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Isaac Yu
b9e67970f6
academic/python3-scipy: Added (py3 math, science, and engineering)
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2 éve | |
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| README | b9e67970f6 academic/python3-scipy: Added (py3 math, science, and engineering) | 2 éve |
| python3-scipy.SlackBuild | b9e67970f6 academic/python3-scipy: Added (py3 math, science, and engineering) | 2 éve |
| python3-scipy.info | b9e67970f6 academic/python3-scipy: Added (py3 math, science, and engineering) | 2 éve |
| slack-desc | b9e67970f6 academic/python3-scipy: Added (py3 math, science, and engineering) | 2 éve |
README
SciPy (pronounced "Sigh Pie") is open-source software for mathematics,
science, and engineering.
The SciPy library is built to work with NumPy arrays, and provides
many user-friendly and efficient numerical routines such as routines
for numerical integration and optimization. Together, they run on
all popular operating systems, are quick to install, and are free of
charge. NumPy and SciPy are easy to use, but powerful enough to be
depended upon by some of the world's leading scientists and engineers.
matplotlib and ipython are nice to have in connection with scipy, but
scipy does not depend on them.
Since ver. 0.14.0 scipy uses SuperLU instead of UMFPACK for solving
unsymmetric sparse linear systems. If you want to use UMFPACK you
must install it in advance of numpy and build numpy accordingly (see
the README to numpy's SlackBuild). Moreover, after installing scipy,
you have to install scikit-umfpack.
If you need to build scipy for debugging, set DEBUG=y.
NOTE: this is for Python 3. If you need Python 2 support, install
python2-scipy.
This script installs scipy ver. 1.9.1, the last possible version for
Slackware 15.0. Newer versions require a newer Cython (as a build
dependency).
science, and engineering.
The SciPy library is built to work with NumPy arrays, and provides
many user-friendly and efficient numerical routines such as routines
for numerical integration and optimization. Together, they run on
all popular operating systems, are quick to install, and are free of
charge. NumPy and SciPy are easy to use, but powerful enough to be
depended upon by some of the world's leading scientists and engineers.
matplotlib and ipython are nice to have in connection with scipy, but
scipy does not depend on them.
Since ver. 0.14.0 scipy uses SuperLU instead of UMFPACK for solving
unsymmetric sparse linear systems. If you want to use UMFPACK you
must install it in advance of numpy and build numpy accordingly (see
the README to numpy's SlackBuild). Moreover, after installing scipy,
you have to install scikit-umfpack.
If you need to build scipy for debugging, set DEBUG=y.
NOTE: this is for Python 3. If you need Python 2 support, install
python2-scipy.
This script installs scipy ver. 1.9.1, the last possible version for
Slackware 15.0. Newer versions require a newer Cython (as a build
dependency).