https://github.com/thompsar/Venison
Revision e9dc3e5319061e2d03f81dcdc28e7c2a32245f2f authored by Andrew Thompson on 12 May 2020, 20:42:22 UTC, committed by Andrew Thompson on 12 May 2020, 20:42:22 UTC
0 parent
Tip revision: e9dc3e5319061e2d03f81dcdc28e7c2a32245f2f authored by Andrew Thompson on 12 May 2020, 20:42:22 UTC
Initial commit
Initial commit
Tip revision: e9dc3e5
Venison-checkpoint.old
{
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{
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"metadata": {},
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{
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" <span id=\"1001\">Loading BokehJS ...</span>\n",
" </div>"
]
},
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"\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",
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" element.onerror = on_error;\n",
" element.rel = \"stylesheet\";\n",
" element.type = \"text/css\";\n",
" element.href = url;\n",
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
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" var element = document.createElement('script');\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.src = url;\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
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" }\n",
" };var element = document.getElementById(\"1001\");\n",
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" return false;\n",
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" console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
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" } else {\n",
" load_libs(css_urls, js_urls, function() {\n",
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
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" });\n",
" }\n",
"}(window));"
],
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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 var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"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.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };var element = document.getElementById(\"1001\");\n if (element == null) {\n console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n return false;\n }\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"from scipy import optimize\n",
"\n",
"\n",
"from ipywidgets import VBox,HBox, interact, interactive, fixed, interact_manual, FloatSlider, IntSlider\n",
"import ipywidgets as widgets\n",
"\n",
"from bokeh.io import push_notebook, show, output_notebook\n",
"from bokeh.plotting import figure\n",
"from bokeh.layouts import column, row\n",
"\n",
"from src.spectrum import spectrum\n",
"from src.spec_plot import spec_plot\n",
"from src.mycolors import mycolors\n",
"\n",
"output_notebook()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path=\"/Users/andrew/Documents/Thomas Lab Files/EPR/161130_Ruff Reanalysis/D2O/UnPhosAMPPNP/unphosAMPPNP_2dDEER.DSC\"\n",
"spec=spectrum(path)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
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\",\"dtype\":\"float64\",\"shape\":[754]},\"y\":{\"__ndarray__\":\"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Y2T+mlp83l+rZPzjBLsNv4dk/P0aSlCz12T8ALNW2uq/ZP0aEBX37ydk/eVnC8vLC2T+CK1t8AeDZPzudWdbK49k/7lsD5qy92T8xjvvGtczZPz77j+lQ8dk/q4HY2+Sz2T/TsLCaiMXZPwIRjweOy9k/hZPHDB6h2T8pUYdQ383ZP98G4eTHwtk/GV7A1avH2T+VnGvQvbTZP5ZESwULxdk/OSS5pja02T8MYn+zf7nZP1knCbS4udk/qXj0xLjA2T/D3hUsOLnZP8vj+b3Pltk/AmnpVlee2T87+29WS6nZP3LW+bidsNk/Su7Y34aO2T92sHpdL4XZP3L5Lqb3jNk/vhl4uaul2T9QdmhxlJjZP1IS9TIKldk/n7abgtiq2T8qHMFgHYzZP/nfADw1k9k/C1lYAPmb2T9wChWsjprZP0zP3+AZmtk/RcuSNomW2T/jZnmMVILZP6fynf8+odk/Q/hFezyi2T9KLgnoXLPZPws2Dn0frtk/d0X4I/dy2T+WbVG5m6XZPzrLNjorfNk/8PUZ/lGK2T+CrCMKTY/ZP1g0lR2fhtk/J482sl6M2T/grOx+TILZP2SjZuapi9k/jOgGWDqZ2T/vajCmGHHZP0FpJvQzhtk/uGI2m22I2T+kB3tyJn3ZP/ak773xodk/sEvQ3c9x2T+6/iBO26XZPzg3FtdThdk/GUYkiPZ62T8FVY4194rZPxb9oR/lgdk/ebCqSEyN2T/YxgerP37ZP4v4tOh3gdk/Q3scKGeF2T9ld+sWUKXZP44vIu7cjtk/ECam7jNz2T9NJzow42zZP9dlKLf3bNk/ObCM2uiR2T8yfoJ8JnbZP/QaLwSwgdk/ni+f/vWE2T9EB7yWIGXZP5Siax6FZdk/DbbdV5Bs2T81XXHF4HLZP08rv3lIZNk/5OagmZ982T+KUGdqG5DZP1hmre42c9k/uwVAoaB02T+tq0Gyg3DZP3HHuONnf9k/LnSU9nt22T8tovO4tW3ZPxRJVCIjZ9k/N6KDegyG2T9tgAXYtoXZP7tpS1U5fNk/Aj2ypA122T84zmL6e3LZP2UMnaIQkdk/zT5Cb/eG2T+lgF+/ymrZPz1pKs4PfNk/4zsSxXKD2T/iEwuD2njZP33lbd/nbNk/pug4GEF52T97v35VKHHZP0Hqlc7vZdk/kbpquMNc2T//Gi0PFnvZP2SWCQRUa9k/wvEUa11p2T82JPcEKY3ZP7YSGUDbRtk/IeVhzo1P2T9e+SO5yW3ZP2SRYdsUYNk/otQfL6802T9badXUq3PZP6F9a55OaNk/WuzfRs9U2T9yIfclEWPZP3WwHGw3ZNk/E64aK6SG2T8TcIW6NWPZP1a6y08TXtk/XXDV+PdV2T8HzvVhKmvZPzC2B2TfYNk/Uu9SfVZr2T+rnWwXoGLZP9v9zWM0W9k/Mj7AvV8y2T9TRoQuKEXZP3rVMXKVW9k/MxFlq4Zi2T/u+RBroljZPyUSYFP7Wdk/G2zp5bZT2T/gSoy6MjzZP3bY+YHQS9k//hGoapc82T80LMavUD3ZP9R93vW9VNk/vzf2pmRK2T9ct8CjfUPZP/ND9vXBLdk/zDQ2O4ku2T9605baLVrZPyzpA1LSLNk/nVwKaeYU2T8mguknICzZP7QvLkxoKtk/yELAlbI92T8ApQ15hhvZP0/bTipEONk/mqTKWWW12D99LJ4oM6zYP6Nr6vP9wtg/DyqJRrrD2D/w1yqLjNrYP/rJWbosq9g/IL+DHZun2D8fovXKeKzYP0eH1U2/xtg/lfB2nYW12D+ZTIBis6LYP+s0mWdiqtg/GXvCTSTB2D/4YiYgH6PYP0JImDmmrdg/7LZbDBWm2D9g5KXVuH7YP400PjxymNg/TX3QPPuu2D9/Lp1wsLPYP5seWySQjtg/ixx3QQiV2D+PgEpWzKjYP9gPmoiRb9g/hqGy21+M2D/m1srezZjYP4dKBAodpdg/+qlBtsGY2D+LOCVRq6bYP6HJ+rRgo9g/UxTBU21q2D8kM152LHPYP8vWXxtmadg/ElZZ78eD2D8Ja5JuZZHYPwE5ToyMktg/dqbIXQaQ2D/G60tlr3HYP6KljVKtodg/2E9sn29z2D8iADw2FnrYP1F3IIp/htg/XfngOZh72D/8EmmbxnHYP9EYYWXefNg/pgOg+FFx2D8cupZzv4LYPyzVOgSMcNg/PWNloj162D9G5Qr9uHjYPwsakfZ3cNg/FGTQmLNw2D/X86Iddk7YP9Nv4TBGS9g/fTBS+ShQ2D9H39GrkHjYP8Jel4rxTtg/4mCKNINd2D9MDtkRdWXYP7T4wkhuRNg/MWjlkxdp2D8yr/pqnHnYPwhvQIA9UNg/5YodNyE92D+tw4ZrPU3YP4MJoGbJUNg/QwgQ//VM2D//To4hgkrYP1guTpPzJdg/WzMREdAn2D9dkIYQUDjYP6xBe2sSQtg/OV+hlllO2D97yrVGIiLYPwUKFsemKtg/vI+pxuYk2D9X/gQfvDjYP5AFOjyFLtg/R8otWTMk2D9XwlOhLSbYP/uk42mwMNg/TM9UhyUs2D9OrTlhYRzYPySn800hJdg/SNGVB3EC2D/yq6v+fzbYP8jRrPWgJ9g/lZZoYyIS2D/iqewJjw7YP0VLThlZD9g/J6DL4hcP2D9cGxwQiwvYP3vNrUF6Gtg/KXF9Bv0B2D8ScMDcKhLYP+WtCckCCtg/RbQm5Mfz1z+NCgstNwHYPwfF1Qug/tc/Xv+d6wQC2D8XUgvRUg3YP8O1AsDZC9g/HLvfweX71z+qbZhJdAfYP9pYF7M6F9g/DmEqLkEH2D8v2jLIFgTYP6hTW6U51Nc/pL3iRlUG2D9scf8kdgPYP+/Zy/46+dc/56CiTbMO2D93PioKXPjXP4xQzTnF9dc/HcslyDHo1z/9J6s/eefXPxhorxZey9c/PSMhhZ3X1z/Wx6+IPOTXP8/+Q3HSydc/pB0mFS7s1z9gQiVh4NPXPx+JBzSC19c/fLCT94Tl1z+Kv8m/3MjXP6RCP/Vn2dc/apWwpDnD1z/BqSFw7c7XP8kEyvdOz9c/DhweODPZ1z9B9Goekc7XPyFyZf0z19c/9FMuw4q51z+h5xVzudXXP9QL9izcw9c/62J3THjW1z9eKP1SJbLXP/a/9O9Xu9c/grGp5D681z89SZfIx7vXP/S7O+H5xdc/ioir1A2w1z+7L1x8PZzXPxh/bKJJwtc/gmYqGfKq1z9oIrxNRcbXP2g6H5iZw9c/fRedZZPK1z+4bqFEDqHXP0yDAJMIoNc/5IMu7KGu1z95sto27qDXP+Rwc8qMvNc/Zj2kC3qJ1z+SmjWkc73XP3OfCJoXrtc/obeokaCq1z/1tl/zwbzXPzPqRYofhtc/WwKw122V1z9ArSsbDZvXP86cO9+Sv9c/j1ANffm91z/FdL8wQZPXPx81umg+eNc/HpCOETmi1z+0ZUqmanvXP0qFTBDarNc/w4hU1reJ1z9bvX7zyJXXP7Vj2ToCndc/fDndee6r1z9zXE7g+HHXP5juW6mvfNc/uEUuyCNz1z9l0O7Ey3HXP8PTVoGTjdc/ruMI/ASD1z/xoo9lqIfXP/JtuR3Phdc/Xd83TrmO1z8tjhKZ8nXXP7R9mFo/Z9c/P+3om2uN1z/yEYJSxn/XP3UZvlLZWNc/xK8d5NiJ1z+90LVUiXXXP9cs0MUCZ9c/RiRiHwxl1z9+R/Yx4nfXP78suVqZfdc/YDl8T4BX1z+2iBcJ01vXP9KGNk9pftc/ZmE2XMRc1z+fh1rfAGzXP8LjgTJCg9c/R9B3gyh41z/Mt5Hm1mPXP29CVNgYadc/mUBDIzps1z+uojI1xlfXPytpA1KyY9c/nIEQ0jRQ1z/fg3bjjWLXP62a+psgUNc/DUr7m5Nx1z/XPJPsv2DXP3DeywMPVNc/E+oSZoxK1z+promCeWHXP+lgrUqpYNc/CpjFVqpl1z+EnTTv9kXXP/SV0Ld+UNc/v5gb11B51z+PMF6ENTvXPz+4QdsiONc/ir0FfSs41z/vpct9ED7XP9tXWKGfQdc/JmYuYK9N1z94GxZO5i/XP8fWEZ+uQNc/GjRcocEl1z+hq1DgYEXXP+X10PlUI9c/4rey6jko1z95tnlxZDPXP9ZYcIPzHtc/KxtiXw431z84p/U/NDXXP6GLONz1Mtc/f/mOw1Qu1z+rHKLrNVXXP+Ar1LkBFNc/9egFvpcK1z//LfsojCDXP2JAsDjFN9c/mPi2FN0B1z/GCnbtFzrXP0BFwYxbAdc/tbQAIjwj1z9n2bgHEALXP9fxbNQCH9c/kavOkd/91j8zCn4+uRjXPyy4uc2DC9c/2fwfSI8R1z8dDqPBPBfXPxtoJKBAJdc/iwgYgB781j8VetksswDXP9D4JZJw+NY/Rhx0YpQA1z9hDwUjNQLXP0szm12z4tY/eELvsx7w1j9wJdycKxPXP8IiJ+510NY/BY73gC7m1j/5MF+IsQrXP05zLxafDdc/V1lObsL01j83quj8I9zWPyj+S+/099Y/V7xVcvrU1j/PNdaB9+DWP1cKmXOm4NY/jhwXlcjd1j84F55D0vPWP9uTKc9c1NY/645cqC7g1j9L38/wSOLWP34+ptMRy9Y/wCp493bf1j+pZtkGO7nWPxgfaTTO3NY/qjBs11rd1j9xBUd4T/PWP6f41TP+1tY/HZcgCZ/b1j8vHauDueHWP+xyj2kS4tY/srt8Am231j9fZq62D5jWPz5Sgbs6zNY/NuYm8zq81j99OAnS08TWP9sRHs8xydY/rBsc3fvO1j8qCGn8L6TWP7Mnq7krtdY/se0R9HWx1j98IbqP967WP1mU7GSOs9Y/TFJmVkW+1j9ZjfL/X7bWP8VCVQkWiNY/y1/0F9ye1j98DL2JCovWP9y0wyRPr9Y/OARMLWSR1j/fpjnKJaDWP2HPZ1IFkNY/CAFqeUmE1j8wk/CIlabWP9fxQym5j9Y/yt64Ahm91j/heEhR+4nWP7O7ofADidY/djxNdHiY1j+mcxZWi5HWP8QsCneamdY/7cQ94DuC1j/Z3mnYKrHWP2idCAs3g9Y/dtKkvqGK1j9s0wnWSW3WP+zTVIlykNY/PCZpOGqQ1j8jRplY/GXWP0wQsEyHqdY/3Lq52RyF1j9LNL+9QorWP0VkvfG/eNY/8RORD4R/1j9EwKWiMorWP7O0c8bcjdY/dr4uSKSA1j/O2KpepXPWP7rva9TEd9Y/KfE46cx61j/KamjJ6VzWP+1uRSV5YdY/PhTI3epq1j/qfthgGVPWP0S5BPGTXNY/n007/r5L1j8224mW427WP3imiGH1WNY/ODtl2spY1j9mac2EQFHWPzdJU+UJbtY/gJCjZNFf1j8iDXKMtmrWP0MIXPq3T9Y/G0sA2npN1j8HnNc1wWLWP+WcjWzxV9Y/RKo2o9Vd1j9HNoMdHVPWP6SYXr1VK9Y/XQIGTwA71j8WjhchBU/WP2KWn/hsSdY/5unhU7xN1j8ppt4LFzvWPxpqxRPvQ9Y/qiwik8Fc1j97GhSg8C/WP1q3n/MOMdY/dVvEFAwu1j8tyMGSBlfWP8a8PofQMNY/ToqpIlkS1j9+UnZ+VDjWPyYH9p4zQNY/4KCy3xw/1j+Vu1/1DiHWPxm/s18zWNY/wqgVRics1j85/jKMahHWP5FDdFtFJNY/lQR+rQoU1j+xQmrMFunVP319sxk3FNY/55bnUm8K1j8qnmPWFgnWP0AvOTrMBdY/7hwW0Sv21T80IzuwAOPVP9XtgJ6K99U/5b2VC/MT1j/1OxyyYBDWPxEHeCqO7tU/I6FEVq0A1j+TdfDc8hbWP5pAhARNANY/t/3hGSQJ1j9TMKGK6hvWP5ASEqEt/tU/sb6kBQvw1T+SQ2WE4/fVP+jnE3gR4tU/5xH0rwPH1T89xmoIV/zVP4vwGYS+0NU/mq19aAvW1T9+r7wTbdTVP2KdAmlC1tU/+7gjfZbe1T83C6pf0czVP+CsqOKxxdU/uSuBH5LI1T+xhDAu7L3VP7GuOpLdxdU/WxLjZs7P1T+jAM8nTuLVP+y3orwcwdU/VQtq/OzV1T9N19PdJOXVP5sVQisC09U/AxS3bnjN1T+0Qd9iS9nVP7GO7sh5tdU/7cAD9LnB1T/No1cThJzVP1Af3w5ehNU/e9WFSwmj1T/W7d8QOKzVPxLqtpMoidU/wkv6eux+1T8NHuv2dHrVP4OtZ35XgNU/XdcX69yL1T8ncYUB2H7VPyS42DZPaNU/sZrUc/d71T86ojbGLYLVP6HKZlP/j9U/ZeSg3nO+1T+5H9+RJMDVP0lwv3KQydU/bkJBYS231T+mCpOB+b7VP5iigZkG1NU/8if08Wyf1T8cixePHqPVP1zvQLEaptU/7KlBKmZ51T8ynJKhRTvVP2odho8UI9U/lwObLo4A1T+Orhwh89PUP9ntgyGrstQ/3ctz+GzZ1D8zpytB6srUPzpFeezq9dQ/ymc9p3cy1T87AujdFUnVP/axKLTbhdU/ToU2QMiY1T8zyIU2f6XVPwHHlkym1dU/HhUCdV/m1T9JunOR3QLWP4fM1GjIAtY/akZ7ativ1T+NlpilusLVP44OeUL+iNU/rEWWqZAX1T+QdRCqSs/UP+n0U0qCddQ/1HaD5A8O1D8ijy1V4rbTPxFLftIcl9M/TH0QHs6w0z9Gwq1mQKLTP+ccpAS8x9M/X6rEtrUA1D9/RQzkMEvUPw5Jc+86jdQ/OJ1fM4cC1T+Mh1KSHEDVPxixXecrf9U//fpU7H1q1D8=\",\"dtype\":\"float64\",\"shape\":[754]}},\"selected\":{\"id\":\"1420\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1419\",\"type\":\"UnionRenderers\"}},\"id\":\"1372\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1330\",\"type\":\"ColumnDataSource\"}},\"id\":\"1334\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1303\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_color\":\"#5e81b5\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1368\",\"type\":\"Line\"},{\"attributes\":{\"line_color\":\"#e19c24\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1373\",\"type\":\"Line\"},{\"attributes\":{\"grid_line_color\":null,\"ticker\":{\"id\":\"1303\",\"type\":\"BasicTicker\"}},\"id\":\"1306\",\"type\":\"Grid\"},{\"attributes\":{\"dimension\":1,\"grid_line_alpha\":0.5,\"grid_line_dash\":[6,4],\"ticker\":{\"id\":\"1350\",\"type\":\"BasicTicker\"}},\"id\":\"1353\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1317\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1298\",\"type\":\"LinearScale\"},{\"attributes\":{\"text\":\"\"},\"id\":\"1401\",\"type\":\"Title\"},{\"attributes\":{\"callback\":null},\"id\":\"1294\",\"type\":\"DataRange1d\"},{\"attributes\":{\"formatter\":{\"id\":\"1408\",\"type\":\"BasicTickFormatter\"},\"major_label_text_font_size\":{\"value\":\"16pt\"},\"ticker\":{\"id\":\"1350\",\"type\":\"BasicTicker\"}},\"id\":\"1349\",\"type\":\"LinearAxis\"},{\"attributes\":{\"source\":{\"id\":\"1372\",\"type\":\"ColumnDataSource\"}},\"id\":\"1376\",\"type\":\"CDSView\"}],\"root_ids\":[\"1377\"]},\"title\":\"Bokeh Application\",\"version\":\"1.4.0\"}};\n",
