{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"Patrick BROCKMANN - LSCE (Climate and Environment Sciences Laboratory)
\n",
"![](\"http://www.lsce.ipsl.fr/Css/img/banniere_LSCE_75.png\")
\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Updated: 2019/11/13"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load ferret magic"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The ferretmagic extension is already loaded. To reload it, use:\n",
" %reload_ext ferretmagic\n"
]
}
],
"source": [
"%load_ext ferretmagic"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%ferret -s 600,500\n",
"\n",
"cancel mode logo\n",
"set text/font=arial\n",
"let a = {7,12,28,3,41}\n",
"plot/symbol=30/line/title=\"title\" a"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load R magic"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"%load_ext rpy2.ipython"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%R\n",
"\n",
"v <- c(7,12,28,3,41)\n",
"plot(v,type = \"o\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"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": "3.7.5"
}
},
"nbformat": 4,
"nbformat_minor": 1
}