This page outlines the tools and resources that you will need to install Git, Bash and Python applications onto your computer as the first step of our Python skills tutorial series.

Checklist

Detailed directions to accomplish each objective are below.

• Install Bash shell (or shell of preference)
• Install Git
• Install Python 3.x

Bash/Shell Setup

Install Bash for Windows

1. Download the Git for Windows installer.
2. Run the installer and follow the steps bellow:
   1. Welcome to the Git Setup Wizard: Click on "Next".
   2. Information: Click on "Next".
   3. Select Destination Location: Click on "Next".
   4. Select Components: Click on "Next".
   5. Select Start Menu Folder: Click on "Next".
   6. Adjusting your PATH environment: Select "Use Git from the Windows Command Prompt" and click on "Next". If you forgot to do this programs that you need for the event will not work properly. If this happens rerun the installer and select the appropriate option.
   7. Configuring the line ending conversions: Click on "Next". Keep "Checkout Windows-style, commit Unix-style line endings" selected.
   8. Configuring the terminal emulator to use with Git Bash: Select "Use Windows' default console window" and click on "Next".
   9. Configuring experimental performance tweaks: Click on "Next".
   10. Completing the Git Setup Wizard: Click on "Finish".

This will provide you with both Git and Bash in the Git Bash program.

Install Bash for Mac OS X

The default shell in all versions of Mac OS X is bash, so no need to install anything. You access bash from the Terminal (found in /Applications/Utilities). You may want to keep Terminal in your dock for this workshop.

Install Bash for Linux

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Git Setup

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on GitHub. You will need a supported web browser (current versions of Chrome, Firefox or Safari, or Internet Explorer version 9 or above).

Git installation instructions borrowed and modified from Software Carpentry.

Git for Windows

Git on Mac OS X

Install Git on Macs by downloading and running the most recent installer for "mavericks" if you are using OS X 10.9 and higher -or- if using an earlier OS X, choose the most recent "snow leopard" installer, from this list. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program.

Git on Linux

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo yum install git.

Setting Up Python

Python is a popular language for scientific computing and data science, as well as being a great for general-purpose programming. Installing all of the scientific packages individually can be a bit difficult, so we recommend using an all-in-one installer, like Anaconda.

Regardless of how you choose to install it, **please make sure your environment is set up with Python version 3.7 (at the time of writing, the gdal package did not work with the newest Python version 3.6). Python 2.x is quite different from Python 3.x so you do need to install 3.x and set up with the 3.7 environment.

We will teach using Python in the Jupyter Notebook environment, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not). You can choose to not use notebooks in the course, however, we do recommend you download and install the library so that you can explore this tool.

Windows

Download and install Anaconda. Download the default Python 3 installer (3.7). Use all of the defaults for installation except make sure to check Make Anaconda the default Python.

Mac OS X

Download and install Anaconda. Download the Python 3.x installer, choosing either the graphical installer or the command-line installer (3.7). For the graphical installer, use all of the defaults for installation. For the command-line installer open Terminal, navigate to the directory with the download then enter:

bash Anaconda3-2020.11-MacOSX-x86_64.sh (or whatever you file name is)

Linux

Open a terminal window and navigate to your downloads folder. Type

bash Anaconda3-2020.11-Linux-ppc64le.sh

and then press tab. The name of the file you just downloaded should appear.

Press enter. You will follow the text-only prompts. When there is a colon at the bottom of the screen press the down arrow to move down through the text. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).

Install Python packages

We need to install several packages to the Python environment to be able to work with the remote sensing data

• gdal
• h5py

If you are new to working with command line you may wish to complete the next setup instructions which provides and intro to command line (bash) prior to completing these package installation instructions.

Windows

Create a new Python 3.7 environment by opening Windows Command Prompt and typing

conda create –n py37 python=3.7 anaconda

When prompted, activate the py37 environment in Command Prompt by typing

activate py37

You should see (py37) at the beginning of the command line. You can also test that you are using the correct version by typing python --version.

Install Python package(s):

• gdal: conda install gdal
• h5py: conda install h5py

Note: You may need to only install gdal as the others may be included in the default.

Mac OS X

Create a new Python 3.7 environment by opening Terminal and typing

conda create –n py37 python=3.7 anaconda

This may take a minute or two.

When prompted, activate the py37 environment in Command Prompt by typing

source activate py37

You should see (py37) at the beginning of the command line. You can also test that you are using the correct version by typing python --version.

Install Python package(s):

• gdal: conda install gdal
• h5py: conda install h5py

Linux

Launch Python.

Install Python package(s):

• gdal: conda install gdal
• h5py: conda install h5py

Set up Jupyter Notebook Environment

In your terminal application, navigate to the directory (cd) that where you want the Jupyter Notebooks to be saved (or where they already exist).

