![]() In fact you can use ImageTank and DataGraph together. You can then send those computations to collaborators that have the same data. Just like DataGraph, the goal is to be able to easily repeat and document the steps you took from data to results. This is very different than tools like matlab which give you the interactivity at the cost of writing your algorithm and code logic in their language. If you use C++/Python as the underlying computational coding language, the way ImageTank interacts with that separates the computation from the UI so that you can easily run your program without any ImageTank dependence. ImageTank is great for computational exploration, and updates things incrementally to speed things up. You don’t have to do anything, ImageTank will automatically adjust and cache/recompute so without you doing anything or at most giving it hints. ImageTank handles caching and schedules computations so that you can run programs which can’t fit into memory. ImageTank is highly optimized, just like DataGraph, and it uses multi-core machines by running a lot of computations concurrently and splits up tasks automatically. And the C++ integration is pretty extensive and includes actions to help you debug the program through Xcode. You can extend it using C++ and Python and it has a lot more graphical power. ImageTank is in some ways Jupyter notebook on steroids. ![]() It should be relatively simple to get going, and example files online and documentation should guide through the starting difficulties. ImageTank is PowerfulĭataGraph is designed to look friendly but with a deep feature set when you start exploring. The image processing definitely is definitely inspired by PDE based image processing. ImageTank is in many ways another seedling from ImageTank, but includes more of the data science focus of DataGraph and reflects research interest in image processing and analysis. DataGraph initially grew out of the 1D drawing routines in DataTank (2006), but it just got the spine from DataTank and grew a body of its own. That version focused on spatial and temporal data, with a focus on PDEs in 2D and 3D. DataTank started on the first version of MacOSX, when it was called Rhaposody. ImageTank is a re-imaging of DataTank, a program that is very mature but shows its age. ![]() Where it goes isn’t completely clear since it will depend very much on early users and use cases. ImageTank is still in public beta and will change quite a bit. In short, since ImageTank aims to do a lot more it needs a bigger foundation. ![]() This means that there are a lot more building blocks than DataGraph and your learning curve is going to longer. This speeds you up, but there are additional concepts that you need to understand in order to use them. You can add actions and give commands while previous actions are still being computed. That means that you can get ahead of where the calculation is. ImageTank also moves computations to the background/extra cores. Then there are other data types that are at the same level such as images, surfaces etc which DataGraph either doesn’t do at all or does inside a specific drawing command. This is closer to the database view of tables. In fact the DataGraph group maps to the Table variable type so each group becomes a separate variable. A lot is, and since DataGraph focuses on a table it can make assumptions fit everything into a table. And most of all, not everything is a table. There are also drawbacks to this model in that files can get large, you end up copying data if it doesn’t make sense to do everything in a single document and it keeps everything in memory. There are certainly benefits to that since you can modify individual values in the table, change in place and view everything at the same time. The main one is that DataGraph combines data, analysis and graphing. This document is intended to compare the two programs and how the goals and design differ. Certainly DataGraph is older and more mature than ImageTank but ImageTank has some functions that can be found in DataGraph. A natural question is what is the relationship between ImageTank and DataGraph.
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