Update urls following repo move (#657)

* Update urls following repo move * Fix formatting with black
qiskit-community · Jun 9, 2023 · 0902988 · 0902988
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diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
@@ -233,7 +233,7 @@ jobs:
           # get current version
           version=$(pip show qiskit-machine-learning | awk -F. '/^Version:/ { print substr($1,10), $2-1 }' OFS=.)
           # download stable version
-          wget https://codeload.github.com/Qiskit/qiskit-machine-learning/zip/stable/$version -O /tmp/repo.zip
+          wget https://codeload.github.com/qiskit-community/qiskit-machine-learning/zip/stable/$version -O /tmp/repo.zip
           unzip /tmp/repo.zip -d /tmp/
           # copy stable tutorials to main tutorials
           cp -R /tmp/qiskit-machine-learning-stable-$version/docs/tutorials/* docs/tutorials

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -242,7 +242,7 @@ particular will be located at `docs/_build/html/release_notes.html`
 ## Installing Qiskit Machine Learning from source
 
 Please see the [Installing Qiskit Machine Learning from
-Source](https://github.com/Qiskit/qiskit-machine-learning#installation)
+Source](https://github.com/qiskit-community/qiskit-machine-learning#installation)
 section of the Qiskit documentation.
 
 Note: Machine Learning depends on Terra, and has optional dependence on Aer and IBM Q Provider, so
@@ -251,7 +251,7 @@ main branches so these should be installed from source too following the instruc
 the same location
 
 Machine Learning also has some other optional dependents see 
-[Machine Learning optional installs](https://github.com/Qiskit/qiskit-machine-learning#optional-installs) for
+[Machine Learning optional installs](https://github.com/qiskit-community/qiskit-machine-learning#optional-installs) for
 further information. Unit tests that require any of the optional dependents will check
 and skip the test if not installed.
 

diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 # Qiskit Machine Learning
 
-[![License](https://img.shields.io/github/license/Qiskit/qiskit-machine-learning.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)<!--- long-description-skip-begin -->[![Build Status](https://github.com/Qiskit/qiskit-machine-learning/workflows/Machine%20Learning%20Unit%20Tests/badge.svg?branch=main)](https://github.com/Qiskit/qiskit-machine-learning/actions?query=workflow%3A"Machine%20Learning%20Unit%20Tests"+branch%3Amain+event%3Apush)[![](https://img.shields.io/github/release/Qiskit/qiskit-machine-learning.svg?style=popout-square)](https://github.com/Qiskit/qiskit-machine-learning/releases)[![](https://img.shields.io/pypi/dm/qiskit-machine-learning.svg?style=popout-square)](https://pypi.org/project/qiskit-machine-learning/)[![Coverage Status](https://coveralls.io/repos/github/Qiskit/qiskit-machine-learning/badge.svg?branch=main)](https://coveralls.io/github/Qiskit/qiskit-machine-learning?branch=main)<!--- long-description-skip-end -->
+[![License](https://img.shields.io/github/license/Qiskit/qiskit-machine-learning.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)<!--- long-description-skip-begin -->[![Build Status](https://github.com/qiskit-community/qiskit-machine-learning/workflows/Machine%20Learning%20Unit%20Tests/badge.svg?branch=main)](https://github.com/qiskit-community/qiskit-machine-learning/actions?query=workflow%3A"Machine%20Learning%20Unit%20Tests"+branch%3Amain+event%3Apush)[![](https://img.shields.io/github/release/Qiskit/qiskit-machine-learning.svg?style=popout-square)](https://github.com/qiskit-community/qiskit-machine-learning/releases)[![](https://img.shields.io/pypi/dm/qiskit-machine-learning.svg?style=popout-square)](https://pypi.org/project/qiskit-machine-learning/)[![Coverage Status](https://coveralls.io/repos/github/Qiskit/qiskit-machine-learning/badge.svg?branch=main)](https://coveralls.io/github/Qiskit/qiskit-machine-learning?branch=main)<!--- long-description-skip-end -->
 