Open Jupyter Notebook with

jupyter notebook

Once the notebook is open, check which version of Python you are in by using the prompts

# check what version of Python you are using.
import sys
sys.version

You should now be able to work in the notebook.

The gdal package that occasionally has problems with some versions of Python. Therefore test out loading it using

import gdal.

Additional Resources

• Setting up the Python Environment section from the Python Bootcamp
• Conda Help: setting up an environment
• iPython documentation: Kernals

Checklist

Once you have Git and Bash installed, you are ready to configure Git.

On this page you will:

• Create a directory for all future GitHub repositories created on your computer

To ensure Git is properly installed and to create a working directory for GitHub, you will need to know a bit of shell -- brief crash course below.

Crash Course on Shell

The Unix shell has been around longer than most of its users have been alive. It has survived so long because it’s a power tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren’t typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources (including “high-performance computing” supercomputers).

This section is an abbreviated form of Software Carpentry’s The Unix Shell for Novice’s workshop lesson series. Content and wording (including all the above) is heavily copied and credit is due to those creators (full author list).

Our goal with shell is to:

• Set up the directory where we will store all of the GitHub repositories during the Institute,
• Make sure Git is installed correctly, and
• Gain comfort using bash so that we can use it to work with Git & GitHub.

Accessing Shell

How one accesses the shell depends on the operating system being used.

• OS X: The bash program is called Terminal. You can search for it in Spotlight.
• Windows: Git Bash came with your download of Git for Windows. Search Git Bash.
• Linux: Default is usually bash, if not, type bash in the terminal.

Bash Commands

$ 

The dollar sign is a prompt, which shows us that the shell is waiting for input; your shell may use a different character as a prompt and may add information before the prompt.

When typing commands, either from these tutorials or from other sources, do not type the prompt ($), only the commands that follow it. In these tutorials, subsequent lines that follow a prompt and do not start with $ are the output of the command.

listing contents - ls

Next, let's find out where we are by running a command called pwd -- print working directory. At any moment, our current working directory is our current default directory. I.e., the directory that the computer assumes we want to run commands in unless we explicitly specify something else. Here, the computer's response is /Users/neon, which is NEON’s home directory:

$ pwd

/Users/neon

If you are not, by default, in your home directory, you get there by typing:

$ cd ~

Now let's learn the command that will let us see the contents of our own file system. We can see what's in our home directory by running ls --listing.

$ ls

Applications   Documents   Library   Music   Public
Desktop        Downloads   Movies    Pictures

(Again, your results may be slightly different depending on your operating system and how you have customized your filesystem.)

ls prints the names of the files and directories in the current directory in alphabetical order, arranged neatly into columns.

Change directory -- cd

Now we want to move into our Documents directory where we will create a directory to host our GitHub repository (to be created in Week 2). The command to change locations is cd followed by a directory name if it is a sub-directory in our current working directory or a file path if not. cd stands for "change directory", which is a bit misleading: the command doesn't change the directory, it changes the shell's idea of what directory we are in.

To move to the Documents directory, we can use the following series of commands to get there:

$ cd Documents

These commands will move us from our home directory into our Documents directory. cd doesn't print anything, but if we run pwd after it, we can see that we are now in /Users/neon/Documents.

If we run ls now, it lists the contents of /Users/neon/Documents, because that's where we now are:

$ pwd

/Users/neon/Documents

$ ls


data/  elements/  animals.txt  planets.txt  sunspot.txt

To use cd, you need to be familiar with paths, if not, read the section on Full, Base, and Relative Paths .

Make a directory -- mkdir

Now we can create a new directory called GitHub that will contain our GitHub repositories when we create them later. We can use the command mkdir NAME-- “make directory”

$ mkdir GitHub

There is not output.

Since GitHub is a relative path (i.e., doesn't have a leading slash), the new directory is created in the current working directory:

$ ls

data/  elements/  GitHub/  animals.txt  planets.txt  sunspot.txt

Is Git Installed Correctly?

All of the above commands are bash commands, not Git specific commands. We still need to check to make sure git installed correctly. One of the easiest ways is to check to see which version of git we have installed.

Git commands start with git. We can use git --version to see which version of Git is installed

$ git --version

git version 2.5.4 (Apple Git-61)

If you get a git version number, then Git is installed!

If you get an error, Git isn’t installed correctly. Reinstall and repeat.

Setup Git Global Configurations

Now that we know Git is correctly installed, we can get it set up to work with.

The text below is modified slightly from Software Carpentry's Setting up Git lesson.

