{ "cells": [ { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import sqlite3\n", "import time\n", "from IPython import display\n", "from datetime import datetime\n", "import scipy.interpolate as inter\n", "from scipy import integrate\n", "\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "%matplotlib notebook" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "db = sqlite3.connect('spectra.sqlite3')" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def load_run(capture_id, gain, zero_cal=False):\n", " if zero_cal:\n", " data = db.execute('SELECT a.step, a.voltage, a.voltage_stdev, b.voltage, b.voltage_stdev '\n", " 'FROM measurements a JOIN measurements b USING (step) '\n", " 'WHERE a.capture_id = ?1 AND a.led_on = 1 AND b.capture_id = ?1 AND b.led_on = 0 '\n", " 'ORDER BY step ASC', (capture_id,)).fetchall()\n", " steps, voltages, voltage_stdevs, zero_voltages, zero_stdevs = map(np.array, zip(*data))\n", " else:\n", " data = db.execute('SELECT step, voltage, voltage_stdev '\n", " 'FROM measurements '\n", " 'WHERE capture_id = ? AND led_on = 1 '\n", " 'ORDER BY step ASC', (capture_id,)).fetchall()\n", " steps, voltages, voltage_stdevs = map(np.array, zip(*data))\n", " zero_voltages = zero_stdevs = np.zeros(len(steps))\n", " \n", " return (steps,\n", " (voltages-zero_voltages)/gain*1e9, # nanoamps\n", " np.sqrt(np.square(voltage_stdevs) + np.square(zero_stdevs))/gain*1e9) #nanoamps" ] }, { "cell_type": "code", "execution_count": 94, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def find_captures(name):\n", " # Get the newest capture for each color\n", " captures = db.execute(\n", " 'SELECT capture_id, color, gain FROM runs WHERE (name, color, timestamp) IN '\n", " '(SELECT name, color, MAX(timestamp) FROM runs '\n", " 'WHERE name=? GROUP BY color ORDER BY timestamp)', (name,)).fetchall()\n", " \n", " if not captures:\n", " raise ValueError('Run not found')\n", " return captures" ] }, { "cell_type": "code", "execution_count": 95, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def live_plot(name,\n", " spline_s=1, interval=1,\n", " live=True, save_svg=None):\n", " captures = find_captures(name)\n", " \n", " fig, ax = plt.subplots(1, 1)\n", " \n", " colors = {\n", "\n", " }\n", " \n", " while True:\n", " ax.clear()\n", " ax.spines['top'].set_visible(False)\n", " ax.spines['right'].set_visible(False)\n", " ax.spines['bottom'].set_color('#08bdf9')\n", " ax.spines['left'].set_color('#08bdf9')\n", " ax.tick_params(axis='x', colors='#01769D')\n", " ax.tick_params(axis='y', colors='#01769D')\n", " ax.xaxis.label.set_color('#01769D')\n", " ax.yaxis.label.set_color('#01769D')\n", " ax.set_xlabel('$x\\;[step]$')\n", " ax.set_ylabel('$I_{pd}\\;[nA]$')\n", " ax.grid(color='#08bdf9', linestyle=':')\n", " \n", " for capture_id, color, gain in captures:\n", " color_dark, color_bright = colors.get(color, ('#fe3ea0', '#ffd2e9'))\n", " steps, values, stdev = load_run(capture_id, gain)\n", " \n", " ax.errorbar(steps, values, yerr=stdev, color=color_bright, zorder=1)\n", " try:\n", " spline = inter.UnivariateSpline(steps, values, s=spline_s)\n", " ax.plot(steps, spline(steps), color=color_dark, zorder=2)\n", " except:\n", " pass\n", " fig.canvas.draw()\n", " if save_svg:\n", " fig.savefig(save_svg)\n", " if save_svg or not live:\n", " break\n", " time.sleep(1)" ] }, { "cell_type": "code", "execution_count": 113, "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", " this.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", " // 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", "\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": [ "ids = (45, 46, 44)\n", "bands = [(260,410), (150,330), (100,260)]\n", "poly_degree = 2\n", "max_stdev = 1.0\n", "remove_thresh = 0.05\n", "\n", "data_rgb = []\n", "for run_id, (l, r) in zip(ids, bands):\n", " steps, values, stdev = load_run_zero_cal(run_id, max_stdev)\n", " \n", " idxs = (np.abs(stdev[1:-1] - stdev[0:-2]) < remove_thresh) |\\\n", " (np.abs(stdev[1:-1] - stdev[2:]) < remove_thresh)\n", " idxs = np.hstack([np.array([True]), idxs, np.array([True])])\n", " steps, values, stdev = steps[idxs], values[idxs], stdev[idxs]\n", " \n", " idxs = (steps < l) | (steps > r)\n", " poly = np.poly1d(np.polyfit(steps[idxs], values[idxs], poly_degree))\n", " print('Poly for run {}: {}'.format(run_id, str(poly).strip()))\n", " \n", " values -= poly(steps)\n", " data_rgb.append((steps, values, stdev))\n", "\n", "plot_rgb_foo(data_rgb, ids, spline_s=0.05)" ] }, { "cell_type": "code", "execution_count": 97, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def plot_rgb_calibrated(data_rgb, spline_s=1, save_svg=None):\n", " fig, ax = plt.subplots(1, 1)\n", "\n", " for steps, values, stdev in data_rgb:\n", " ax.errorbar(steps, values, yerr=stdev, color='#ffd2e9', zorder=1)\n", " \n", " spline = inter.UnivariateSpline(steps, values, s=spline_s)\n", " ax.plot(steps, spline(steps), color='#fe3ea0', zorder=2)\n", " \n", " ax.spines['top'].set_visible(False)\n", " ax.spines['right'].set_visible(False)\n", " ax.spines['bottom'].set_color('#08bdf9')\n", " ax.spines['left'].set_color('#08bdf9')\n", " ax.tick_params(axis='x', colors='#01769D')\n", " ax.tick_params(axis='y', colors='#01769D')\n", " ax.xaxis.label.set_color('#01769D')\n", " ax.yaxis.label.set_color('#01769D')\n", " ax.grid(color='#08bdf9', linestyle=':')\n", " \n", " ax.set_xlim([380, 720])\n", " ax.set_xlabel('$\\lambda\\;[nm]$')\n", " ax.set_ylabel('$I_{pd}\\;[nA]$')\n", " \n", " if save_svg:\n", " fig.savefig(save_svg)" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\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", " this.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", " // 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", "\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": [ "captures = find_captures('cheap_rgb')\n", "\n", "# Approximate bands of interest for R, G and B channelsfor offset and stray light correction.\n", "bands = {\n", " 'red': (260,410), # [step]\n", " 'green': (150,330),\n", " 'blue': (100,260)\n", "}\n", "\n", "# The wavelengths are from a random RGB LED datasheet and are just preliminary starting values.\n", "# https://www.sparkfun.com/datasheets/Components/YSL-R596CR3G4B5C-C10.pdf\n", "λ_led = {'red': 623, 'green': 518, 'blue': 466} # [nm] Assumed wavelengths of R, G and B spectral peaks.\n", "λ_be = 400 # [nm] Approximate short-λ edge of blue band\n", "y_edge_min = 0.5\n", "transimpedance = 630e6 # Ohms.\n", "\n", "poly_degree = 1 # degree of polynomial for stray light and offset correction. Should be 1 or 2.\n", "\n", "#remove_thresh = 10.0 # [V] standard deviation delta threshold for outlier removal\n", "\n", "# ---\n", "data_rgb = {}\n", "for capture_id, color, gain in captures:\n", " # Load this channel from the database\n", " steps, values, stdev = load_run(capture_id, gain)\n", " \n", " # Remove outlier values whose standard deviation is much larger than that of their right and left neighbors\n", " #idxs = (np.abs(stdev[1:-1] - stdev[0:-2]) < remove_thresh) |\\\n", " # (np.abs(stdev[1:-1] - stdev[2:]) < remove_thresh)\n", " #idxs = np.hstack([np.array([True]), idxs, np.array([True])])\n", " #steps, values, stdev = steps[idxs], values[idxs], stdev[idxs]\n", " \n", " # Remove offset and stray light by fitting a second-order polynomial over the parts of the curve\n", " # that are clearly *not* part of the primary peak.\n", " l, r = bands[color]\n", " idxs = (steps < l) | (steps > r)\n", " poly = np.poly1d(np.polyfit(steps[idxs], values[idxs], poly_degree))\n", " print('Poly for', color, 'channel')\n", " print(poly)\n", " values -= poly(steps)\n", " \n", " data_rgb[color] = (steps, values, stdev)\n", "\n", "\n", "# Produce a first estimate for wavelength scaling. Use the short-wavelength edge of the blue band and the red peak\n", "# for this, as both can be assumed to remain stable even after photodiode response compensation. Then apply photodiode\n", "# response compensation and do another, second round of wavelength scaling estimation but this time using all three\n", "# peaks and a proper least-squares fit.