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jhitesma/purple.ipynb

Created April 28, 2017 23:27
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purple.ipynb
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"Autotune data: pts = 1024, aux_data_len = 0, timestep = 0.62ms\n"
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"source": [
"%matplotlib inline\n",
"\n",
"# Import all the numerical computing stuff we need...\n",
"\n",
"from dronin import autotune\n",
"import numpy as np\n",
"import pandas\n",
"import math\n",
"from scipy import fftpack, signal\n",
"from bokeh.plotting import figure, show\n",
"from bokeh.io import output_notebook\n",
"from bokeh.models import LinearAxis, Range1d, Span\n",
"\n",
"output_notebook() # Tell bokeh to send plots to notebook\n",
"\n",
"# And load up a datafile of autotune data. In this file, the average\n",
"# motor commands and gyro responses from all 90-120 wobbles during the\n",
"# autotune sequence are stored.\n",
"df, time_step = autotune.read_autotune_lump('/Users/jhitesma/Downloads/purple.bin', filter_freq=55, filter_order=0)#, filter_order=6)\n"
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"source": [
"# next let's plot what the roll gyro does vs. the flight controller's roll command\n",
"\n",
"p = figure(title=\"roll gyro vs actuators\")\n",
"p.line(df.time, df.gyroX)\n",
"p.extra_y_ranges = { 'actuation' : Range1d(min(df.desiredX), max(df.desiredX)) }\n",
"p.line(df.time, df.desiredX, y_range_name='actuation', color=\"red\")\n",
"p.add_layout(LinearAxis(y_range_name=\"actuation\"), 'right')\n",
"\n",
"show(p)\n",
"\n",
"# Looks really nasty, huh? This is the gyro data vs. the actuator data. They're clearly related\n",
"# but phase is off and shape is a fair bit different."
]
},
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"outputs": [
{
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" if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
" window._bokeh_timeout = Date.now() + 0;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
" function display_loaded() {\n",
" if (window.Bokeh !== undefined) {\n",
" document.getElementById(\"ad8c748c-e20c-4ae6-8159-4fc2033afc1c\").textContent = \"BokehJS successfully loaded.\";\n",
" } else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
" }\n",
" \n",
" function run_callbacks() {\n",
" window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
" \n",
" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
" if (window._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"ad8c748c-e20c-4ae6-8159-4fc2033afc1c\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'ad8c748c-e20c-4ae6-8159-4fc2033afc1c' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" (function() {\n",
" var fn = function() {\n",
" var docs_json = 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}
],
"source": [
"p = figure(title=\"roll gyrodiff vs actuators\")\n",
"p.line(df.time, df.derivgyroX)\n",
"p.extra_y_ranges = { 'actuation' : Range1d(min(df.desiredX), max(df.desiredX)) }\n",
"p.line(df.time, df.desiredX, y_range_name='actuation', color=\"red\")\n",
"p.add_layout(LinearAxis(y_range_name=\"actuation\"), 'right')\n",
"\n",
"show(p)\n",
"\n",
"# If we differentiate the gyro, the shape is more clearly related, but boy is\n",
"# there a lot of noise."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
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"editable": true,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
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" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
" function display_loaded() {\n",
" if (window.Bokeh !== undefined) {\n",
" document.getElementById(\"4b4e8a99-4460-4ce4-a5fd-82e1e786d586\").textContent = \"BokehJS successfully loaded.\";\n",
" } else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
" }\n",
" \n",
" function run_callbacks() {\n",
" window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
" \n",
" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
" if (window._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"4b4e8a99-4460-4ce4-a5fd-82e1e786d586\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid '4b4e8a99-4460-4ce4-a5fd-82e1e786d586' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" (function() {\n",
