Update intersphinx links and others (#321) (#324)

Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com> (cherry picked from commit 0db2638) Co-authored-by: Steve Wood <[email protected]>
qiskit-community · Feb 7, 2024 · 4d9a94d · 4d9a94d
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diff --git a/README.md b/README.md
@@ -20,7 +20,7 @@ pip install qiskit-finance
 If you want to work on the very latest work-in-progress versions, either to try features ahead of
 their official release or if you want to contribute to Finance, then you can install from source.
 To do this follow the instructions in the
- [documentation](https://qiskit.org/ecosystem/finance/getting_started.html#installation).
+ [documentation](https://qiskit-community.github.io/qiskit-finance/getting_started.html#installation).
 
 
 ----------------------------------------------------------------------------------------------------
@@ -77,7 +77,7 @@ When running the above the estimated value result should be 2.46 and probability
 ### Further examples
 
 Learning path notebooks may be found in the
-[finance tutorials](https://qiskit.org/ecosystem/finance/tutorials/index.html) section
+[finance tutorials](https://qiskit-community.github.io/qiskit-finance/tutorials/index.html) section
 of the documentation and are a great place to start.
 
 ----------------------------------------------------------------------------------------------------

diff --git a/docs/conf.py b/docs/conf.py
@@ -177,9 +177,9 @@
     "python": ("https://docs.python.org/3", None),
     "numpy": ("https://numpy.org/doc/stable", None),
     "scipy": ("https://docs.scipy.org/doc/scipy", None),
-    "qiskit_algorithms": ("https://qiskit.org/ecosystem/algorithms", None),
-    "qiskit_optimization": ("https://qiskit.org/ecosystem/optimization", None),
-    "qiskit": ("https://qiskit.org/documentation", None),
+    "qiskit_algorithms": ("https://qiskit-community.github.io/qiskit-algorithms", None),
+    "qiskit_optimization": ("https://qiskit-community.github.io/qiskit-optimization", None),
+    "qiskit": ("https://docs.quantum.ibm.com/api/qiskit", None),
 }
 
 html_context = {"analytics_enabled": True}
diff --git a/docs/tutorials/00_amplitude_estimation.ipynb b/docs/tutorials/00_amplitude_estimation.ipynb
@@ -24,7 +24,7 @@
     "    \\mathcal{Q} = \\mathcal{A}\\mathcal{S}_0\\mathcal{A}^\\dagger\\mathcal{S}_{\\Psi_1}\n",
     "$$\n",
     "\n",
-    "where $\\mathcal{S}_0$ and $\\mathcal{S}_{\\Psi_1}$ are reflections about the $|0\\rangle$ and $|\\Psi_1\\rangle$ states, respectively, and phase estimation. However this algorithm, called [AmplitudeEstimation](https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.AmplitudeEstimation.html) in [Qiskit Algorithms](https://qiskit.org/ecosystem/algorithms/), requires large circuits and is computationally expensive. Therefore, other variants of QAE have been proposed, which we will showcase in this tutorial for a simple example.\n",
+    "where $\\mathcal{S}_0$ and $\\mathcal{S}_{\\Psi_1}$ are reflections about the $|0\\rangle$ and $|\\Psi_1\\rangle$ states, respectively, and phase estimation. However this algorithm, called [AmplitudeEstimation](https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.AmplitudeEstimation.html) in [Qiskit Algorithms](https://qiskit-community.github.io/qiskit-algorithms/), requires large circuits and is computationally expensive. Therefore, other variants of QAE have been proposed, which we will showcase in this tutorial for a simple example.\n",
     "\n",
     "In our example, $\\mathcal{A}$ describes a Bernoulli random variable with (assumed to be unknown) success probability $p$:\n",
     "\n",
@@ -127,7 +127,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Qiskit Algorithms implements several QAE algorithms that all derive from the [AmplitudeEstimator](https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.AmplitudeEstimator.html) interface. In the initializer we specify algorithm specific settings and the `estimate` method, which does all the work, takes an [EstimationProblem](https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.EstimationProblem.html) as input and returns an [AmplitudeEstimationResult](https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.AmplitudeEstimatorResult.html) object. Since all QAE variants follow the same interface, we can use them all to solve the same problem instance. \n",
+    "Qiskit Algorithms implements several QAE algorithms that all derive from the [AmplitudeEstimator](https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.AmplitudeEstimator.html) interface. In the initializer we specify algorithm specific settings and the `estimate` method, which does all the work, takes an [EstimationProblem](https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.EstimationProblem.html) as input and returns an [AmplitudeEstimationResult](https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.AmplitudeEstimatorResult.html) object. Since all QAE variants follow the same interface, we can use them all to solve the same problem instance. \n",
     "\n",
     "Next, we'll run all different QAE algorithms. To do so, we first define the estimation problem which will contain the $\\mathcal{A}$ and $\\mathcal{Q}$ operators as well as how to identify the $|\\Psi_1\\rangle$ state, which in this simple example is just $|1\\rangle$."
    ]

