{
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"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Hueristics"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Objective"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We seek to try out various heuristics to quantify spectral data; these are a prototype which ultimately will be used to correlate gold nanoparticle coverage in SEM images with spectral data."
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Environment Setup"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Configure notebook style (see NBCONFIG.ipynb), add imports and paths. The **%run** magic used below **requires IPython 2.0 or higher.**"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%run NBCONFIG.ipynb"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"html": [
""
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"metadata": {},
"output_type": "display_data",
"text": [
""
]
}
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},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Step 1: Load in test data of AuNPs on glass; this is a great example of a monolayer of gold particles form our dataset."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from skspec.data import aunps_glass\n",
"\n",
"ts = aunps_glass()\n",
"ts.baseline = 220.0\n",
"ts.sub_base()\n",
"ts = ts.ix[440.0:680.0]\n",
"\n",
"ts.plot(color='bone');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"WARNING:skspec.core.timespectra:SpecIndex unit was changed internally from \"None\" to \"nm\"\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"CRITICAL:skspec.core.timespectra:Subtracting baseline, but may not have all: elements being equal. Fix index\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
""
]
},
{
"metadata": {},
"output_type": "display_data",
"svg": [
"\n",
"\n",
"\n",
"\n"
],
"text": [
""
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}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ts.reference = 0\n",
"\n",
"ts_norm = ts.as_iunit('r')\n",
"ts_norm.plot(cbar=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"svg": [
"\n",
"\n",
"\n",
"