Skip to main content

Visualization tools for openPMD files

Project description

openPMD-viewer

pypi version Binder License

Overview

This package contains a set of tools to load and visualize the contents of a set of openPMD files (typically, a timeseries).

The routines of openPMD-viewer can be used in two ways :

  • Use the Python API, in order to write a script that loads the data and produces a set of pre-defined plots.

  • Use the interactive GUI inside the Jupyter Notebook, in order to interactively visualize the data.

Usage

Tutorials

The notebooks in the folder tutorials/ demonstrate how to use both the API and the interactive GUI. You can view these notebooks online here.

Alternatively, you can even run our tutorials online!

You can also download and run these notebooks on your local computer (when viewing the notebooks with the above link, click on Raw to be able to save them to your local computer). In order to run the notebook on your local computer, please install openPMD-viewer first (see below), as well as wget (pip install wget).

Notebook quick-starter

If you wish to use the interactive GUI, the installation of openPMD-viewer provides a convenient executable which automatically creates a new pre-filled notebook and opens it in a browser. To use this executable, simply type in a regular terminal:

openPMD_notebook

(This executable is installed by default, when installing openPMD-viewer.)

Installation

Installation on a local computer

Installation with conda

In order to install openPMD-viewer with conda, please install the Anaconda distribution, and then type

conda install -c conda-forge openpmd-viewer

If you are using JupyterLab, please also install the jupyter-matplotlib extension (See installation instructions here).

Installation with pip

You can also install openPMD-viewer using pip

pip install openpmd-viewer

In addition, if you wish to use the interactive GUI, please type

pip install jupyter

Installation on a remote scientific cluster

If you wish to install the openPMD-viewer on a remote scientific cluster, please make sure that the packages numpy, scipy and h5py are available in your environment. This is typically done by a set of module load commands (e.g. module load h5py) -- please refer to the documentation of your scientific cluster.

Then type

pip install openPMD-viewer --user

Note: The package jupyter is only required for the interactive GUI and thus it does not need to be installed if you are only using the Python API. For NERSC users, access to Jupyter notebooks is provided when logging to https://ipython.nersc.gov.

Contributing to the openPMD-viewer

We welcome contributions to the code! Please read this page for guidelines on how to contribute.

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

openPMD-viewer-1.10.0.tar.gz (63.5 kB view details)

Uploaded Source

Built Distribution

openPMD_viewer-1.10.0-py3-none-any.whl (75.3 kB view details)

Uploaded Python 3

File details

Details for the file openPMD-viewer-1.10.0.tar.gz.

File metadata

  • Download URL: openPMD-viewer-1.10.0.tar.gz
  • Upload date:
  • Size: 63.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for openPMD-viewer-1.10.0.tar.gz
Algorithm Hash digest
SHA256 86d73ea278d30a421d5d7ec3961d19a42f785cef2a0a5618ac8820bab26a358b
MD5 664afddd8215d585c139ad8f7fe40467
BLAKE2b-256 a3afc44e4bbacf2fcf05d4809ab4dc9780c489df7a023ce4a4c544a253f18f84

See more details on using hashes here.

File details

Details for the file openPMD_viewer-1.10.0-py3-none-any.whl.

File metadata

File hashes

Hashes for openPMD_viewer-1.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f3dc7469765f36e18d8e31960a3525fa7255aefa71c3bb00a31ef5a8b523fce5
MD5 621cfbbe73a4472f070e889af274482b
BLAKE2b-256 a5b656b7924d2438f46dda159ae1fbaa5995ab2ea5586ec4e9bc42b9dbcd5b4c

See more details on using hashes here.

Supported by

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