discrete_time _signal_generation_3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dcfce3e0",
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   "outputs": [
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       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
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       "\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",
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       "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",
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       "\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",
       "    fig.canvas_div.style.cursor = msg['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",
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       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
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       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
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       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\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",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\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": [
    "'''\n",
    "Abdülhalim YAYDEMİR  \n",
    "'''\n",
    "# DSP environment' da numpy ve matplotlib paketleri mevcut değil onlar anaconda üzerinden eklendi \n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt           \n",
    "%matplotlib notebook                     \n",
    "\n",
    "# font ayarı https://matplotlib.org/stable/gallery/text_labels_and_annotations/text_fontdict.html#sphx-glr-gallery-text-labels-and-annotations-text-fontdict-py\n",
    "font = {'family': 'serif',\n",
    "       'color'  : 'black',\n",
    "       'weight' : 'normal',\n",
    "       'size'   :  18,\n",
    "       }\n",
    "\n",
    "\n",
    "# böyle yaparak her seferinde np.pi demek yerine sadece pi diyebliriz                           \n",
    "pi = np.pi \n",
    "\n",
    "\n",
    "# gözlemlenecek aralığı belirle\n",
    "t = np.arange(0,100+0.001,pi/100)\n",
    "n = np.arange(0,100,1) \n",
    "\n",
    "\n",
    "# x[n] = sin(pi*n/19)\n",
    "# degişkene denklem atama      https://numpy.org/doc/stable/reference/generated/numpy.sin.html\n",
    "continous = np.sin(0.1*pi*t)+(1/3)*np.sin(0.3*pi*t)+(1/5)*np.sin(0.4*pi*t)\n",
    "discrete = np.sin(0.05*pi*n)+(1/3)*np.sin(0.15*pi*n)+(1/5)*np.sin(0.2*pi*n)\n",
    "\n",
    "\n",
    "# sinyal çizdirildi\n",
    "\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(t, continous,'b-')\n",
    "plt.title('x(t)', fontdict=font)\n",
    "plt.grid(True)\n",
    "plt.annotate('T = 20s', xy=(21, 1.12), xytext=(-13, 1.16), arrowprops=dict(facecolor='red', shrink=0.05))\n",
    "\n",
    "\n",
    "plt.subplot(2,1,2)\n",
    "plt.stem(n, discrete,'r-')\n",
    "plt.title('x[n]', fontdict=font)\n",
    "plt.xlabel('t,n')\n",
    "plt.grid(True)\n",
    "plt.annotate('N = 40 ÖRNEK', xy=(82, 1.18), xytext=(15, 1.20), arrowprops=dict(facecolor='blue', shrink=0.05))\n",
    "plt.ylim(-1.3,1.4)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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",
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