" var render_items = [{\"docid\":\"7dab86ce-3a5c-4bd2-9375-7179d62bf77e\",\"notebook_comms_target\":\"1422\",\"roots\":{\"1377\":\"06c86f32-dbe7-451d-8bec-9994ed9d625f\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "1377"
}
},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c1272f23245a43d18b285c40bbb67a96",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(interactive(children=(SelectionSlider(description='value', index=3, options=(0, 1, 2, 3), value…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"\n",
"#Plot definitions\n",
"plotlist2D=[spec.raw_time,spec.real2D[0],\n",
" spec.raw_time,spec.imaginary2D[0]]\n",
"\n",
"plotlistavg = [spec.raw_time,spec.real,\n",
" spec.raw_time,spec.imaginary]\n",
"\n",
"spec2D = spec_plot(plotlist2D,y_range = (spec.imaginary2D.min(),spec.real2D.max()*1.02))\n",
"specavg = spec_plot(plotlistavg, y_range = (spec.imaginary.min(),spec.real.max()*1.02)) \n",
"\n",
"\n",
"#Widget Defintions\n",
"\n",
"\n",
"def on_button_clicked(val):\n",
" if np.sum(spec.slice_mask)>1: #prevent deleting of all slices\n",
" spec.delete_slice(myslider.value)\n",
" myslider.options=valuelist[spec.slice_mask]\n",
" myslider.value = myslider.options[-1]\n",
" spec.avg_slices()\n",
" update(myslider.value)\n",
" \n",
"def update(index):\n",
" for idx,line in enumerate(spec2D.renderers):\n",
" line.data_source.data['y'] = [spec.real2D,spec.imaginary2D][idx][index]\n",
" \n",
" for idx,line in enumerate(specavg.renderers):\n",
" line.data_source.data['y'] = [spec.real,spec.imaginary][idx]\n",
" \n",
" push_notebook(handle=sliceplots)\n",
" return index\n",
"\n",
"valuelist=np.arange(spec.real2D.shape[0])\n",
"\n",
"myslider=widgets.SelectionSlider(description='value', value=valuelist[-1],options=valuelist)\n",
"deletebutton=widgets.Button(description='Delete Slice')\n",
"deletebutton.on_click(on_button_clicked)\n",
"\n",
"\n",
"\n",
"#Render plots, widgets\n",
"sliceplots=show(row(spec2D,specavg),notebook_handle=True)\n",
"HBox([interactive(update,index=myslider),deletebutton])\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" <div class=\"bk-root\" id=\"4cad5b6c-5755-4aa3-b139-29c0f611fb72\" data-root-id=\"1086\"></div>\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"(function(root) {\n",
" function embed_document(root) {\n",
" \n",
" var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[754]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[754]}},\"selected\":{\"id\":\"1107\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1106\",\"type\":\"UnionRenderers\"}},\"id\":\"1081\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1108\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1091\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1022\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1078\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1068\",\"type\":\"HelpTool\"},{\"attributes\":{\"callback\":null},\"id\":\"1003\",\"type\":\"DataRange1d\"},{\"attributes\":{\"overlay\":{\"id\":\"1103\",\"type\":\"BoxAnnotation\"}},\"id\":\"1023\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1051\",\"type\":\"LinearScale\"},{\"attributes\":{\"line_color\":\"#e19c24\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1082\",\"type\":\"Line\"},{\"attributes\":{\"text\":\"\"},\"id\":\"1087\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"1007\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1024\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null,\"end\":25131884.04,\"start\":3661770.0},\"id\":\"1005\",\"type\":\"Range1d\"},{\"attributes\":{\"axis_label\":\"Evolution Time (\\u03bcs)\",\"axis_label_text_font_size\":{\"value\":\"24pt\"},\"axis_label_text_font_style\":\"normal\",\"formatter\":{\"id\":\"1097\",\"type\":\"BasicTickFormatter\"},\"major_label_text_font_size\":{\"value\":\"16pt\"},\"ticker\":{\"id\":\"1054\",\"type\":\"BasicTicker\"}},\"id\":\"1053\",\"type\":\"LinearAxis\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1083\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1025\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1054\",\"type\":\"BasicTicker\"}],\"root_ids\":[\"1086\"]},\"title\":\"Bokeh Application\",\"version\":\"1.4.0\"}};\n",