diff --git a/docs/tutorials/01_portfolio_optimization.ipynb b/docs/tutorials/01_portfolio_optimization.ipynb
@@ -36,7 +36,7 @@
     "\n",
     "The equality constraint $1^T x = B$ is mapped to a penalty term $(1^T x - B)^2$ which is scaled by a parameter and subtracted from the objective function. \n",
     "The resulting problem can be mapped to a Hamiltonian whose ground state corresponds to  the optimal solution.\n",
-    "This notebook shows how to use the Sampling Variational Quantum Eigensolver (`SamplingVQE`) or the Quantum Approximate Optimization Algorithm (`QAOA`) from [Qiskit Algorithms](https://qiskit.org/ecosystem/algorithms/apidocs/qiskit_algorithms.html#minimum-eigensolvers) to find the optimal solution for a given set of parameters.\n",
+    "This notebook shows how to use the Sampling Variational Quantum Eigensolver (`SamplingVQE`) or the Quantum Approximate Optimization Algorithm (`QAOA`) from [Qiskit Algorithms](https://qiskit-community.github.io/qiskit-algorithms/apidocs/qiskit_algorithms.html#minimum-eigensolvers) to find the optimal solution for a given set of parameters.\n",
     "\n",
     "Experiments on real quantum hardware for this problem are reported for instance in the following paper:\n",
     "<br>\n",

diff --git a/docs/tutorials/02_portfolio_diversification.ipynb b/docs/tutorials/02_portfolio_diversification.ipynb
@@ -163,7 +163,7 @@
     "\n",
     "[4] DJ. Berndt and J. Clifford, *Using dynamic time warping to find patterns in time series*. In KDD workshop 1994  (Vol. 10, No. 16, pp. 359-370).\n",
     "\n",
-    "[5] [Max-Cut and Traveling Salesman Problem](https://qiskit.org/ecosystem/optimization/tutorials/06_examples_max_cut_and_tsp.html)"
+    "[5] [Max-Cut and Traveling Salesman Problem](https://qiskit-community.github.io/qiskit-optimization/tutorials/06_examples_max_cut_and_tsp.html)"
    ]
   },
   {

diff --git a/qiskit_finance/__init__.py b/qiskit_finance/__init__.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2019, 2023.
+# (C) Copyright IBM 2019, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -18,9 +18,9 @@
 
 This is the Qiskit Finance module. It has applications based on
 `Amplitude Estimation
-<https://qiskit.org/ecosystem/algorithms/apidocs/qiskit_algorithms.html#amplitude-estimators>`__
+<https://qiskit-community.github.io/qiskit-algorithms/apidocs/qiskit_algorithms.html#amplitude-estimators>`__
 and optimization using
-`Qiskit Optimization <https://qiskit.org/ecosystem/optimization/>`__,
+`Qiskit Optimization <https://qiskit-community.github.io/qiskit-optimization/>`__,
 some library circuits useful for finance applications,
 and data providers which supply a source of financial data.
 

diff --git a/qiskit_finance/data_providers/_base_data_provider.py b/qiskit_finance/data_providers/_base_data_provider.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2019, 2023.
+# (C) Copyright IBM 2019, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -41,7 +41,7 @@ class BaseDataProvider(ABC):
     Doing so requires that the required driver interface is implemented.
 
