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"source": [
"# Import libraries\n",
"import numpy as np\n",
"from numpy import linalg as LA\n",
"\n",
"import random\n",
"import time\n",
"from IPython import display\n",
"import matplotlib.animation as animation\n",
"import matplotlib.pyplot as plt\n",
"plt.rcParams['text.usetex'] = True\n",
"\n",
"import seaborn as sns"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## MA934\n",
"\n",
"## Solving linear systems - the direct way\n",
"\n",
"### Backward substitution and LU factorisation"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"We start with the most basic solver - a backward substitution algorithm for a favourable dataset.\n",
"\n",
"#### Expected input:\n",
"U - an nxn upper triangular matrix with non-zero entries on the diagonal
\n",
"b - an n-sized right hand side\n",
"\n",
"#### Expected output:\n",
"x - an n-sized vector, solution to Ux=b "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### A simple example\n",
"\n",
"Designed for $x_1=5$, $x_2=1$ and $x_3=2$ as target solutions."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[5]\n",
" [1]\n",
" [2]]\n"
]
}
],
"source": [
"# Initialize upper triangular matrix\n",
"U0 = np.matrix([[1,2,3],[0,1,1],[0,0,5]])\n",
"# Initialize right hand side\n",
"b0 = np.matrix([[13],[3],[10]])\n",
"# Set the solution vector to zero\n",
"x0 = np.zeros_like(b0)\n",
"\n",
"# Naive/direct translation of algorithm\n",
"n = b0.size\n",
"# First step considered outside loop to avoid \n",
"# iterating index exceeding size of matrix\n",
"x0[n-1] = b0[n-1]/U0[n-1, n-1]\n",
"\n",
"# Main loop\n",
"for i in range(n-2, -1, -1):\n",
" h = 0 # helper variable\n",
" for j in range (i+1, n):\n",
" h += U0[i, j]*x0[j]\n",
" x0[i] = (b0[i] - h)/U0[i, i]\n",
"\n",
"# Consult result\n",
"print(np.matrix(x0))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Primary backward substitution function\n",
"\n",
"More elegantly, we define a function we can use as part of more complicated workflows."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def simpleBackwardSubstitution(U: np.ndarray, b: np.ndarray) -> np.ndarray:\n",
" n = b.size\n",
" x = np.zeros_like(b)\n",
" \n",
" # First step\n",
" x[n-1] = b[n-1]/U[n-1, n-1]\n",
" \n",
" # Main loop\n",
" for i in range(n-2, -1, -1):\n",
" h = 0 # helper variable\n",
" for j in range (i+1, n):\n",
" h += U[i, j]*x[j]\n",
" x[i] = (b[i] - h)/U[i, i]\n",
"\n",
" return x"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### General solution\n",
"\n",
"First test the function to make sure we retrieve the expected output, then design a larger ($64 \\times 64$) matrix for a more realistic test."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"First verify the simple 3x3 case:\n",
"[[5]\n",
" [1]\n",
" [2]]\n",
"The error norm between our solution and the default solver is 3.7054528131284762e-09\n"
]
}
],
"source": [
"# Use a function (defined below) instead and compare results\n",
"x0F = simpleBackwardSubstitution(U0,b0);\n",
"print(\"First verify the simple 3x3 case:\")\n",
"print(np.matrix(x0F))\n",
"\n",
"# Now for a real challenge - a larger upper triangular matrix\n",
"# Generate a random 64x64 matrix (the 0.1 offset is to ensure non-zero\n",
"# diagonal entries)\n",
"A = 0.1 + np.random.rand(64,64)\n",
"# Select upper triangular part\n",
"U = np.triu(A)\n",
"# ... and an appropriately sized vector, either artificially\n",
"b = U.sum(axis=1) # expect a solution of 1's if constructing the rhs this way\n",
"# b = np.random.rand(len(A),1) # uncomment if you wish to test more generally\n",
"\n",
"x = simpleBackwardSubstitution(A,b)\n",
"\n",
"# Compare result to in-built function\n",
"xInbuilt = np.linalg.solve(U, b)\n",
"# using Euclidean vector norm\n",
"errorNorm = LA.norm(x - xInbuilt)\n",
"print(\"The error norm between our solution and the default solver is \", errorNorm)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### How do we factorise a matrix to retrieve triangular components?\n",
"\n",
"\n",
"#### Expected input:\n",
"A - an nxn matrix with invertible principal sub-matrices
\n",
"\n",
"#### Expected output\n",
"L - an nxn unit lower triangular matrix
\n",
"U - an nxn regular upper triangular matrix"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"Define again a simple test matrix for which we know the desired answer (```testA```) and a larger random counterpart that acts as the primary target once we have convinced ourselves that the implemented algorithm works. (Aside: one simple test is not sufficient of course, and you are of course encouraged to try different examples and special cases before declaring victory.)\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# A simple matrix to test out the functionality\n",
"testA = np.array([[1, 2, 4], [3, 8, 14], [2, 6, 13]])\n",
"\n",
"# Generate a random matrix of specified size\n",
"randomA = np.random.rand(32,32)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### LU factorisation function\n",
"\n",
"Below is the straightfoward translation of the pseudocode for the standard LU factorisation (without pivoting)."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def simpleLU(A,nk):\n",
" \n",
" n = len(A)\n",
" \n",
" # Initialise L and U matrices\n",
" U = A.copy()\n",
" L = np.identity(n)\n",
" \n",
" # Main loop as in the lecture notes pseudocode\n",
" for k in range(nk): # for full LU factorisation, nk = n (nk added as a variable only for the animation)\n",
" for j in range (k+1,n):\n",
" L[j,k] = U[j,k]/U[k,k]\n",
" U[j,k] = 0\n",
" for i in range(k+1,n):\n",