" var fn = function() {\n",
" var docs_json = 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" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }(this));\n",
"</script>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"p = figure(title=\"filtered roll gyrodiff vs actuators\")\n",
"p.line(df.time, df.derivfilteredX)\n",
"p.extra_y_ranges = { 'actuation' : Range1d(min(df.desiredX), max(df.desiredX)) }\n",
"p.line(df.time, df.desiredX, y_range_name='actuation', color=\"red\")\n",
"p.add_layout(LinearAxis(y_range_name=\"actuation\"), 'right')\n",
"\n",
"show(p)\n",
"\n",
"# Low pass filtering clearly helps. Now let's get down to business of finding how the input\n",
"# relates to the output."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true,
"scrolled": false,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
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\",\"dtype\":\"float64\",\"shape\":[1024]}}},\"id\":\"f6f9f026-949c-4bfe-80be-34c68aa94e44\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"f0c5286a-e8c3-4d14-9598-3405fada9c61\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"80eb9d48-03c8-48bb-be98-69a348661413\",\"type\":\"BasicTicker\"},{\"attributes\":{\"below\":[{\"id\":\"ce01335f-99dd-4a4c-a908-1d74eecf9c39\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"1f0aadd9-c1af-42f6-bda2-381482d0b71c\",\"type\":\"LinearAxis\"}],\"renderers\":[{\"id\":\"ce01335f-99dd-4a4c-a908-1d74eecf9c39\",\"type\":\"LinearAxis\"},{\"id\":\"2c020f04-d39e-43d4-9df2-ef71a62c9791\",\"type\":\"Grid\"},{\"id\":\"1f0aadd9-c1af-42f6-bda2-381482d0b71c\",\"type\":\"LinearAxis\"},{\"id\":\"d1dd3d0d-f852-49e5-92e5-995a200a255f\",\"type\":\"Grid\"},{\"id\":\"2de95c9c-d9cf-4dd6-8233-a09f8e48f6c3\",\"type\":\"BoxAnnotation\"},{\"id\":\"e7fcd6ae-5462-43e2-bd5f-5e5e9fe458cf\",\"type\":\"GlyphRenderer\"},{\"id\":\"0d065d26-43c3-40f5-9623-81436b2737bb\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"6fff711f-b83e-4421-a70c-e8f89de0ebd5\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"db4ebb8d-77b3-4078-967f-d0b564da9b9f\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"de97b81c-948f-459e-b08a-cf749dce9eef\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"27aab032-ae12-48e1-905d-a82ec25ba448\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"986fe650-bfab-4ff4-8f15-9895cfb94873\",\"type\":\"DataRange1d\"}},\"id\":\"4896b77d-73d2-4046-a36f-58b59001d80d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"29521e7d-81a4-4db0-8fb5-b8ba0bf7780f\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null},\"id\":\"27aab032-ae12-48e1-905d-a82ec25ba448\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"4896b77d-73d2-4046-a36f-58b59001d80d\"]},\"title\":\"Bokeh 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" \n",
" Bokeh.embed.embed_items(docs_json, render_items);\n",
" };\n",
" if (document.readyState != \"loading\") fn();\n",
" else document.addEventListener(\"DOMContentLoaded\", fn);\n",
" })();\n",
" },\n",
" function(Bokeh) {\n",
" }\n",
" ];\n",
" \n",
" function run_inline_js() {\n",
" \n",
" if ((window.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i](window.Bokeh);\n",
" }if (force === true) {\n",
" display_loaded();\n",
" }} else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!window._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" window._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(\"3517fca9-e22b-4e1e-957c-21ca7bb9ac11\")).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
" \n",
" }\n",
" \n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }(this));\n",
"</script>"
]
},
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{
"data": {
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"\n",
"\n",
" <div class=\"bk-root\">\n",
" <div class=\"bk-plotdiv\" id=\"5dec8391-acf9-4eed-9c48-d7ff701443ce\"></div>\n",
" </div>\n",
"<script type=\"text/javascript\">\n",
" \n",
" (function(global) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
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" var force = false;\n",
