By Liam E. Gumley
more and more, scientists and engineers needs to fast and successfully study and visualize tremendous huge units of knowledge. Interactive facts Language, IDL, was once designed to deal with simply this desire. a well-liked info research and visualization programming atmosphere, IDL is used around the globe through scientists and engineers in fields as various because the actual sciences, clinical physics, and engineering try out and research.
In functional IDL Programming , Liam E. Gumley presents an excellent beginning within the basics of procedural programming in IDL. He provides concise info on easy methods to improve IDL programmers which are good based, trustworthy, and effective. the instance courses within the e-book show key strategies and supply performance that may be utilized instantly. additionally, the e-book deals readers functional assistance and recommendation on IDL programming, which they might differently realize merely after years of expertise.
whereas simply modest previous programming adventure is thought, readers with event in any procedural language will quick translate their abilities to IDL, studying the simplest programming practices for this new setting. Scientists, engineers, and scholars in academic, executive, and advertisement study and improvement environments will all have fun with the author's suggestions in supporting them successfully study and visualize info. * provides a entire and exact therapy of IDL facts forms, operators, expressions, array operations, enter and output, direct snap shots, plotting and imaging, book caliber output, and graphical consumer interfaces. * Designed for newbies and skilled IDL clients and programmers alike. * presents an accompanying site with downloadable types of all IDL courses within the publication and a hyperlink to downloadable demonstration types of the IDL software program.
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Extra info for Practical IDL programming: creating effective data analysis and visualization applications
Example text
Name Normalized Test Image Arrays of Structures Anonymous structure arrays can be created by calling the r e p l i c a t e function: IDL> i m a g e - {name:'Test Image', v a l i d _ r a n g e : [ O . 0], $ In this example, an array of structures was created with 10 elements. name = ' F i r s t Test Image' IDL> s e q u e n c e [ O ] . 0 In contrast, anonymous structures that are seemingly identical cannot be formed into an array by enclosing the structures in square brackets, as demonstrated in the following example: IDL> a - {name:'Sean', age:32} IDL> b = { n a m e : ' K a t e ' , age:25} IDL> c = [a, b] % C o n f l i c t i n g data s t r u c t u r e s : B , c o n c a t e n a t i o n .
25 IDL> y r e c = rec IDL> y r e c . 50 Named structure arrays can be created by calling the rep 1 i ca te function: IDL> rec = { n a v _ r e c o r d , IDL> t i m e . O, l a t . O, l o n . O . 8. The n_tags f u n c t i o n r e t u r n s the n u m b e r of variables (also k n o w n as tags) in a structure: IDL> image = {name. 'Test Image', v a l i d _ r a n g e . [ O . 0], $ The tag_names function r e t u r n s the n a m e s of each variable in a structure in a string array: IDL> p r i n t , tag_names(image) NAME VALID_RANGE DATA The n a m e s are always r e t u r n e d in u p p e r c a s e .
0000 In this example, the mask is set to zero where the array elements are less than five, and one where the array elements are greater than or equal to five. Thus multiplying the mask by the array returns only the array values that are greater than or equal to five. The tota 1 function always returns a f 1o a t result. Tip Equality tests (eq, ne) should be avoided when comparing floating-point variables because the precision of floating-point arithmetic varies between IDL platforms. Instead, test for agreement within a small tolerance that is larger than machine precision: IDL> t o l = 1 .