Scientific Tools for Python

Edit Package python-scipy
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.

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Source Files
Filename Size Changed
_multibuild 0000000082 82 Bytes
python-scipy.changes 0000111917 109 KB
python-scipy.spec 0000012244 12 KB
scipy-1.14.1.tar.gz 0058620554 55.9 MB
scipy-datasets.tar.gz 0001874165 1.79 MB
scipy-pr21063-gcc14.patch 0000001043 1.02 KB
scipy-pybind11-2.13.patch 0000002851 2.78 KB
Latest Revision
Ana Guerrero's avatar Ana Guerrero (anag+factory) accepted request 1225155 from Dirk Mueller's avatar Dirk Mueller (dirkmueller) (revision 77)
- relax pythran requirement

  * BUG: stats.zipf: incorrect pmf values
  * 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
  * scipy.stats added tools for survival analysis, multiple hypothesis
  * A new function was added for quasi-Monte Carlo integration, and linear
  * An axes argument was added broadly to ndimage functions, facilitating
- Test in parallel (pytest-xdist)
    python -Wd and check for `DeprecationWarning`s).
    All convolution-based filters also now accept complex-valued inputs
    * `scipy.spatial.SphericalVoronoi` now supports n-dimensional input,
      * `scipy.fft` is a new submodule that supersedes the `scipy.fftpack` submodule.
        or the most part, this is a drop-in replacement for ``numpy.fft`` and
      * uses NumPy's conventions for real transforms (``rfft``). This means the
        his is different from the output of ``fftpack`` which returned a real array
      * the inverse real to real transforms (``idct`` and ``idst``) are normalized
        or ``norm=None`` in thesame way as ``ifft``. This means the identity
      * This submodule is based on the ``pypocketfft`` library, developed by the
      * Note that `scipy.fftpack` has not been deprecated and will continue to be
        aintained but is now considered legacy. New code is recommended to use
      * `scipy.integrate.solve_ivp` can now return a ``y_events`` attribute
        unge-Kutta method originally implemented in Fortran. Now we provide a pure
      * `scipy.integrate.quad` provides better user feedback when break points are
      * New boolean keyword argument ``check_finite`` for `scipy.linalg.norm`; whether
        o check that the input matrix contains only finite numbers. Disabling may
      * It is now possible to use linear and non-linear constraints with
      * `scipy.optimize.linear_sum_assignment` has been re-written in C++ to improve
      * The implementation of ``choose_conv_method`` has been updated to reflect the
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