 Qiskit Machine Learning introduces fundamental computational building blocks - such as Quantum Kernels
 and Quantum Neural Networks - used in different applications, including classification and regression.
@@ -147,11 +147,11 @@ of quantum machine learning.
 ## Contribution Guidelines
 
 If you'd like to contribute to Qiskit, please take a look at our
-[contribution guidelines](https://github.com/Qiskit/qiskit-machine-learning/blob/main/CONTRIBUTING.md).
-This project adheres to Qiskit's [code of conduct](https://github.com/Qiskit/qiskit-machine-learning/blob/main/CODE_OF_CONDUCT.md).
+[contribution guidelines](https://github.com/qiskit-community/qiskit-machine-learning/blob/main/CONTRIBUTING.md).
+This project adheres to Qiskit's [code of conduct](https://github.com/qiskit-community/qiskit-machine-learning/blob/main/CODE_OF_CONDUCT.md).
 By participating, you are expected to uphold this code.
 
-We use [GitHub issues](https://github.com/Qiskit/qiskit-machine-learning/issues) for tracking requests and bugs. Please
+We use [GitHub issues](https://github.com/qiskit-community/qiskit-machine-learning/issues) for tracking requests and bugs. Please
 [join the Qiskit Slack community](https://qisk.it/join-slack)
 and for discussion and simple questions.
 For questions that are more suited for a forum, we use the **Qiskit** tag in [Stack Overflow](https://stackoverflow.com/questions/tagged/qiskit).
@@ -160,11 +160,11 @@ For questions that are more suited for a forum, we use the **Qiskit** tag in [St
 
 Machine Learning was inspired, authored and brought about by the collective work of a team of researchers.
 Machine Learning continues to grow with the help and work of
-[many people](https://github.com/Qiskit/qiskit-machine-learning/graphs/contributors), who contribute
+[many people](https://github.com/qiskit-community/qiskit-machine-learning/graphs/contributors), who contribute
 to the project at different levels.
 If you use Qiskit, please cite as per the provided
 [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib).
 
 ## License
 
-This project uses the [Apache License 2.0](https://github.com/Qiskit/qiskit-machine-learning/blob/main/LICENSE.txt).
+This project uses the [Apache License 2.0](https://github.com/qiskit-community/qiskit-machine-learning/blob/main/LICENSE.txt).
diff --git a/docs/_templates/theme_variables.jinja b/docs/_templates/theme_variables.jinja
diff --git a/docs/conf.py b/docs/conf.py
@@ -72,9 +72,7 @@
         __"""
 
 vers = version.split(".")
-link_str = (
-    f" https://github.com/Qiskit/qiskit-machine-learning/blob/stable/{vers[0]}.{vers[1]}/docs/"
-)
+link_str = f" https://github.com/qiskit-community/qiskit-machine-learning/blob/stable/{vers[0]}.{vers[1]}/docs/"
 nbsphinx_prolog += link_str + "{{ docname }}"
 
 # -- General configuration ---------------------------------------------------

diff --git a/docs/getting_started.rst b/docs/getting_started.rst
@@ -62,7 +62,7 @@ See :ref:`optional_installs` for more information.
 
           .. code:: sh
 
-             git clone https://github.com/Qiskit/qiskit-machine-learning.git
+             git clone https://github.com/qiskit-community/qiskit-machine-learning.git
 
        2. Cloning the repository creates a local folder called ``qiskit-machine-learning``.
 

diff --git a/docs/index.rst b/docs/index.rst
@@ -77,7 +77,7 @@ Next Steps
     Tutorials <tutorials/index>
     API Reference <apidocs/qiskit_machine_learning>
     Release Notes <release_notes>
-    GitHub <https://github.com/Qiskit/qiskit-machine-learning>
+    GitHub <https://github.com/qiskit-community/qiskit-machine-learning>
 
 
 

diff --git a/docs/tutorials/03_quantum_kernel.ipynb b/docs/tutorials/03_quantum_kernel.ipynb
@@ -65,7 +65,7 @@
     "* $\\phi(\\vec{x})$ is the quantum feature map\n",
     "* $\\left| \\langle a|b \\rangle \\right|^{2}$ denotes the overlap of two quantum states $a$ and $b$\n",
     "\n",
-    "Quantum kernels can be plugged into common classical kernel learning algorithms such as SVMs or clustering algorithms, as you will see in the examples below. They can also be leveraged in new quantum kernel methods like `QSVC` [class](https://qiskit.org/documentation/machine-learning/stubs/qiskit_machine_learning.algorithms.QSVC.html) provided by `qiskit-machine-learning` which is explored in this tutorial, and other methods as shown in later tutorials on [Pegasos QSVC](https://github.com/Qiskit/qiskit-machine-learning/blob/main/docs/tutorials/07_pegasos_qsvc.ipynb) and [QKA](https://github.com/Qiskit/qiskit-machine-learning/blob/main/docs/tutorials/08_quantum_kernel_trainer.ipynb).\n",
+    "Quantum kernels can be plugged into common classical kernel learning algorithms such as SVMs or clustering algorithms, as you will see in the examples below. They can also be leveraged in new quantum kernel methods like `QSVC` [class](https://qiskit.org/documentation/machine-learning/stubs/qiskit_machine_learning.algorithms.QSVC.html) provided by `qiskit-machine-learning` which is explored in this tutorial, and other methods as shown in later tutorials on [Pegasos QSVC](https://github.com/qiskit-community/qiskit-machine-learning/blob/main/docs/tutorials/07_pegasos_qsvc.ipynb) and [QKA](https://github.com/qiskit-community/qiskit-machine-learning/blob/main/docs/tutorials/08_quantum_kernel_trainer.ipynb).\n",
     "\n",
     "***\n",
     "\n",
@@ -229,7 +229,7 @@
     "\n",
     "The next step is to create a quantum kernel instance that will help classify this data. \n",
     "\n",
-    "We use the `FidelityQuantumKernel` [class](https://github.com/Qiskit/qiskit-machine-learning/blob/main/qiskit_machine_learning/kernels/fidelity_quantum_kernel.py), and pass two input arguments to its constructor: \n",
+    "We use the `FidelityQuantumKernel` [class](https://github.com/qiskit-community/qiskit-machine-learning/blob/main/qiskit_machine_learning/kernels/fidelity_quantum_kernel.py), and pass two input arguments to its constructor: \n",
     "\n",
     "1. `feature_map`: in this case, a two-qubit `ZZFeatureMap` [instance](https://qiskit.org/documentation/stubs/qiskit.circuit.library.ZZFeatureMap.html).\n",
     "\n",

diff --git a/setup.py b/setup.py
@@ -44,7 +44,7 @@
     description='Qiskit Machine Learning: A library of quantum computing machine learning experiments',
     long_description=README,
     long_description_content_type="text/markdown",
-    url='https://github.com/Qiskit/qiskit-machine-learning',
+    url='https://github.com/qiskit-community/qiskit-machine-learning',
     author='Qiskit Machine Learning Development Team',
     author_email='[email protected]',
     license='Apache-2.0',
@@ -73,9 +73,9 @@
         'sparse': ["sparse"],
     },
     project_urls={
-        "Bug Tracker": "https://github.com/Qiskit/qiskit-machine-learning/issues",
+        "Bug Tracker": "https://github.com/qiskit-community/qiskit-machine-learning/issues",
         "Documentation": "https://qiskit.org/ecosystem/machine-learning/",
-        "Source Code": "https://github.com/Qiskit/qiskit-machine-learning",
+        "Source Code": "https://github.com/qiskit-community/qiskit-machine-learning",
     },
     zip_safe=False
 )