SciPy Free and open source package of tools for science and engineering for Python
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science library python library engineering process signal science library

SciPy Description

Free and open source package of tools for science and engineering for Python SciPy includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, genetic algorithms, ODE solvers, and more.The SciPy library depends on 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. SciPy and NumPy are easy to use, but powerful enough to be depended upon by some of the world's leading engineers and scientists.If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try! Requirements: · Numpy · Python 2.4 or later What's New in This Release: · #503, #640: iv: problems at large arguments fixed by new implementation · #623: jv: fix errors at large arguments · #679: struve: fix wrong output for v < 0 · #803: pbdv produces invalid output · #804: lqmn: fix crashes on some input · #823: betainc: fix documentation · #834: exp1 strange behavior near negative integer values · #852: jn_zeros: more accurate results for large s, also in jnp/yn/ynp_zeros · #853: jv, yv, iv: invalid results for non-integer v < 0, complex x · #854: jv, yv, iv, kv: return nan more consistently when out-of-domain · #927: ellipj: fix segfault on Windows · #946: ellpj: fix segfault on Mac OS X/python 2.6 combination. · ive, jve, yve, kv, kve: with real-valued input, return nan for out-of-domain · instead of returning only the real part of the result.

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