Elegant Scipy : The Art of Scientific Python
Language: English
Published by O'reilly Media Sep 2017, 2017
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
Neuware - Welcome to Scientific Python and its community. If you're a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. You'll learn how to write elegant code that's clear, concise, and efficient at executing the task at hand.Throughout the book, you'll work with examples from the wider scientific Python ecosystem, using code that illustrates principles outlined in the book. Using actual scientific data, you'll work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries.- Explore the NumPy array, the data structure that underlies numerical scientific computation- Use quantile normalization to ensure that measurements fit a specific distribution- Represent separate regions in an image with a Region Adjacency Graph- Convert temporal or spatial data into frequency domain data with the Fast Fourier Transform- Solve sparse matrix problems, including image segmentations, with SciPy's sparse module- Perform linear algebra by using SciPy packages- Explore image alignment (registration) with SciPy's optimize module- Process large datasets with Python data streaming primitives and the Toolz library.…
Seller Inventory # 9781491922873
- Title
- Elegant Scipy : The Art of Scientific Python
- Author
- Harriet Dashnow
- Publisher
- O'reilly Media Sep 2017
- Publication year
- 2017
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1491922877
- ISBN 13
- 9781491922873
- Item weight
- 492 grams
- Dimensions
- 234x179x17 mm
Welcome to Scientific Python and its community. If youâ re a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. Youâ ll learn how to write elegant code thatâ s clear, concise, and efficient at executing the task at hand.
Throughout the book, youâ ll work with examples from the wider scientific Python ecosystem, using code that illustrates principles outlined in the book. Using actual scientific data, youâ ll work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries.
- Explore the NumPy array, the data structure that underlies numerical scientific computation
- Use quantile normalization to ensure that measurements fit a specific distribution
- Represent separate regions in an image with a Region Adjacency Graph
- Convert temporal or spatial data into frequency domain data with the Fast Fourier Transform
- Solve sparse matrix problems, including image segmentations, with SciPyâ s sparse module
- Perform linear algebra by using SciPy packages
- Explore image alignment (registration) with SciPyâ s optimize module
- Process large datasets with Python data streaming primitives and the Toolz library
"Synopsis" may belong to another edition of this title.
About the Author
Stéfan van der Walt is an assistant researcher at the Berkeley Institute for Data Science at the University of California, Berkeley and a senior lecturer in applied mathematics at Stellenbosch University, South Africa. He has been involved in the development of scientific open-source software for more than a decade, and enjoys teaching Python at workshops and conferences. Stéfan is the founder of scikit-image and a contributor to numpy, scipy, and dipy.
Harriet Dashnow is a bioinformatician and has worked at the Murdoch Childrens Research Institute, the Department of Biochemistry at the University of Melbourne and the Victorian Life Sciences Computation Initiative (VLSCI). Harriet obtained a BA (Psychology), a BS (Genetics and Biochemistry), and a MS (Bioinformatics) from the University of Melbourne. She is currently working towards a PhD. She organises and teaches computational skills workshops in such areas as genomics, Software Carpentry, Python, R, Unix, and Git version control.
"About the title" may belong to another edition of this title.
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