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" if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
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" window._bokeh_is_loading = undefined;\n",
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" \n",
" \n",
" if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
" window._bokeh_timeout = Date.now() + 0;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
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" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
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" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
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" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
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" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
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" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"5dec8391-acf9-4eed-9c48-d7ff701443ce\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid '5dec8391-acf9-4eed-9c48-d7ff701443ce' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" (function() {\n",
" var fn = function() {\n",
" var docs_json = 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"Axis Y: tau=38.1 samples (23.84 ms / -3.736)\n",
"\tgain=21.8 (beta=10.460), bias=21.2\n"
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" var render_items = [{\"docid\":\"df2d8540-5ddc-4471-8092-4e33fe51611f\",\"elementid\":\"30187cc0-ae5d-419b-a2b0-6280071ef3e5\",\"modelid\":\"df446bdc-ca8e-48dc-a9d2-56fcdab6891e\"}];\n",
" \n",
" Bokeh.embed.embed_items(docs_json, render_items);\n",
" };\n",
" if (document.readyState != \"loading\") fn();\n",
" else document.addEventListener(\"DOMContentLoaded\", fn);\n",
" })();\n",
" },\n",
" function(Bokeh) {\n",
" }\n",
" ];\n",
" \n",
" function run_inline_js() {\n",
" \n",
" if ((window.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i](window.Bokeh);\n",
" }if (force === true) {\n",
" display_loaded();\n",
" }} else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!window._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" window._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(\"30187cc0-ae5d-419b-a2b0-6280071ef3e5\")).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
" \n",
" }\n",
" \n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }(this));\n",
"</script>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" <div class=\"bk-root\">\n",
" <div class=\"bk-plotdiv\" id=\"119ad911-a1c4-41b1-895f-af4d23fd5fb1\"></div>\n",
" </div>\n",
"<script type=\"text/javascript\">\n",
" \n",
" (function(global) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
" \n",
" var force = false;\n",
" \n",
" if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
" window._bokeh_onload_callbacks = [];\n",
" window._bokeh_is_loading = undefined;\n",
" }\n",
" \n",
" \n",
" \n",
" if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
" window._bokeh_timeout = Date.now() + 0;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
" function display_loaded() {\n",
" if (window.Bokeh !== undefined) {\n",
" document.getElementById(\"119ad911-a1c4-41b1-895f-af4d23fd5fb1\").textContent = \"BokehJS successfully loaded.\";\n",
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" }\n",
" }\n",
" \n",
" function run_callbacks() {\n",
" window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
" \n",
" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
" if (window._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
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" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"119ad911-a1c4-41b1-895f-af4d23fd5fb1\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid '119ad911-a1c4-41b1-895f-af4d23fd5fb1' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" (function() {\n",
" var fn = function() {\n",
" var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[1024]}}},\"id\":\"a5fd5d9b-da7e-4c77-9404-71289cf5ee8f\",\"type\":\"ColumnDataSource\"}],\"root_ids\":[\"6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" </div>\n",
"<script type=\"text/javascript\">\n",
" \n",
