+
+
+
+
+VAPOR Python Cookbook
+
+
This Project Pythia Cookbook provides an overview of the VAPOR Python API with example workflows.
+Motivation
+The Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) provides an interactive 3D visualization environment for exploratory visual analysis and the production of captivating animations and high-quality images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards.
+Authors
+Nihanth W. Cherukuru, Stanislaw ‘Stas’ Jarosynski, Philip Austin, Ian Franda
+Contributors
+ +
+ 
+ 
+ 
+ 
+ 
+
+Structure
+This cookbook is divided into three main sections. The “Quickstart” section is a good starting point for a general overview of VAPOR’s features and capabilities. The “Foundations” section gives more detailed examples for specific features in VAPOR. The “Example Workflows” section provides practical examples to see VAPOR in action and to gain an understanding of various workflows. Feel free to visit the sections that best fit your needs – it’s not necessary to follow them sequentially!
+VAPOR Foundations
+The foundation section gives a quick overview of the major components of VAPOR python. These include the funcationality to load/read data, set camera parameters, annotations, save animations and images, implementing renderes for data visualization.
+Additionally, the links below can serve as a helpful reference.
+Discussion forum for VAPOR.
+Use this to delve deeper into the python classes
+GUI version provides a graphical interface for VAPOR
+Example Workflows
+The example workflows section provides examples showing and end-end pipeline for analysis and visualization using VAPOR python.
+Running the Notebooks
+These notebooks cannot be run on Binder at the moment and need to be run on your machine.
+Running on Your Machine
+If you are interested in running this material locally on your computer, you will need to follow this workflow:
+-
+
Clone the
+https://github.com/ProjectPythia/vapor-python-cookbookrepository:++git clone https://github.com/ProjectPythia/vapor-python-cookbook.git +
+Move into the
+vapor-python-cookbookdirectory++cd vapor-python-cookbook +
+Create and activate your conda environment from the
+environment.ymlfile++conda env create -f vapor_environment.yml +conda activate vapor-cookbook-dev +
+Move into the
+notebooksdirectory and start up Jupyterlab++cd notebooks/ +jupyter lab +
+
At this point, you can interact with the notebooks! Make sure to check out the “Getting Started with Jupyter” content from the Pythia Foundations material if you are new to Jupyter or need a refresher.
+
+
+# VAPOR Python Cookbook
+
+[](https://github.com/ProjectPythia/cookbook-template/actions/workflows/nightly-build.yaml)
+[](https://zenodo.org/badge/latestdoi/656355302)
+
+This Project Pythia Cookbook provides an overview of the VAPOR Python API with example workflows.
+
+## Motivation
+
+The Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) provides an interactive 3D visualization environment for exploratory visual analysis and the production of captivating animations and high-quality images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards.
+
+## Authors
+
+[Nihanth W. Cherukuru](https://github.com/NihanthCW), [Stanislaw 'Stas' Jarosynski](https://github.com/StasJ), [Philip Austin](https://github.com/phaustin), [Ian Franda](github.com/ifranda)
+
+### Contributors
+
+![\"Project](\"images/ProjectPythia_Logo_Final-01-Blue.svg\"){kind=logo}
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Project Pythia Notebook Template\n",
+ "\n",
+ "Next, title your notebook appropriately with a top-level Markdown header, `#`. Do not use this level header anywhere else in the notebook. Our book build process will use this title in the navbar, table of contents, etc. Keep it short, keep it descriptive. Follow this with a `---` cell to visually distinguish the transition to the prerequisites section."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Overview\n",
+ "If you have an introductory paragraph, lead with it here! Keep it short and tied to your material, then be sure to continue into the required list of topics below,\n",
+ "\n",
+ "1. This is a numbered list of the specific topics\n",
+ "1. These should map approximately to your main sections of content\n",
+ "1. Or each second-level, `##`, header in your notebook\n",
+ "1. Keep the size and scope of your notebook in check\n",
+ "1. And be sure to let the reader know up front the important concepts they'll be leaving with"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Prerequisites\n",
+ "This section was inspired by [this template](https://github.com/alan-turing-institute/the-turing-way/blob/master/book/templates/chapter-template/chapter-landing-page.md) of the wonderful [The Turing Way](https://the-turing-way.netlify.app) Jupyter Book.\n",
+ "\n",
