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SoTaInverSpinel/粘菌ネットワーク-Copy1.ipynb

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粘菌ネットワーク-Copy1.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3.0.3\n"
]
}
],
"source": [
"import matplotlib\n",
"print(matplotlib.__version__)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import networkx as nx\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"#import matplotlib.animation as anm\n",
"from matplotlib.animation import PillowWriter, FuncAnimation\n",
"#import matplotlib\n",
"#from scipy import sparse"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {},
"outputs": [],
"source": [
"G=nx.Graph()\n",
"\n",
"G.add_nodes_from([0,1,2,3,4])\n",
"G.add_edges_from([(0,2),(0,3),(2,3),(2,4),(1,4),(1,3),(3,4)])\n",
"pos = nx.spring_layout(G)\n",
"#print(G.adj)"
]
},
{
"cell_type": "code",
"execution_count": 114,
"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",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<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"
],
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nx.draw_networkx(G,pos)\n",
"plt.axis('off')\n",
"plt.show()\n",
"#plt.savefig('nenkin02.png')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#変数宣言\n",
"nt=13\n",
"#dt=1とする\n",
"nnodes=nx.number_of_nodes(G)\n",
"edge_list=list(G.edges)\n",
"nbr_mtx=nx.to_numpy_matrix(G)\n",
"\n",
"conductivity=np.zeros((nt,nnodes,nnodes)) #D\n",
"length=np.zeros((nnodes,nnodes)) #L\n",
"pressure=np.zeros((nt,nnodes)) #p\n",
"flux=np.zeros(nnodes) #Q\n",
"\n",
"#初期値と定数の設定\n",
"conductivity[0]=nbr_mtx #各エッジの流れやすさは最初1.0\n",
"length=nbr_mtx #各エッジの長さは1.0とする\n",
"I0=2.0\n",
"flux[0]=I0\n",
"flux[1]=-I0\n",
"gamma=1.8"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"#ゼロ除算が発生しないように非ゼロ要素のみで割り算を行う\n",
"def divide_non_zero_element(D,L,num_nodes,list_edges):\n",
" X=np.zeros((num_nodes,num_nodes))\n",
" for i,j in list_edges:\n",
" X[i,j]=D[i,j]/L[i,j]\n",
" X[j,i]=D[j,i]/L[j,i]\n",
" return X\n",
"\n",
"#f(Q) for dD/dt \n",
"def f(x):\n",
" powered=x**gamma\n",
" return powered/(powered+1)\n",
"\n",
"#Dの時間変化量を求める\n",
"def dD(D,L,p,num_nodes,list_edges):\n",
" X=divide_non_zero_element(D,L,num_nodes,list_edges)\n",
" print(X)\n",
" #print(p)\n",
" #print(\"diffs=\")\n",
" #print(np.expand_dims(p,axis=1)-p)\n",
" Q=np.multiply(X,np.expand_dims(p,axis=1)-p)\n",
" #print(\"Q=\")\n",
" #print(Q)\n",
" ans=f(np.abs(Q))\n",
" return ans\n",
"\n",
"#一次連立方程式を解きpを求める\n",
"def deduce_p(D,L,B,num_nodes,list_edges):\n",
" Y=divide_non_zero_element(D,L,num_nodes,list_edges)\n",
" \n",
" A=np.diag(np.sum(Y,axis=1))-Y\n",
" #print(\"C=\")\n",
" #print(C)\n",
" p=np.linalg.solve(A,B)\n",
" #print(\"p=\")\n",
" #print(p)\n",
" return p"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.9047619 , -1.38095238, 0.04761905, -0.23809524, -0.52380952])"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pressure[0]=deduce_p(conductivity[0],length,flux,nnodes,edge_list)\n",
"pressure[0]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"[[0. 0. 1. 1. 0.]\n",
" [0. 0. 0. 1. 1.]\n",
" [1. 0. 0. 1. 1.]\n",
" [1. 1. 1. 0. 1.]\n",
" [0. 1. 1. 1. 0.]]\n",
"1\n",
"[[0. 0. 0.43107385 0.5598015 0. ]\n",
" [0. 0. 0. 0.5598015 0.43107385]\n",
" [0.43107385 0. 0. 0.09492134 0.26750693]\n",
" [0.5598015 0.5598015 0.09492134 0. 0.09492134]\n",
" [0. 0.43107385 0.26750693 0.09492134 0. ]]\n",
"2\n",
"[[0. 0. 0.301779 0.63875166 0. ]\n",
" [0. 0. 0. 0.63875166 0.301779 ]\n",
" [0.301779 0. 0. 0.01412666 0.24364023]\n",
" [0.63875166 0.63875166 0.01412666 0. 0.01412666]\n",
" [0. 0.301779 0.24364023 0.01412666 0. ]]\n",
"3\n",
"[[0.00000000e+00 0.00000000e+00 1.95391811e-01 6.86203886e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 6.86203886e-01\n",
" 1.95391811e-01]\n",