" var render_items = [{\"docid\":\"3d781e5a-7f19-4e1a-97cd-3c1a157d84d9\",\"notebook_comms_target\":\"1109\",\"roots\":{\"1086\":\"4cad5b6c-5755-4aa3-b139-29c0f611fb72\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "1086"
}
},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3c567a96d7964b9e8a6c3d3f37d9e9af",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(interactive(children=(SelectionSlider(description='value', index=3, options=(0, 1, 2, 3), value…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"\n",
"#Plot definitions\n",
"plotlist2D=[spec.raw_time,spec.real2D[0],\n",
" spec.raw_time,spec.imaginary2D[0]]\n",
"\n",
"plotlistavg = [spec.raw_time,spec.real,\n",
" spec.raw_time,spec.imaginary]\n",
"\n",
"spec2D = spec_plot(plotlist2D,y_range = (spec.imaginary2D.min(),spec.real2D.max()*1.02))\n",
"specavg = spec_plot(plotlistavg, y_range = (spec.imaginary.min(),spec.real.max()*1.02)) \n",
"\n",
"\n",
"#Widget Defintions\n",
"\n",
"\n",
"def on_button_clicked(val):\n",
" if np.sum(spec.slice_mask)>1: #prevent deleting of all slices\n",
" spec.delete_slice(myslider.value)\n",
" myslider.options=valuelist[spec.slice_mask]\n",
" myslider.value = myslider.options[-1]\n",
" spec.avg_slices()\n",
" update(myslider.value)\n",
" \n",
"def update(index):\n",
" for idx,line in enumerate(spec2D.renderers):\n",
" line.data_source.data['y'] = [spec.real2D,spec.imaginary2D][idx][index]\n",
" \n",
" for idx,line in enumerate(specavg.renderers):\n",
" line.data_source.data['y'] = [spec.real,spec.imaginary][idx]\n",
" \n",
" push_notebook(handle=sliceplots)\n",
" return index\n",
"\n",
"valuelist=np.arange(spec.real2D.shape[0])\n",
"\n",
"myslider=widgets.SelectionSlider(description='value', value=valuelist[-1],options=valuelist)\n",
"deletebutton=widgets.Button(description='Delete Slice')\n",
"deletebutton.on_click(on_button_clicked)\n",
"\n",
"\n",
"\n",
"#Render plots, widgets\n",
"sliceplots=show(row(spec2D,specavg),notebook_handle=True)\n",
"HBox([interactive(update,index=myslider),deletebutton])\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ True, True, True, False])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"spec.slice_mask\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" <div class=\"bk-root\" id=\"4a9a24ac-0d91-474b-8606-a4b2bc1e4176\" data-root-id=\"1352\"></div>\n"
]
},
"metadata": {},
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},
{
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Time (\\u03bcs)\",\"axis_label_text_font_size\":{\"value\":\"24pt\"},\"axis_label_text_font_style\":\"normal\",\"formatter\":{\"id\":\"1425\",\"type\":\"BasicTickFormatter\"},\"major_label_text_font_size\":{\"value\":\"16pt\"},\"ticker\":{\"id\":\"1362\",\"type\":\"BasicTicker\"}},\"id\":\"1361\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1367\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1362\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1423\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"overlay\":{\"id\":\"1433\",\"type\":\"BoxAnnotation\"}},\"id\":\"1373\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1374\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1375\",\"type\":\"ResetTool\"}],\"root_ids\":[\"1352\"]},\"title\":\"Bokeh Application\",\"version\":\"1.4.0\"}};\n",
