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dvha-stats
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|logo|
|build| |Docs| |pypi| |python-version| |lgtm| |lgtm-cq| |Codecov| |lines| |repo-size| |code-style|
A library of prediction and statistical process control tools. Although based
on work in DVH Analytics <http://www.dvhanalytics.com>, all tools in this
library are generic and not specific to radiation oncology. See
our documentation <http://dvha-stats.readthedocs.io> for advanced uses.
MIT license <https://github.com/cutright/DVHA-Stats/blob/master/LICENSE>__Read the docs <https://dvha-stats.readthedocs.io>__scipy <https://scipy.org>__numpy <http://www.numpy.org>__scikit-learn <http://scikit-learn.org>__regressors <https://pypi.org/project/regressors/>__matplotlib <http://matplotlib.org>__PTable <https://github.com/kxxoling/PTable>__.. code-block:: python
>>> from dvhastats.ui import DVHAStats
>>> s = DVHAStats("your_data.csv") # use s = DVHAStats() for test data
>>> s.var_names
['V1', 'V2', 'V3', 'V4', 'V5', 'V6']
>>> s.show('V1') # or s.show(0), can provide index or var_name
|plot|
Multivariate Control Chart (w/ non-normal data) ############################################### .. code-block:: python
>>> ht2_bc = s.hotelling_t2(box_cox=True)
>>> ht2_bc.show()
|hotelling-t2-bc|
Principal Component Analysis (PCA) ################################## .. code-block:: python
>>> pca = s.pca()
>>> pca.show()
|pca|
.. |build| image:: https://github.com/cutright/DVHA-Stats/workflows/build/badge.svg :target: https://github.com/cutright/DVHA-Stats/actions :alt: build .. |pypi| image:: https://img.shields.io/pypi/v/dvha-stats.svg :target: https://pypi.org/project/dvha-stats :alt: PyPI .. |python-version| image:: https://img.shields.io/pypi/pyversions/dvha-stats.svg :target: https://pypi.org/project/dvha-stats :alt: PyPI .. |lgtm-cq| image:: https://img.shields.io/lgtm/grade/python/g/cutright/DVHA-Stats.svg?logo=lgtm&label=code%20quality :target: https://lgtm.com/projects/g/cutright/DVHA-Stats/context:python :alt: lgtm code quality .. |lgtm| image:: https://img.shields.io/lgtm/alerts/g/cutright/DVHA-Stats.svg?logo=lgtm :target: https://lgtm.com/projects/g/cutright/DVHA-Stats/alerts :alt: lgtm .. |Codecov| image:: https://codecov.io/gh/cutright/DVHA-Stats/branch/master/graph/badge.svg :target: https://codecov.io/gh/cutright/DVHA-Stats :alt: Codecov .. |Docs| image:: https://readthedocs.org/projects/dvha-stats/badge/?version=latest :target: https://dvha-stats.readthedocs.io :alt: Documentation Status .. |code-style| image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black :alt: Code style: black
.. |lines| image:: https://img.shields.io/tokei/lines/github/cutright/dvha-stats :target: https://img.shields.io/tokei/lines/github/cutright/dvha-stats :alt: Lines of code
.. |repo-size| image:: https://img.shields.io/github/languages/code-size/cutright/dvha-stats :target: https://img.shields.io/github/languages/code-size/cutright/dvha-stats :alt: Repo Size
.. |plot| image:: https://user-images.githubusercontent.com/4778878/91908372-0c4c2d80-ec71-11ea-9dfc-7c4f6c209542.png :width: 350 :alt: Basic Plot
.. |hotelling-t2-bc| image:: https://user-images.githubusercontent.com/4778878/91908394-179f5900-ec71-11ea-88a0-9c95d714fb4c.png :width: 350 :alt: Multivariate Control Chart w/ Box Cox Transformation
.. |pca| image:: https://user-images.githubusercontent.com/4778878/92050205-16922880-ed52-11ea-9967-d390577380b6.png :width: 350 :alt: Principal Component Analysis
.. |logo| image:: https://user-images.githubusercontent.com/4778878/92505112-351c7780-f1c9-11ea-9b5c-0de1ad2d131d.png :width: 400 :alt: DVHA logo
FAQs
A library of prediction and statistical process control tools
We found that dvha-stats demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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