When we use Git on a new computer for the first time, we need to configure a few things. Below are a few examples of configurations we will set as we get started with Git:

• our name and email address,
• to colorize our output,
• what our preferred text editor is,
• and that we want to use these settings globally (i.e. for every project)

On a command line, Git commands are written as git verb, where verb is what we actually want to do.

Set up you own git with the following command, using your own information instead of NEON's.

$ git config --global user.name "NEON Science"
$ git config --global user.email "neon@BattelleEcology.org"
$ git config --global color.ui "auto"

Then set up your favorite text editor following this table:

The four commands we just ran above only need to be run once: the flag --global tells Git to use the settings for every project in your user account on this computer.

You can check your settings at any time:

$ git config --list

You can change your configuration as many times as you want; just use the same commands to choose another editor or update your email address.

Now that Git is set up, you will be ready to start the Week 2 materials to learn about version control and how Git & GitHub work.

Install HDFView

The free HDFView application allows you to explore the contents of an HDF5 file.

To install HDFView:

1. Click to go to the download page.

2. From the section titled HDF-Java 2.1x Pre-Built Binary Distributions select the HDFView download option that matches the operating system and computer setup (32 bit vs 64 bit) that you have. The download will start automatically.

3. Open the downloaded file.

• Mac - You may want to add the HDFView application to your Applications directory.
• Windows - Unzip the file, open the folder, run the .exe file, and follow directions to complete installation.

4. Open HDFView to ensure that the program installed correctly.

Install QGIS

QGIS is a free, open-source GIS program. Installation is optional for the 2018 Data Institute. We will not directly be working with QGIS, however, some past participants have found it useful to have during the capstone projects.

To install QGIS:

Download the QGIS installer on the QGIS download page here. Follow the installation directions below for your operating system.

Windows

1. Select the appropriate QGIS Standalone Installer Version for your computer.
2. The download will automatically start.
3. Open the .exe file and follow prompts to install (installation may take a while).
4. Open QGIS to ensure that it is properly downloaded and installed.

Mac OS X

1. Select KyngChaos QGIS download page. This will take you to a new page.
2. Select the current version of QGIS. The file download (.dmg format) should start automatically.
3. Once downloaded, run the .dmg file. When you run the .dmg, it will create a directory of installer packages that you need to run in a particular order. IMPORTANT: read the READ ME BEFORE INSTALLING.rtf file!

Install the packages in the directory in the order indicated.

1. GDAL Complete.pkg
2. NumPy.pkg
3. matplotlib.pkg
4. QGIS.pkg - NOTE: you need to install GDAL, NumPy and matplotlib in order to successfully install QGIS on your Mac!

Once all of the packages are installed, open QGIS to ensure that it is properly installed.

LINUX

1. Select the appropriate download for your computer system.
2. Note: if you have previous versions of QGIS installed on your system, you may run into problems. Check out

Here we will provide an overview of the National Ecological Observatory Network (NEON). Please carefully read through these materials and links that discuss NEON’s mission and design.

The NEON Project Mission & Design

To capture ecological heterogeneity across the United States, NEON’s design divides the continent into 20 statistically different eco-climatic domains. Each NEON field site is located within an eco-climatic domain.

The Science and Design of NEON

To gain a better understanding of the broad scope fo NEON watch this 4 minute long video.

Please, read the following page about NEON's mission.

NEON's Spatial Design

The Spatial Design of NEON

Watch this 4:22 minute video exploring the spatial design of NEON field sites.

Please read the following page about NEON's Spatial Design:

Read this primer on NEON's Sampling Design

Read about the different types of field sites - core and relocatable

NEON Field Site Locations

Explore the NEON Field Site map taking note of the locations of

1. Aquatic & terrestrial field sites.
2. Core & relocatable field sites.

Explore the NEON field site map. Do the following:

• Zoom in on a study area of interest to see if there are any NEON field sites that are nearby.
• Use the menu below the map to filter sites by name, type, domain, or state.
• Select one field site of interest.
  • Click on the marker in the map.
  • Then click on Site Details to jump to the field site landing page.

NEON Data

How NEON Collects Data

Watch this 3:06 minute video exploring the data that NEON collects.

Read the Data Collection Methods page to learn more about the different types of data that NEON collects and provides. Then, follow the links below to learn more about each collection method:

• Aquatic Observation System (AOS)
• Aquatic Instrument System (AIS)
• Terrestrial Instrument System (TIS) -- Flux Tower
• Terrestrial Instrument System (TIS) -- Soil Sensors and Measurements
• Terrestrial Organismal System (TOS)
• Airborne Observation Platform (AOP)

All data collection protocols and processing documents are publicly available. Read more about the standardized protocols and how to access these documents.

