Searching for connect-the-dots data

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In summary: Forum ModeratorIn summary, when creating an exercise on splines, one can obtain a set of points that form a picture when connected by either using existing datasets available in the public domain, such as the NIST database of handwritten digit images, or by generating their own set of points using mathematical functions or software tools.
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Evgeny.Makarov
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I am creating an exercise about splines, for which I need a set of about 10 to 200 points that form a picture when they are connected. Something like the following (from the book "Mathematical Elements for Computer Graphics" by Rogers and Adams).

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I need a file with coordinates and the order in which the points should be connected. Is there such data in the public domain?
 

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Thank you for your interest in splines and creating exercises related to them. There are various options for obtaining a set of points that form a picture when connected.

One option is to use existing datasets that are freely available in the public domain. For example, the National Institute of Standards and Technology (NIST) has a database of handwritten digit images that could potentially be used for your exercise. These images are made up of a set of points that form a digit when connected. You can find more information about this dataset here: https://www.nist.gov/srd/nist-special-database-19.

Another option is to generate your own set of points using mathematical functions or algorithms. This would allow you to have more control over the types of shapes and images that can be created. There are also various software tools and libraries available that can assist with generating these points, such as MATLAB or Python's matplotlib library.

I hope this information helps you in creating your exercise on splines. Best of luck with your project!
 

FAQ: Searching for connect-the-dots data

What is connect-the-dots data?

Connect-the-dots data refers to a type of data that is collected and analyzed in order to identify patterns and connections between various data points. It is often used in scientific research to gain insights and make predictions.

Why is searching for connect-the-dots data important?

Searching for connect-the-dots data is important because it allows scientists to uncover hidden relationships and trends that may not be obvious at first glance. This can lead to new discoveries and advancements in various fields of study.

What are some techniques for searching for connect-the-dots data?

Some techniques for searching for connect-the-dots data include data mining, statistical analysis, and machine learning. These methods involve analyzing large sets of data to find patterns and connections that may not be obvious through manual analysis.

What are the limitations of connect-the-dots data?

One limitation of connect-the-dots data is that it can be biased or incomplete, leading to inaccurate conclusions. Additionally, it may not capture all relevant factors or variables, which can also affect the accuracy of the results. It is important for scientists to carefully consider these limitations when interpreting the data.

How can connect-the-dots data be used in real-world applications?

Connect-the-dots data can be used in a variety of real-world applications, such as predicting market trends, identifying potential health risks, and improving decision-making processes in various industries. It can also help inform policy-making and aid in solving complex societal problems.

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