" (function(global) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
" \n",
" var force = false;\n",
" \n",
" if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
" window._bokeh_onload_callbacks = [];\n",
" window._bokeh_is_loading = undefined;\n",
" }\n",
" \n",
" \n",
" \n",
" if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
" window._bokeh_timeout = Date.now() + 0;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
" function display_loaded() {\n",
" if (window.Bokeh !== undefined) {\n",
" document.getElementById(\"edabfbe7-e49e-477a-828d-23e27a0d0cff\").textContent = \"BokehJS successfully loaded.\";\n",
" } else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
" }\n",
" \n",
" function run_callbacks() {\n",
" window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
" \n",
" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
" if (window._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"edabfbe7-e49e-477a-828d-23e27a0d0cff\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'edabfbe7-e49e-477a-828d-23e27a0d0cff' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" (function() {\n",
" var fn = function() {\n",
" var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[1024]}}},\"id\":\"845fd251-093e-4380-84a9-ee6dcaf3f2c2\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"188b12db-4b5a-457c-ad1a-47349beb53ae\",\"type\":\"BasicTicker\"},{\"attributes\":{\"data_source\":{\"id\":\"f16907ce-f744-4076-8f85-5987624ed2c3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"76f99bf6-3f25-4651-973b-8ecfeb5548f4\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"2bbe0fce-0a4e-4c67-a69a-e91e78014b78\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"9823e0da-5f6e-4ab4-b8dd-7d30c580e4b2\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"ff794bfe-e6fa-4ff9-829e-c662cd63e1c0\",\"type\":\"PanTool\"},{\"id\":\"bdd3612d-2851-4400-8603-0fb01c29c24c\",\"type\":\"WheelZoomTool\"},{\"id\":\"848be6c3-7088-4483-8fcc-af7a0cdda763\",\"type\":\"BoxZoomTool\"},{\"id\":\"38761db9-5532-4a2c-93e7-7ac73ec7c86b\",\"type\":\"SaveTool\"},{\"id\":\"eedf80c9-94b3-474a-99af-e1297ab1e2fa\",\"type\":\"ResetTool\"},{\"id\":\"3d5d7a59-2d9b-4773-bcdf-a7e3b94b65f2\",\"type\":\"HelpTool\"}]},\"id\":\"7142b571-e50f-4992-a42e-523e957bff28\",\"type\":\"Toolbar\"}],\"root_ids\":[\"58387d13-99cf-44fb-be3c-ef0d80e8bed8\"]},\"title\":\"Bokeh 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" var render_items = [{\"docid\":\"39d0491c-8843-4550-a83e-1ce9820edd95\",\"elementid\":\"6ed7a1c9-e852-4545-af8e-852dcb4760e7\",\"modelid\":\"58387d13-99cf-44fb-be3c-ef0d80e8bed8\"}];\n",
" \n",
" Bokeh.embed.embed_items(docs_json, render_items);\n",
" };\n",
" if (document.readyState != \"loading\") fn();\n",
" else document.addEventListener(\"DOMContentLoaded\", fn);\n",
" })();\n",
" },\n",
" function(Bokeh) {\n",
" }\n",
" ];\n",
" \n",
" function run_inline_js() {\n",
" \n",
" if ((window.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i](window.Bokeh);\n",
" }if (force === true) {\n",
" display_loaded();\n",
" }} else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!window._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" window._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(\"6ed7a1c9-e852-4545-af8e-852dcb4760e7\")).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
" \n",
" }\n",
" \n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }(this));\n",
"</script>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" <div class=\"bk-root\">\n",
" <div class=\"bk-plotdiv\" id=\"afb6a788-e7d2-4b2e-87c2-fe2d95e788aa\"></div>\n",
" </div>\n",
"<script type=\"text/javascript\">\n",
" \n",
" (function(global) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
" \n",
" var force = false;\n",
" \n",
" if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
" window._bokeh_onload_callbacks = [];\n",
" window._bokeh_is_loading = undefined;\n",
" }\n",
" \n",
" \n",
" \n",
" if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
" window._bokeh_timeout = Date.now() + 0;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
" function display_loaded() {\n",
" if (window.Bokeh !== undefined) {\n",