" [1.95391811e-01 0.00000000e+00 0.00000000e+00 3.93440752e-04\n",
" 1.87431012e-01]\n",
" [6.86203886e-01 6.86203886e-01 3.93440752e-04 0.00000000e+00\n",
" 3.93440752e-04]\n",
" [0.00000000e+00 1.95391811e-01 1.87431012e-01 3.93440752e-04\n",
" 0.00000000e+00]]\n",
"4\n",
"[[0.00000000e+00 0.00000000e+00 1.11364511e-01 7.18840944e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 7.18840944e-01\n",
" 1.11364511e-01]\n",
" [1.11364511e-01 0.00000000e+00 0.00000000e+00 5.43271716e-07\n",
" 1.11177785e-01]\n",
" [7.18840944e-01 7.18840944e-01 5.43271716e-07 0.00000000e+00\n",
" 5.43271716e-07]\n",
" [0.00000000e+00 1.11364511e-01 1.11177785e-01 5.43271716e-07\n",
" 0.00000000e+00]]\n",
"5\n",
"[[0.00000000e+00 0.00000000e+00 4.66770656e-02 7.44756425e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 7.44756425e-01\n",
" 4.66770656e-02]\n",
" [4.66770656e-02 0.00000000e+00 0.00000000e+00 3.87441324e-12\n",
" 4.66768699e-02]\n",
" [7.44756425e-01 7.44756425e-01 3.87441324e-12 0.00000000e+00\n",
" 3.87441324e-12]\n",
" [0.00000000e+00 4.66770656e-02 4.66768699e-02 3.87441324e-12\n",
" 0.00000000e+00]]\n",
"6\n",
"[[0.00000000e+00 0.00000000e+00 1.05449974e-02 7.63864511e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 7.63864511e-01\n",
" 1.05449974e-02]\n",
" [1.05449974e-02 0.00000000e+00 0.00000000e+00 2.18868885e-21\n",
" 1.05449974e-02]\n",
" [7.63864511e-01 7.63864511e-01 2.18868885e-21 0.00000000e+00\n",
" 2.18868885e-21]\n",
" [0.00000000e+00 1.05449974e-02 1.05449974e-02 2.18868885e-21\n",
" 0.00000000e+00]]\n",
"7\n",
"[[0.00000000e+00 0.00000000e+00 7.40390445e-04 7.74024148e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 7.74024148e-01\n",
" 7.40390445e-04]\n",
" [7.40390445e-04 0.00000000e+00 0.00000000e+00 4.99776770e-38\n",
" 7.40390445e-04]\n",
" [7.74024148e-01 7.74024148e-01 4.99776770e-38 0.00000000e+00\n",
" 4.99776770e-38]\n",
" [0.00000000e+00 7.40390445e-04 7.40390445e-04 4.99776770e-38\n",
" 0.00000000e+00]]\n",
"8\n",
"[[0.00000000e+00 0.00000000e+00 6.16112518e-06 7.76696430e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 7.76696430e-01\n",
" 6.16112518e-06]\n",
" [6.16112518e-06 0.00000000e+00 0.00000000e+00 5.50270442e-68\n",
" 6.16112518e-06]\n",
" [7.76696430e-01 7.76696430e-01 5.50270442e-68 0.00000000e+00\n",
" 5.50270442e-68]\n",
" [0.00000000e+00 6.16112518e-06 6.16112518e-06 5.50270442e-68\n",
" 0.00000000e+00]]\n",
"9\n",
"[[0.00000000e+000 0.00000000e+000 1.10616852e-009 7.76893737e-001\n",
" 0.00000000e+000]\n",
" [0.00000000e+000 0.00000000e+000 0.00000000e+000 7.76893737e-001\n",
" 1.10616852e-009]\n",
" [1.10616852e-009 0.00000000e+000 0.00000000e+000 6.51053048e-122\n",
" 1.10616852e-009]\n",
" [7.76893737e-001 7.76893737e-001 6.51053048e-122 0.00000000e+000\n",
" 6.51053048e-122]\n",
" [0.00000000e+000 1.10616852e-009 1.10616852e-009 6.51053048e-122\n",
" 0.00000000e+000]]\n",
"10\n",
"[[0.00000000e+000 0.00000000e+000 2.00040135e-016 7.76895386e-001\n",
" 0.00000000e+000]\n",
" [0.00000000e+000 0.00000000e+000 0.00000000e+000 7.76895386e-001\n",
" 2.00040135e-016]\n",
" [2.00040135e-016 0.00000000e+000 0.00000000e+000 5.55768968e-219\n",
" 2.00040135e-016]\n",
" [7.76895386e-001 7.76895386e-001 5.55768968e-219 0.00000000e+000\n",
" 5.55768968e-219]\n",
" [0.00000000e+000 2.00040135e-016 2.00040135e-016 5.55768968e-219\n",
" 0.00000000e+000]]\n",
"11\n",
"[[0.00000000e+00 0.00000000e+00 1.45964754e-28 7.76895387e-01\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 7.76895387e-01\n",
" 1.45964754e-28]\n",
" [1.45964754e-28 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
" 1.45964754e-28]\n",
" [7.76895387e-01 7.76895387e-01 0.00000000e+00 0.00000000e+00\n",
" 0.00000000e+00]\n",
" [0.00000000e+00 1.45964754e-28 1.45964754e-28 0.00000000e+00\n",
" 0.00000000e+00]]\n"
]
}
],
"source": [
