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moorepants/02-book-balancing-intro.ipynb

Created September 13, 2017 04:44
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First draft of the firt notebook for ENG 122
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02-book-balancing-intro.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$$\n",
"\\def\\CC{\\bf C}\n",
"\\def\\QQ{\\bf Q}\n",
"\\def\\RR{\\bf R}\n",
"\\def\\ZZ{\\bf Z}\n",
"\\def\\NN{\\bf N}\n",
"$$\n",
"# 2. Introducing Mechanical Vibrations By Investigating a Book Oscillating on a Cylindrical Cup\n",
"\n",
"## Introduction\n",
"\n",
"This notebook introduces a single degree of freedom vibratory system of a textbook balancing on a cylindrical cup. The system is implemented as a model that students can interact with in order to visualize its free response and compare the computer simulation to a demonstration in the classroom.\n",
"\n",
"### Learning Objectives\n",
"\n",
"After the completion of this assignment students will be able to:\n",
"\n",
"- load a specific system\n",
"- view and set parameters on a system\n",
"- create a visualization that depicts the system's configuration\n",
"- visualize a system's free response\n",
"- estimate the period of a sinusoidal vibration from a time series\n",
"- compare a computer simulation result to experimental result\n",
"- interactively adjust the book inertia to see the affect on system response\n",
"- understand the concept of natural frequency nd its relationship to mass/inertia\n",
"\n",
"## What are vibrations?\n",
"\n",
"Here we will study a simple vibratory system. A vibrating mechanical system is typically defined as a collection of rigid and flexible objects that interact in a closed envelope. If you set a cylindrical cup on its side and place a book lying flat on top of it, the book will oscillate if initially displaced at a small non-horizontal angle. Note that it oscillates about a horizontal position. This position is called an *equilibrium point*, *equilibrium state*, or *equilibrium configuration* which is a natural position the system comes to when there is no motion. Vibration is formally defined as an *oscillation about an equilibrium*.\n",
"\n",
"During this class we will examine and explore many different vibratory systems, such as this simple book on a cup system. We will have some live demos, as we are showing now, but in general we will work with computational representations of systems to experiment and learn about the nature of vibration. For example, here is a system that represents the book on a cup. To execute the following Jupyter code cell press the shift and enter key simultaneously:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from resonance.linear_systems import BookOnCupSystem"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The line above loads the command, `BookOnCupSystem`, that can create systems that behave like the live demo at the front of the room. To create a system and assign it to a variable called `sys`, execute the following cell:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sys = BookOnCupSystem()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This system has many variables and functions associated with it. You can see what the system has and can do by using the Python dot notation. Type `sys.` and press the tab key to see a list of all the variables and functions that the system applies.\n",
"\n",
"## Constant Parameters\n",
"\n",
"Systems have different parameters, for example this system has geometry, such as the book's height and length and the cup's radius. The book also has a mass and, in this case, an underlying assumption is that the book is uniformly dense. Note that these parameters do not change with time, i.e. they are constant with respect to time. You can view all of the constant parameters, which are stored in a Python dictionary by typing:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'height': 0.029, 'length': 0.238, 'mass': 1.058, 'radius': 0.042}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys.parameters"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A Python dictionary maps keys, the variable name, to values, the default numerical value. For example the key `'height'` is associated with a value `0.029`. An individual parameter value can be accessed by using square brackets:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.042"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys.parameters['radius']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can set the values of these attributes as such:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sys.parameters['height'] = 1.0 # cm\n",
"sys.parameters['width'] = 6.0 # cm\n",
"sys.parameters['length'] = 10.0 # cm\n",
"sys.parameters['radius'] = 3.0 # cm\n",
"sys.parameters['mass'] = 1.0 # kg"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Note that you will be responsible for ensuring that the units are consistent and that all angles should be in radians.* Overwrite the `sys` variable by loading the system again to get back the default parameters."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'height': 0.029, 'length': 0.238, 'mass': 1.058, 'radius': 0.042}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys = BookOnCupSystem()\n",
"sys.parameters"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"All systems will have different sets of constant parameters. This system could also have more parameters, for example what if you were on the moon? Maybe the acceleration due to gravity could be changed. Or what if the book to cup connection was very slippery? Maybe the coefficient of friction would be a specific parameter. It is important to note that the system parameters, as we've defined here, are constant with respect to time.\n",
"\n",
"## Time Varying Parameters\n",
"\n",
"There are other types of parameters too. Another very important type of parameter are those that vary with time.\n",
"\n",
"### Exercise\n",
"\n",
"What are the time varying parameters of this system?\n",
"\n",
"There are are an infinite number of time varying parameters. Most systems are described by a uniquely simple set of time varying parameters, often called *generalized coordinates*. These coordinates define the configuration of the system. In our case the vertical and horizontal location of the book's mass center could uniquely describe the configuration of the system (if the book can't slip on the cup). But a better choice would be to use the single time varying angle of the books surface relative to horizontal to define the configuration. The angle of the book is thus a generalized coordinate because no fewer number of time varying parameters can possibly be used to describe the configuration. For simple systems, the number of generalized coordinates corresponds to the number of *degrees of [freedom]()* of a system. The degrees of freedom are the number of independent parameters that define the configuration. The non-slipping book on a cup has 1 degree of freedom which is described by the single generalized coordinate, the book's angle. The system's generalized coordinates can be accessed as such:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'book_angle': 0.0}"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys.coordinates"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.0"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys.coordinates['book_angle']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another type of time varying parameter that can be extracted from systems are non-generalized coordinates or other combinations of constant parameters. We will call these *measurement parameters*. For example, maybe you are interested in the vertical and horizontal location of the book's lower left corner. If you had an appropriate dynamics distance sensor you could measure this location as it changes with time. Or you can define how these two measurement parameters are a function of the book angle and the system's geometry. You can add measurement parameters to a system by defining a Python functions that compute the geometric relationship. Given the value of a generalized coordinate and the values of the system's constant parameters, we can define a function that computes the measurement parameter. These functions need to be to accept scalars and arrays, so import NumPy to make use of array aware functions like `cos()` and `sin()` :"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The height of the bottom left corner of the book relative to the origin is defined by this mathematical function:\n",
"\n",
"$$P_y = r + r \\cos{\\theta} + (r \\theta + l / 2) \\sin{\\theta}$$\n",
"\n",
"and the Python function that implements this would look like:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def bottom_left_y(radius, height, length, book_angle):\n",
" r = radius\n",
" h = height\n",
" l = length\n",
" theta = book_angle\n",
" return r + r * np.cos(theta) + (r * theta + l / 2) * np.sin(theta)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that the variable names in the function signature must be exactly as you have defined them in the parameters. This function can be used independently like so:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.084 , 0.08608323, 0.08817862, 0.09028551, 0.09240325,\n",
" 0.09453115, 0.09666855, 0.09881473, 0.10096901, 0.10313066])"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"angles = np.deg2rad(np.arange(10))\n",
"bottom_left_y(0.042, 0.029, 0.238, angles)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And you can add this measurement function to the system, so that it automatically calculates the measurement for you with:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Warning : cannot set measurement values.\n"
]
}
],
"source": [
"sys.add_measurement('bottom_left_y', bottom_left_y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Similarly, you can add the horizontal position:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Warning : cannot set measurement values.\n"
]
}
],
"source": [
"def bottom_left_x(radius, height, length, book_angle):\n",
" r = radius\n",
" h = height\n",
" l = length\n",
" theta = book_angle\n",
" return r * np.sin(theta) - (r * theta + l / 2) * np.cos(theta)\n",
"\n",
"sys.add_measurement('bottom_left_x', bottom_left_x)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, if you change the book angle you'll get a different measurement:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.086083232844703692"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys.coordinates['book_angle'] = np.deg2rad(1)\n",
"sys.measurements['bottom_left_y']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Notice that all angles must be in radians and that we use the NumPy function `rad2deg()` to do this.\n",