" document.getElementById(\"afb6a788-e7d2-4b2e-87c2-fe2d95e788aa\").textContent = \"BokehJS successfully loaded.\";\n",
" } else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
" }\n",
" \n",
" function run_callbacks() {\n",
" window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
" \n",
" function load_libs(js_urls, callback) {\n",
" window._bokeh_onload_callbacks.push(callback);\n",
" if (window._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" window._bokeh_is_loading--;\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"afb6a788-e7d2-4b2e-87c2-fe2d95e788aa\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'afb6a788-e7d2-4b2e-87c2-fe2d95e788aa' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" (function() {\n",
" var fn = function() {\n",
" var docs_json = 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BKMAw+/VUmS4ewMDD7UPPJ/s/0ENRAcbFEUBAm18tDB0ewJC4meAUly3ABPdO6RiSPMDIbcXqS0kywOTG7awkBzvAMEdIsXvrLsAQmPc509UjwMDA58pK5/E/QKs5eagJ/L+Qd5W/g/UcwBjOLgjgii7A6EruHPuIKMAglFhzZ6U0wMiWEDRMYCTAfJZJhRZ6MsCA1jTzvdojwJg+MRAxgCHAEGyP54AZF8Coi5CMweMpwEB+pa6TFQjAgF2iPvQH5T/IU/CNcegpQLAbetHZHRvA4KTqn4R5IMBMwIEHyFQ1wFRg09RT6zTAIO3TyZElMcAAMFMfUMPEvxDOCUmanidAPK+sn3JNPkBUQkJtEvE2QFgsL4kW7C5AQMCvcQoqGsA0ErdViGUywLAktlEDN0HAoEprnGsOKcAk2b0Pkwg4QF6GvA2FAUBAPKn8V9KPOkA4A0RlH4Q8QAhR1W6Z6ilAoPgZgzCWGECgXC49FyQIwPgAtRMWJyDAgBRTZLpB/7+kkQtnfJA2QLQDeLwBRztAVD+pqFNhMkCYziXj7X0lQPggRp9AUCRAEJCDfg7/E0AgLNmyB+ooQIA+yqB26wBAQNNO9NrZIkCYo3yG1Hw1QODvMXRivSxAsKgZPrOaGkAA4LK2Rz11vwDrWI+FcfI/HC13vFgOJEC84/KE1PQ0QNyhDqfHzDhAv/QL5GtuQkAveW9+zOxDQF691gCK1DxAnGVQ4TxALED6EUnYlHJGQNgbWeOEnBbAACBa8zr/uL/gB6uG7xRNQGhBrD3lx1VAEJ/tob0QV0DvWweEIq1TQCTP21+ITU1AoLhvQ5s+M0AAOtnwS2IMQCCg+6M1exVATKFdB3QaN0BQfpuII7lNQDjH6o6+jVNAjeYXs+YMVkDUPXDFntRNQKCTGF3Go0JAIIqC05jMFUCAj0vhD2ERwMDnNHbvTxFAfCYa4H8jNUCuUMLQmsJJQNy0eE4r9FFAJ8Qug9VfU0Bld60WGzNRQJIlyCfwIUZAeHk9LorcL0BABCJsieQeQOQ1kvzJzTBAByNad0+RR0D2zbYEMbpRQDhpBDMTGlRAABEzT63jUkAakPyUOfpPQNuQTeJY60NAcKSTyJ3GLUBQsb+xTokkQDD8SVHGbj5Afl3Ii0gnSUDKSm3Bw3dRQOgcc7YB81FAKIT9qrBZSUAfSy727UpBQPaRw5x5KDRAkKoLjDAyHUCIlNRE9D8bQMLV244/wT1A/jg20dxQSUBiXDABkKJNQLKn1Nnr4ktA4EIy+qeaQ0AIPhhbOz82QBCB2lf9OBNAMMmU188BAMCA8m1ArmchQIyVrrr92zJA7ApokV87SECdFzS0RGlOQL0ieJmCFE1AtzaeqRaJQUC0Jl5fj/YiQHgHVbQ2vhrARNogCsWgIsD4/LIl9qEWwLC49C8DazlAzFRnvpiGSUD+tvvNVVtPQKy05YtMNk1AGaNw9R3MQ0Ag5sJiKW4IQBQ3usI6hS/AknEuTO6LM8BArEVSyUjzP1IRAEB7+TVAI7GluW3ASECK+a+5Xa5OQLxY+95CC01A5CjwL6MkN0AAm/DKtx/Zv5zjjoTV4jDA2F0qO/SGEMC4ehFSm0gcwMwvVZEvEDNA5OH+9isoQkCfQbfB/UxJQLwERZUo6UFAHAWY23lRLUBoIcaOr/kpwDh8cb/LHRHAyA//aQbVEsBwgafzHlcAQEwlBivbNCpA+HucV0MGNkASApzU15czQNqxE5CwxzBA4NI1Vi9nEsBAxzG8BfAgwBDnGjnO0yHAALgTQ059FsDAwxhnXfIPQCTsqN9ojSZAdCsL6VyWJkDo+XhoqGciQADdsTxN+wBAANT2dDnADECg6u2N/oQHQABIBO55CPG/yHwyc3MBEsCAMXBWsfj0PzRYXGXiOStAyPPzbB2DLECIscbM+DMrQNgJOI98/SpAyPtu7czYLEB0FQ6d3fUxQCAvyLjv7CdAYAuSIErZCEAAP2DKnFAHQOA7VMi/tB1AapjS4wBQNUDY6JPBFLY7QIx6HgrvVDtAvBxesnlELEBoNl4jRRQrQDA4hgRoAitA8GrybGcrMUDwfQQr6ywqQAAoDgRb98W/cP1mMjroScBgQD+vQ8Q3QNQI9JpB8EJAAKa8zgbexT/gkYjIpCQNwH61FFqyb0RAAvt3TxJNSUByvbtlIkNGQDJzEGxldUBALDCihqHYO0Csrvkmmk03QKJefB76JkhAFJ3CKhNCOEAM9G8l9KI0QLStsWSJEzpAss612m/iSUBCLMIi3X1FQMLFydYyGEhAfENtJk7JQkAk2k1o+cY0QAjiJHjLASxAuJjHABOWM0CoShabKpojQGyKY7IktjJAgOtANnyiI0C4UWSdxVE1QACwYW1UGTpAcMrB6LLxMUDQzFnoKDwaQOjsc4B2EiNAAIFo3fyX2T/g7zXWe8cOQCAul568yg9AkM0ucEhQHECQPTO0OQMSQMSqwQ5yeDFARC9yJkjhMEAI7lTmzj80QBy2d/QSODZA/NwknmbSN0BOm3XTvMk1QNxWhyNwGT9AhDN2lOb5LEAmWs4dvesxQNwVC1Cosy1AaqOkPGTRMEBk873cs4Y5QAtH5yQGbUdAWuZB+DwsRUCaJFLST6lFQBoxOfMKMUFA0jwBjLXmM0AoCThbnsQZQAw63STcgCRA+hvmTUI3M0BZRV8jOqlBQNZG+KSPQklAtQfs7d3oR0BeB84k7fhDQJyRrQJhyzhAkJNRCCmDKkCAH1IKDzXSv3RzAfHK4zBAcFC5FF5/KkDIPNvDTr84QF4vuugBeUVAoTkxIlwuQUBYsxafuoc0QOA3yN07qiBACDl7akRuIUAwG5N6VO8JQIAlaOacHR5AIJLB4MaXCED8ulnjekAtQEjkyUEhSClAzJgLvv4mN0Ag7Qkcm4sgQIAFl6tu19e/gIwzlR1q6D+A8/OR3pUDQCA5mXp4jADATAXi6vU5I0DAj7zf88v8PwCgfG549Lw/wIalKewu6D+wluwn3QkIwODx3a+SRzzAdNFH5XhUJsA8Yai1uVgkwBCdL8jEvwRA0M0eQWNEE0DwjbGEztcjQMA9VWR0xR7AIEcaS+w2CsCEDpWFKaQ1wKylV7GxRDHAyIP4ai2xPsBUl1QVOJAxwBBIOgzF/BHA2Mt0gUC9IUDAMNxs1pr2v0BiRwf+SPC/lPGiK+XcMsCI3TdqJpUgwOzRQIm1/DfAxEc9AKL4NcAenPYnWK1CwND6qeoApTTA0DJt2QVoI8DoQtA5VnsxQJAzTibSrBVAoCjOkgxYGUAgaIaTjhIxwKi0VnyjuTLASsjbCmwAQsCQ/I+v4bg3wLhrJi0rGjfAQKEqNz+aF0Cg1I6