1251 lines
71 KiB
Plaintext
1251 lines
71 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"%matplotlib notebook\n",
|
|
"from scipy.stats import norm\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"import pandas as pd\n",
|
|
"from pandas import DataFrame as df\n",
|
|
"from scipy.stats import norm as NORM\n",
|
|
"from numpy.random import randn,rand,random,multivariate_normal\n",
|
|
"from numpy.linalg import eig,eigvals,cholesky,det\n",
|
|
"from numpy import diag,sqrt,transpose,matmul,dot,trace"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {
|
|
"code_folding": [],
|
|
"hide_input": false
|
|
},
|
|
"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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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": {
|
|
"text/html": [
|
|
"<img src=\"data:image/png;base64,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\" width=\"640\">"
|
|
],
|
|
"text/plain": [
|
|
"<IPython.core.display.HTML object>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x7f32b821b908>]"
|
|
]
|
|
},
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"#Test normal distribution clac\n",
|
|
"mean, var, skew, kurt = norm.stats(moments='mvsk')\n",
|
|
"X=np.linspace(norm.ppf(0.001),norm.ppf(0.999),100)\n",
|
|
"Y=norm.pdf(X)\n",
|
|
"fig, ax = plt.subplots(1, 1)\n",
|
|
"ax.plot(X, Y,'r-', lw=5, alpha=0.6, label='norm pdf')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#IM chart\n",
|
|
"def scatterchart(x,y,colour):\n",
|
|
" import matplotlib.lines as mlines\n",
|
|
" import matplotlib.transforms as mtransforms\n",
|
|
" \n",
|
|
" fig,ax=plt.subplots()\n",
|
|
" ax.scatter(x,y,c=colour)\n",
|
|
" line=mlines.Line2D([0,1],[0,1], color='red')\n",
|
|
" transform=ax.transAxes\n",
|
|
" line.set_transform(transform)\n",
|
|
" ax.add_line(line)\n",
|
|
" plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Norms"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"code_folding": [
|
|
0
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"#Test Norm Calculations\n",
|
|
"x=np.random.randn(10)\n",
|
|
"norm_frob=np.sqrt(np.sum(x*x))\n",
|
|
"norm_pinf=max(abs(x))\n",
|
|
"norm_ninf=min(abs(x))\n",
|
|
"print (\"Frobenius\",np.linalg.norm(x),norm_frob)\n",
|
|
"print (\"inf\",np.linalg.norm(x,np.inf),norm_pinf)\n",
|
|
"print (\"ninf\",np.linalg.norm(x,-np.inf),norm_ninf)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Random Covariance and Correlation Matrixwith printoptions(threshold=5, edgeitems=4):\n",
|
|
" \n",
|
|
"https://stats.stackexchange.com/questions/124538/how-to-generate-a-large-full-rank-random-correlation-matrix-with-some-strong-cor"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {
|
|
"code_folding": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"#create random positive semid definite matrix - covariance matrix\n",
|
|
"def correlmatrix_psd(d, check=True):\n",
|
|
"\n",
|
|
" W = randn(d,d); #factors\n",
|
|
" S = matmul(W,transpose(W)) + np.diag(rand(1,d));\n",
|
|
" P=diag(1./sqrt(diag(S))) \n",
|
|
" C=matmul(matmul(P,S),P)\n",
|
|
" status=True\n",
|
|
" if check==True:\n",
|
|
" status=(np.all(eigvals(C)>0.0))\n",
|
|
" return C,status\n",
|
|
"\n",
|
|
"def correlmatrix_simm(d, check=True):\n",
|
|
" rho=np.random.uniform(low=-1, high=1.0)\n",
|
|
" C=np.ones((d,d))*rho\n",
|
|
" np.fill_diagonal(C,1.)\n",
|
|
" status=True\n",
|
|
" if check==True:\n",
|
|
" status=(np.all(eigvals(C)>0.0))\n",
|
|
" return C,status\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#IM Gammma Formula\n",
|
|
"def IMformula_check():\n",
|
|
" M=np.random.randint(low=2, high=100)#NumFactor\n",
|
|
"\n",
|
|
" #Random Variance weighted Gamma Matrix\n",
|
|
" mu=0; sigma=1000;\n",
|
|
" G=diag(sigma*randn(M)+ mu)\n",
|
|
" var=random(M)\n",
|
|
" Ghat=matmul(G,diag(var))\n",
|
|
" norm=sum(np.abs(diag(Ghat)))*0.5\n",
|
|
" Ghatnorm=Ghat/norm #normalise\n",
|
|
"\n",
|
|
" #MxM correlation flat matrix \n",
|
|
" correl,ispsd=correlmatrix_psd(M,False)\n",
|
|
" correlsq=correl**2\n",
|
|
"\n",
|
|
" #IM formula\n",
|
|
" beta=trace(Ghatnorm)/(trace(np.abs(Ghatnorm)))\n",
|
|
" perc_sq=(NORM.ppf(0.995)**2)-1\n",
|
|
" eta=1+min(beta,0)-(min(beta,0)/(perc_sq))\n",
|
|
" X=diag(Ghatnorm)\n",
|
|
" quadraticform=np.dot(X.T,dot(correlsq,X)) #quadraticform\n",
|
|
" IM=max(0.5*trace(Ghatnorm)+eta*perc_sq*sqrt(0.25*quadraticform),0)\n",
|
|
" \n",
|
|
" #simulated IM\n",
|
|
" N=10000\n",
|
|
" mean=np.zeros(M)\n",
|
|
" mktshocks=multivariate_normal(mean,correl,N)\n",
|
|
" IM_path=np.zeros(N)\n",
|
|
