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Merge pull request #1870 from edumur/master 

Update README
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@ -23,7 +23,7 @@ heavy leverage of numpy for number crunching, Qt's GraphicsView framework for
Requirements
------------
pyqtgraph has adopted [NEP 29](https://numpy.org/neps/nep-0029-deprecation_policy.html).
PyQtGraph has adopted [NEP 29](https://numpy.org/neps/nep-0029-deprecation_policy.html).
This project supports:
@ -36,16 +36,33 @@ Currently this means:
* Python 3.7+
* Qt 5.12-5.15, 6.1
* Required
* PyQt5, PyQt6, PySide2 or PySide6
* `numpy` 1.17+
* Optional
* `scipy` for image processing
* `pyopengl` for 3D graphics
* `pyopengl` on macOS Big Sur only works with python 3.9.1+
* `hdf5` for large hdf5 binary format support
* `colorcet` for supplemental colormaps
* [`cupy`](https://docs.cupy.dev/en/stable/install.html) for CUDA-enhanced image processing
* On Windows, CUDA toolkit must be >= 11.1
* [PyQt5](https://www.riverbankcomputing.com/software/pyqt/), [PyQt6](https://www.riverbankcomputing.com/software/pyqt/), [PySide2](https://wiki.qt.io/Qt_for_Python) or [PySide6](https://wiki.qt.io/Qt_for_Python)
* [`numpy`](https://github.com/numpy/numpy) 1.17+
Optional added functionalities
------------------------------
Through 3rd part libraries, additional functionality may be added to PyQtGraph, see the table below for a summary.
| Library | Added functionality |
|----------------|-|
| [`scipy`] | <ul><li> Image processing through [`ndimage`]</li><li> Data array filtering through [`signal`] </li><ul> |
| [`pyopengl`] | <ul><li> 3D graphics </li><li> Faster image processing </li><li>Note: on macOS Big Sur only works with python 3.9.1+</li></ul> |
| [`h5py`] | <ul><li> Export in hdf5 format </li></ul> |
| [`colorcet`] | <ul><li> Add a collection of perceptually uniform colormaps </li></ul> |
| [`matplotlib`] | <ul><li> Export of PlotItem in matplotlib figure </li><li> Add matplotlib collection of colormaps </li></ul> |
| [`cupy`] | <ul><li> CUDA-enhanced image processing </li><li> Note: On Windows, CUDA toolkit must be >= 11.1 </li></ul> |
| [`numba`] | <ul><li> Faster image processing </li></ul> |
[`scipy`]: https://github.com/scipy/scipy
[`ndimage`]: https://docs.scipy.org/doc/scipy/reference/ndimage.html
[`signal`]: https://docs.scipy.org/doc/scipy/reference/signal.html
[`pyopengl`]: https://github.com/mcfletch/pyopengl
[`h5py`]: https://github.com/h5py/h5py
[`colorcet`]: https://github.com/holoviz/colorcet
[`matplotlib`]: https://github.com/matplotlib/matplotlib
[`numba`]: https://github.com/numba/numba
[`cupy`]: https://docs.cupy.dev/en/stable/install.html
Qt Bindings Test Matrix
-----------------------
@ -80,7 +97,7 @@ Installation Methods
* Last released version: `conda install -c conda-forge pyqtgraph`
* To install system-wide from source distribution: `python setup.py install`
* Many linux package repositories have release versions.
* To use with a specific project, simply copy the pyqtgraph subdirectory
* To use with a specific project, simply copy the PyQtGraph subdirectory
anywhere that is importable from your project.
Documentation
@ -88,7 +105,7 @@ Documentation
The official documentation lives at [pyqtgraph.readthedocs.io](https://pyqtgraph.readthedocs.io)
The easiest way to learn pyqtgraph is to browse through the examples; run `python -m pyqtgraph.examples` to launch the examples application.
The easiest way to learn PyQtGraph is to browse through the examples; run `python -m pyqtgraph.examples` to launch the examples application.
Used By
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