Creating Figures/Images/Graphics for Visualization

In summary, the conversation discussed options for creating professional-level diagrams and figures for visual demonstrations, with a preference for free programs. For 2D, xfig and other vector-based drawing packages were suggested, while for 3D, options included vpython, Maple, AutoCAD, and POVRAY. Clarifications were also made regarding the definition of "professional" and the intended audience, with a focus on figures found in physics textbooks.
  • #1
Sir_Deenicus
85
1
I don't know where to put this but this seems to be the most logical home for my question. Which is, if you are interested in creating professional level diagrams and figures that demonstrate concepts and ideas visually (say for example, a problem in statics), what is used? Free programs ofcourse, will have priority in my figuring of what it is I want. :smile:

Thanks for the help in advance.
 
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  • #2
For 2D, you might try xfig or some other vector-based drawing package.
Some fancier programs would be something like AutoCAD LT or Adobe Illustrator.

For 3D, I use http://www.vpython.org or output from Maple. For something fancy, you might try AutoCAD or some super-fancy ray-tracing program like POVRAY.

What does "professional" mean? Can you give an example of what you are looking for? and for what kind of audience? Are you looking for something for precision mechanical drawings? scientific visualization? or just nice artwork?
 
  • #3
Thanks for the reply. Well what I have in mind would be something like the figures found in books (physics texts) often given on the side as concept building explanatory asides (the ones that are not real pictures ofcourse). Thanks again.
 

FAQ: Creating Figures/Images/Graphics for Visualization

What are the key elements to consider when creating figures/images/graphics for visualization?

The key elements to consider when creating figures/images/graphics for visualization include the purpose of the visualization, the target audience, the data being presented, the type of visualization (e.g. bar graph, pie chart, etc.), and the overall design and aesthetics.

How can I effectively choose the appropriate type of visualization for my data?

Choosing the appropriate type of visualization for your data depends on several factors such as the type of data (e.g. numerical, categorical), the relationships between the data points, and the message you want to convey. It's important to consider the strengths and limitations of each type of visualization and choose the one that best represents your data and effectively communicates your message.

What are some best practices for creating visually appealing figures/images/graphics?

Some best practices for creating visually appealing figures/images/graphics include using a consistent color scheme, avoiding clutter and unnecessary elements, labeling all axes and data points clearly, and using appropriate fonts and font sizes. It's also important to ensure that the design is easy to understand and visually appealing for the target audience.

How can I effectively use labels and annotations in my visualizations?

Labels and annotations are important elements in visualizations as they provide context and help viewers understand the data being presented. When using labels and annotations, make sure they are clear, concise, and placed in a way that doesn't clutter the visualization. Use them to highlight important data points or trends and provide additional information or explanations.

What are some common mistakes to avoid when creating figures/images/graphics for visualization?

Some common mistakes to avoid when creating figures/images/graphics for visualization include using misleading or incorrect scales, not clearly labeling axes or data points, using too many colors or visual elements, and not considering the target audience. It's also important to avoid clutter and ensure that the visualization is easy to understand and accurately represents the data being presented.

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