" var render_items = [{\"docid\":\"fbedec1e-02e2-4bd7-8852-f1e95f1e9d9c\",\"notebook_comms_target\":\"1434\",\"roots\":{\"1352\":\"4a9a24ac-0d91-474b-8606-a4b2bc1e4176\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "1352"
}
},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "415e576270b44c449e2290fa96be565d",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(interactive(children=(SelectionSlider(description='Cutoff', index=753, options=(-0.068, -0.0600…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cutoffx=[spec.raw_time.max(),spec.raw_time.max()]\n",
"cutoffy=[-.1,1]\n",
"\n",
"cutoffslider=widgets.SelectionSlider(description='Cutoff', value=spec.raw_time[-1], options=spec.raw_time)\n",
"signal=spec.real+1j*spec.imaginary\n",
"forphasing=signal[int(len(signal)/8):list(spec.raw_time).index(cutoffslider.value)]\n",
"spec.phase=optimize.fmin(lambda x:abs((forphasing*np.e**(1j*x)).imag.mean()),1,disp=False)[0]\n",
"phaseslider=widgets.FloatSlider(description='Phase', value=spec.phase, min=-np.pi, max=np.pi, step=0.001)\n",
"\n",
"\n",
"plotlist=[spec.raw_time,np.real(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase))),\n",
" spec.raw_time,np.imag(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase)))]\n",
"\n",
"\n",
"phaseplot=spec_plot(plotlist)\n",
"phaseplot.line(cutoffx,cutoffy, color=(255,0,0), line_width=1) #decorate plot with cutoff line\n",
"phaser=show(phaseplot, notebook_handle=True);\n",
"\n",
"\n",
"phasebutton=widgets.Button(description='Phase')\n",
"kernelbutton=widgets.Button(description='Build Kernel')\n",
"\n",
"def phase_button_clicked(val):\n",
" forphasing=signal[int(len(signal)/8):list(spec.raw_time).index(cutoffslider.value)]\n",
" spec.phase=optimize.fmin(lambda x:abs((forphasing*np.e**(1j*x)).imag.mean()),1,disp=False)[0]\n",
" phaseslider.value=spec.phase\n",
" \n",
"def kernel_button_clicked(val):\n",
" \n",
" dimensions=512\n",
" tmax=cutoffslider.value\n",
" rmin=1.5\n",
" rmax=10.\n",
" spec.kernel,spec.t,spec.r,spec.Lmatrix = buildkernels(dimensions,rmin,rmax,tmax,spec.dt)\n",
" spec.cutoff=cutoffslider.value\n",
" spec.real=np.real(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase)))\n",
" spec.imag=np.imag(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase)))\n",
" \n",
" alphas = np.logspace(-4,6, 51)\n",
" spec.hMats=np.asarray([np.diag(hMat(x, spec.kernel, spec.Lmatrix)) for x in alphas])\n",
" \n",
"\n",
" \n",
"def updatePhase(value):\n",
" phaseplot.renderers[-3].data_source.data['y'] = np.real(signal*np.e**(1j*value))/np.max(np.real(signal*np.e**(1j*value)))\n",
" phaseplot.renderers[-2].data_source.data['y'] = np.imag(signal*np.e**(1j*value))/np.max(np.real(signal*np.e**(1j*value)))\n",
" phaseplot.renderers[-1].data_source.data['y'] = [np.min(np.imag(signal*np.e**(1j*value))/np.max(np.real(signal*np.e**(1j*value)))),1]\n",
" push_notebook(handle=phaser)\n",
" return value\n",
"\n",
"def updateCutoff(value):\n",
" phaseplot.renderers[-1].data_source.data['x'] = [value,value]\n",
" push_notebook(handle=phaser)\n",
" return value\n",
"\n",
"#kernel,spec.t,spec.r,Lmatrix,spec.cutoff = \n",
"\n",
"phasebutton.on_click(phase_button_clicked)\n",
"kernelbutton.on_click(kernel_button_clicked)\n",
"HBox([interactive(updateCutoff,value=cutoffslider),interactive(updatePhase,value=phaseslider),phasebutton,kernelbutton])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'XMIN': None, 'XWID': None, 'XPTS': None, 