"\n",
"## Visualizing the Configuration\n",
"\n",
"It is often very helpful to visualize a system's configuration. In this case we need a two dimensional drawing similar to the diagram above. The package `matplotlib` provides \"patch\" objects that represent a circle and a rectangle that should be able to make a reasonable diagram. First import these functions:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"from matplotlib.patches import Circle, Rectangle"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And for nice interactive plotting in the Jupyter notebook, use this command to turn it on:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"% matplotlib notebook"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Just as we did with the measurement functions, you can create a function that generates the figure using the system's various parameters."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def create_plot(radius, length, height, book_angle, bottom_left_x, bottom_left_y):\n",
" # create a blank figure and set basic settings on the axis\n",
" fig, ax = plt.subplots(1, 1)\n",
" ax.set_xlim((-0.15, 0.15))\n",
" ax.set_ylim((0.0, 0.2))\n",
" ax.set_xlabel('x [m]')\n",
" ax.set_ylabel('y [m]')\n",
" ax.set_aspect('equal')\n",
"\n",
" # circles are created by supplying an (x, y) pair and the radius\n",
" circ = Circle((0.0, radius), radius=radius)\n",
"\n",
" # rectangles are created by supplying the (x, y) pair locating the\n",
" # bottom left corner, the width, the height, and the to rotation\n",
" # angle. notice that the rotation angle is defined in the opposite\n",
" # direction as we have and it is supposed to be in degrees not radians\n",
" rect = Rectangle((bottom_left_x, bottom_left_y),\n",
" length, height,\n",
" angle=-np.rad2deg(book_angle),\n",
" color='black')\n",
"\n",
" ax.add_patch(circ)\n",
" ax.add_patch(rect)\n",
"\n",
" return fig"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A system can have a single configuration plot function and it is set like so:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sys.configuration_plot_function = create_plot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now have a look at the configuration plot by calling `plot_configuration()` :"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
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" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
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" // 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 = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></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 = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.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",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\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<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 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": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
{
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],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sys.plot_configuration();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Exercise\n",
"\n",
"Change the system's parameters (constant parameters and the book angle) and see how the plot reflects these changes.\n",
"\n",
"## Free Response\n",
"\n",
"Now that we have a system with defined constant parameters we can make it vibrate. There are two ways to create this motion: apply perturbing forces to the system or set the coordinate to an initial angle other than the equilibrium angle. We will do the later here. The resulting motion is called the *free response* of the system, meaning that no external forces are causing the motion. To simulate the free response of the system, some values of time are needed. In this case an initial time value and a final time value are passed into the `free_response()` function. First, set the initial angle of the book and then call `free_repsonse)`, storing the result in a variable named `trajectories` :"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Simulating system with no damping.\n"
]
}
],
"source": [
"sys.coordinates['book_angle'] = np.deg2rad(1)\n",
"trajectories = sys.free_response(0, 5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This creates what is called a data frame. Data frames are defined in the Pandas Python package and are one of the most common Python data types. They are essentially a 2D table with labels for each column and an index for each row. In our case the index is the time value and the columns are the values of the coordinates and the measurements at that particular time:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"pandas.core.frame.DataFrame"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(trajectories)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
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" <th>4.531773</th>\n",
" <td>-0.005137</td>\n",
" <td>0.083389</td>\n",
" <td>-0.118998</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.548495</th>\n",
" <td>-0.007142</td>\n",
" <td>0.083151</td>\n",
" <td>-0.118997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.565217</th>\n",
" <td>-0.009039</td>\n",
" <td>0.082926</td>\n",
