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Merge pull request #369 from SimonRohou/codac2_dev
Towards tube documentation and official V2 release
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‎README.md‎

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# [Codac: constraint-programming for robotics](http://codac.io/v2) [![Build Status](https://github.com/codac-team/codac/workflows/.github/workflows/tests.yml/badge.svg)](https://github.com/codac-team/codac/actions)
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# [Codac: constraint-programming for robotics](http://codac.io) [![Build Status](https://github.com/codac-team/codac/workflows/.github/workflows/tests.yml/badge.svg)](https://github.com/codac-team/codac/actions)
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See the official website: http://codac.io/v2
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See the official website: http://codac.io
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Codac (Catalog Of Domains And Contractors) is a C++/Python/Matlab library providing tools for interval computations and constraint programming over real numbers, trajectories and sets.
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It has numerous applications in parameter estimation, guaranteed integration, robot localization, and provides reliable outputs.

‎doc/manual/_static/css/custom.css‎

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/* Adding VIBes + IPE logos in the lateral menu */
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background:url("../logos/logos_vibes_ipe.png") no-repeat center / contain;
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background: url("../logos/logos_vibes_ipe.png") no-repeat center / contain,
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var(--color-sidebar-item-background--hover);
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}
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background: url("../logos/logos_vibes_ipe.png") no-repeat center / contain,
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var(--color-sidebar-item-background--current);
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}
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figcaption .caption-text
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{
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font-style: italic;
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‎doc/manual/conf.py.in‎

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"color-toc-item-text--active": "#FFFFFF",
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},
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"announcement": "You are currently reading the new Codac documentation, which is currently in preparation. <a href=\"http://codac.io\">See the v1 website</a>.",
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#"announcement": "You are currently reading the new Codac documentation, which is currently in preparation. <a href=\"http://codac.io\">See the v1 website</a>.",
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}
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# See https://www.sympy.org/sphinx-math-dollar/

‎doc/manual/index.rst‎

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* The class SetMembershipFunction
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* Extension to custom expressions
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* Tubes
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* What is a tube?
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* Temporal domains
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* The Tube classes
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* :ref:`sec-domains-tubes`
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* :ref:`sec-domains-tubes-tdomain`
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* :ref:`sec-domains-tubes-slicedtube`
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* The Trajectory classes
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* Increasing performances using views
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manual/introduction/index.rst
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manual/installation/index.rst
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manual/intervals/index.rst
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manual/tubes/index.rst
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manual/linear/index.rst
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manual/functions/index.rst
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manual/contractors/index.rst

‎doc/manual/manual/functions/analytic/analytic_operators.rst‎

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If an operator, for which the centered form is not defined, is involved in an expression, then this expression cannot be evaluated using the centered form (calculation is disabled for the entire operation). A simple natural evaluation will then be computed.
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.. _sec-functions-temporal-operator:
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Expressions involving a temporal operator
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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.. code-tab:: py
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x = # some sampled trajectory...
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x = # some tube or sampled trajectory...
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g = x.as_function() # intermediate operation
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t = ScalarVar()
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.. code-tab:: c++
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x = // some sampled trajectory...
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x = // some tube or sampled trajectory...
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g = x.as_function(); // intermediate operation
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ScalarVar t;

‎doc/manual/manual/installation/cpp.rst‎

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.. code-block:: bash
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choco install doxygen.install --version=1.13
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choco install doxygen.install --version=1.16
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choco install graphviz
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python -m pip install --upgrade pip
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pip install --upgrade wheel setuptools sphinx sphinx_rtd_theme furo sphinx-math-dollar sphinx_tabs breathe sphinx_togglebutton

‎doc/manual/manual/installation/matlab.rst‎

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.. code-block:: bash
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pip install codac4matlab --pre
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# Option --pre has to be set because Codac v2 is only available in pre-release
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pip install codac4matlab
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Once Codac is installed, you can use it in your MATLAB scripts using the following import command:
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‎doc/manual/manual/installation/python.rst‎

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In case you want to use Codac only with Python, then the installation procedure is simply:
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1. **Dependencies**: Ensure you have a supported version of Python (>=3.6).
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1. **Dependencies**: Ensure you have a supported version of Python (>=3.8).
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2. **Install via pip**: Use the following command to install Codac:
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.. code-block:: bash
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pip install codac --pre
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# Option --pre has to be set because Codac v2 is only available in pre-release
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pip install codac
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You can also update and test your Codac Python package.
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You can also update and test your Codac Python package:
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* **Update via pip**: Use the following command to update your already installed Codac package:
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.. code-block:: bash
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pip install codac --upgrade --pre
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# Option --pre has to be set because Codac v2 is only available in pre-release
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pip install codac --upgrade
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* **Testing the installation**: In order to verify that your installation is working properly in Python, you can run:
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pip3 install --break-system-packages codac --pre
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pip3 install --break-system-packages codac
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.. admonition:: macOS Big Sur and later (x86_64)
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‎doc/manual/manual/tools/index.rst‎

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serialization.rst
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registration.rst
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octasym.rst
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octasym.rst
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sampled_traj_npz.rst

‎doc/manual/manual/tools/sampled_traj_npz.rst‎

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.. _sec-trajectories-sampledtraj:
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Sampled trajectories
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====================
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In Python, the ``SampledTraj`` name is a convenience wrapper that mimics the
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C++ template deduction style. Depending on the provided samples, it builds and
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returns one of the following objects:
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- ``SampledTraj_Scalar``
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- ``SampledTraj_Vector``
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- ``SampledTraj_Matrix``
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This keeps the user-facing syntax short and consistent with ``AnalyticTraj``.
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Loading a sampled trajectory from a ``.npz`` file
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-------------------------------------------------
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A sampled trajectory cannot be constructed directly from a file path.
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The recommended workflow is:
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1. load the ``.npz`` file with ``numpy.load``;
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2. extract the arrays containing the sampling times and sampled values;
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3. call ``SampledTraj(t, x)``.
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The wrapper then deduces the appropriate trajectory type from ``x``.
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.. tabs::
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.. group-tab:: Python
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.. code-block:: python
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import numpy as np
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from codac import *
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data = np.load("traj_vec.npz")
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traj = SampledTraj(data["t"], data["x"])
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print(type(traj))
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In the above example, if ``x`` is a 2D array of shape ``(N,n)``, then
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``traj`` is a ``SampledTraj_Vector``.
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Another example:
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.. tabs::
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.. group-tab:: Python
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.. code-block:: python
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import numpy as np
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from codac import *
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t = np.array([0.0, 0.5, 1.0, 1.5])
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x = np.array([
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[0.0, 1.0],
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[0.5, 1.5],
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[1.0, 2.0],
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[1.5, 2.5],
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])
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traj = SampledTraj(t, x)
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print(traj) # outputs: SampledTraj. [0, 1.5]↦[[0, 1.5][1, 2.5]], 4 pts

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