"for t in range(0,nt-1):\n",
" conductivity[t+1]=dD(conductivity[t],length,pressure[t],nnodes,edge_list)\n",
" pressure[t+1]=deduce_p(conductivity[t+1],length,flux,nnodes,edge_list)\n",
" print(t)\n",
" print(conductivity[t])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"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",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<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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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib nbagg\n",
"fig=plt.figure()\n",
"\n",
"datatype=[('conductivity',float)]\n",
"\n",
"def animate(i):\n",
" A=np.matrix(conductivity[i],dtype=datatype)\n",
" G=nx.from_numpy_matrix(A)\n",
" weights=[G[u][v]['conductivity'] for u,v in G.edges()]\n",
" \n",
" plt.cla()\n",
" nx.draw_networkx(G,pos,width=weights)\n",
" plt.axis('off')\n",
" plt.title('t=' + str(i))\n",
" #plt.show()\n",
" \n",
"anim = FuncAnimation(fig,animate,frames=nt,repeat=True)\n",
"anim.save(\"nenkin02.gif\", writer='pillow',fps=6)\n",
"#plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"sys.version_info(major=3, minor=6, micro=8, releaselevel='final', serial=0)\n"
]
}
],
"source": [
"import sys\n",
"print(sys.version_info)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"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",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<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": [
"G0=nx.triangular_lattice_graph(10,10)\n",
"pos0=nx.spring_layout(G0)\n",
"nx.draw_networkx(G0,pos0)\n",
"plt.show()\n",
"#plt.savefig('nenkin03.png')"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [],
"source": [
"nbr_mtx=nx.to_numpy_matrix(G0)"
]
},
{
"cell_type": "code",
"execution_count": 105,
"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",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<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": [
"G=nx.from_numpy_matrix(nbr_mtx)\n",
"pos=nx.spring_layout(G)\n",
"nx.draw_networkx(G,pos)\n",
"#plt.show()\n",
"plt.savefig('nenkin04.png')"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [],
"source": [
"#変数宣言\n",
"nt=12\n",
"#dt=1とする\n",
"nnodes=nx.number_of_nodes(G)\n",
"edge_list=list(G.edges)\n",
"nbr_mtx=nx.to_numpy_matrix(G)\n",
"\n",
"conductivity=np.zeros((nt,nnodes,nnodes)) #D\n",
"length=np.zeros((nnodes,nnodes)) #L\n",
"pressure=np.zeros((nt,nnodes)) #p\n",
"flux=np.zeros(nnodes) #Q\n",
"\n",
"#初期値と定数の設定\n",
"conductivity[0]=nbr_mtx #各エッジの流れやすさは最初1.0\n",
"length=nbr_mtx #各エッジの長さは1.0とする\n",
"I0=2.0\n",
"source_list=[0,35]\n",
"sink_list=[5,60,65]\n",
"source_len=len(source_list)\n",
"sink_len=len(sink_list)\n",
"\n",
"for i in source_list:\n",
" flux[i]=I0\n",
" \n",
"for i in sink_list:\n",
" flux[i]=-I0*(source_len/sink_len)\n",
"\n",
"gamma=1.5"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1.96599376, 1.00577286, 0.53076023, 0.19908174, -0.12803551,\n",
" -0.63018956, 0.92621466, 0.60012278, 0.31806353, 0.07553871,\n",
" -0.15657292, -0.27262691, 0.5684348 , 0.4907491 , 0.32917631,\n",
" 0.17370141, 0.04699401, -0.03111826, 0.28834065, 0.23220538,\n",
" 0.16021568, 0.1122202 , 0.10819491, 0.11841962, 0.07981061,\n",
" 0.07050335, 0.0542472 , 0.05974358, 0.12447164, 0.27818223,\n",
" -0.11941216, -0.11217158, -0.08501321, -0.00768002, 0.19616891,\n",
" 0.84365604, -0.32284939, -0.31235381, -0.28100083, -0.22321762,\n",
" -0.11823339, 0.05661699, -0.53678219, -0.50190671, -0.45134206,\n",
" -0.39603624, -0.33525239, -0.30325423, -0.79403882, -0.75276223,\n",
" -0.67719912, -0.62869182, -0.61948016, -0.63112729, -1.09257203,\n",
" -0.91407453, -0.81441736, -0.81367598, -0.91209726, -0.98555241,\n",
" -1.80929665, -1.19268793, -0.95480851, -0.89805422, -1.00931503,\n",
" -1.41343268])"
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pressure[0]=deduce_p(conductivity[0],length,flux,nnodes,edge_list)\n",
"pressure[0]"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"#ゼロ除算が発生しないように非ゼロ要素のみで割り算を行う\n",
"def divide_non_zero_element(D,L,num_nodes,list_edges):\n",
" X=np.zeros((num_nodes,num_nodes))\n",
" for i,j in list_edges:\n",
" X[i,j]=D[i,j]/L[i,j]\n",
" X[j,i]=D[j,i]/L[j,i]\n",
" return X\n",
"\n",
"#f(Q) for dD/dt \n",
"def f(x):\n",
" powered=x**gamma\n",
" return powered/(powered+1)\n",
"\n",
"#Dの時間変化量を求める\n",
"def dD(D,L,p,num_nodes,list_edges):\n",
" X=divide_non_zero_element(D,L,num_nodes,list_edges)\n",
" \n",
" #print(p)\n",
" #print(\"diffs=\")\n",
" #print(np.expand_dims(p,axis=1)-p)\n",
" Q=np.multiply(X,np.expand_dims(p,axis=1)-p)\n",
" #print(\"Q=\")\n",
" #print(Q)\n",
" ans=f(np.abs(Q))\n",
" return ans\n",
"\n",
"#一次連立方程式を解きpを求める\n",
"def deduce_p(D,L,B,num_nodes,list_edges):\n",
" Y=divide_non_zero_element(D,L,num_nodes,list_edges)\n",
" #print(Y)\n",
" A=np.diag(np.sum(Y,axis=1))-Y\n",
" #print(\"C=\")\n",
" #print(C)\n",
" p=np.linalg.solve(A,B)\n",
" #print(\"p=\")\n",
" #print(p)\n",
" return p"
]
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"[[0. 1. 0. ... 0. 0. 0.]\n",
" [1. 0. 1. ... 0. 0. 0.]\n",
" [0. 1. 0. ... 0. 0. 0.]\n",
" ...\n",
" [0. 0. 0. ... 0. 1. 0.]\n",
" [0. 0. 0. ... 1. 0. 1.]\n",
" [0. 0. 0. ... 0. 1. 0.]]\n",
"1\n",
"[[0. 0.48478273 0. ... 0. 0. 0. ]\n",
" [0.48478273 0. 0.24663862 ... 0. 0. 0. ]\n",
" [0. 0.24663862 0. ... 0. 0. 0. ]\n",
" ...\n",
" [0. 0. 0. ... 0. 0.0357839 0. ]\n",
" [0. 0. 0. ... 0.0357839 0. 0.20439086]\n",
" [0. 0. 0. ... 0. 0.20439086 0. ]]\n",
"2\n",
"[[0. 0.4859283 0. ... 0. 0. 0. ]\n",
" [0.4859283 0. 0.33535814 ... 0. 0. 0. ]\n",
" [0. 0.33535814 0. ... 0. 0. 0. ]\n",
" ...\n",
" [0. 0. 0. ... 0. 0.00150345 0. ]\n",
" [0. 0. 0. ... 0.00150345 0. 0.09054783]\n",
" [0. 0. 0. ... 0. 0.09054783 0. ]]\n",
"3\n",
"[[0.00000000e+00 5.13535978e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.13535978e-01 0.00000000e+00 4.09747392e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 4.09747392e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 3.96267568e-05 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 3.96267568e-05\n",
" 0.00000000e+00 2.74030674e-02]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.74030674e-02 0.00000000e+00]]\n",
"4\n",
"[[0.00000000e+00 5.36811190e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.36811190e-01 0.00000000e+00 4.65951195e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 4.65951195e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 8.81752736e-07 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 8.81752736e-07\n",
" 0.00000000e+00 5.95145129e-03]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 5.95145129e-03 0.00000000e+00]]\n",
"5\n",
"[[0.00000000e+00 5.57754204e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.57754204e-01 0.00000000e+00 5.11638690e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 5.11638690e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.62764259e-09 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 2.62764259e-09\n",
" 0.00000000e+00 7.08642972e-04]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 7.08642972e-04 0.00000000e+00]]\n",
"6\n",
"[[0.00000000e+00 5.73473075e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.73473075e-01 0.00000000e+00 5.44869211e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 5.44869211e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.85161525e-13 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 2.85161525e-13\n",
" 0.00000000e+00 2.89934688e-05]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.89934688e-05 0.00000000e+00]]\n",
"7\n",
"[[0.00000000e+00 5.83343154e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.83343154e-01 0.00000000e+00 5.67255554e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 5.67255554e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.14244620e-19 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 2.14244620e-19\n",
" 0.00000000e+00 2.39334066e-07]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.39334066e-07 0.00000000e+00]]\n",
"8\n",
"[[0.00000000e+00 5.91148044e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.91148044e-01 0.00000000e+00 5.83878898e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 5.83878898e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 1.22289621e-28 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 1.22289621e-28\n",
" 0.00000000e+00 1.78781619e-10]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 1.78781619e-10 0.00000000e+00]]\n",
"9\n",
"[[0.00000000e+00 5.98070736e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [5.98070736e-01 0.00000000e+00 5.95839010e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 5.95839010e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 1.65397303e-42 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 1.65397303e-42\n",
" 0.00000000e+00 3.58218648e-15]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 3.58218648e-15 0.00000000e+00]]\n",
"10\n",
"[[0.00000000e+00 6.03126494e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [6.03126494e-01 0.00000000e+00 6.02761270e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 6.02761270e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 2.59690833e-63 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 2.59690833e-63\n",
" 0.00000000e+00 3.05968041e-22]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 3.05968041e-22 0.00000000e+00]]\n",
"11\n",
"[[0.00000000e+00 6.05561345e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [6.05561345e-01 0.00000000e+00 6.05538842e-01 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" [0.00000000e+00 6.05538842e-01 0.00000000e+00 ... 0.00000000e+00\n",
" 0.00000000e+00 0.00000000e+00]\n",
" ...\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 1.60138810e-94 0.00000000e+00]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 1.60138810e-94\n",
" 0.00000000e+00 6.83032577e-33]\n",
" [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
" 6.83032577e-33 0.00000000e+00]]\n",
"12\n",
"[[0.00000000e+000 6.06173353e-001 0.00000000e+000 ... 0.00000000e+000\n",
" 0.00000000e+000 0.00000000e+000]\n",
" [6.06173353e-001 0.00000000e+000 6.06173030e-001 ... 0.00000000e+000\n",
" 0.00000000e+000 0.00000000e+000]\n",
" [0.00000000e+000 6.06173030e-001 0.00000000e+000 ... 0.00000000e+000\n",
" 0.00000000e+000 0.00000000e+000]\n",
" ...\n",
" [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000\n",
" 2.41251683e-141 0.00000000e+000]\n",
" [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 2.41251683e-141\n",
" 0.00000000e+000 6.01616106e-049]\n",
" [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000\n",
" 6.01616106e-049 0.00000000e+000]]\n"
]
},
{
"ename": "LinAlgError",
"evalue": "Singular matrix",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mLinAlgError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<timed exec>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n",
