{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import math\n", "import sqlite3\n", "import struct\n", "import datetime\n", "\n", "import matplotlib\n", "from matplotlib import pyplot as plt\n", "from matplotlib import patches\n", "import numpy as np\n", "from scipy import signal, optimize\n", "from tqdm.notebook import tnrange, tqdm" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%matplotlib notebook" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "db = sqlite3.connect('waveform.sqlite3')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Run 000: 2020-01-30 14:24:25 - 2020-01-30 14:24:33 ( 0:00:07.571, 6880sp)\n", "Run 001: 2020-01-30 14:24:56 - 2020-01-30 14:25:25 ( 0:00:28.305, 8992sp)\n", "Run 002: 2020-01-30 14:25:33 - 2020-01-30 14:30:37 ( 0:05:04.016, 290112sp)\n", "Run 003: 2020-01-30 14:31:31 - 2020-01-30 14:37:59 ( 0:06:27.900, 384192sp)\n", "Run 004: 2020-01-30 14:38:30 - 2020-01-30 14:45:27 ( 0:06:56.604, 417216sp)\n", "Run 005: 2020-01-30 15:18:50 - 2020-01-30 15:19:01 ( 0:00:10.690, 10240sp)\n", "Run 006: 2020-01-30 16:37:15 - 2020-01-30 16:37:17 ( 0:00:02.527, 2560sp)\n", "Run 007: 2020-01-30 16:44:23 - 2020-01-30 16:58:48 ( 0:14:24.293, 665600sp)\n", "Run 008: 2020-01-30 17:06:35 - 2020-01-30 17:46:16 ( 0:39:41.608, 2163168sp)\n", "Run 009: 2020-01-30 17:46:20 - 2020-01-30 18:11:16 ( 0:24:55.928, 1492480sp)\n", "Run 010: 2020-01-30 18:11:39 - 2020-01-30 18:22:29 ( 0:10:50.025, 642560sp)\n", "Run 011: 2020-01-30 18:22:32 - 2020-01-30 19:33:52 ( 1:11:20.495, 4280320sp)\n", "Run 012: 2020-01-31 13:16:53 - 2020-01-31 13:18:12 ( 0:01:19.317, 79360sp)\n", "Run 013: 2020-01-31 13:30:54 - 2020-01-31 13:31:35 ( 0:00:40.762, 40960sp)\n", "Run 014: 2020-01-31 13:45:37 - 2020-01-31 13:45:42 ( 0:00:05.090, 5120sp)\n", "Run 015: 2020-01-31 13:53:56 - 2020-01-31 13:54:01 ( 0:00:05.089, 5120sp)\n", "Run 016: 2020-01-31 13:54:21 - 2020-01-31 13:54:26 ( 0:00:05.088, 5120sp)\n", "Run 017: 2020-01-31 13:55:41 - 2020-01-31 13:55:46 ( 0:00:05.087, 5120sp)\n", "Run 018: 2020-01-31 13:56:13 - 2020-01-31 13:56:19 ( 0:00:05.091, 5120sp)\n", "Run 019: 2020-01-31 13:56:27 - 2020-01-31 13:56:30 ( 0:00:02.527, 2560sp)\n", "Run 020: 2020-01-31 13:56:40 - 2020-01-31 13:56:48 ( 0:00:07.649, 7680sp)\n", "Run 021: 2020-01-31 13:57:10 - 2020-01-31 13:58:34 ( 0:01:24.342, 84416sp)\n", "Run 022: 2020-01-31 14:05:08 - 2020-01-31 14:05:24 ( 0:00:15.242, 15360sp)\n", "Run 023: 2020-01-31 14:05:33 - 2020-01-31 14:12:50 ( 0:07:17.092, 435200sp)\n", "Run 024: 2020-01-31 14:13:21 - 2020-01-31 14:15:39 ( 0:02:18.190, 138240sp)\n", "Run 025: 2020-01-31 14:18:16 - 2020-01-31 18:58:25 ( 4:40:09.251, 16611840sp)\n" ] } ], "source": [ "for run_id, start, end, count in db.execute('SELECT run_id, MIN(rx_ts), MAX(rx_ts), COUNT(*) FROM measurements GROUP BY run_id'):\n", " foo = lambda x: datetime.datetime.fromtimestamp(x/1000)\n", " start, end = foo(start), foo(end)\n", " print(f'Run {run_id:03d}: {start:%Y-%m-%d %H:%M:%S} - {end:%Y-%m-%d %H:%M:%S} ({str(end-start)[:-3]:>13}, {count*32:>9d}sp)')\n", "last_run, n_records = run_id, count\n", "sampling_rate = 1000.0" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "par = lambda *rs: 1/sum(1/r for r in rs) # resistor parallel calculation\n", "\n", "# FIXME: These are for the first prototype only!\n", "vmeas_source_impedance = 330e3\n", "vmeas_source_scale = 0.5\n", "\n", "vcc = 15.0\n", "vmeas_div_high = 27e3\n", "vmeas_div_low = par(4.7e3, 10e3)\n", "vmeas_div_voltage = vcc * vmeas_div_low / (vmeas_div_high + vmeas_div_low)\n", "vmeas_div_impedance = par(vmeas_div_high, vmeas_div_low)\n", "\n", "#vmeas_overall_factor = vmeas_div_impedance / (vmeas_source_impedance + vmeas_div_impedance)\n", "v0 = 1.5746\n", "v100 = 2.004\n", "vn100 = 1.1452\n", "\n", "adc_vcc = 3.3 # V\n", "adc_fullscale = 4095\n", "\n", "adc_val_to_voltage_factor = 1/adc_fullscale * adc_vcc\n", "\n", "adc_count_to_vmeas = lambda x: (x*adc_val_to_voltage_factor - v0) / (v100-v0) * 100" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": false }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ba042a79e76742dfae88bd0a5913cb1f", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntProgress(value=0, max=519120), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "limit = n_records\n", "record_size = 32\n", "skip_dropped_sections = False\n", "\n", "data = np.zeros(limit*record_size)\n", "data[:] = np.nan\n", "\n", "last_seq = None\n", "write_index = 0\n", "for i, (seq, chunk) in tqdm(enumerate(db.execute(\n", " 'SELECT seq, data FROM measurements WHERE run_id = ? ORDER BY rx_ts LIMIT ? OFFSET ?',\n", " (last_run, limit, n_records-limit))), total=n_records):\n", " \n", " if last_seq is None or seq == (last_seq + 1)%0xffff:\n", " last_seq = seq\n", " idx = write_index if skip_dropped_sections else i\n", " data[idx*record_size:(idx+1)*record_size] = np.frombuffer(chunk, dtype=' last_seq:\n", " last_seq = seq\n", " # nans = np.empty((record_size,))\n", " # nans[:] = np.nan\n", " # data = np.append(data, nans) FIXME\n", " \n", "data = (data * adc_val_to_voltage_factor - v0) / (v100-v0) * 100" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "227.138252895397" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_not_nan = data[~np.isnan(data)]\n", "np.sqrt(np.mean(np.square(data_not_nan)))" ] }, { "cell_type": "code", "execution_count": 124, "metadata": { "scrolled": 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 = $('
');\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", " '
');\n", " var titletext = $(\n", " '
');\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 = $('
');\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 = $('');\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 = $('');\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 = $('
')\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 = $('');\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 = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var 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= 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": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(9, 3))\n", "fig.tight_layout(pad=2, h_pad=0.1)\n", "\n", "ax.pcolormesh(t[-200:-100], f[:250], np.abs(Zxx[:250,-200:-100]))\n", "ax.set_title(f\"Run {last_run}\", pad=-20, color='white')\n", "ax.grid()\n", "ax.set_ylabel('f [Hz]')\n", "ax.set_ylim([30, 75]) # Hz\n", "ax.set_xlabel('simulation time t [s]')\n", "None" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "scrolled": false }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "bb14b5b4747148898f1d8f046318bb55", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntProgress(value=0, max=166118), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "f_t = t\n", "\n", "n_f, n_t = Zxx.shape\n", "# start, stop = 180, 220\n", "# start, stop = 90, 110\n", "# start, stop = 15, 35\n", "# bounds_f = slice(start // 4 * nfft_factor, stop // 4 * nfft_factor)\n", "f_min, f_max = 30, 70 # Hz\n", "bounds_f = slice(np.argmax(f > f_min), np.argmin(f < f_max))\n", "\n", "\n", "f_mean = np.zeros(Zxx.shape[1])\n", "for le_t in tnrange(1, Zxx.shape[1] - 1):\n", " frame_f = f[bounds_f]\n", " frame_step = frame_f[1] - frame_f[0]\n", " time_step = f_t[1] - f_t[0]\n", " #if t == 10:\n", " # axs[-1].plot(frame_f, frame_Z)\n", " frame_Z = np.abs(Zxx[bounds_f, le_t])\n", " # frame_f = f[180:220]\n", " # frame_Z = np.abs(Zxx[180:220, 40])\n", " # frame_f = f[15:35]\n", " # frame_Z = np.abs(Zxx[15:35, 40])\n", " # plt.plot(frame_f, frame_Z)\n", "\n", " # peak_f = frame_f[np.argmax(frame)]\n", " # plt.axvline(peak_f, color='red')\n", "\n", "# def gauss(x, *p):\n", "# A, mu, sigma, o = p\n", "# return A*np.exp(-(x-mu)**2/(2.*sigma**2)) + o\n", "\n", " def gauss(x, *p):\n", " A, mu, sigma = p\n", " return A*np.exp(-(x-mu)**2/(2.*sigma**2))\n", "\n", " f_start = frame_f[np.argmax(frame_Z)]\n", " A_start = np.max(frame_Z)\n", " p0 = [A_start, f_start, 1.]\n", " try:\n", " coeff, var = optimize.curve_fit(gauss, frame_f, frame_Z, p0=p0)\n", " # plt.plot(frame_f, gauss(frame_f, *coeff))\n", " #print(coeff)\n", " A, mu, sigma, *_ = coeff\n", " f_mean[le_t] = mu\n", " except Exception:\n", " f_mean[le_t] = np.nan" ] }, { "cell_type": "code", "execution_count": 119, "metadata": { "scrolled": 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 = $('
