![]() ![]() Many neuroscience labs working on extracellular recordings had been using a file format for almost two decades. You can add metadata to groups, whereas file systems don't support this.HDF5 datasets have a rigid structure: they are all homogeneous (hyper)rectangular numerical arrays, whereas files in a file system can be anything.However it does depend on the HDF5 library. An HDF5 file is portable: the entire structure is contained in the file and doesn't depend on the underlying file system.However, the HDF Group doesn't seem to like this comparison. File system within a fileĮffectively, you can see HDF5 as a file system within a file, where files are datasets and folders are groups. ![]() HDF5 also supports lossless compression of datasets. If the latter, it is split uniformly in rectangular chunks organized in a B-tree. If the former, the dataset is stored in a contiguous buffer in the file. What's in an HDF5 file?Īn HDF5 file contains a POSIX-like hierarchy of numerical arrays (aka datasets) organized within groups.Ī dataset can be stored in two ways: contiguously or chunked. ![]() Development of HDF5 is done by the HDF Group, a non-profit corporation. The specification is open and the tools are open source. What is HDF5?įor those who haven't come across it, Hierarchical Data Format, or HDF, is a multipurpose hierarchical container format capable of storing large numerical datasets with their metadata. In this post, I'll describe what is HDF5 and what are the issues that made us move away from it. Recently, despite the high costs, we decided to abandon this format in our software. While the choice of HDF5 was looking compelling on paper, we found many issues with it. This includes not only a program but also a new file format based on HDF5 for a specific type of data. In the research lab where I work, we've been developing a data processing pipeline for several years. ![]()
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