Add tutorial notebook: Poisson on a molecular grid - #332
Open
Specter842 wants to merge 1 commit into
Open
Conversation
covers solve_poisson_bvp on a MolGrid (two-center Gaussian density), checks the result against the analytic sum-of-erf potential, and plots it along the bond axis. related to theochem#215.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
@PaulWAyers suggested this in #215.
A short
examples/Poisson_on_a_Molecular_Grid.ipynbthat runssolve_poisson_bvpon aMolGrid(two s-type Gaussians on the x-axis, 2 electrons), checks the potential against the analytic sum-of-erf solution (rel L2 ~4e-4), and plots it along the bond axis. Also adds the_toc.ymlentry so it shows up in the website build.The existing
Interpolation_and_Poisson.ipynbonly covers the single-atom case, so this fills in the multi-center usage that #215 was about. Executes clean underjupyter executein ~20s.