" <td>-0.118995</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.581940</th>\n",
" <td>-0.010801</td>\n",
" <td>0.082717</td>\n",
" <td>-0.118993</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.598662</th>\n",
" <td>-0.012399</td>\n",
" <td>0.082528</td>\n",
" <td>-0.118991</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.615385</th>\n",
" <td>-0.013810</td>\n",
" <td>0.082361</td>\n",
" <td>-0.118989</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.632107</th>\n",
" <td>-0.015014</td>\n",
" <td>0.082218</td>\n",
" <td>-0.118987</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.648829</th>\n",
" <td>-0.015991</td>\n",
" <td>0.082103</td>\n",
" <td>-0.118985</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.665552</th>\n",
" <td>-0.016727</td>\n",
" <td>0.082015</td>\n",
" <td>-0.118983</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.682274</th>\n",
" <td>-0.017212</td>\n",
" <td>0.081958</td>\n",
" <td>-0.118982</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.698997</th>\n",
" <td>-0.017437</td>\n",
" <td>0.081932</td>\n",
" <td>-0.118982</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.715719</th>\n",
" <td>-0.017399</td>\n",
" <td>0.081936</td>\n",
" <td>-0.118982</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.732441</th>\n",
" <td>-0.017099</td>\n",
" <td>0.081971</td>\n",
" <td>-0.118983</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.749164</th>\n",
" <td>-0.016541</td>\n",
" <td>0.082037</td>\n",
" <td>-0.118984</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.765886</th>\n",
" <td>-0.015735</td>\n",
" <td>0.082133</td>\n",
" <td>-0.118985</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.782609</th>\n",
" <td>-0.014691</td>\n",
" <td>0.082256</td>\n",
" <td>-0.118987</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.799331</th>\n",
" <td>-0.013425</td>\n",
" <td>0.082406</td>\n",
" <td>-0.118989</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.816054</th>\n",
" <td>-0.011958</td>\n",
" <td>0.082580</td>\n",
" <td>-0.118992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.832776</th>\n",
" <td>-0.010310</td>\n",
" <td>0.082775</td>\n",
" <td>-0.118994</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.849498</th>\n",
" <td>-0.008507</td>\n",
" <td>0.082989</td>\n",
" <td>-0.118996</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.866221</th>\n",
" <td>-0.006576</td>\n",
" <td>0.083218</td>\n",
" <td>-0.118997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.882943</th>\n",
" <td>-0.004546</td>\n",
" <td>0.083459</td>\n",
" <td>-0.118999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.899666</th>\n",
" <td>-0.002447</td>\n",
" <td>0.083709</td>\n",
" <td>-0.119000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.916388</th>\n",
" <td>-0.000312</td>\n",
" <td>0.083963</td>\n",
" <td>-0.119000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.933110</th>\n",
" <td>0.001829</td>\n",
" <td>0.084218</td>\n",
" <td>-0.119000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.949833</th>\n",
" <td>0.003941</td>\n",
" <td>0.084469</td>\n",
" <td>-0.118999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.966555</th>\n",
" <td>0.005995</td>\n",
" <td>0.084714</td>\n",
" <td>-0.118998</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.983278</th>\n",
" <td>0.007958</td>\n",
" <td>0.084948</td>\n",
" <td>-0.118996</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.000000</th>\n",
" <td>0.009801</td>\n",
" <td>0.085168</td>\n",
" <td>-0.118994</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>300 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" book_angle bottom_left_y bottom_left_x\n",
"Time [s] \n",
"0.000000 0.017453 0.086083 -0.118982\n",
"0.016722 0.017322 0.086067 -0.118982\n",
"0.033445 0.016929 0.086021 -0.118983\n",
"0.050167 0.016282 0.085943 -0.118984\n",
"0.066890 0.015389 0.085836 -0.118986\n",
"0.083612 0.014264 0.085702 -0.118988\n",
"0.100334 0.012925 0.085541 -0.118990\n",
"0.117057 0.011390 0.085358 -0.118992\n",
"0.133779 0.009684 0.085154 -0.118994\n",
"0.150502 0.007832 0.084933 -0.118996\n",
"0.167224 0.005862 0.084698 -0.118998\n",
"0.183946 0.003804 0.084453 -0.118999\n",
"0.200669 0.001689 0.084201 -0.119000\n",
"0.217391 -0.000452 0.083946 -0.119000\n",
"0.234114 -0.002587 0.083692 -0.119000\n",
"0.250836 -0.004682 0.083443 -0.118999\n",
"0.267559 -0.006706 0.083203 -0.118997\n",
"0.284281 -0.008630 0.082975 -0.118996\n",
"0.301003 -0.010424 0.082762 -0.118994\n",
"0.317726 -0.012060 0.082568 -0.118991\n",
"0.334448 -0.013515 0.082396 -0.118989\n",
"0.351171 -0.014766 0.082247 -0.118987\n",
"0.367893 -0.015795 0.082126 -0.118985\n",
"0.384615 -0.016586 0.082032 -0.118984\n",
"0.401338 -0.017127 0.081968 -0.118983\n",
"0.418060 -0.017409 0.081935 -0.118982\n",
"0.434783 -0.017430 0.081932 -0.118982\n",
"0.451505 -0.017188 0.081961 -0.118982\n",
"0.468227 -0.016687 0.082020 -0.118983\n",
"0.484950 -0.015934 0.082109 -0.118985\n",
"... ... ... ...\n",
"4.515050 -0.003055 0.083637 -0.118999\n",
"4.531773 -0.005137 0.083389 -0.118998\n",
"4.548495 -0.007142 0.083151 -0.118997\n",
"4.565217 -0.009039 0.082926 -0.118995\n",
"4.581940 -0.010801 0.082717 -0.118993\n",
"4.598662 -0.012399 0.082528 -0.118991\n",
"4.615385 -0.013810 0.082361 -0.118989\n",
"4.632107 -0.015014 0.082218 -0.118987\n",
"4.648829 -0.015991 0.082103 -0.118985\n",
"4.665552 -0.016727 0.082015 -0.118983\n",