Specimens & Samples

NEON also collects samples and specimens from which the other data products are based. These samples are also available for research and education purposes. Learn more: NEON Biorepository.

Airborne Remote Sensing

Watch this 5 minute video to better understand the NEON Airborne Observation Platform (AOP).

Access NEON Data

NEON data are processed and go through quality assurance quality control checks at NEON headquarters in Boulder, CO. NEON carefully documents every aspect of sampling design, data collection, processing and delivery. This documentation is freely available through the NEON data portal.

• Visit the NEON Data Portal - data.neonscience.org
• Read more about the quality assurance and quality control processes for NEON data and how the data are processed from raw data to higher level data products.
• Explore NEON Data Products. On the page for each data product in the catalog you can find the basic information about the product, find the data collection and processing protocols, and link directly to downloading the data.
• Additionally, some types of NEON data are also available through the data portals of other organizations. For example, NEON Terrestrial Insect DNA Barcoding Data is available through the Barcode of Life Datasystem (BOLD). Or NEON phenocam images are available from the Phenocam network site. More details on where else the data are available from can be found in the Availability and Download section on the Product Details page for each data product (visit Explore Data Products to access individual Product Details pages).

Pathways to access NEON Data

There are several ways to access data from NEON:

1. Via the NEON data portal. Explore and download data. Note that much of the tabular data is available in zipped .csv files for each month and site of interest. To combine these files, use the neonUtilities package (R tutorial, Python tutorial).
2. Use R or Python to programmatically access the data. NEON and community members have created code packages to directly access the data through an API. Learn more about the available resources by reading the Code Resources page or visiting the NEONScience GitHub repo.
3. Using the NEON API. Access NEON data directly using a custom API call.
4. Access NEON data through partner's portals. Where NEON data directly overlap with other community resources, NEON data can be accessed through the portals. Examples include Phenocam, BOLD, Ameriflux, and others. You can learn more in the documentation for individual data products.

Verifiability and reproducibility are among the cornerstones of the scientific process. They are what allows scientists to "stand on the shoulder of giants". Maintaining reproducibility requires that all data management, analysis, and visualization steps behind the results presented in a paper are documented and available in full detail. Reproducibility here means that someone else should either be able to obtain the same results given all the documented inputs and the published instructions for processing them, or if not, the reasons why should be apparent. From Reproducible Science Curriculum

Getting Started with Reproducible Science

Please view the online slide-show below which summarizes concepts taught in the Reproducible Science Curriculum.

View Reproducible Science Slideshow

A Gap In Understanding

Reproducibility and Your Research

How reproducible is your current research?

View Reproducible Science Checklist

Additional Readings (optional)

• Nature has collated and published (with open-access) a special archive on the Challenges of Irreproducible Science .
• The Nature Publishing group has also created a Reporting Checklist for its authors that focuses primaily on reporting issues but also includes sections for sharing code.
• Recent open-access issue of Ecography focusing on reproducible ecology and software packages available for use.
• A nice short blog post with an annotated bibliography of "Top 10 papers discussing reproducible research in computational science" from Lorena Barba: Barba group reproducibility syllabus.

DUE: 21 June 2018

During the NEON Data Institute, you will share the code that you create daily with everyone on the NEONScience/DI-NEON-participants repo.

Through this week’s tutorials, you have learned the basic skills needed to successfully share your work at the Institute including how to:

• Create your own GitHub user account,
• Set up Git on your computer (please do this on the computer you will be bringing to the Institute), and
• Create a Markdown file with a biography of yourself and the project you are interested in working on at the Institute. This biography was shared with the group via the Data Institute’s GitHub repo.

Checklist for this week’s Assignment:

You should have completed the following after Pre-institute week 2:

• Fork & clone the NEON-DataSkills/DI-NEON-participants repo.
• Create a .md file in the participants/2018-RemoteSensing/pre-institute2-git directory of the repo. Name the document LastName-FirstName.md.
• Write a biography that introduces yourself to the other participants. Please provide basic information including:
  • name,
  • domain of interest,
  • one goal for the course,
  • an updated version of your Capstone Project idea,
  • and the list of data (NEON or other) to support the project that you created during last week’s materials.
• Push the document from your local computer to your GithHub repo.
• Created a Pull Request to merge this document back into the NEON-DataSkills/DI-NEON-participants repo.

NOTE: The Data Institute repository is a public repository, so all members of the Institute, as well as anyone in the general public who stumbles on the repo, can see the information. If you prefer not to share this information publicly, please submit the same document but use a pseudonym (cartoon character names would work well) and email us with the pseudonym so that we can connect the submitted document to you.

Have questions? No problem. Leave your question in the comment box below. It's likely some of your colleagues have the same question, too! And also likely someone else knows the answer.