"\u001b[1;32m<ipython-input-43-3e9fb17c04e6>\u001b[0m in \u001b[0;36mdeduce_p\u001b[1;34m(D, L, B, num_nodes, list_edges)\u001b[0m\n\u001b[0;32m 32\u001b[0m \u001b[1;31m#print(\"C=\")\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 33\u001b[0m \u001b[1;31m#print(C)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 34\u001b[1;33m \u001b[0mp\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 35\u001b[0m \u001b[1;31m#print(\"p=\")\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 36\u001b[0m \u001b[1;31m#print(p)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\numpy\\linalg\\linalg.py\u001b[0m in \u001b[0;36msolve\u001b[1;34m(a, b)\u001b[0m\n\u001b[0;32m 401\u001b[0m \u001b[0msignature\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'DD->D'\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misComplexType\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;34m'dd->d'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 402\u001b[0m \u001b[0mextobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_linalg_error_extobj\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_raise_linalgerror_singular\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 403\u001b[1;33m \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgufunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msignature\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msignature\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mextobj\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mextobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 404\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 405\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mwrap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult_t\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\numpy\\linalg\\linalg.py\u001b[0m in \u001b[0;36m_raise_linalgerror_singular\u001b[1;34m(err, flag)\u001b[0m\n\u001b[0;32m 95\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 96\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_raise_linalgerror_singular\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflag\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 97\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mLinAlgError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Singular matrix\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 98\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 99\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_raise_linalgerror_nonposdef\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflag\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mLinAlgError\u001b[0m: Singular matrix"
]
}
],
"source": [
"%%time\n",
"\n",
"for t in range(0,nt-1):\n",
" conductivity[t+1]=dD(conductivity[t],length,pressure[t],nnodes,edge_list)\n",
" pressure[t+1]=deduce_p(conductivity[t+1],length,flux,nnodes,edge_list)\n",
" print(t)\n",
" print(conductivity[t])"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [
{
"data": {
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" 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",
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"\n",
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" 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",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overridden (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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<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": [
"%matplotlib nbagg\n",
"fig=plt.figure()\n",
"\n",
"datatype=[('conductivity',float)]\n",
"\n",
"def animate(i):\n",
" A=np.matrix(conductivity[i],dtype=datatype)\n",
" G=nx.from_numpy_matrix(A)\n",
" weights=[G[u][v]['conductivity'] for u,v in G.edges()]\n",
" \n",
" plt.cla()\n",
" nx.draw_networkx(G,pos,width=weights,node_size=100)\n",
" nx.draw_networkx_nodes(G,pos,nodelist=source_list,node_color='red',)\n",
" nx.draw_networkx_nodes(G,pos,nodelist=sink_list,node_color='purple',)\n",
" plt.axis('off')\n",
" plt.title('t=' + str(i))\n",
" #plt.show()\n",
" \n",
"anim = FuncAnimation(fig,animate,interval=500,frames=12,repeat=True)\n",
"anim.save(\"nenkin03.gif\", writer='pillow',fps=2)\n",
"#plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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