#### Overview of this book

Today's world of science and technology is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy will give you both speed and high productivity. "NumPy Cookbook" will teach you all about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, it is free and open source. "Numpy Cookbook" will teach you to write readable, efficient, and fast code that is as close to the language of Mathematics as much as possible with the cutting edge open source NumPy software library. You will learn about installing and using NumPy and related concepts. At the end of the book, we will explore related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project through examples. "NumPy Cookbook" will help you to be productive with NumPy and write clean and fast code.
NumPy Cookbook
Credits
www.PacktPub.com
Preface
Free Chapter
Winding Along with IPython
Get to Grips with Commonly Used Functions
Connecting NumPy with the Rest of the World
Audio and Image Processing
Special Arrays and Universal Functions
Profiling and Debugging
Quality Assurance
Speed Up Code with Cython
Index

## Using the array interface

The array interface is a yet another mechanism to communicate with other Python applications. This protocol, as its name suggests, is only applicable to array-like objects. A demonstration is in order. Let's use PIL again, but without saving files.

We will be reusing part of the code from the previous recipe, so the prerequisites are similar. We will skip the first step of the previous step here, and assume it is already known.

### How to do it...

The following steps will let us explore the array interface:

1. The PIL image array interface attribute.

The PIL image object has a `__array_interface__` attribute. Let's inspect its contents. The value of this attribute is a `dictionary`:

```array_interface = img.__array_interface__
print "Keys", array_interface.keys()
print "Shape", array_interface['shape']
print "Typestr", array_interface['typestr']```

This code prints the following information:

```Keys ['shape', 'data', 'typestr']
Shape (512, 512, 4)
Typestr |u1
```
2. The NumPy array...