Timeline for How to plot a Gaussian cube file with python/matplotlib?
Current License: CC BY-SA 4.0
17 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 7, 2022 at 0:58 | answer | added | Gianluca | timeline score: 5 | |
| May 6, 2022 at 22:33 | history | reopened | Tyberius♦ | ||
| May 6, 2022 at 13:47 | comment | added | Pol Febrer | Was the question about a specific function to plot the data (e.g. plotly's volume plot trace) or more of a general question on how one must process the grid of values to get to a visualization (a "rawer" approach, let's say)? If it's the second one I can answer, since it was hard for me to find the answer and maybe someone finds it useful :) | |
| Nov 10, 2021 at 19:14 | history | closed | Tyberius♦ | Needs details or clarity | |
| Nov 10, 2021 at 19:13 | comment | added | Tyberius♦ | The closure of this question is really just for bookkeeping to separate it from the truly unaswered questions. Once you are ready to self-answer, I can reopen this post. | |
| Oct 26, 2021 at 18:14 | comment | added | Tyberius♦ | Perfect! I figured it wasn't anything too difficult, but I didn't want to discourage other users by answering. Getting rep is a lot trickier than it was when the site started, so I want other users to get those chances when they are available. | |
| Oct 26, 2021 at 17:54 | comment | added | johnymm | @Tyberius I was able to figure it out. The plotly "volume plot" function essentially does it: plotly.com/python/3d-volume-plots .When I have the time I'll try to write up an answer. | |
| Oct 26, 2021 at 16:15 | comment | added | Hans Wurst | @Tyberius Thank you for your consideration. I'm quite busy myself currently and don't intend to write an answer so please feel free to write one. Anyone should feel free to do so, my comments are never meant to "block" other people from answering or as "reservation" for myself. | |
| Oct 26, 2021 at 14:01 | comment | added | Tyberius♦ | @HansWurst I might try to add an answer here when I find the time, but from the comments it looks like you already have most of whats needed for an answer, so I'll give you the first crack at it if you want it. It would also essentially address this prior question, so it seems like an explicit answer could be useful to a decent number of users. | |
| Oct 19, 2021 at 20:57 | history | edited | Nike Dattani | edited tags | |
| Oct 19, 2021 at 20:32 | comment | added | Nike Dattani | +1 and welcome to our new community! Thank you for contributing your question here and we hope to see much more of you in the future !!! | |
| Oct 11, 2021 at 20:11 | comment | added | johnymm | Mostly the first. I understand physically what it is, but I guess I don't have enough experience in geometry/visualization to know how to plot it. Like, what exactly in the cube file determines the "shape" of the density in 3d surface? For example, the Plotly module has functions for isosurface and volumetric plots, but I can't figure out how to parse the data within a cube file to convert them to arguments for either of those functions (assuming they're right for this type of visualization) | |
| Oct 11, 2021 at 19:36 | comment | added | Hans Wurst | A good explanation of the cube format is given here, paulbourke.net/dataformats/cube, I hope that link makes it clear what I meant. The Gaussian website also provides a description, gaussian.com/cubegen. I do not clearly understand what your question is. Is all that you need a clear explanation of the cube format so that you can parse it ? Or do you not understand what kind of physical property the cube file represents ? | |
| Oct 11, 2021 at 16:44 | comment | added | johnymm | I think the plotly package can do isosurface plots. I don't quite understand what you mean by: "The position of this cube is encoded in the arrangement of the data points. I.e. you can map the linear index of each data point to a point in 3 dimensional space." Could you elaborate? Or point me to a suitable reference? | |
| Oct 11, 2021 at 9:57 | comment | added | Hans Wurst | The data is electron density on a discretized volume. Each data point is the value of the electron density inside a cube of size dxdydz. The position of this cube is encoded in the arrangement of the data points. I.e. you can map the linear index of each data point to a point in 3 dimensional space. Three dimensional densities are often plotted as volume plots or as iso-surface plots. But 3D plots of this kind are not the strong suite of matplotlib and I wouldn't expect particularly good results, especially not straight out-of-the-box. | |
| S Oct 11, 2021 at 6:02 | review | First questions | |||
| Oct 11, 2021 at 7:08 | |||||
| S Oct 11, 2021 at 6:02 | history | asked | johnymm | CC BY-SA 4.0 |