" for i in np.arange(N):\n",
|
|
" mktshock=mktshocks[i];\n",
|
|
" IM_path[i]=dot(dot(mktshocks[i].T,Ghatnorm),mktshocks[i])\n",
|
|
" p99=np.quantile(IM_path,np.array([0.99]),axis=0)\n",
|
|
" \n",
|
|
" results={}\n",
|
|
" results['Valid']=ispsd\n",
|
|
" results['IM_SIM']=IM\n",
|
|
" results['IM_Theoretical']=max(p99[0],0)*0.5\n",
|
|
" results['beta']=beta\n",
|
|
" results['eta']=eta\n",
|
|
" results['correl']=correl\n",
|
|
" \n",
|
|
" return results\n",
|
|
"\n",
|
|
"\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"res=[IMformula_check() for i in np.arange(2050)]\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"y=df(res)['IM_SIM']\n",
|
|
"x=df(res)['IM_Theoretical']\n",
|
|
"scatterchart(x,y,'yellowgreen')\n",
|
|
"df(res)['eta']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"code_folding": [
|
|
0
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"#numpy options\n",
|
|
"import contextlib\n",
|
|
"@contextlib.contextmanager\n",
|
|
"def printoptions(*args, **kwargs):\n",
|
|
" original = np.get_printoptions()\n",
|
|
" np.set_printoptions(*args, **kwargs)\n",
|
|
" yield\n",
|
|
" np.set_printoptions(**original)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[ 1. , 0.15038307, -0.12812563, 0.39491592, -0.45057115],\n",
|
|
" [ 0.15038307, 1. , 0.80270364, 0.78289921, 0.09731917],\n",
|
|
" [-0.12812563, 0.80270364, 1. , 0.41560772, 0.64968718],\n",
|
|
" [ 0.39491592, 0.78289921, 0.41560772, 1. , -0.33755688],\n",
|
|
" [-0.45057115, 0.09731917, 0.64968718, -0.33755688, 1. ]])"
|
|
]
|
|
},
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"c,flag=correlmatrix_psd(5,False)\n",
|
|
"d,flag1=correlmatrix_simm(5,False)\n",
|
|
"c\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {
|
|
"hide_input": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([-0.11213889, -0.6250052 , -0.5623519 , -0.50960626, -0.14441316])"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# w : (..., M) array\n",
|
|
"# The eigenvalues, each repeated according to its multiplicity.\n",
|
|
"# The eigenvalues are not necessarily ordered. The resulting\n",
|
|
"# array will be of complex type, unless the imaginary part is\n",
|
|
"# zero in which case it will be cast to a real type. When `a`\n",
|
|
"# is real the resulting eigenvalues will be real (0 imaginary\n",
|
|
"# part) or occur in conjugate pairs\n",
|
|
"\n",
|
|
"# v : (..., M, M) array\n",
|
|
"# The normalized (unit \"length\") eigenvectors, such that the\n",
|
|
"# column ``v[:,i]`` is the eigenvector corresponding to the\n",
|
|
"# eigenvalue ``w[i]``.\n",
|
|
"\n",
|
|
"val,vec=eig(c)\n",
|
|
"vec[:,0]\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([2.41005261, 1.89741777, 0.57136001, 0.10892562, 0.01224399])"
|
|
]
|
|
},
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"val"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>0</th>\n",
|
|
" <th>1</th>\n",
|
|
" <th>2</th>\n",
|
|
" <th>3</th>\n",
|
|
" <th>4</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>-0.112139</td>\n",
|
|
" <td>-0.553560</td>\n",
|
|
" <td>-0.824166</td>\n",
|
|
" <td>-0.039783</td>\n",
|
|
" <td>0.012813</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>-0.625005</td>\n",
|
|
" <td>-0.048798</td>\n",
|
|
" <td>0.153767</td>\n",
|
|
" <td>-0.587653</td>\n",
|
|
" <td>0.487860</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>-0.562352</td>\n",
|
|
" <td>0.337652</td>\n",
|
|
" <td>-0.157800</td>\n",
|
|
" <td>-0.080380</td>\n",
|
|
" <td>-0.733750</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>-0.509606</td>\n",
|
|
" <td>-0.377737</td>\n",
|
|
" <td>0.289840</td>\n",
|
|
" <td>0.712587</td>\n",
|
|
" <td>0.076347</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>-0.144413</td>\n",
|
|
" <td>0.659163</td>\n",
|
|
" <td>-0.433818</td>\n",
|
|
" <td>0.372613</td>\n",
|
|
" <td>0.466487</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" 0 1 2 3 4\n",
|
|
"0 -0.112139 -0.553560 -0.824166 -0.039783 0.012813\n",
|
|
"1 -0.625005 -0.048798 0.153767 -0.587653 0.487860\n",
|
|
"2 -0.562352 0.337652 -0.157800 -0.080380 -0.733750\n",
|
|
"3 -0.509606 -0.377737 0.289840 0.712587 0.076347\n",
|
|
"4 -0.144413 0.659163 -0.433818 0.372613 0.466487"
|
|
]
|
|
},
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df(vec)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"1.0"
|
|
]
|
|
},
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"sum(vec[:,0]*vec[:,0])"
|
|
]
|
|
},
|
|
{
|
|
"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": "3.6.9"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|