Scientific Tools for Python
http://www.scipy.org/
SciPy is open-source software for mathematics, science, and engineering. The core library is NumPy which provides convenient and fast N-dimensional array manipulation. 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.
- Sources inherited from project devel:languages:python:numeric
- Devel package for openSUSE:Factory
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Source Files
| Filename | Size | Changed |
|---|---|---|
| _link | 0000000147 147 Bytes | |
| _multibuild | 0000000082 82 Bytes | |
| python-scipy.changes | 0000089537 87.4 KB | |
| python-scipy.spec | 0000011315 11 KB | |
| scipy-1.11.1.tar.gz | 0056031509 53.4 MB | |
| scipy-datasets.tar.gz | 0001874187 1.79 MB |
Revision 88 (latest revision is 108)
Dirk Mueller (dirkmueller)
accepted
request 1100589
from
Markéta Machová (mcalabkova)
(revision 88)
- Update to 1.11.1
* Several scipy.sparse array API improvements, including sparse.sparray,
a new public base class distinct from the older sparse.spmatrix class,
proper 64-bit index support, and numerous deprecations paving the way
to a modern sparse array experience.
* scipy.stats added tools for survival analysis, multiple hypothesis
testing, sensitivity analysis, and working with censored data.
* A new function was added for quasi-Monte Carlo integration, and linear
algebra functions det and lu now accept nD-arrays.
* An axes argument was added broadly to ndimage functions, facilitating
analysis of stacked image data.
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