Python and HDF5 Unlocking Scientific Data 12803

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Все про “Python and HDF5 Unlocking Scientific Data”

Від видавця

Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share чисельного datasets ranging in size from gigabytes to terabytes. Through real-world examples and practical exercises, you'll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you're familiar with the basics of Python data analysis, this is an ideal introduction to HDF5. Get set up with HDF5 tools and create your first file HDF5 Work with datasets learning by the HDF5 Dataset object Understand advanced features like dataset chunking and compression Learn how to work with HDF5's hierarchical structure, using groups Create self-describing files by adding metadata with HDF5 attributes Take advantage of HDF5's type system to create interoperable files Express relationships among data with references, named types, dimension and scales Discover how Python mechanisms for writing parallel code interact with HDF5

Зміст

Chapter 1 : Introduction
Python and HDF5
Exactly What Is HDF5?
Chapter 2 : Getting Started
HDF5 Basics
Setting Up
The HDF5 Tools
Your First HDF5 File
Chapter 3 : Working with Datasets
Dataset Basics
Reading and Writing Data
Resizing Datasets
Chapter 4 : How Chunking and Compression Can Help You
Contiguous Storage
Chunked Storage
Setting the Chunk Shape
Performance Example: Resizable Datasets
Filters and Compression
Other Filters
Third-Party Filters
Chapter 5 : Groups, Links, and Iteration: The "H" in HDF5
The Root Group and Subgroups
Group Basics
Working with Links
Iteration and Containership
Multilevel Iteration with the Visitor Pattern
Copying Objects
Object Comparison and Hashing
Chapter 6 : Storing Metadata with Attributes
Attribute Basics
Real-World Example: Particle Accelerator Database
Chapter 7 : More About Types
The HDF5 Type System
Integers and Floats
Fixed-Length Strings
Variable-Length Strings
Compound Types
Complex Numbers
Enumerated Types
Booleans
The Type array
Opaque Types
Dates and Times
Chapter 8 : Organizing Data with References, Types, Dimension and Scales
Object References
Region References
Named Types
Dimension Scales
Chapter 9 : Concurrency: Parallel HDF5, Threading, and Multiprocessing
Python Parallel Basics
Threading
Multiprocessing
MPI and Parallel HDF5
Chapter 10 : Next Steps
Asking for Help
Contributing
Index
Colophon

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Python and HDF5 Unlocking Scientific Data

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