Bt0oRQFQzHyKaLT1A4IOiS8aGCUAg44+at8wbwHhLfGRJZUHAYIH45nZwO8BUFcBUGH4zwBC6CCBbDCxAEDKTEJLMGkCARDYHmRj0P656tnCwtVDAMAjVJlRKKsAc5WGZRms0wBZWxGRqvkHAPtv+2m3dQsAgiZqEIVwKQLBburOOPhJAQJHMXFa5+L/Kdh9i4ztGwBYqa0nmHUjAIhfnsYExTsAk1i+NyNk5wJzIvjl9OzfAMFWfZs2iEMCsf/Iimzs7wJ7H2PWj70DAmrujrEr3SsD+3rb2RhhLwLGlziKp3FDANu5n+8nmRcDcR+Rs+Gs9wFgrda6kOSfArHTGKlv9OMBiv6z4zApHwI0INpcpE1DANg5fjCHnSsDCjdZ2EZlKwExZlBPQ4D/AJNX94v81QsA0PZx6jRlAwFNUv8YSLVDAVSHR/7t9UMD2eX6pPWBPwHptZQxQGELAjEUcQeTJPsBU6hPxtAsywBid95QAgzvAzl/KFBVtR8BFyRnY0hBTwBtx1EOdnlDA4s0ba1T/TMDMmzDh5aY3wCiM/0Tg8THAqH51QOUeLsC+8VOk/FdBwIJW5WnMLEzAmaNS7N+6UcDIqgmqt2RSwLanOs1NH0nAAjTWQKUeQcCgl/vOZ+o/wETrr44kND3AYMmiw3LgRcDwCZF2sv1OwJ0wqXbB6FHAg4NK8ZW5UMBadT0MQLtHwHjf78W0lUPA4LE6FlB+QsCe58qYxX1FwNzkOnO7hkrA5vtlsiSfSsCm+LHpUzBFwMIxN3URl0vANLITaTllScBkfYLEwuU9wERPN4d2ajzA/Bj63HvhP8CKsPUpdfBEwI6K0Cmjz0fAdFvHtYOZSMBcZsK4415FwBBUckFhvzzAKP59tk3/OcDYjTIxDIUywFCyX7zEniPAcK2cpvdTLsAI6YFmMYM/wIxIZUCmnDzAqmM6gQi5RMAA9cHRp0w/wERFudaR8DTAgOCrpPeG9D8AUMh8pO4SQGDq6XPpyRdACFzTzITEJMAo0asAsV00wAYVOMM/x0LAqP4OegHQNcBgWRFlAI8fwCwESrG29jFAPEPFgsiOMUCk2G/i6hM2QOB3mYg3bRFAQL/RiFDC9D8gZM0mgewlwCCCK5pMnSbAIDmQdN4lDkCEDwJoJgQ6QByO6fG5+jhAWNw4HegfO0DoJR9DOPwjQMDlDbfq8gJAAA++3sH6B8AoTYlLKHYvQNxsjhCVgDBAPNYTQR5kNECQsndp1i0ZQNDwWo++RBdAYFnUPl98BcDgS6fMwFQMQIACO4kCQAZAsPtDXrLdI0CQI3lV3EMrQHCFAKoYOS9AIG+oEhRXAsDw8M8VdlMnwFywtHiW+DvA/DNGwb47NMCAlZMImY8GwNAGAnga5ylAUDmFOecHFEDAwjz2QjIKwCgNi6bstSPA5DABmL/POMAs5TOHK7NCwMDHWw+l4TTAqDq6pFagJcDoLoGrrzBIQOgf+X5SVCxA4M97n/bfC0BQRjsmeMInQHgnKwrUnyLAuFmFqP5ERMCwRFHlVvI9wJDb/ghraSHAoCjp5DlzEkDgkgovt9MsQMzvMIS2GTBAYNTTEg2bI8Bgs8DLebAowDRXvcl4xzvAaDXzkxzZPcCaL0vuKLFAwBizlcwn9zPAoJSEWgQeCEB60zAqSIY5QPyMBBrL8jFAQEYQPN0WIMB2dwJAHEE/wDwaqUQSM0LADmx+0bEdOMAAFx/o564iwAC7cVzkqR/AMITfQaiuBEAgIQ/j/t4YwFgoX81L/xzA2KlqD/cuNcCaUPbcGBswwBDBZkCZxgfAECZ6nZN/H0AM+5wGj6ciQKCm3VtP9fk/oo5L8jGtMsA0C2imEcVCwNL7fWUGjUDAmO9GUMC1IsCAtORSn08yQChGlTXS0EJAhKYjc8U7M0Ag9HwtshEVQEDOwbaDEh/ATA6mH3JmO8Asmgsqu1FBwKgH9E2O4THAQOYgKtQZG0Dk0LpIeak7QHAOOpTKBThAEDfnrpMmKkDAqTtCznoZwODZLgNIERjAIFiZBFV3EsDYSMHSRbojQDDn25Xw8BVAsLDUipwKIcAkryml3sUzwEzOWM0C1zbAsPzIA+gjIsDAwJ9Tb4EKwOTAWvRVCDBA4IOZva+OOEDIqmMgvrY3QLBjUlZX3xtAuAqMaF5/NcDcQwnEmIVHwOxNmMVDYEbAqIz4x+JUO8AAcAwLKWTwPxxp/pO/dDlA5HGZ8wUTOEAYGUmqR3wuQKAfnnD/owHAcLv8z8xxMsAEAS/EeJs1wMxQ9e5I3DnAxCp2l3Y2McBYERxfmU8twCATmjDVMxnAABLx7hvv3L+g6VoWF+0bwIChNiI+KOy/wMO8NdPtEUAAUBYOllcAwOD96vH39wzAAK9Wr2fqMsAoYPVbAVVAwI5Ca5oe3EHACC3Ess6VNMDAUHkR2OsJwID8gzudxgzAEPYRi2a2IECgzHQXmggZQGDvrcANFQJAxGRawGgiMMBaZDR1HMxBwHjA3XyDpEfAYMfVWZrJO8Bgjw33qFsOwADHXNfjJyRAAHfJNLaqAUAAhY3bobLnP5DE7K1M7hHA8Gakzf6RMMAAYUPBqlw2wAg3eSeMNjPA/GPHvCUyMMAQjUnVgiETwGBghin0/QRAsKSXN5kvIkBgrPi7vNIhwNhB4HD4IinA6BqkwhGCIcAAmAn/kfD1PzDk3Q9ucx9AUECs0+EhL0AAjYZsHtEIQMjSsmNdRyBASLcZbKFVMEAgpBy8p+YWQGDk33b8dzDAcKLQsuxkIMCAxeDm6b4qQLD/H0OVLztADrfDuEZ9QkDMmU7lQTRFQMC/DBv+ZkZAGOtNcNGNVEDUW7DL3xYwQMj8ZaDh7CDA0P0FgBR0KkDA943F6KlBQJIUcZ97F0RAFEwC0joOT0ANJr+bOmVSQKpMseXAbVFAcrdi7Ud6R0BwD+BC0vgtQKDmrNsCqyrAgNtR1UJk879As6NUGssxQIYir7A4EkZASNccS72kTED2n5X50XZPQKLlzq6pBk5AvG2YhWElQUB4eC8/ohIrQMBciklLFQlAQOZrS57LLkBQUdA1K188QKCdKgIIR0JAwN/ybB4NQ0DkF/LfgQxJQDmLwSV+Q0pACHSK//VpQkDueMsYS1wzQCDhOrbyuTJAXkmUoF2/M0AUhtuDimA3QJzU/9fyszhABEZ2CGnaMUBYekjobxg3QJbKe3qPN0FA9uTKL20mQkAw+wpe+cFAQHbIo3KfXzVA6LvUlLhjM0B2iI3UNwwwQL4aZWeV0DNAQFpiKmhOLUBs6DyKQIorQHynC5uErjpA8U3KSi3MQEDAaEt+dCVEQHLBry/+CEJAMmwGPIHCNkAcafp0nYo0QDb5B0mEtjlACtX3WfysNkDYR38wWnwpQKIlv3JH9z1A7P+/vsM5QEAFWQIr7atBQA9BwOEP/kJAKYh6Aw6jQEDOQl2HtEEwQBIizMbQVzFADPP8xODhKkAsvdHsT683QJIRSXJ4yDRAarntl8xEQEBEh4AApFBDQLzVCRzUNz9AVPhAlNrvMkBkfzwiZvcqQLiLdzMyqipABN6kNukfL0CguyQzFrMoQGzKWM4BCTBAjKtPzH+wPUD0IaitcBpCQFANFHw7LTtAgDyOFtAhFEAAmPJFZ92wPxDS4g9RLRfAAIXT/Z/O2r8AAJsuya0XQGpyF94USjNAtM8R+XJjREA+1WXI+LNAQLAJGYjAbTRA8DqTMrgnAUBISIb0FfcxwEyhYKiPxDTAAK6R2CYd1L9MAlPPg8cuQOOKGbAhNkFAe5z9yLt7QUC2oziVVgw8QED5dIbrlO8/wMlNa/jUI8CchIvKm4gwwECrhXBa5RLAQIL8RqYVJEB4v9vU8PI+QBnSJc6yZEBAsE20jZOsOEAID8tuWL4SQLDv8zz5+SrA0JNv4pp/HsAMg5gXRkUiQAQqnKMVlDhA2CPJbuJoM0AM5yHWkOI0QKD3OJOT2SRAQAggoIeG67+cYCUW4tAtwDAQjEbAsA7AxPArDFdqIUAECZscs987QJZEEzCqR0FADnXNLm4UOUDQpwiwoZsCwLjp8DrDJTfAAJ4b6q8aNMDUOJt/dfchwLwZm79LGiZArGhzbKDwMUDK4hB8o/c7QMjLNUTNWTlAysaWdmitNkAwDP5Z3cscwCy4xCTeHjbAhHHSFbKzN8A4tVGaE38vwAKAuRzZFEzAqL/27YWAOkAG5BFWqddEQFCoMyr99RBAQGRvom7O87/kX2S3/6gzQMiANAXvJyJAcElHRYo6E8DglZWOJ90NwAjXnozh3ipAxBCEUrfZM0AEtAK9CHk8QFgbwIuyMCJAEKYi5UnXEUAoXT4/miklQM6jiiPMzUBAGuDUtDFbQkBUm2tFsDQ8QNARUV19eiRA4Jyr39cLFcDwzcSNp3oXwNC/pFArVxDAwAvQ616f9L8QkRcEohs0QKgE7MlnIEVAyssYWq4rRkCU+VPb/2dBQLiqwvjBEidAfMJMnQEkM8D03B/JdQtCwECmZjR/jTzAUCHmU2uQIMDQZLq10H8ZQFjrsmfq7ThAyrM/y1HqQ0Co++DGx6A9QID7rQ5UuyVAlAgmInoBNsCo6wfHRPdDwCarY1VJXELAcCaewO/XK8AQjiQnCTw0QKC7nCDwbUFAADe8SQkyPUBMIMChzIAxQJAyWUOx6RxAAEdRpD+pMMD0pIPlDpw4wGC62nBVeyzAIAGL2SfoAkDASa7NeBY1QMwpd6N8XkBAfETqYPGOMUAAeU1vcEEYQIDBTcTeY+g/AOe6jKGj2D/A/zyav0T3v5D7HG9gDRNAoMzR0eCWG0Bgwr8pXFAkQACSVQXorBhAUFArOGFqEsBAcoXjUvX0P0A+4ctH7RTAIFZ6gu0ADEDAZ0AdsYQOQLB7vXHpKh5AACOgARHL9z9AIhcZPrYEwDiRhULlbi/AQO0YDS60MMAwRNNjOKgmwCB2nchVtQTAUIm1b6Y1JsAglrym8hYWwAARNnPpKRRAgDpyOhCD9z8oZsaLnw0hwAjfRALTMDPANGYwNnlUOsAMniRosq0ywLjlpE+Y/iDAgPqAeKanDsCAAsho34ftP9B91tENKh1AgCUaRZ3x9D+os+0xFKMlwNzc+l5f9TfAjH951XZfOcAk2GDhePU1wOgrVAFCGCDAAJN9ABhN4r+QHaAkhE4oQCAp2XN4mwNAAGSxP9RHGsBMfNBJSxw0wEiu3UhO6jLA5D78sszwMsCAbUHXHuT6v0ACZ2hBSAHAwNrcLKyJ8b8QijJUIHQcwMCYcwf0bCLAzF6BWsxHMsBQjUI4CtUwwFwdrM/hwzbA0KA7ebaeHMCA4AZ46icRwEDCxZplA/W/AJXSGZ8iCsBY8Za9RhIrwETQLDuesjTAvIv9ZfhGOcDEvNf3zWo7wDB7WvFayCvA0Ne/UmBxFcAgXnM5KqEJQNBiv6QkIyhAoCW0h1UCA0B4QbnDKKMxwAwIEezvgTjAXro6IkPRQMBQ2rqhhsk2wOCl9BTsfhvAEBRxY1ULHUA=\",\"dtype\":\"float64\",\"shape\":[1024]}}},\"id\":\"9fd3f92e-091f-4366-b940-313096d46c51\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"19c2461c-403f-43a2-b407-e6cdfc92141f\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b0ab76b0-fd7e-43ba-9a09-fd71445f433b\",\"type\":\"BasicTicker\"}},\"id\":\"030df609-b72a-4195-bcbc-3bb21a304242\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"bbbd16e3-2e39-4a5c-8329-d8b2063f6b6a\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"formatter\":{\"id\":\"ec855c38-07c0-4826-bf9e-756beb81fb47\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"19c2461c-403f-43a2-b407-e6cdfc92141f\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"4c54cc19-2b05-49f4-ad14-511f8265cf31\",\"type\":\"BasicTicker\"}},\"id\":\"98661567-ff4c-45b3-97e0-3aa7d62f8ddd\",\"type\":\"LinearAxis\"},{\"attributes\":{\"overlay\":{\"id\":\"11ab30a3-efbe-4eb4-83ba-a2be38514c58\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"19c2461c-403f-43a2-b407-e6cdfc92141f\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\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" var render_items = [{\"docid\":\"906e3bc1-639c-4c32-b338-feea3a754e2b\",\"elementid\":\"afb6a788-e7d2-4b2e-87c2-fe2d95e788aa\",\"modelid\":\"19c2461c-403f-43a2-b407-e6cdfc92141f\"}];\n",
" \n",
" Bokeh.embed.embed_items(docs_json, render_items);\n",
" };\n",
" if (document.readyState != \"loading\") fn();\n",
" else document.addEventListener(\"DOMContentLoaded\", fn);\n",
" })();\n",
" },\n",
" function(Bokeh) {\n",
" }\n",
" ];\n",
" \n",
" function run_inline_js() {\n",
" \n",
" if ((window.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i](window.Bokeh);\n",
" }if (force === true) {\n",
" display_loaded();\n",
" }} else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!window._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" window._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(\"afb6a788-e7d2-4b2e-87c2-fe2d95e788aa\")).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
" \n",
" }\n",
" \n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }(this));\n",
"</script>"
]
},
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"text": [
"[ 14150149.16729155]\n",
"[ 467790.04443476]\n",
"[ 566534.80823698]\n",
"[ 8012476.7354157]\n",
"[ 752190.89311072]\n",
"[ 1711471.16805952]\n"
]
}
],
"source": [
"def find_real_peak(series):\n",
" p = np.argmax(series)\n",
" \n",
" min_idx = p - 3\n",
" \n",
" if (min_idx < 0):\n",
" min_idx = 0\n",
" \n",
" max_idx = p + 3\n",
" \n",
" if (max_idx >= len(series)):\n",
" max_idx = len(series) - 1\n",
" \n",
" fit = np.polyfit(range(min_idx, max_idx+1), series[min_idx:max_idx+1], 2)\n",
" \n",
" peak = fit[1] / -fit[0] / 2\n",
"\n",
" return fit[1] / -fit[0] / 2\n",
"\n",
"\n",
"\n",
"# For now, we just want to figure the parameters that existing autotune\n",
