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"A.table(results, end=3)"
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"You can see them in context as well:"
]
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"execution_count": 6,
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{
"data": {
"text/html": [
"result 1"
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notation=TeX
${1\\over 3} {4\\over 9} {16\\over 27} {64\\over 81}$
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$4.900x^{6} \\ {\\it aequat}\\ - 4.899x^{5} + 2.354x^{4} + 16.858x^{3} + 9.458xx + 429x - 4.900$
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${\\displaystyle\\strut {3xx - 1x}\\over \\displaystyle\\strut 2}$
![](\"images/tf.png\")
\n",
"![](\"images/huc.png\"/)
\n",
"![](\"images/logo.png\"){kind=logo}
\n",
"\n",
"# Start\n",
"\n",
"This notebook gets you started with using\n",
"[Text-Fabric](https://github.com/annotation/text-fabric) for coding in the\n",
"letters of René Descartes.\n",
"\n",
"Familiarity with the underlying\n",
"[data model](https://annotation.github.io/text-fabric/tf/about/datamodel.html)\n",
"is recommended.\n",
"\n",
"For provenance, see the documentation:\n",
"[about](https://github.com/CLARIAH/descartes-tf/blob/master/docs/about.md)."
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"## Overview\n",
"\n",
"* we tell you how to get Text-Fabric on your system;\n",
"* we tell you how to get the Descartes corpus on your system."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Installing Text-Fabric\n",
"\n",
"See the [installation instructions](https://annotation.github.io/text-fabric/tf/about/install.html)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Running Text-Fabric\n",
"\n",
"We will run computer code in the cells below, and this code makes use of the\n",
"text-fabric library, shortly called `tf`.\n",
"\n",
"We import some standard Python modules and then we import the `use` function from text-fabric."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-17T09:33:07.029915Z",
"start_time": "2018-05-17T09:33:07.006073Z"
}
},
"outputs": [],
"source": [
"import sys, os\n",
"from tf.app import use"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we are going to *use* the `use` function.\n",
"We want to *use* a corpus, and if we specify what corpus, text-fabric will the data for us.\n",
"\n",
"If you have cloned the `CLARIAH/descartes-tf` repository to your local machine under the directory\n",
"\n",
"`~/github/CLARIAH/descartes-tf`\n",
"\n",
"then you already have the data.\n",
"In that case you have to call the use command like this:\n",
"\n",
"```\n",
"A = use(\"CLARIAH/descartes-tf:clone\", checkout=\"clone\", hoist=globals())\n",
"```\n",
"\n",
"Below we give the command for the case where you have not cloned the repository.\n",
"Text-Fabric will fetch the data from the internet and store it in your directory\n",
"\n",
"`~/text-fabric-data/github/CLARIAH/descartes-tf`.\n",
"\n",
"In both cases, the corpus data will be optimised for fast processing, a one time job."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-17T09:33:10.782586Z",
"start_time": "2018-05-17T09:33:09.929360Z"
}
},
"outputs": [
{
"data": {
"text/markdown": [
"**Locating corpus resources ...**"
],
"text/plain": [
"