AutonomousVehicleControlBeginnersGuide
Python sample codes and documents about Autonomous vehicle control algorithm. This project can be used as a technical guide book to study the algorithms and the software architectures for beginners.
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Main repository of SageMath
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教育Python · CythonGitHub @sagemath自分でインストール所有者未確認
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Read the full README ↗Sage is open source mathematical software released under the GNU General Public Licence GPLv2+, and includes packages that have compatible software licenses. People all around the globe have contributed to the development of Sage. Full documentation is available online.
Those who are impatient may use prebuilt Sage available online from any of
without local installation. Otherwise read on.
The Sage Installation Guide provides a decision tree that guides you to the type of installation that will work best for you. This includes building from source, obtaining Sage from a package manager, using a container image, or using Sage in the cloud.
This README contains self-contained instructions for building Sage from source. This requires you to clone the git repository (as described in this README) or download the sources in the form of a tarball.
If you have questions or encounter problems, please do not hesitate to email the sage-support mailing list or ask on the Ask Sage questions and answers site.
Sage attempts to support all major Linux distributions, recent versions of macOS, and Windows (using Windows Subsystem for Linux or virtualization).
Detailed information on supported platforms for a specific version of Sage can be found in the section Availability and installation help of the release tour for this version.
We highly appreciate contributions to Sage that fix portability bugs and help port Sage to new platforms; let us know at the sage-devel mailing list.
The preferred way to run Sage on Windows is using Windows Subsystem for Linux (WSL). Follow the official WSL setup guide to install Ubuntu (or another Linux distribution). Make sure you allocate WSL sufficient RAM; 5GB is known to work, while 2GB might be not enough for building Sage from source. Then all instructions for installation in Linux apply.
As an alternative, you can also run Sage on Windows using Docker (see below) or other virtualization solutions.
If your Mac uses the Apple Silicon (M1, M2, M3, M4; arm64) architecture and
you set up your Mac by transferring files from an older Mac, make sure
that the directory /usr/local does not contain an old copy of Homebrew
(or other software) for the x86_64 architecture that you may have copied
over. Note that Homebrew for the M1 is installed in /opt/homebrew, not
/usr/local.
If you wish to use conda, please see the section on conda in the Sage Installation Manual for guidance.
Otherwise, we strongly recommend to use Homebrew ("the missing package
manager for macOS") from https://brew.sh/, which provides the gfortran
compiler and many libraries.
Otherwise, if you do not wish to install Homebrew, you will need to install
the latest version of Xcode Command Line Tools. Open a terminal window and
run xcode-select --install; then click "Install" in the pop-up window. If
the Xcode Command Line Tools are already installed, you may want to check if
they need to be updated by typing softwareupdate -l.
Like many other software packages, Sage is built from source using
./configure, followed by make. However, we strongly recommend to
read the following step-by-step instructions for building Sage.
The instructions cover all of Linux, macOS, and WSL.
More details, providing a background for these instructions, can be found in the section Install from Source Code in the Installation Guide.
Decide on the source/build directory (SAGE_ROOT):
On personal computers, any subdirectory of your :envvar:HOME
directory should do.
For example, you could use SAGE_ROOT=~/sage/sage, which we
will use as the running example below.
You need at least 10 GB of free disk space.
The full path to the source directory must contain no spaces.
After starting the build, you cannot move the source/build directory without breaking things.
You may want to avoid slow filesystems such as network file systems (NFS) and the like.
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