'YPTS': None}"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dict.fromkeys(['XMIN','XWID','XPTS','YPTS'])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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0)\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1486\",\"type\":\"Line\"},{\"attributes\":{\"data_source\":{\"id\":\"1485\"},\"glyph\":{\"id\":\"1486\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1487\"},\"selection_glyph\":null,\"view\":{\"id\":\"1489\"}},\"id\":\"1488\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1464\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1465\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1447\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1466\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1449\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1515\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1445\",\"type\":\"DataRange1d\"},{\"attributes\":{\"data\":{\"x\":[5.956,5.956],\"y\":[-0.1,1]},\"selected\":{\"id\":\"1523\"},\"selection_policy\":{\"id\":\"1522\"}},\"id\":\"1485\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#5e81b5\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1477\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1517\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1461\"},{\"id\":\"1462\"},{\"id\":\"1463\"},{\"id\":\"1464\"},{\"id\":\"1465\"},{\"id\":\"1466\"}]},\"id\":\"1468\",\"type\":\"Toolbar\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1467\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"data_source\":{\"id\":\"1475\"},\"glyph\":{\"id\":\"1476\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1477\"},\"selection_glyph\":null,\"view\":{\"id\":\"1479\"}},\"id\":\"1478\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1518\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1519\",\"type\":\"Selection\"},{\"attributes\":{\"axis\":{\"id\":\"1453\"},\"grid_line_color\":null,\"ticker\":null},\"id\":\"1456\",\"type\":\"Grid\"},{\"attributes\":{\"line_color\":\"#5e81b5\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1476\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1520\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1451\",\"type\":\"LinearScale\"},{\"attributes\":{\"source\":{\"id\":\"1475\"}},\"id\":\"1479\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1521\",\"type\":\"Selection\"}],\"root_ids\":[\"1444\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
" var render_items = [{\"docid\":\"c37e3b1b-b084-4818-ba31-d95cc138ae5c\",\"notebook_comms_target\":\"1525\",\"root_ids\":[\"1444\"],\"roots\":{\"1444\":\"a3757010-7ba7-40fa-9f16-86840d5c7e57\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "1444"
}
},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "a418a44817a845acbbe5556fe74acbe9",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(interactive(children=(SelectionSlider(description='Cutoff', index=753, options=(-0.068, -0.0600…"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"ename": "NameError",
"evalue": "name 'buildkernels' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-8-1f83fe9ec2c8>\u001b[0m in \u001b[0;36mkernel_button_clicked\u001b[0;34m(val)\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[0mrmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1.5\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 33\u001b[0m \u001b[0mrmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 34\u001b[0;31m \u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLmatrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuildkernels\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdimensions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrmin\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrmax\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtmax\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 35\u001b[0m \u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcutoff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcutoffslider\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreal\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1j\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphase\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1j\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mspec\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphase\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: name 'buildkernels' is not defined"
