.HDF5 library version mismatched error. The HDF5 header files used to compile this application do not match the version used by the HDF5 library to which this application is linked. Data corruption or segmentation faults may occur if the application continues. Jan 08, 2013 Make a symbolic link “latest” to point to the latest (only, at this point) version installed: lariosadd@hydra hdf5$ sudo ln -s hdf5-1.8.13-linux-x8664-shared latest. Run the h5redeploy script to change the paths in a few scripts.

Learning Objectives

After completing this tutorial, you will be able to:

Understand how HDF5 files can be created and structured in R using the rhdf5 libraries.
Understand the three key HDF5 elements: the HDF5 file itself, groups, and datasets.
Understand how to add and read attributes from an HDF5 file.

Things You’ll Need To Complete This Tutorial

To complete this tutorial you will need the most current version of R and, preferably, RStudio loaded on your computer.

R Libraries to Install:

rhdf5: The rhdf5 package is hosted on Bioconductor not CRAN. Directions for installation are in the first code chunk.

More on Packages in R – Adapted from Software Carpentry.

Data to Download

We will use the file below in the optional challenge activity at the end of this tutorial.

NEON Teaching Data Subset: Field Site Spatial Data

Install Hdf5 Library Windows

These remote sensing data files provide information on the vegetation at the National Ecological Observatory Network's San Joaquin Experimental Range and Soaproot Saddle field sites. The entire dataset can be accessed by request from the NEON Data Portal.

Set Working Directory: This lesson assumes that you have set your working directory to the location of the downloaded and unzipped data subsets.

R Script & Challenge Code: NEON data lessons often contain challenges that reinforce learned skills. If available, the code for challenge solutions is found in thedownloadable R script of the entire lesson, available in the footer of each lesson page.

Additional Resources

Consider reviewing the documentation for the RHDF5 package.

About HDF5

The HDF5 file can store large, heterogeneous datasets that include metadata. It also supports efficient data slicing, or extraction of particular subsets of a dataset which means that you don't have to read large files read into the computers memory / RAM in their entirety in order work with them.

HDF5 in R

To access HDF5 files in R, we will use the rhdf5 library which is part of the Bioconductor suite of R libraries. It might also be useful to install the free HDF5 viewer which will allow you to explore the contents of an HDF5 file using a graphic interface.

First, let's get R setup. We will use the rhdf5 library. To access HDF5 files in R, we will use the rhdf5 library which is part of the Bioconductor suite of R packages. As of May 2020 this package was not yet on CRAN.

Read more about the rhdf5 package here.

Create an HDF5 File in R

Now, let's create a basic H5 file with one group and one dataset in it.

Please Install The Hdf5 Library

Next, let's create some dummy data to add to our H5 file.

Write the sample data to the H5 file.

View a 'dump' of the entire HDF5 file. NOTE: use this command with CAUTION if youare working with larger datasets!

Add Metadata (attributes)

Let's add some metadata (called attributes in HDF5 land) to our dummy temperaturedata. Copytrans 5.606 activation code free. First, open up the file.

Now we can add some attributes to the file.

Working with an HDF5 File in R

Now that we've created our H5 file, let's use it! First, let's have a look at the attributes of the dataset and group in the file.

Once we've extracted data from our H5 file, we can work with itin R.

Challenge: Work with HDF5 Files

Time to practice the skills you've learned. Open up the D17_2013_SJER_vegStr.csv in R.

Install Hdf5 Library

Create a new HDF5 file called vegStructure.
Add a group in your HDF5 file called SJER.
Add the veg structure data to that folder.
Add some attributes the SJER group and to the data.
Now, repeat the above with the D17_2013_SOAP_vegStr csv.
Name your second group SOAP

Hint: read.csv() is a good way to read in .csv files.