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Mathematical Functions — Numpy V1.13 Manual

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This is documentation for an old release of NumPy (version 1.10.0). Read this page in the documentation of the latest stable release (version > 1.17). What is NumPy? ¶ NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived

Mathematical functions — NumPy v1.4 Manual

Installation and Functions of NumPy in Python - The Engineering Projects

numpy.round ¶ numpy. round_ (a, decimals=0, out=None) [source] ¶ Round an array to the given number of decimals. Refer to around for full documentation.

Rounding ¶ Sums, products, differences ¶ Exponents and logarithms ¶ Other special functions ¶ Floating point routines ¶ Arithmetic operations ¶ Handling complex numbers ¶

This is documentation for an old release of NumPy (version 1.14). Search for this page in the documentation of the latest stable release (version 2.2). This is documentation for an old release of NumPy (version 1.3.). Read this page in the documentation of the latest stable release (version > 1.17).

This is documentation for an old release of NumPy (version 1.14.2). Read this page in the documentation of the latest stable release (version > 1.17).

  • NumPy: the absolute basics for beginners — NumPy v1.26 Manual
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Rounding ¶ Sums, products, differences ¶ Exponents and logarithms ¶ Other special functions ¶ Floating point routines ¶ Arithmetic operations ¶ Handling complex numbers ¶

Release Notes — NumPy v1.13 Manual

The reference guide contains a detailed description of the functions, modules, and objects included in NumPy. The reference describes how the methods work and which parameters can scimath available after NumPy can be used to perform a wide variety of mathematical operations on arrays. It adds powerful data structures to Python that guarantee efficient calculations with arrays and

Wrapper functions to more user-friendly calling of certain math functions whose output data-type is different than the input data-type in certain domains of the input. For This is documentation for an old release of NumPy (version 1.5.). Read this page in the documentation of the latest stable release (version > 1.17).

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Universal functions (ufunc) ¶ A universal function (or ufunc for short) is a function that operates on ndarrays in an element-by-element fashion, supporting array broadcasting,

Sums, products, differences #Exponents and logarithms # numpy.frompyfunc numpy.piecewise NumPy-specific help functions Finding help Reading help Indexing routines Generating index arrays Indexing-like operations Inserting data Notes If out is provided, the function writes the result into it, and returns a reference to out. (See Examples) References M. Abramowitz and I. A. Stegun, Handbook of

Miscellaneous #previous numpy.not_equal next numpy.sin Mathematical functions with automatic domain # Note numpy.emath is a preferred alias for numpy.lib.scimath, available after numpy is imported. Wrapper functions to more user-friendly

This is documentation for an old release of NumPy (version 1.13.0). Read this page in the documentation of the latest stable release Rounding ¶ Sums, products, differences ¶ Exponents and logarithms ¶ Other special functions ¶ Floating point routines ¶ Rational routines ¶ Arithmetic This reference manual details functions, modules, and objects included in NumPy, describing what they are and what they do. For learning how to use NumPy, see the complete

numpy.fft.fft ¶ numpy.fft. fft (a, n=None, axis=-1, norm=None) [source] ¶ Compute the one-dimensional discrete Fourier Transform. This function computes the one-dimensional n Wrapper functions to more user-friendly calling of certain math functions whose output data-type is different than the input data-type in certain domains of the input. For numpy.emath is a preferred alias for numpy.lib.scimath , available after numpy is imported. Wrapper functions to more user-friendly calling of certain math functions whose output data

This is documentation for an old release of NumPy (version 1.17.0). Read this page in the documentation of the latest stable release (version > 1.17). Note numpy.emath is a preferred alias for numpy.lib.scimath, available after numpy is imported. Wrapper functions to more user-friendly calling of certain math functions whose output data

In 1.13 np.average will preserve subclasses, to match the behavior of most other numpy functions such as np.mean. In particular, this means calls which returned a scalar may return a 0-d Mathematical functions with automatic domain # Note numpy.emath is a preferred alias for numpy.lib.scimath, available after numpy is imported. Wrapper functions to more user-friendly

This reference manual details functions, modules, and objects included in NumPy, describing what they are and what they do. For learning how to use NumPy, see also NumPy Mathematical functions with automatic domain # Note numpy.emath is a preferred alias for numpy.lib.scimath, available after numpy is imported. Wrapper functions to more user-friendly

Sums, products, differences ¶Exponents and logarithms ¶ Wrapper functions to more user-friendly calling of certain math functions whose output data-type is different than the input data-type in certain domains of the input. For

Trigonometric functions ¶ Hyperbolic functions ¶ Rounding ¶ Sums, products, differences ¶ Exponents and logarithms ¶