![]() ![]() ![]() For the C-API, it is usually the programmer’s responsibility to close manually an HDF5-ID that is being used by calling the appropriate “close” function. ![]() In this package, the C-API of HDF5 is being used. They key information can usually also be extracted with one of the “higher-level” methods shown above, but sometimes the info methods are more efficient.Ĥ.1 Closing of unused ids and garbage collection ![]() This function is usually not of interest to the casual user It can only be applied to an object of class H5File. file_info: It extracts relatively technical information about a file.get_obj_name: Similar as get_file_name, applies to the same object, but returns the path inside the file to the object.get_file_name: For an H5File or H5Group, H5D or H5T (where D is for dataset and T stands for a committed type) object, returns the name of the file it is in.For very large groups, this way is however more efficient. For the casual user, the most interesting information is the number of items in the group, which can also be retrieved using the names function. get_group_info: Information about the storage type of the group, if a file is mounted to the group and the number of items in the group.The difference between them and how to create them will be discussed further below. get_link_info: For links, mainly yields information on the link type, i.e. hard link or soft link.get_obj_info: Various information on the number of attributes, the type of the object, the reference count, access times (if set to be recorded) and other more technical information.In HDF5, there are also various ways of getting more detailed information about objects. We will end with a technical overview on the underlying implementation.Ģ.2.3 Detailed information about various objects Next, more advanced features will be discussed such as the creation of complex datatypes, datasets with special datatypes, the setting of the various available filters when reading/writing a package etc. In the following sections of this vignette, first a simple example will be given that shows how standard operations are being performed. Tracking and closing of unused HDF5 resources is done completely automatically using the R garbage collector.Furthermore, all functions that in HDF5 return C-structs, return a data frame with the same variable names as in the structs (usually used by the various “-info” functions). All HDF5 functions that return constants do this in the format of an extended-factor-variable, giving the constants value as well as the name.All HDF5 constants and datatypes are available under their regular name.It ships with the newest version 1.10.0 of HDF5.Some exceptions are for example functions that expect other C-functions as arguments. The library is almost feature complete, implementing most of the functionality of the HDF5 C-API.All HDF5 classes are implemented using R6 classes, allowing for a very simple way of manipulating objects.User friendly interface that allows access to datasets in the same fashion a user would access regular R arrays.These are also good implementations, but there are several points that make this package here – hdf5r – stand out: As of the writing of this vignette, there are 2 other packages available that also implement an interface to HDF5, h5 on CRAN and rhdf5 on Bioconductor. It supports an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for high volume and complex data.Īs R is very often used to process large amounts of data, having a direct interface to HDF5 is very useful. HDF5 is a data model, library, and file format for storing and managing data. ![]()
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