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Added installation from conda to README
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README.md

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@@ -75,11 +75,10 @@ xladmm, _ = LinearizedADMM(l2, l1, Dop, tau=tau, mu=mu,
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```
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## Why another library for proximal algorithms?
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Several other projects in the Python ecosystem provide implementations of proximal
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operators and/or algorithms, which present some clear overlap with this project.
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A (possibly not exahustive) list of other projects is:
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A (possibly not exhaustive) list of other projects is:
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* http://proximity-operator.net
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* https://github.com/ganguli-lab/proxalgs/blob/master/proxalgs/operators.py
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* **tutorials**: set of python script tutorials to be embedded in documentation using sphinx-gallery
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## Getting started
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You need **Python 3.8 or greater**.
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*Note: Versions prior to v0.3.0 work alsi with Python 3.6 or greater, however they
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*Note: Versions prior to v0.3.0 work also with Python 3.6 or greater, however they
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require scipy version to be lower than v1.8.0.*
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#### From PyPi
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If you want to use PyProximal within your codes,
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you want to use PyProximal within your codes,
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install it in your Python environment by typing the following command in your terminal:
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To get the most out of PyLops straight out of the box, we recommend `conda` to install PyLops:
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```bash
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conda install -c conda-forge pyproximal
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```
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pip install pyproximal
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```
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Open a python terminal and type:
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#### From PyPi
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You can also install pyproximal with `pip`:
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```bash
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pip install pylops
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```
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import pyproximal
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```
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#### From Github
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You can also directly install from the master node (although this is not reccomended)
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Finally, you can also directly install from the main branch (although this is not recommended)
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```
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pip install git+https://[email protected]/PyLops/pyproximal.git@main
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```
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## Contributing
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*Feel like contributing to the project? Adding new operators or tutorial?*
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We advise using the [Anaconda Python distribution](https://www.anaconda.com/download)
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file before getting started.
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### 1. Fork and clone the repository
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Execute the following command in your terminal:
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```

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