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colbertz2 committed 0b273b0 Jul 9, 2020
[DOC] add examples for eval_legendre()

  * range() is exclusive, so these examples only plot polynomial orders 0 through 4. (Facepalm!)
    Inline comments on np.linspace and for loop are unnecessary.


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SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.

SciPy depends on NumPy, which provides convenient and fast N-dimensional array manipulation. SciPy 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. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!

For the installation instructions, see INSTALL.rst.txt.

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