]
}
],
"source": [
"cutoffx=[spec.raw_time.max(),spec.raw_time.max()]\n",
"cutoffy=[-.1,1]\n",
"\n",
"cutoffslider=widgets.SelectionSlider(description='Cutoff', value=spec.raw_time[-1], options=spec.raw_time)\n",
"signal=spec.real+1j*spec.imaginary\n",
"forphasing=signal[int(len(signal)/8):list(spec.raw_time).index(cutoffslider.value)]\n",
"spec.phase=optimize.fmin(lambda x:abs((forphasing*np.e**(1j*x)).imag.mean()),1,disp=False)[0]\n",
"phaseslider=widgets.FloatSlider(description='Phase', value=spec.phase, min=-np.pi, max=np.pi, step=0.001)\n",
"\n",
"\n",
"plotlist=[spec.raw_time,np.real(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase))),\n",
" spec.raw_time,np.imag(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase)))]\n",
"\n",
"\n",
"phaseplot=spec_plot(plotlist)\n",
"phaseplot.line(cutoffx,cutoffy, color=(255,0,0), line_width=1) #decorate plot with cutoff line\n",
"phaser=show(phaseplot, notebook_handle=True);\n",
"\n",
"\n",
"phasebutton=widgets.Button(description='Phase')\n",
"kernelbutton=widgets.Button(description='Build Kernel')\n",
"\n",
"def phase_button_clicked(val):\n",
" forphasing=signal[int(len(signal)/8):list(spec.raw_time).index(cutoffslider.value)]\n",
" spec.phase=optimize.fmin(lambda x:abs((forphasing*np.e**(1j*x)).imag.mean()),1,disp=False)[0]\n",
" phaseslider.value=spec.phase\n",
" \n",
"def kernel_button_clicked(val):\n",
" \n",
" dimensions=512\n",
" tmax=cutoffslider.value\n",
" rmin=1.5\n",
" rmax=10.\n",
" spec.kernel,spec.t,spec.r,spec.Lmatrix = buildkernels(dimensions,rmin,rmax,tmax,spec.dt)\n",
" spec.cutoff=cutoffslider.value\n",
" spec.real=np.real(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase)))\n",
" spec.imag=np.imag(signal*np.e**(1j*spec.phase))/np.max(np.real(signal*np.e**(1j*spec.phase)))\n",
" \n",
" alphas = np.logspace(-4,6, 51)\n",
" spec.hMats=np.asarray([np.diag(hMat(x, spec.kernel, spec.Lmatrix)) for x in alphas])\n",
" \n",
"\n",
" \n",
"def updatePhase(value):\n",
" phaseplot.renderers[-3].data_source.data['y'] = np.real(signal*np.e**(1j*value))/np.max(np.real(signal*np.e**(1j*value)))\n",
" phaseplot.renderers[-2].data_source.data['y'] = np.imag(signal*np.e**(1j*value))/np.max(np.real(signal*np.e**(1j*value)))\n",
" phaseplot.renderers[-1].data_source.data['y'] = [np.min(np.imag(signal*np.e**(1j*value))/np.max(np.real(signal*np.e**(1j*value)))),1]\n",
" push_notebook(handle=phaser)\n",
" return value\n",
"\n",
"def updateCutoff(value):\n",
" phaseplot.renderers[-1].data_source.data['x'] = [value,value]\n",
" push_notebook(handle=phaser)\n",
" return value\n",
"\n",
"#kernel,spec.t,spec.r,Lmatrix,spec.cutoff = \n",
"\n",
"phasebutton.on_click(phase_button_clicked)\n",
"kernelbutton.on_click(kernel_button_clicked)\n",
"HBox([interactive(updateCutoff,value=cutoffslider),interactive(updatePhase,value=phaseslider),phasebutton,kernelbutton])"
]
},
{
"cell_type": "code",
"execution_count": 267,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.008"
]
},
"execution_count": 267,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"spec.raw_time[1]-spec.raw_time[0]"
]
},
{
"cell_type": "code",
"execution_count": 268,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.008"
]
},
"execution_count": 268,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"spec.dt"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'test' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-1-4e1243bd22c6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtest\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'test' is not defined"
]
}
],
"source": [
"test"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": 4
}
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