"4.682274 -0.017212 0.081958 -0.118982\n",
"4.698997 -0.017437 0.081932 -0.118982\n",
"4.715719 -0.017399 0.081936 -0.118982\n",
"4.732441 -0.017099 0.081971 -0.118983\n",
"4.749164 -0.016541 0.082037 -0.118984\n",
"4.765886 -0.015735 0.082133 -0.118985\n",
"4.782609 -0.014691 0.082256 -0.118987\n",
"4.799331 -0.013425 0.082406 -0.118989\n",
"4.816054 -0.011958 0.082580 -0.118992\n",
"4.832776 -0.010310 0.082775 -0.118994\n",
"4.849498 -0.008507 0.082989 -0.118996\n",
"4.866221 -0.006576 0.083218 -0.118997\n",
"4.882943 -0.004546 0.083459 -0.118999\n",
"4.899666 -0.002447 0.083709 -0.119000\n",
"4.916388 -0.000312 0.083963 -0.119000\n",
"4.933110 0.001829 0.084218 -0.119000\n",
"4.949833 0.003941 0.084469 -0.118999\n",
"4.966555 0.005995 0.084714 -0.118998\n",
"4.983278 0.007958 0.084948 -0.118996\n",
"5.000000 0.009801 0.085168 -0.118994\n",
"\n",
"[300 rows x 3 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trajectories"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The data frames have useful plotting functions associated with them, so it is rather easy to plot the various coordinates and measurements versus time:"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
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" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
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"\n",
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" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></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 = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.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",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\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<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 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": [
"<IPython.core.display.Javascript object>"
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},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"trajectories.plot();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It is often a little clearer if each column is in a subplots, especially if they have different units, as these do:"
]
},
{
"cell_type": "code",
"execution_count": 24,
"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 = $('<div/>');\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",
" this.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",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></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 = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.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",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\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<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 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": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"trajectories.plot(subplots=True);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A single column can be accessed and plotted too:"
]
},
{
"cell_type": "code",
"execution_count": 25,
"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 = $('<div/>');\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",
" this.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",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></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 = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.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",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\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<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 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": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"trajectories['book_angle'].plot();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Maybe you want to use degrees for the book angle instead, just make a new column:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"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 = $('<div/>');\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",
" this.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",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></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 = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.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",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\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<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 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": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"trajectories['book_angle_deg'] = np.rad2deg(trajectories['book_angle'])\n",
"plt.figure()\n",
"trajectories['book_angle_deg'].plot();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Exercise\n",
"\n",
"Create the free response of the system with different initial coordinate values and parameter values.\n",
"\n",
"- Does the simulation always work, if not what doesn't work? *Hint: try a tall stack of books, can you find a stack height that is significant?*\n",
"- What mathematical function can be used describe the change in the book angle?\n",
"\n",
"## Animate The Motion\n",
"\n",
