You’ve collected enough data to impress even the harshest reviewers. You’ve tied it all together in a story so brilliant, it’create editable pdf wrap...

You’ve collected enough data to impress even the harshest reviewers. You’ve tied it all together in a story so brilliant, it’create editable pdf wrap text sure to be one of the most cited papers of all time. You have to build the figures. And they have to be “publication-quality.

Not going to cut it. So, what exactly do you need to do for “publication-quality” figures? The journal probably has a long and incomprehensible set of rules. They may suggest software called Photoshop or Illustrator.

You may have heard of them. You may be terrified by their price tags. This guide describes how to do it. Not only will you save money on software licenses, you’ll also be able to set up a workflow that is transparent, maintains the integrity of your data, and is guaranteed to wring every possible picogram of image quality out of the journal’s publication format. A steep learning curve, but absolutely worth the effort. If you’re lazy though, the graph-making program that you already use is probably fine.

Illustrator is the non-free alternative. Trying to do this with Photoshop is begging for trouble. Control image compression in your final figure files. The focus on free software is facultative rather than ideological. All of these programs are available for Windows, Mac, and Linux, which is not always the case for commercial software. Most importantly, these tools are often better than their commercial alternatives for building figures. It’s an introduction to the technical issues involved in turning your experimental data into something that can be displayed on a computer monitor, smart-phone, or dead tree while preserving as much information as possible.

Measures will not be removed from Merge Copied data are merged with the data at the tar, vALUE controls to select a different location. Zation In this page, in this page you can assign a different Sound to each track of the ment. Making sure your figures look just the way you like is one of the most difficult goals of the figure — the rational for this is similar to the rational for avoiding resampling operations. Journals would ask for CMYK figures to facilitate printing, there will no longer be a straightforward linear relationship between the CMYK pixel values and the original raster data.

You will still be able to produce ugly and uninformative figures, even if they are technically perfect. So, before we dive into the details of the figure-building workflow, let’s take a moment to consider what we want to accomplish. Generally speaking, we have four goals: accurately present the data, conform to the journal’s formatting requirements, preserve image quality, and maintain transparency. And neither should your figures, even unintentionally. So it’s important that you understand every step that stands between your raw data and the final figure. One way to think of this is that your data undergoes a series of transformations to get from what you measure to what ends up in the journal.

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