     To use the subclasses, please see
-    https://qiskit.org/ecosystem/finance/tutorials/11_time_series.html
+    https://qiskit-community.github.io/qiskit-finance/tutorials/11_time_series.html
 
     """
 

diff --git a/qiskit_finance/data_providers/data_on_demand_provider.py b/qiskit_finance/data_providers/data_on_demand_provider.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2019, 2023.
+# (C) Copyright IBM 2019, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -30,7 +30,7 @@ class DataOnDemandProvider(BaseDataProvider):
     """NASDAQ Data on Demand data provider.
 
     Please see:
-    https://qiskit.org/ecosystem/finance/tutorials/11_time_series.html
+    https://qiskit-community.github.io/qiskit-finance/tutorials/11_time_series.html
     for instructions on use, which involve obtaining a NASDAQ DOD access token.
     """
 

diff --git a/qiskit_finance/data_providers/exchange_data_provider.py b/qiskit_finance/data_providers/exchange_data_provider.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2019, 2023.
+# (C) Copyright IBM 2019, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -27,7 +27,7 @@ class ExchangeDataProvider(BaseDataProvider):
     """Exchange data provider.
 
     Please see:
-    https://qiskit.org/ecosystem/finance/tutorials/11_time_series.html
+    https://qiskit-community.github.io/qiskit-finance/tutorials/11_time_series.html
     for instructions on use, which involve obtaining a Nasdaq Data Link access token.
     """
 

diff --git a/qiskit_finance/data_providers/wikipedia_data_provider.py b/qiskit_finance/data_providers/wikipedia_data_provider.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2019, 2023.
+# (C) Copyright IBM 2019, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -27,7 +27,7 @@ class WikipediaDataProvider(BaseDataProvider):
     """Wikipedia data provider.
 
     Please see:
-    https://qiskit.org/ecosystem/finance/tutorials/11_time_series.html
+    https://qiskit-community.github.io/qiskit-finance/tutorials/11_time_series.html
     for instructions on use.
     """
 

diff --git a/qiskit_finance/data_providers/yahoo_data_provider.py b/qiskit_finance/data_providers/yahoo_data_provider.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2020, 2023.
+# (C) Copyright IBM 2020, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -36,7 +36,7 @@ class YahooDataProvider(BaseDataProvider):
     """Yahoo data provider.
 
     Please see:
-    https://qiskit.org/ecosystem/finance/tutorials/11_time_series.html
+    https://qiskit-community.github.io/qiskit-finance/tutorials/11_time_series.html
     for instructions on use.
     """
 

diff --git a/setup.py b/setup.py
@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2021, 2023.
+# (C) Copyright IBM 2021, 2024.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -70,7 +70,7 @@
     python_requires=">=3.8",
     project_urls={
         "Bug Tracker": "https://github.com/qiskit-community/qiskit-finance/issues",
-        "Documentation": "https://qiskit.org/ecosystem/finance/",
+        "Documentation": "https://qiskit-community.github.io/qiskit-finance/",
         "Source Code": "https://github.com/qiskit-community/qiskit-finance",
     },
     zip_safe=False
-Original file line number
+Diff line change
@@ Expand Up / @@ -163,7 +163,7 @@ @@
         "\n",
         "[4] DJ. Berndt and J. Clifford, *Using dynamic time warping to find patterns in time series*. In KDD workshop 1994  (Vol. 10, No. 16, pp. 359-370).\n",
         "\n",
-        "[5] [Max-Cut and Traveling Salesman Problem](https://qiskit.org/ecosystem/optimization/tutorials/06_examples_max_cut_and_tsp.html)"
+        "[5] [Max-Cut and Traveling Salesman Problem](https://qiskit-community.github.io/qiskit-optimization/tutorials/06_examples_max_cut_and_tsp.html)"
        ]
       },
       {
@@ Expand Down @@