{
"metadata": {
"name": "",
"signature": "sha256:34d911ab9b3d9f3c4de0e631d4b7f5524709c2a8c257b2a6d8d566e5a373b567"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"%load_ext load_style\n",
"%load_style talk.css\n",
"from talktools import website"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<style>\n",
"\n",
".rendered_html {\n",
" font-family: \"proxima-nova\", helvetica;\n",
" font-size: 130%;\n",
" line-height: 1.5;\n",
"}\n",
"\n",
".rendered_html h1 {\n",
" margin: 0.25em 0em 0.5em;\n",
" color: #015C9C;\n",
" text-align: center;\n",
" line-height: 1.2; \n",
" page-break-before: always;\n",
"}\n",
"\n",
".rendered_html h2 {\n",
" margin: 1.1em 0em 0.5em;\n",
" color: #26465D;\n",
" line-height: 1.2;\n",
"}\n",
"\n",
".rendered_html h3 {\n",
" margin: 1.1em 0em 0.5em;\n",
" color: #002845;\n",
" line-height: 1.2;\n",
"}\n",
"\n",
".rendered_html li {\n",
" line-height: 1.5; \n",
"}\n",
"\n",
"/*.prompt {\n",
" font-size: 120%; \n",
"}*/\n",
"\n",
".CodeMirror-lines {\n",
" font-size: 110%; \n",
"}\n",
"\n",
"/*.output_area {\n",
" font-size: 120%; \n",
"}*/\n",
"\n",
"/*#notebook {\n",
" background-image: url('files/images/witewall_3.png');\n",
"}*/\n",
"\n",
"h1.bigtitle {\n",
" margin: 4cm 1cm 4cm 1cm;\n",
" font-size: 300%;\n",
"}\n",
"\n",
"h3.point {\n",
" font-size: 200%;\n",
" text-align: center;\n",
" margin: 2em 0em 2em 0em;\n",
" #26465D\n",
"}\n",
"\n",
".logo {\n",
" margin: 20px 0 20px 0;\n",
"}\n",
"\n",
"a.anchor-link {\n",
" display: none;\n",
"}\n",
"\n",
"h1.title { \n",
" font-size: 250%;\n",
"}\n",
"\n",
"</style>"
],
"metadata": {},
"output_type": "display_data",
"text": [
"<IPython.core.display.HTML at 0x1049b42d0>"
]
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"conda and anaconda"
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"<hr size=5>\n",
"anaconda "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[anaconda](https://store.continuum.io/cshop/anaconda/) is a Scientific Python distribution, developed by [](), \n",
"from their web-page: \n",
" \n",
" Anaconda is a completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing\n",
" \n",
"some advantages: \n",
"\n",
"+ free \n",
"+ cross-platform \n",
"+ 195+ of the [most popular Python packages](http://docs.continuum.io/anaconda/pkg-docs.html) for science, math, engineering, data analysis, ... notably:\n",
" <br><br>\n",
" + <a href=\"http://www.numpy.org/\">NumPy</a>\n",
" + <a href=\"http://www.scipy.org/\">SciPy</a>\n",
" + <a href=\"http://pandas.pydata.org/\">Pandas</a>\n",
" + <a href=\"http://ipython.org/\">IPython</a>\n",
" + <a href=\"http://matplotlib.org/\">Matplotlib</a>\n",
" + <a href=\"http://numba.pydata.org/\">Numba</a>\n",
" + <a href=\"http://blaze.pydata.org/\">Blaze</a>\n",
" + <a href=\"http://bokeh.pydata.org/\">Bokeh</a>\n",
" <br><br>\n",
" \n",
"+ easily install, update, revert Python packages (with dependencies ..)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"website('https://store.continuum.io/cshop/anaconda/',width=1000)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<iframe src=\"https://store.continuum.io/cshop/anaconda/\" width=\"1000\" height=\"450\">"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
"<IPython.core.display.HTML at 0x1040c0e10>"
]
}
],
"prompt_number": 2
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"<hr size=5>\n",
"conda"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[conda](http://conda.pydata.org/docs/) is a package and **environment management system** akin to virtualenv"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"example, I want to test the [iris](http://scitools.org.uk/iris/index.html) and [cartopy](http://scitools.org.uk/cartopy/index.html) packages.\n",
"\n",
"These are developed by the [UK Met. Office](http://scitools.org.uk/).\n",
"\n",
"+ [iris](http://scitools.org.uk/iris/index.html) is a Python package for analysing and visualising meteorological and oceanographic data sets\n",
"+ [cartopy](http://scitools.org.uk/cartopy/index.html) is a Python package for advanced map generation with a simple matplotlib interface.\n",
"<br>\n",
"<br>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"first create a conda environment named *iris*, with the minimum: python and ipython [+ libraries for the notebook]\n",
"\n",
" \u1405 conda create -n iris python ipython ipython-notebook\n",
"\n",
"then: \n",
"\n",
" \u1405 source activate iris\n",
"\n",
"and to install (in the `iris` environment)\n",
"\n",
" \u1405 conda install -c https://conda.binstar.org/scitools cdat-lite\n",
" \u1405 conda install -c https://conda.binstar.org/scitools iris\n",
" \u1405 conda install -c https://conda.binstar.org/scitools cartopy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A (quick and dirty) exploration of iris and cartopy can be found in [this notebook](./iris_cartopy.ipynb)\n",
"\n",
"<font color='red'>IMPORTANT</font>: **you need to launch a new instance of the IPython notebook from the `iris` environment**: \n",
"\n",
" ~/Documents/talks_seminars/metocean/notebooks \u1405 source activate iris\n",
"\n",
" (iris)~/Documents/talks_seminars/metocean/notebooks \u1405 ipython notebook "
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"binstar"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[binstar](https://binstar.org) is a free service for hosting public packages for pip and conda"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For example, the [GDAL](http://www.gdal.org/) library is not available through **Anaconda** (the package distribution), but some people have compiled it on different platforms, packaged it according to the conda package management system specifications, and made it available through **binstar**, and it can be install via conda. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"website('https://binstar.org/dashboard', width=1000, height=700)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<iframe src=\"https://binstar.org/dashboard\" width=\"1000\" height=\"700\">"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
"<IPython.core.display.HTML at 0x104ab75d0>"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import iris"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "ImportError",
"evalue": "No module named iris",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-3-005053b25f37>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0miris\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mImportError\u001b[0m: No module named iris"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}