"Now that we we have a time varying response, we can animate the configure figure to visualize how the system moves. There is one minor change that needs to be made to the configuration plot function first. We need to make sure that it returns any of the objects that change with time."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def create_plot(radius, length, height, book_angle, bottom_left_x, bottom_left_y):\n",
" fig, ax = plt.subplots(1, 1)\n",
" ax.set_xlim((-0.15, 0.15))\n",
" ax.set_ylim((0.0, 0.2))\n",
" ax.set_xlabel('x [m]')\n",
" ax.set_ylabel('y [m]')\n",
" ax.set_aspect('equal')\n",
"\n",
" circ = Circle((0.0, radius), radius=radius)\n",
"\n",
" rect = Rectangle((bottom_left_x, bottom_left_y),\n",
" length, height,\n",
" angle=-np.rad2deg(book_angle),\n",
" color='black')\n",
"\n",
" ax.add_patch(circ)\n",
" ax.add_patch(rect)\n",
"\n",
" # make sure to return the rectangle, which moves at each time step!\n",
" return fig, rect\n",
"\n",
"sys.configuration_plot_function = create_plot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, an animation update function can be created which updates the bottom left corner's x and y coordinate at each time step. The last argument in the function signature must be the object that changes."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def animate(book_angle, bottom_left_x, bottom_left_y, rect):\n",
" rect.set_xy((bottom_left_x, bottom_left_y))\n",
" rect._angle = -np.rad2deg(book_angle)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Lastly, add this function to the system:"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sys.configuration_plot_update_function = animate"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The visualization can now be animated with:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"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 = $('<div/>');\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",
" this.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",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\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 = $('<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 = $('<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 = $('<canvas/>');\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 = $('<div/>')\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 = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></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 = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.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",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\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<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 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": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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},
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},
{
"data": {
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"<matplotlib.animation.FuncAnimation at 0x7fdb1d792978>"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sys.animate_configuration()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Exercie\n",
"\n",
"There is a special variable `time` that can be specified in the plot setup and update functions. Add this variable to the function signatures and create some text on the plot that displays the current time using:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# text = ax.text(-0.125, 0.025, 'Time = {:0.3f} s'.format(time))\n",
"# text.set_text('Time = {:0.3f} s'.format(time))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Time Series Analysis\n",
"\n",
"From the above plots you can see that the oscillation is periodic and sinusoidal. Using your program, create a function that calculates the period of the non-linear model to three significant figures of the 11 oscillations when the initial book angle is X degrees. Compare the period predicted by the system to the period measured in class.\n",
"\n",
"*Hint: Look for sign changes with np.sign(), use boolean indexing to extract important times, and finally np.diff() and np.mean() can be useful for finding the delta times and averaging. Note that np.diff() returns one fewer item in the array it operates on.*"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.85618729096989965"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def find_period(t, theta):\n",
" \"\"\"Computes the period of oscillation based on the trajectory of theta.\n",
"\n",
" Parameters\n",
" ==========\n",
" t : array_like, shape(n,)\n",
" An array of monotonically increasing time values.\n",
" theta : array_like, shape(n,)\n",
" An array of values for theta at each time in ``t``.\n",
"\n",
" Returns\n",
" =======\n",
" T : float\n",
" An estimate of the period of oscillation.\n",
"\n",
" \"\"\"\n",
"\n",
" peak_idxs = np.diff(np.sign(theta)) < 0\n",
" peak_idxs = np.hstack((peak_idxs, False))\n",
" T = np.diff(t[peak_idxs]).mean()\n",
"\n",
" return T\n",
"\n",
"find_period(trajectories.index, trajectories.book_angle)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Exercise\n",
"\n",
"Plot the period versus change in mass, length, and radius. Is there anything interesting about these plots?"
]
}
],
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"kernelspec": {
"display_name": "Python 3",
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"file_extension": ".py",
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