First test

[jpivarski]

How can I convert an HDF5 file into a ROOT file?

[hep-helper[bot]]

Potentially useful sources

30 January, 2024: GitHub issue scikit-hep/uproot5#257, writing std::vector in TTree output

Score: 75 out of 100

The conversation discusses different options for converting an HDF5 file to a ROOT file, including using Uproot3, PyROOT, and RDataFrame in PyROOT. It also mentions that writing ROOT files with unsigned integers will be included in the upcoming release. Look for examples of using Uproot3 to write basic TTrees and jagged arrays, as well as information on RDataFrame and RNumpyDS in PyROOT. These examples can help you understand how to convert your HDF5 file to a ROOT file.

10 July, 2022: GitHub discussion scikit-hep/uproot5#649, Appending data in a TTree object

Score: 60 out of 100

The conversation provides information about using HDF5 as an alternative to ROOT files for storing data, which could be useful for your question about converting an HDF5 file into a ROOT file. Look for references to HDF5, h5cpp, h5py, and the benefits of using HDF5 for data storage. While the conversation doesn't directly address converting an HDF5 file to a ROOT file, the information on HDF5 could be helpful in understanding the differences between the two formats.

26 January, 2024: GitHub discussion scikit-hep/uproot5#1106, TTree performance improvements advice needed

Score: 40 out of 100

The conversation contains information about reading data from a ROOT file using Uproot and creating histograms, which can be helpful when dealing with ROOT files. While it doesn't directly address converting an HDF5 file to a ROOT file, the discussion on handling arrays and writing histograms to a ROOT file can provide insights into working with different data formats. Look for examples of reading arrays from a ROOT file, creating histograms, and writing them to a new ROOT file to understand the process of handling data in different formats.

5 December, 2019: GitHub discussion scikit-hep/awkward#29, Pulling Awkward Arrays from or pushing them to Zarr (and maybe other storage mechanisms)

Score: 40 out of 100

The conversation contains information about converting data between different storage formats, such as npy/npz, Zarr, HDF5, Arrow, and Parquet. While it doesn't directly address converting from HDF5 to ROOT, it provides insights into handling data in different formats, which could be helpful in understanding the general process of data conversion. Look for examples of unpacking and repacking data structures when discussing different storage formats, as this can provide a basis for understanding the conversion process.

30 August, 2021: GitHub issue scikit-hep/uproot5#25, Thoughts about porting Uproot3 writing to Uproot4

Score: 40 out of 100

The conversation discusses writing data to ROOT files, which is related to converting HDF5 to ROOT. Look for examples of handling data serialization and writing to ROOT files, as this knowledge can be applied to converting HDF5 files to ROOT. While not directly addressing the conversion process, the conversation provides insights into working with data formats that can be helpful in understanding the conversion process.

15 January, 2024: GitHub discussion scikit-hep/awkward#2954, Write to HDF5 (optionally read) but from C++

Score: 25 out of 100

The conversation provides information about using Parquet as a more flexible data format compared to HDF5. While it doesn't directly address converting an HDF5 file into a ROOT file, it does mention using HDF5 with Geant4 and provides links to resources for working with Parquet and HDF5 in C++. Look for references to Parquet, Geant4, and working with metadata in the conversation for potential guidance on converting file formats.

[jpivarski]

A reply doesn't trigger it, right?

[jpivarski]

Another comment doesn't trigger it, right?