\n", "peaks = { color: x[np.argmax(y)] for color, (x, y, σ2) in data_rgb.items() }\n", "edgesl = { color: x[np.argmax(y > y_edge_min)] for color, (x, y, σ2) in data_rgb.items() }\n", "\n", "Λ_est = np.poly1d(np.polyfit([edgesl['blue'], peaks['red']], [λ_be, λ_led['red']], 1))\n", "\n", "data_tmp = { color: (x, Λ_est(x), y, σ2) for color, (x, y, σ2) in data_rgb.items() }\n", "data_tmp = { color: (x, λ, y/Λ_sfh2701(λ), σ2) for color, (x, λ, y, σ2) in data_tmp.items() }\n", "# Limit wavelength range\n", "data_tmp = { color: (x[λ > 380], λ[λ > 380], y[λ > 380], σ2[λ > 380]) for color, (x, λ, y, σ2) in data_tmp.items() }\n", "\n", "# Calibrate wavelength axis using assumed peaks for r, g and b. Use least-squares polyfit for getting coefficients.\n", "peaks = { color: x[np.argmax(y)] for color, (x, λ, y, σ2) in data_tmp.items() }\n", "Λ = np.poly1d(np.polyfit(\n", " [peaks['red'], peaks['green'], peaks['blue']],\n", " [λ_led['red'], λ_led['green'], λ_led['blue']], 1))\n", "\n", "data_rgb = { color: (Λ(x), y, σ2) for color, (x, y, σ2) in data_rgb.items() }\n", "data_rgb = { color: (λ, y/Λ_sfh2701(λ), σ2) for color, (λ, y, σ2) in data_rgb.items() }\n", "\n", "# Limit wavelength range to slightly-larger-than visible range. We're getting improbably large values in the\n", "# utraviolet region that are probably caused by stray light.\n", "data_rgb = { color: (λ[λ > 380], y[λ > 380], σ2[λ > 380]) for color, (λ, y, σ2) in data_rgb.items() }\n", "\n", "# Normalize amplitude data to brightest channel for ease of reading\n", "#max_val = max(np.max(y) for λ, y, σ2 in data_rgb)\n", "#data_rgb = [ (λ, y/max_val, σ2/max_val) for λ, y, σ2 in data_rgb ]\n", "\n", "# Convert amplitude data to current in nanoampère\n", "data_rgb = { color: (λ, y/transimpedance / 1e-9, σ2/transimpedance / 1e-9) for color, (λ, y, σ2) in data_rgb.items() }\n", "\n", "plot_rgb_calibrated(data_rgb.values(), spline_s=0.005, save_svg='/tmp/processed_plot_cheap_rgb.svg')" ] }, { "cell_type": "code", "execution_count": 114, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# CIE XYZ Color matching functions from http://cvrl.ioo.ucl.ac.uk/\n", "# rows are: λ[nm], x, y, z\n", "CMFs = { fn[:-4]: np.genfromtxt(fn, delimiter=',')\n", " for fn in ['cie_xyz_1931.csv', 'cie_xyz_judd_1951.csv', 'cie_xyz_judd_vos_1978.csv'] }\n", "CMFs = { name: np.hstack([inter.interp1d(d[:,0], d[:,i]) for i in range(1,4)])\n", " for name, d in CMFs.items() }" ] }, { "cell_type": "code", "execution_count": 119, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def integrate_tristimulus_response(data, channels=('red', 'green', 'blue'), colorspace='cie_xyz_1931'):\n", " a = np.array([[\n", " integrate.simps(\n", " np.multiply(CMFs[colorspace][j](data[color][0]), data[color][1]), data[color][0])\n", " for j in range(3) ]\n", " for color in channels ])\n", " # normalize by largest component\n", " return a / np.max(np.sum(a, axis=0))" ] }, { "cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0.06995882, 0.02007191, -0.0260505 ],\n", " [ 0.05310356, 0.0995779 , 0.03458726],\n", " [ 0.16122952, 0.16639874, 0.99146324]])" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tristimulus_data = integrate_tristimulus_response(data_rgb)\n", "tristimulus_data\n", "#array([[ 3.46142003e-01, 1.73335974e-01, -7.18827590e-05],\n", "# [ 9.01721797e-02, 1.69512416e-01, 2.15830281e-02],\n", "# [ 1.75128165e-01, 2.49230694e-01, 9.78488855e-01]])" ] }, { "cell_type": "code", "execution_count": 121, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def led_setpoint_from_xyz(x, y, z):\n", " # returns [r, g, b] array.\n", " # Note that many xyz tristimulus values cannot be produced because one component is outside [0, 1]\n", " #return np.linalg.solve(tristimulus_data.T, np.array([x, y, z]))\n", " return np.dot(np.linalg.inv(tristimulus_data.T), np.array([x, y, z]))" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 2.96363627, 1.00231926, 0.24462504])" ] }, "execution_count": 122, "metadata": {}, "output_type": "execute_result" } ], "source": [ "led_setpoint_from_xyz(0.3, 0.2, 0.2)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 1 }