+ "Following your overview, tell your reader what concepts, packages, or other background information they'll **need** before learning your material. Tie this explicitly with links to other pages here in Foundations or to relevant external resources. Remove this body text, then populate the Markdown table, denoted in this cell with `|` vertical brackets, below, and fill out the information following. In this table, lay out prerequisite concepts by explicitly linking to other Foundations material or external resources, or describe generally helpful concepts.\n",
+ "\n",
+ "Label the importance of each concept explicitly as **helpful/necessary**.\n",
+ "\n",
+ "| Concepts | Importance | Notes |\n",
+ "| --- | --- | --- |\n",
+ "| [Intro to Cartopy](https://foundations.projectpythia.org/core/cartopy/cartopy.html) | Necessary | |\n",
+ "| [Understanding of NetCDF](https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html) | Helpful | Familiarity with metadata structure |\n",
+ "| Project management | Helpful | |\n",
+ "\n",
+ "- **Time to learn**: estimate in minutes. For a rough idea, use 5 mins per subsection, 10 if longer; add these up for a total. Safer to round up and overestimate.\n",
+ "- **System requirements**:\n",
+ " - Populate with any system, version, or non-Python software requirements if necessary\n",
+ " - Otherwise use the concepts table above and the Imports section below to describe required packages as necessary\n",
+ " - If no extra requirements, remove the **System requirements** point altogether"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Imports\n",
+ "Begin your body of content with another `---` divider before continuing into this section, then remove this body text and populate the following code cell with all necessary Python imports **up-front**:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-06-22T17:21:49.397346Z",
+ "iopub.status.busy": "2023-06-22T17:21:49.397015Z",
+ "iopub.status.idle": "2023-06-22T17:21:49.404929Z",
+ "shell.execute_reply": "2023-06-22T17:21:49.404314Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "import sys"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Your first content section"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This is where you begin your first section of material, loosely tied to your objectives stated up front. Tie together your notebook as a narrative, with interspersed Markdown text, images, and more as necessary,"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-06-22T17:21:49.408360Z",
+ "iopub.status.busy": "2023-06-22T17:21:49.408082Z",
+ "iopub.status.idle": "2023-06-22T17:21:49.411749Z",
+ "shell.execute_reply": "2023-06-22T17:21:49.411099Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Hello world!\n"
+ ]
+ }
+ ],
+ "source": [
+ "# as well as any and all of your code cells\n",
+ "print(\"Hello world!\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### A content subsection\n",
+ "Divide and conquer your objectives with Markdown subsections, which will populate the helpful navbar in Jupyter Lab and here on the Jupyter Book!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-06-22T17:21:49.415204Z",
+ "iopub.status.busy": "2023-06-22T17:21:49.414943Z",
+ "iopub.status.idle": "2023-06-22T17:21:49.418072Z",
+ "shell.execute_reply": "2023-06-22T17:21:49.417360Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# some subsection code\n",
+ "new = \"helpful information\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Another content subsection\n",
+ "Keep up the good work! A note, *try to avoid using code comments as narrative*, and instead let them only exist as brief clarifications where necessary."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Your second content section\n",
+ "Here we can move on to our second objective, and we can demonstrate"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Subsection to the second section\n",
+ "\n",
+ "#### a quick demonstration\n",
+ "\n",
+ "##### of further and further\n",
+ "\n",
+ "###### header levels"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "as well $m = a * t / h$ text! Similarly, you have access to other $\\LaTeX$ equation [**functionality**](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Typesetting%20Equations.html) via MathJax (demo below from link),\n",
+ "\n",
+ "\\begin{align}\n",
+ "\\dot{x} & = \\sigma(y-x) \\\\\n",
+ "\\dot{y} & = \\rho x - y - xz \\\\\n",
+ "\\dot{z} & = -\\beta z + xy\n",
+ "\\end{align}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Check out [**any number of helpful Markdown resources**](https://www.markdownguide.org/basic-syntax/) for further customizing your notebooks and the [**Jupyter docs**](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Working%20With%20Markdown%20Cells.html) for Jupyter-specific formatting information. Don't hesitate to ask questions if you have problems getting it to look *just right*."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Last Section\n",
+ "\n",
+ "If you're comfortable, and as we briefly used for our embedded logo up top, you can embed raw html into Jupyter Markdown cells (edit to see):"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "