Numeric computations based on repetitive tasks (or loops) are not too efficient in scripting languages, such as Jython/Python. Loops offer an easy way to do something repeatedly, but creating objects in loops is slow. This has already been illustrated using Jython arrays in Sect. 2.13.2. In most cases, what we really want is to manipulate with primitive data types, such as floats or integers, rather than with immutable objects used for representation of numbers in Jython. Therefore, our strategy for this book will be the following: Jython will be viewed as interface language, i.e., a language designed to link and manipulate with high-level Java classes that implement repetitive operations with primitive types. In the following chapters, we discuss objects used for data storage and manipulation—building blocks from which a typical data analysis program is constructed. Unlike Jython classes, the objects to be discussed below are derived from pure Java classes and imported from the Java libraries of DMelt.
CITATION STYLE
Chekanov, S. V. (2016). Data arrays. In Advanced Information and Knowledge Processing (pp. 131–186). Springer London. https://doi.org/10.1007/978-3-319-28531-3_4
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