By Ivan Idris
ISBN-10: 1782166084
ISBN-13: 9781782166085
An motion packed consultant utilizing genuine international examples of the simple to take advantage of, excessive functionality, unfastened open resource NumPy mathematical library.
Overview
• practice excessive functionality calculations with fresh and effective NumPy code;
• learn huge info units with statistical functions;
• Execute advanced linear algebra and mathematical computations.
In Detail
NumPy is an extension to, and the basic package deal for clinical computing with Python. In today's international of technology and know-how, it's all approximately velocity and adaptability. by way of clinical computing, NumPy is at the most sensible of the list.
NumPy Beginner's advisor will train you approximately NumPy, a number one clinical computing library. NumPy replaces most of the performance of Matlab and Mathematica, yet not like these items, is unfastened and open source.
Write readable, effective, and quick code, that's as with regards to the language of arithmetic as is presently attainable with the innovative open resource NumPy software program library. research the entire bits and bobs of NumPy that calls for you to understand uncomplicated Python purely. shop millions of greenbacks on pricey software program, whereas retaining the entire flexibility and gear of your favorite programming language.
You will find out about fitting and utilizing NumPy and comparable techniques. on the finish of the publication we'll discover a few comparable medical computing initiatives. This ebook offers you a fantastic starting place in NumPy arrays and common services. via examples, additionally, you will know about plotting with Matplotlib and the similar SciPy venture. NumPy Beginner's advisor may also help you be efficient with NumPy and feature you writing fresh and speedy code very quickly at all.
What you'll research from this book
• set up NumPy
• NumPy arrays
• common functions
• NumPy matrices
• NumPy modules
• Plot with Matplotlib
• try NumPy code
• Relation to SciPy
Approach
The publication is written in beginner’s consultant sort with every one point of NumPy confirmed with actual global examples and required screenshots.
Who this publication is written for
If you're a programmer, scientist, or engineer who has easy Python wisdom and wish to be capable of do numerical computations with Python, this e-book is for you. No past wisdom of NumPy is needed.
Read Online or Download NumPy Beginner's Guide (2nd Edition) PDF
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Additional resources for NumPy Beginner's Guide (2nd Edition)
Example text
N --noncritical tag Tests having this tag are overridden to be of non-critical type. -v --variable name:value Set variables in tests, only scalar variables(${}) are supported. -V --variablefile path Specify explicitly the file that contains variables. -d --output dir Specify the desired directory where resultant files are placed. -o --output file The generated XML output file. -l --log file The generated HTML log file. -r --report file The generated HTML log file. -x --xunit file xUnit compatible result file (not created by default).
Note Note that variable names are case-sensitive. In order to differentiate between variables and other keywords, keep in mind that generally the variables are kept in uppercase but there is no such rule. The variables are defined as ${Variable Name} for normal, single-valued variables and as @{Variable Name} for a variable containing a list of different values. In a test configuration file, when only the variable table is specified, then the test file becomes a variable file and on its usage, only the table starting with variables will be considered.
The test configuration is written in a tabular format with each column having separate elements such as test element. The Robot Framework allows flexibility in specifying the separations among the different columns in a test file as well as supporting different formats for the test files, which you can choose at your discretion. Note that depending upon the file extension; a suitable parser is selected during runtime. Some of the supported formats are as follows: HTMLTSVPlaintextPiped textRestructuredText HTML format In an HTML format, the HTML is read, which comprises of different tables for different portions of the test configuration.