Chapter 7. Analysis and Visualization

Churning out terabytes of data from simulations or experiments does not, on its own, constitute science. Only analysis and visualization can transform raw data into true scientific insight. Unanalyzed data is merely data—only interpretation and communication can sufficiently illuminate and clarify the scientific meaning of results. When analysis and visualization succeed, compelling data becomes a convincing result.

There was an era in the physical sciences when data was collected in laboratory notebooks, and when the time to publish plots of that data came about, it was done by hand. Legend has it that this was sometimes begun on enormous sheets of graph paper on the wall of a lab and scaled down to a reasonable publishable size by big, slow scanning machines. Many physicists and mathematicians, Roger Penrose not least among them, continue to make plots and diagrams with pen and paper. Nonetheless, it is an increasingly lost art.

While it is tempting to feel a nostalgia for freehand drawings of the complex plane, this chapter should inspire you to embrace the future instead. This chapter will provide an overview of principles and tools for data preparation, analysis, and visualization appropriate for publication-quality results in the physical sciences. Finally, a few examples of analysis and visualization using Python tools will be addressed. This chapter will provide a taste of the analysis tools that will then be discussed in detail in ...

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