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data-slicer-1.0.3a1
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مشاهده بیشترتوضیحات
Tools for quick visualization of three dimensional datasets.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | data-slicer-1.0.3a1 |
| نام | data-slicer |
| نسخه کتابخانه | 1.0.3a1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Kevin Kramer |
| ایمیل نویسنده | kevin.kramer@uzh.ch |
| آدرس صفحه اصلی | https://github.com/kuadrat/data_slicer.git |
| آدرس اینترنتی | https://pypi.org/project/data-slicer/ |
| مجوز | - |
# Data slicer
The `data-slicer` package offers fast tools for inspection, visualization,
slicing and analysis of 3(+) dimensional datasets at a general level.
It also provides a framework and building blocks for users to easily create
more specialized and customized tools for their individual use cases.
`data-slicer` was originally developed to deal with the high data throughput of
modern measurement instruments, where quick visualizations and preliminary
analyses are necessary to guide the direction of a measurement session.
However, the package is designed to be agnostic of the concrete use-case and
all scientific, engineering, medical, artistic or other data driven
disciplines where inspection and slicing of (hyper)cubes is required could
potentially benefit from `data-slicer`.
## Documentation
This README just gives a minimal overview.
For more information, guides, examples and more, visit the documentation which is hosted
by the friendly people over at ReadTheDocs.org:
https://data-slicer.readthedocs.io/en/latest/
## Installation
`data-slicer` should run on all platforms that support python and has been
shown to run on Windows, macOS ans Linux.
The package can be installed from [PyPI](https://pypi.org/project/data-slicer/)
using `pip install data_slicer`.
It is recommended to do this from within some sort of virtual environment.
Visit the documentation for more detailed instructions:
https://data-slicer.readthedocs.io/en/latest/installation.html
### Dependencies
This software is built upon on a number of other open-source frameworks.
The complete list of packages can be found in the file `requirements.txt`.
Most notably, this includes [matplotlib](https://matplotlib.org/),
[numpy](https://numpy.org/) and
[pyqtgraph](https://pyqtgraph.readthedocs.io/en/latest/).
## Citing
If you use `data-slicer` in your work, please credit it by citing the following publication:
[](https://doi.org/10.21105/joss.02969)
Kramer et al., (2021). Visualization of Multi-Dimensional Data -- The data-slicer Package. Journal of Open Source Software, 6(60), 2969, https://doi.org/10.21105/joss.02969
## Contributing
You are welcome to help making this software package more useful!
You can do this by giving feedback, reporting bugs, issuing feature requests
or fixing bugs and adding new features yourself.
Furthermore, you can create and share your own plugins (refer to the
[documentation](https://data-slicer.readthedocs.io/en/latest/)).
### Feedback, bugs and feature requests
The most straightforward and organized way to help improve this software is
by opening an **issue** on [the github
repository](https://github.com/kuadrat/data-slicer/issues).
To do this, navigate to the **Issues** tab and click **New issue**.
Please try to describe the bug you encountered or the new feature you would
like to see as detailed as possible.
If you have several bugs/ideas please open a separate issue for each of them
in order to keep the discussions focused.
If you have anything to tell me that does not seem to warrant opening an
issue or you simply prefer to contact me directly you can do this via e-mail:
kevin.pasqual.kramer@protonmail.ch
### Contributing code
If you have fixed a bug or created a new feature in the source code yourself,
it can be merged into this project.
Code contributions will be acknowledged in this README or, if the number of
contributors grows too large, in a separate file.
If you are familiar with the workflow on github, please go ahead and create a
pull request.
If you are unsure you can always contact me via e-mail (see above).
### Plugins
If you have created a PIT plugin, feel free to add it to the list below,
either via pull request or through an e-mail (see above).
Also check the
[documentation](https://data-slicer.readthedocs.io/en/latest/contributing.html)
for a guide on how to create a plugin.
| Plugin Name (link) | Description |
| ------------------ | ----------- |
| [ds-example-plugin](https://github.com/kuadrat/ds-example-plugin) | exists as a minimal example that can be used for guidance when creating your own plugins. A step-by-step tutorial on how it was made can be found in [the documentation](https://data-slicer.readthedocs.io/en/latest/contributing.html) |
| [ds-arpes-plugin](https://github.com/kuadrat/ds_arpes_plugin) | tools for angle-resolved photoelectron spectroscopy (ARPES) |
نیازمندی
| مقدار | نام |
|---|---|
| >=3.1.1a1 | PyOpenGL |
| >=5.13.2 | PyQt5 |
| >=3.1.1 | matplotlib |
| >=1.17.3 | numpy |
| >=0.11.0 | pyqtgraph |
| >=3.3.0 | pytest-qt |
| >=6.2.2 | pytest |
| >=4.6.0 | qtconsole |
نحوه نصب
نصب پکیج whl data-slicer-1.0.3a1:
pip install data-slicer-1.0.3a1.whl
نصب پکیج tar.gz data-slicer-1.0.3a1:
pip install data-slicer-1.0.3a1.tar.gz