Skip to main content

Convert Beker&Hickl, PicoQuant and other formats to Photon-HDF5.

Project description

Tests

phconvert

phconvert is a python 3 library that helps writing valid Photon-HDF5 files, a file format for time stamp-based single-molecule spectroscopy. Additionally, phconvert can convert to Photon-HDF5 all the common binary formats used in solution-based single-molecule spectroscopy. These includes PicoQuant's .HT3/.PT3/.PTU/.T3R, Becker & Hickl's .SPC/.SET and the .SM format used by WeissLab and others for µs-ALEX smFRET.

For questions or issues running this software please use the Photon-HDF5 Google Group or open an issue on GitHub.

What's new

Feb. 2025: PhConvert 0.10 released

Nov. 2018: Phconvert 0.9 released, see the release notes.

Quick-start: Converting files to Photon-HDF5

Converting one of the supported files formats to Photon-HDF5 does not require being able to program in python. All you need is running the "notebook" corresponding to the file format you want to convert from, and follow the instructions therein.

For demonstration purposes, we provide a demo service to run the notebooks online without any installation. With this online service, you can convert data files up to 35MB to Photon-HDF5. To launch the demo click on the following button (see also instructions):

Binder

To execute the phconvert notebooks on your machine, you need to install the Jupyter Notebook App first. A quick-start guide on installing and running the Jupyter Notebook App is available here:

Next, you need to install the phconvert library with the following command (type it in Terminal on OS X or Linux, or in the cmd prompt on Windows):

conda install -c conda-forge phconvert

Finally, you can download one of the provided notebooks and run it on your machine. Simply, download the phconvert zip, which contains all the notebooks in the notebooks subfolder.

For questions or issues:

Project details

What's inside?

phconvert repository contains a python package (library) and a set of notebooks (online viewer). Each notebook can convert a different format to Photon-HDF5 using the phconvert library.

If you have a file format that is not yet supported, please open an new Issue. We are willing add support for as many file formats as possible!

Why phconvert?

When writing Photon-HDF5 files, phconvert saves you time and protects you against common errors that risk to make the file not a valid Photon-HDF5. Also a description is automatically added to each Photon-HDF5 field. The descriptions are extracted from a JSON file which contains the list Photon-HDF5 field names, types, and descriptions.

See also Writing Photon-HDF5 files in the Photon-HDF5 reference documentation.

Read Photon-HDF5 files

In case you just want to read Photon-HDF5 files you don't need to use phconvert. Photon-HDF5 files can be directly opened with a standard HDF5 viewer HDFView.

See also Reading Photon-HDF5 files in the Photon-HDF5 reference documentation.

Installation

The recommended way to install phconvert is using conda:

conda install -c conda-forge phconvert

If you don't have conda installed, please install the free python distribution Anaconda choosing the python 3 version. Starting from version 0.9, the aging python 2.7 is not supported anymore.

Alternatively, you can install phconvert in any python installation using PIP:

pip install phconvert

In this latter case, make sure that numpy and pytables are installed.

See also:

Dependencies

  • python 3.4 or greater (3.6+ recommended)
  • numpy >=1.9
  • pytables >=3.1
  • numba (optional) for faster PicoQuant files decoding

Note when installing via conda all the dependencies are automatically installed.

The phconvert library documentation (for developers)

The phconvert API documentation can be found on ReadTheDocs:

License

phconvert is released under the open source MIT license.

Contributing

As with other Photon-HDF5 subprojects, we encourage contributions in any form, from simple suggestions, typo fix to the addition of new features. Please use GitHub by opening Issues or sending Pull Requests.

All the contributors will be acknowledged in this website, and will included as authors in the next software-paper publication.

For more details see our contribution policy.

Authors & Contributors

List of contributors:

  • Antonino Ingargiola (@tritemio)
  • Ted Laurence (@talaurence)
  • Marco Lamperti (@lampo808) <marco.lampo AT gmail.com>
  • Xavier Michalet (@smXplorer)
  • Anders Barth (@AndersBarth) <anders.barth AT gmail.com>
  • Biswajit Pradhan (@biswajitSM) <biswajitp145 AT gmail.com.
  • Sébastien Weber (@seb5g) <sebastien.weber AT cemes.fr>
  • David Palmer (@dmopalmer)

We thank also @ncodina for providing PTU files and helping in testing the PTU decoder in phconvert.

Acknowledgements

This work was supported by NIH Grant R01-GM95904.

Release 0.9 was supported by Prof. Eitan Lerner.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

phconvert-0.10.1.tar.gz (213.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

phconvert-0.10.1-py3-none-any.whl (83.7 kB view details)

Uploaded Python 3

File details

Details for the file phconvert-0.10.1.tar.gz.

File metadata

  • Download URL: phconvert-0.10.1.tar.gz
  • Upload date:
  • Size: 213.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for phconvert-0.10.1.tar.gz
Algorithm Hash digest
SHA256 e4a946923770a246ec010c0b18c1d596db0062bc0235c57e7a5874ce61ba56dd
MD5 ff41063b99970980b76e3dd88c4a35a9
BLAKE2b-256 ea42c5f73dbc4e138a7fe13af0fdbcb83986f94f3ddb896169a41f1e0294539b

See more details on using hashes here.

File details

Details for the file phconvert-0.10.1-py3-none-any.whl.

File metadata

  • Download URL: phconvert-0.10.1-py3-none-any.whl
  • Upload date:
  • Size: 83.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for phconvert-0.10.1-py3-none-any.whl
Algorithm Hash digest
SHA256 2811693459f04cf5a53f12e3752f9b483bba4a3b929bdd9a3741e72374fb9c7b
MD5 67fd230959ec49355781a4e7589838fd
BLAKE2b-256 653944b25972b1a076b8264b4867f435787a2a1cbf2649f25c92d4a78f167359

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page