{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "skip" } }, "source": [ "\n", "[*NBJoint test on a collection of notebooks about some thermodynamic properperties of water*](https://github.com/rmsrosa/nbjoint)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "skip" } }, "source": [ "\n", "\"Open\"Open\"View\"View " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "skip" } }, "source": [ "\n", "| [Water Contents](00.00-Water_Contents.ipynb) | [References](BA.00-References.ipynb) | [Introduction ->](01.00-Introduction.ipynb)\n", "\n", "---\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Water Contents\n", "\n", "The purpose of these notes are solely to illustrate the use of the `nbjoint` library with notebooks that include not only pure-text markdown cells, but also pictures and code cells. \n", "\n", "They would normally fit into a single Jupyter notebook, but that would miss the point of the module, which is to joint several notebooks. Thus, the presentation is split into a number of them." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "\n", "## [Table of Contents](#)\n", "\n", "### [Water Contents](00.00-Water_Contents.ipynb)\n", "\n", "### [1. Introduction](01.00-Introduction.ipynb)\n", "\n", "### [2. Reading the Data](02.00-Data.ipynb)\n", "\n", "### [3. Low-Dimensional Fittings](03.00-Low_Dim_Fittings.ipynb)\n", "\n", "### [4. High-Dimensional Fittings](04.00-High_Dim_Fittings.ipynb)\n", "\n", "### [5. Choosing the Best Fit with AIC](05.00-Best_AIC_Fitting.ipynb)\n", "\n", "### [References](BA.00-References.ipynb)\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "skip" } }, "source": [ "\n", "\n", "---\n", "| [Water Contents](00.00-Water_Contents.ipynb) | [References](BA.00-References.ipynb) | [Introduction ->](01.00-Introduction.ipynb)" ] } ], "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": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 }