", " norm: `.Normalize`\n", " offset_position: [ 'screen' | 'data' ] \n", " offsets: float or sequence of floats \n", " path_effects: `.AbstractPathEffect` \n", " picker: [None | bool | float | callable] \n", " pickradius: float distance in points\n", " rasterized: bool or None \n", " sketch_params: (scale: float, length: float, randomness: float) \n", " snap: bool or None \n", " transform: `.Transform` \n", " url: a url string \n", " urls: List[str] or None \n", " visible: bool \n", " zorder: float \n", " \n", " See Also\n", " --------\n", " quiverkey : Add a key to a quiver plot\n", "\n" ] } ], "source": [ "help(plt.quiver)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So we need the x,y coordinates of the gravity vector and plot the arrows\n", "at the evaluation points. " ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# we need to redo what we already did. but at lower resolution\n", "%matplotlib inline\n", "z=3.\n", "G=6.67e-11 # grav constant in Nm^2/kg^2 (SI)\n", "R=2. # radius in meters\n", "drho=500 # density contrast in kg/m^3\n", "\n", "h=np.sqrt(X**2+Y**2) # get the horizontal distance from ground zero for x,y\n", "# and make the g array\n", "g=gravity(G,R,drho,h,z) # multipy by a million to get the units reasonable for the plots.\n", "\n", "x=np.arange(-6,6.5,1) # range of x values\n", "y=np.arange(-6.,6.5,1) # range of y values\n", "X,Y=np.meshgrid(x,y) # make a meshgrid\n", "h=np.sqrt(X**2+Y**2) # get the horizontal distance from ground zero for x,y\n", "g=gravity(G,R,drho,h,z) # re-use our lambda function\n", "\n", "# now make the horizontal projections along X and Y\n", "U=-X*g\n", "V=-Y*g\n", "# and plot\n", "plt.quiver(x,y,U,V)\n", "plt.axis('equal');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is a lovely plotting package with lots more options (although not 3D). One of them is a nicer quiver plot option, **plotly.create_quiver**. Let's take a look: " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import plotly.figure_factory as ff" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "mode": "lines", "type": "scatter", "x": [ -6, -5.172170943231845, null, -5, -4.201736266687851, null, -4, -3.2671677202380267, null, -3, -2.379128207423884, null, -2, -1.5438492952502005, null, -1, -0.7570501681223892, null, 0, 0, null, 1, 0.7570501681223892, null, 2, 1.5438492952502005, null, 3, 2.379128207423884, null, 4, 3.2671677202380267, null, 5, 4.201736266687851, null, 6, 5.172170943231845, null, -6, -5.042083520025421, null, -5, -4.052907435053382, null, -4, -3.1059446186903927, null, -3, -2.2203005395555753, null, -2, -1.4118056701910477, null, 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "fig=ff.create_quiver(X,Y,U,V)\n", "fig.show() # for some reason, this plotting option requires this line. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's return for a moment to the topic of Lecture 17 where we plotted the data with **seaborn.pairplot** which showed some interesting relationships. Now we can plot the different components on a 3D plot. We can use a new trick to create a discrete color map based on an input color map, too. Here's a function **discrete_cmap** that does it: " ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "def discrete_cmap(N, base_cmap=None):\n", " \"\"\"Create an N-bin discrete colormap from the specified input map\"\"\"\n", "\n", " # Note that if base_cmap is a string or None, you can simply do\n", " # return plt.cm.get_cmap(base_cmap, N)\n", " # The following works for string, None, or a colormap instance:\n", "\n", " base = plt.cm.get_cmap(base_cmap)\n", " color_list = base(np.linspace(0, 1, N))\n", " cmap_name = base.name + str(N)\n", " return color_list" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So we read in the data from Lecture 17. We can use some concepts from Lecture 24 and apply a PCA approach to split the data into the principal components. " ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "MantleArray=pd.read_csv('Datasets/GeoRoc/MantleArray_OIB.csv')\n", "from sklearn.decomposition import PCA\n", "\n", "X_PCA=np.array([MantleArray['EPSILON_ND'],MantleArray['SR87_SR86'],MantleArray['PB206_PB204'],\\\n", " MantleArray['EPSILON_HF']])\n", "X_PCA=X_PCA.T\n", "\n", "pca = PCA(3)\n", "pca.fit(X_PCA)\n", "Y_pca = pca.transform(X_PCA)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "MantleArray['PCA_1']=Y_pca[:,0]\n", "MantleArray['PCA_2']=Y_pca[:,1]\n", "MantleArray['PCA_3']=Y_pca[:,2]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's plot the end members in 3D! " ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
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');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('