Visualization tools for openPMD files
Project description
openPMD-viewer
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file openpmd_viewer-1.11.0.tar.gz
.
File metadata
- Download URL: openpmd_viewer-1.11.0.tar.gz
- Upload date:
- Size: 63.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 875fa81acf96cef12410b38793d39c1e0270ce63a94295f40a65bc83d8bbb427 |
|
MD5 | 4465ceeded7f36d8fdc5d5c64e8f37d5 |
|
BLAKE2b-256 | d63827a56b84a3f19b48937a9c445e47cacb358182175c630dc4e62e22cc4421 |
Provenance
The following attestation bundles were made for openpmd_viewer-1.11.0.tar.gz
:
Publisher:
publish-to-pypi.yml
on openPMD/openPMD-viewer
-
Statement type:
https://in-toto.io/Statement/v1
- Predicate type:
https://docs.pypi.org/attestations/publish/v1
- Subject name:
openpmd_viewer-1.11.0.tar.gz
- Subject digest:
875fa81acf96cef12410b38793d39c1e0270ce63a94295f40a65bc83d8bbb427
- Sigstore transparency entry: 148482992
- Sigstore integration time:
- Predicate type:
File details
Details for the file openPMD_viewer-1.11.0-py3-none-any.whl
.
File metadata
- Download URL: openPMD_viewer-1.11.0-py3-none-any.whl
- Upload date:
- Size: 75.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 41b2ad4b610022fe1b8ae1b26c276a10d0992d07ce5d5dca3a609ed8fb20c9a1 |
|
MD5 | 43c9d0b1d820715c442000a499c39821 |
|
BLAKE2b-256 | d64e97374d9b47e1cb6aaccd8b86a0552c742a704f0bc89a2b073a83409c10b8 |
Provenance
The following attestation bundles were made for openPMD_viewer-1.11.0-py3-none-any.whl
:
Publisher:
publish-to-pypi.yml
on openPMD/openPMD-viewer
-
Statement type:
https://in-toto.io/Statement/v1
- Predicate type:
https://docs.pypi.org/attestations/publish/v1
- Subject name:
openpmd_viewer-1.11.0-py3-none-any.whl
- Subject digest:
41b2ad4b610022fe1b8ae1b26c276a10d0992d07ce5d5dca3a609ed8fb20c9a1
- Sigstore transparency entry: 148482993
- Sigstore integration time:
- Predicate type: