#### Overview of this book

Mastering SciPy
Credits
www.PacktPub.com
Preface
Free Chapter
Numerical Linear Algebra
Interpolation and Approximation
Differentiation and Integration
Nonlinear Equations and Optimization
Initial Value Problems for Ordinary Differential Equations
Computational Geometry
Descriptive Statistics
Inference and Data Analysis
Mathematical Imaging
Index

## Optimization

The optimization problem is best described as the search for a local maximum or minimum value of a scalar-valued function f(x). This search can be performed for all possible input values in the domain of f (and in this case, we refer to this problem as an unconstrained optimization), or for a specific subset of it that is expressible by a finite set of identities and inequalities (and we refer to this other problem as a constrained optimization). In this section, we are going to explore both modalities in several settings.

### Unconstrained optimization for univariate functions

We focus on the search for the local minima of a function f(x) in an interval [a, b] (the search for local maxima can then be regarded as the search of the local minima of the function –f(x) in the same interval). For this task, we have the routine `minimize_scalar` in the module `scipy.optimize`. It accepts as obligatory input a univariate function f(x), together with a search method.

Most search methods are based...