');\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", " '
');\n", " var titletext = $(\n", " '
');\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 = $('
');\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 = $('');\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 = $('');\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 = $('
')\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 = $('');\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 = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var 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= 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": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f_copy = np.copy(f_mean[1:-1])\n", "f_copy[np.isnan(f_copy)] = np.mean(f_copy[~np.isnan(f_copy)])\n", "b, a = signal.cheby2(7, 86, 100, 'low', output='ba', fs=1000)\n", "filtered = signal.lfilter(b, a, f_copy)\n", "\n", "b2, a2 = signal.cheby2(3, 30, 1, 'high', output='ba', fs=1000)\n", "filtered2 = signal.lfilter(b2, a2, filtered)\n", "\n", "fig, (ax2, ax1) = plt.subplots(2, figsize=(9,7))\n", "ax1.plot(f_t[1:-1], f_copy, color='lightgray')\n", "ax1.set_ylim([49.90, 50.10])\n", "ax1.grid()\n", "formatter = matplotlib.ticker.FuncFormatter(lambda s, x: str(datetime.timedelta(seconds=s)))\n", "ax1.xaxis.set_major_formatter(formatter)\n", "zoom_offx = 7000 # s\n", "zoom_len = 300 # s\n", "ax1.set_xlim([zoom_offx, zoom_offx + zoom_len])\n", "\n", "ax1.plot(f_t[1:-1], filtered, color='orange')\n", "ax1r = ax1.twinx()\n", "ax1r.plot(f_t[1:-1], filtered2, color='red')\n", "ax1r.set_ylim([-0.015, 0.015])\n", "ax1.set_title(f'Zoomed trace ({datetime.timedelta(seconds=zoom_len)})', pad=-20)\n", "\n", "\n", "ax2.set_title(f'Run {last_run}')\n", "ax2.plot(f_t[1:-1], f_copy, color='orange')\n", "\n", "ax2r = ax2.twinx()\n", "ax2r.set_ylim([-0.1, 0.1])\n", "ax2r.plot(f_t[1:-1], filtered2, color='red')\n", "#ax2.plot(f_t[1:-1], filtered, color='orange', zorder=1)\n", "ax2.set_ylim([49.90, 50.10])\n", "ax2.set_xlim([0, f_t[-2]])\n", "ax2.grid()\n", "formatter = matplotlib.ticker.FuncFormatter(lambda s, x: str(datetime.timedelta(seconds=s)))\n", "ax2.xaxis.set_major_formatter(formatter)\n", "\n", "ax2.legend(handles=[\n", " patches.Patch(color='lightgray', label='Raw frequency'),\n", " patches.Patch(color='orange', label='low-pass filtered'),\n", " patches.Patch(color='red', label='band-pass filtered')])\n", "\n", "#ax2r.spines['right'].set_color('red')\n", "ax2r.yaxis.label.set_color('red')\n", "#ax2r.tick_params(axis='y', colors='red')\n", "\n", "#ax1r.spines['right'].set_color('red')\n", "ax1r.yaxis.label.set_color('red')\n", "#ax1r.tick_params(axis='y', colors='red')\n", "\n", "ax1.set_ylabel('f [Hz]')\n", "ax1r.set_ylabel('band-pass Δf [Hz]')\n", "ax2.set_ylabel('f [Hz]')\n", "ax2r.set_ylabel('band-pass Δf [Hz]')\n", "\n", "# Cut out first 10min of filtered data to give filters time to settle\n", "rms_slice = filtered2[np.where(f_t[1:] > 10*60)[0][0]:]\n", "rms = np.sqrt(np.mean(np.square(rms_slice)))\n", "ax1.text(0.5, 0.1, f'RMS (band-pass): {rms*1e3:.3f}mHz', transform=ax1.transAxes, color='white', bbox=bbox, ha='center')\n", "None" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [], "source": [ "chunk_size = 256\n", "\n", "with open('filtered_freq.bin', 'wb') as f:\n", " for chunk in range(0, len(rms_slice), chunk_size):\n", " out_data = rms_slice[chunk:chunk+chunk_size]\n", " f.write(struct.pack(f'{len(out_data)}f', *out_data))\n", " \n", "with open('raw_freq.bin', 'wb') as f:\n", " for chunk in range(0, len(f_copy), chunk_size):\n", " out_data = f_copy[chunk:chunk+chunk_size]\n", " f.write(struct.pack(f'{len(out_data)}f', *out_data))" ] }, { "cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "54.0" ] }, "execution_count": 128, "metadata": {}, "output_type": "execute_result" } ], "source": [ "27000 * 2e-3" ] } ], "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": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 2 }