In this recipe, we will look at how to compute data polynomial interpolation by applying some important methods which are discussed in detail in the coming How to do it... section.
Computing a polynomial interpolation for a set of data points
by V Kishore Ayyadevara, Ruben Oliva Ramos, L. Felipe Martins
SciPy Recipes
- Preface
- Getting to Know the Tools
- Introduction
- Installing Anaconda on Windows
- Installing Anaconda on macOS
- Installing Anaconda on Linux
- Checking the Anaconda installation
- Installing SciPy from a binary distribution on Windows
- Installing SciPy from a binary distribution on macOS
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- Getting Started with NumPy
- Introduction
- Creating NumPy arrays
- How to do it…
- Creating an array from a list
- Specifying the data type for elements in an array
- Creating an empty array with a given shape
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- Creating arrays with equally spaced values
- Creating an array by repeating elements
- Creating an array by tiling another array
- Creating an array with the same shape as another array
- Using object arrays to store heterogeneous data
- See also
- How to do it…
- Querying and changing the shape of an array
- Storing and retrieving NumPy arrays
- Indexing
- Operations on arrays
- Using masked arrays to represent invalid data
- Using object arrays to store heterogeneous data
- Defining, symbolically, a function operating on arrays
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- Data Wrangling with pandas
- Creating Series objects
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- Matrices and Linear Algebra
- Introduction
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- Finding the best linear fit for a set of data
- Doing non-linear regression for a set of data
- Regression
- Constants and Special Functions
- Calculus, Interpolation, and Differential Equations
- Introduction
- Integration
- Computing integrals using a Gaussian quadrature
- Computing integrals with weighting functions
- Computing multiple integrals
- Interpolation
- Computing a polynomial interpolation for a set of data points
- Univariate interpolation
- Finding a cubic spline that interpolates a set of data
- Defining a B-spline for a given set of control points
- Differentiation
- Solving a one-dimensional ordinary differential equation
- Solving a system of ordinary differential equations
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- Statistics and Probability
- Introduction
- Computing the probability mass function of a discrete random variable
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- Advanced Computations with SciPy
- Discrete Fourier transforms
- Computing the discrete Fourier transform (DFT) of a data series using the FFT algorithm
- Computing the inverse DFT of a data series
- Computing signal construction
- Getting started with filters
- Computing the DFT for two-dimensional data
- How to find the DFT of the derivative of a function
- Computing the convolution of two functions
- Mathematical imaging
- Computing pairwise distances from a dataset, using different distance metrics
- How to identify neighborhoods and nearest neighbors for a dataset and a given metric
- Nearest neighbors regression
Computing a polynomial interpolation for a set of data points
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