" U[j,i] = U[j,i] - L[j,k]*U[k,i] \n",
" return L, U"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We now deploy the implemented function for both the simple and the more complex case, while monitoring results and error norms."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[1. 0. 0.]\n",
" [3. 1. 0.]\n",
" [2. 1. 1.]]\n",
"[[1 2 4]\n",
" [0 2 2]\n",
" [0 0 3]]\n",
"The error norm of the solution for the simple case is: 0.0\n",
"The error norm of the solution for the larger case is: 2.697379928804404e-13\n"
]
}
],
"source": [
"# Execute the simple algorithm (defined via previous function)\n",
"testL, testU = simpleLU(testA, nk = len(testA))\n",
"\n",
"# The simple results can be inspected visually\n",
"print(np.matrix(testL))\n",
"print(np.matrix(testU))\n",
"\n",
"# The larger matrix case is simply stored for future verification\n",
"randomL, randomU = simpleLU(randomA, nk = len(randomA))\n",
"\n",
"# Verify that the factorisation is indeed accurate\n",
"# using a classical 2-norm for the error matrix\n",
"\n",
"# Simple case first\n",
"testErrorNorm = LA.norm(testA-testL@testU)\n",
"print (\"The error norm of the solution for the simple case is: \", testErrorNorm)\n",
"\n",
"# More complicated case next\n",
"randomErrorNorm = LA.norm(randomA-randomL@randomU)\n",
"print(\"The error norm of the solution for the larger case is: \", randomErrorNorm)\n",
"\n",
"# If we wish to restrict our verification for a specific accuracy level: \n",
"# print (\"The error norm of the solution when testing against standard multiplication for the larger case is: \",end=\"\")\n",
"# print (\"{0:.6f}\".format(randomErrorNorm))\n",
"\n",
"# Can also verify the in-built Python functionality for LU via scipy\n",
"# tP, tL, tU = lu(testA)\n",
"# rP, rL, rU = lu(randomA)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Required for creating the animation in the LU factorisation below\n",
"\n",
"# pip install nodejs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## LU factorisation in action (soon in cinemas near you)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
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"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",
"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",
"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], msg['forward']);\n",
" fig.send_message('refresh', {});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
" var x0 = msg['x0'] / fig.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
" var x1 = msg['x1'] / fig.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
" 0,\n",
" fig.canvas.width / fig.ratio,\n",
" fig.canvas.height / fig.ratio\n",
" );\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",
" 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.handle_history_buttons = function (fig, msg) {\n",
" for (var key in msg) {\n",
" if (!(key in fig.buttons)) {\n",
" continue;\n",
" }\n",
" fig.buttons[key].disabled = !msg[key];\n",
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
" if (msg['mode'] === 'PAN') {\n",
" fig.buttons['Pan'].classList.add('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" } else if (msg['mode'] === 'ZOOM') {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.add('active');\n",
" } else {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" }\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",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" } else if (\n",
" typeof evt.data === 'string' &&\n",
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
" ) {\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(\n",
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
" msg\n",
" );\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(\n",
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
" e,\n",
" e.stack,\n",
" msg\n",
" );\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",
" }\n",
" if (e.target) {\n",
" targ = e.target;\n",
" } else if (e.srcElement) {\n",
" targ = e.srcElement;\n",
" }\n",
" if (targ.nodeType === 3) {\n",
" // defeat Safari bug\n",
" targ = targ.parentNode;\n",
" }\n",
"\n",
" // pageX,Y are the mouse positions relative to the document\n",
" var boundingRect = targ.getBoundingClientRect();\n",
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
" }\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",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * this.ratio;\n",
" var y = canvas_pos.y * this.ratio;\n",
"\n",
" this.send_message(name, {\n",
" x: x,\n",
" y: y,\n",
" button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event),\n",
" });\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",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
" if (event.which === this._key) {\n",
" return;\n",
" } else {\n",
" this._key = event.which;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
" this._key = null;\n",
" }\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which !== 17) {\n",
" value += 'ctrl+';\n",
" }\n",
" if (event.altKey && event.which !== 18) {\n",
" value += 'alt+';\n",
" }\n",
" if (event.shiftKey && event.which !== 16) {\n",
" value += 'shift+';\n",
" }\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, 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
"\n",
"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 = document.getElementById(id);\n",
" var ws_proxy = comm_websocket_adapter(comm);\n",
"\n",
" function ondownload(figure, _format) {\n",
" window.open(figure.canvas.toDataURL());\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\n",
" fig.cell_info = mpl.find_output_cell(\"