#### Overview of this book

Learning SciPy for Numerical and Scientific Computing Second Edition
Credits
www.PacktPub.com
Preface
Free Chapter
Introduction to SciPy
Working with the NumPy Array As a First Step to SciPy
SciPy for Linear Algebra
SciPy for Numerical Analysis
SciPy for Signal Processing
SciPy for Data Mining
SciPy for Computational Geometry
Interaction with Other Languages
Index

## Convenience and test functions

All the convenience functions are designed to facilitate a computational environment where the user does not need to worry about relative errors. The functions seem to be pointless at first sight, but behind their codes, there are state-of-the-art ideas that offer faster and more reliable results.

We have convenience functions beyond the ones defined in the NumPy libraries to find the solutions of trigonometric functions in degrees (`cosdg`, `sindg`, `tandg`, and `cotdg`); to compute angles in radians from their expressions in degrees, minutes, and seconds (`radian`); common powers (`exp2` for 2**x, and `exp10` for 10**x); and common functions for small values of the variable (`log1p` for log(1 + x), `expm1` for exp(x) - 1, and `cosm1` for cos(x) - 1).

For instance, in the following code snippet, `the log1p` function computes the natural logarithm of 1 + x. Why not simply add 1 to the value of x and then take the logarithm instead? Let's compare:

```>>> import numpy
>>...```