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Sigh. Datashader is not a paper, it's an actual usable piece of software, so it should be compared to other tools and libraries for rendering data. Unlike nearl

Sigh. Datashader is not a paper, it's an actual usable piece of software, so it should be compared to other tools and libraries for rendering data. Unlike nearly ever other 2D plotting library available for Python, it can operate in core or out of core, so it's entirely appropriate to advertise that fact (why hide it?). Unlike OpenGL's point drawing functions and nearly every other 2D plotting library available for Python, it avoids overplotting and z-ordering issues that make visualizations misleading (so why hide that?). Unlike NumPy's histogram2D, it allows you to define what it means to aggregate the contents of each bin (mean, min, std, etc.), to focus on different aspects of your data. It's a mystery to me why you think Datashader should somehow fail to advertise what it's useful for!

BubRoss 8y ago
> Datashader is not a paper https://www.semanticscholar.org/paper/Abstract-rendering%3A-out-of-core-rendering-for-Cottam-Lumsdaine/41a157f01b27bcf20143fc578a0db49f4e7b90f3 https://www.semanticscholar.org/paper/Abstract-rendering%3A-... You keep defending the project as a whole while not confronting the fact that they are touting rendering breakthroughs, while I have given a lot of explanation of why there are no rendering breakthroughs and the actual rendering, no matter where it is done and no matter how much data is used, is trivial. I'm not sure what can help you focus in on the point I'm making here, I haven't strayed from it. This isn't about the workflow or the language used or anything else. It is about false claims and buzzwords to make people think that it is solving rendering problems that have never existed like 'accuracy' and 'big data' ( in the context of these visualizations ).
- eggie 8y ago
  They are touting it specifically in the context of the visualization of very large datasets. The fact that their software exists is itself a breakthrough. It enabled me to do things that other equivalent tools (such as in statistical packages) could not allow. I would have been reduced to directly implementing my rendering pipelines, and I would also have had to make many of the same design decisions they made, such as doing things out of core.

BubRoss 8y ago

> Datashader is not a paper https://www.semanticscholar.org/paper/Abstract-rendering%3A-out-of-core-rendering-for-Cottam-Lumsdaine/41a157f01b27bcf20143fc578a0db49f4e7b90f3 https://www.semanticscholar.org/paper/Abstract-rendering%3A-... You keep defending the project as a whole while not confronting the fact that they are touting rendering breakthroughs, while I have given a lot of explanation of why there are no rendering breakthroughs and the actual rendering, no matter where it is done and no matter how much data is used, is trivial. I'm not sure what can help you focus in on the point I'm making here, I haven't strayed from it. This isn't about the workflow or the language used or anything else. It is about false claims and buzzwords to make people think that it is solving rendering problems that have never existed like 'accuracy' and 'big data' ( in the context of these visualizations ).

eggie 8y ago
They are touting it specifically in the context of the visualization of very large datasets. The fact that their software exists is itself a breakthrough. It enabled me to do things that other equivalent tools (such as in statistical packages) could not allow. I would have been reduced to directly implementing my rendering pipelines, and I would also have had to make many of the same design decisions they made, such as doing things out of core.