"# uses, but in a more accurate and more robust way. In the future we'll\n",
"# do much fancier things.\n",
"\n",
"# So, for each of the three axes, let's perform fourier analysis in order to\n",
"# correlate the differentiated, filtered gyros vs. the actuator command.\n",
"# This will tell us the delay, or tau. From \n",
"\n",
"def compute_axis(desired_series, diff_gyro_series, filter_order=3,\n",
" percentile_cutoff=2, plot_tau=True, series_cutoff=2,\n",
" axis_name=\"\"):\n",
" desired_fft = fftpack.fft(desired_series)\n",
" diff_fft = fftpack.fft(diff_gyro_series)\n",
"\n",
" desired_fft_r = -desired_fft.conjugate()\n",
"\n",
" correl = fftpack.ifft(desired_fft_r * diff_fft) \n",
"\n",
" tau_offset = find_real_peak(np.abs(correl[0:len(correl)/series_cutoff]))\n",
" \n",
" if plot_tau:\n",
" p = figure(title=\"%s delay time vs. correlation\"%(axis_name), y_axis_type = \"log\")\n",
" p.line(np.linspace(0,len(correl) / 2 * time_step, len(correl) / 2), np.abs(correl[0:len(correl)/2]))\n",
" tauspan = Span(location=tau_offset * time_step, dimension='height', line_color='red', line_width=1)\n",
" #bogospan = Span(location=.0168, dimension='height', line_color='green', line_width=1)\n",
" #p.renderers.extend([bogospan])\n",
" p.renderers.extend([tauspan])\n",
" show(p)\n",
"\n",
" # half cycles per sample.e\n",
" filter_edge = filter_order / tau_offset / 3.14159 / 1.22\n",
"\n",
" # A nth order filter doesn't result in n* the delay with bessel\n",
" # design technique. 1.22 is a fudge factor for order 3. Not sure where\n",
" # 1.22 comes from :D\n",
" db, da = signal.iirfilter(filter_order, [filter_edge], btype='lowpass', ftype='bessel')\n",
"\n",
" #w, gd = signal.group_delay((db, da))\n",
" #p = figure()\n",
" #p.line(w, gd)\n",
" #show(p)\n",
" \n",
" desired_series = pandas.concat([desired_series, desired_series], ignore_index = True)\n",
" \n",
" delayedact = signal.lfilter(db, da, desired_series)\n",
" \n",
" delayedact = delayedact[len(delayedact)/2:]\n",
" \n",
" # Now compare the response magnitude of the filtered waveform vs. the\n",
" # differentiated gyro series, to compute beta and then the bias.\n",
" span_desired = np.percentile(delayedact, [percentile_cutoff, 100-percentile_cutoff])\n",
"\n",
" span_gyrodiff = np.percentile(diff_gyro_series, [percentile_cutoff, 100-percentile_cutoff])\n",
"\n",
" lin_gain = (span_gyrodiff[1]-span_gyrodiff[0]) / (span_desired[1]-span_desired[0])\n",
" \n",
" bias = delayedact.mean() * lin_gain - diff_gyro_series.mean()\n",
"\n",
" return (tau_offset, lin_gain, bias, delayedact * lin_gain - bias)\n",
" \n",
"def compute_axis_by_name(series_name, do_plots=True, series_cutoff=2):\n",
" desired = df['desired'+series_name]\n",
" deriv_filtered = df['derivfiltered'+series_name]\n",
" \n",
" tau_offset, lin_gain, bias, adjact = compute_axis(desired, deriv_filtered, plot_tau=do_plots,\n",
" series_cutoff=series_cutoff,\n",
" axis_name=series_name)\n",
" \n",
" df['adjdesired' + series_name] = pandas.Series(adjact)\n",
" \n",
" print \"Axis %s: tau=%.1f samples (%0.2f ms / %0.3f)\"%(series_name, tau_offset, tau_offset*time_step*1000, math.log(tau_offset*time_step))\n",
" print \"\\tgain=%0.1f (beta=%0.3f), bias=%0.1f\"%(lin_gain, math.log(lin_gain / time_step), bias)\n",
" \n",
" if (do_plots):\n",
" p = figure(title=\"%s shifted to line up\"%(series_name))\n",
" \n",
" p.line(df.time, deriv_filtered)\n",
" p.line(df.time, adjact, color=\"green\")\n",
"\n",
" show(p)\n",
" \n",
" p = figure(title=\"residual %s\"%(series_name))\n",
" \n",
" p.line(df.time, deriv_filtered - adjact)\n",
" show(p)\n",
"\n",
"compute_axis_by_name(\"X\", series_cutoff=5)\n",
"compute_axis_by_name(\"Y\", series_cutoff=5)\n",
"compute_axis_by_name(\"Z\", series_cutoff=5)\n",
"\n",
"print np.correlate(df.derivfilteredX, df.derivfilteredX)\n",
"print np.correlate(df.derivfilteredX, df.derivfilteredY)\n",
"print np.correlate(df.derivfilteredX, df.derivfilteredZ)\n",
"print np.correlate(df.derivfilteredY, df.derivfilteredY)\n",
"print np.correlate(df.derivfilteredY, df.derivfilteredZ)\n",
"print np.correlate(df.derivfilteredZ, df.derivfilteredZ)"
]
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